CN120063395A - Submarine pipeline soil liquefaction slip real-time monitoring system based on sensor network - Google Patents
Submarine pipeline soil liquefaction slip real-time monitoring system based on sensor network Download PDFInfo
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Abstract
The invention relates to the technical field of ocean engineering safety monitoring, in particular to a submarine pipeline soil liquefaction slip real-time monitoring system based on a sensor network, which comprises a sensor network deployment module, a dynamic baseline analysis module, a multi-source data space-time calibration module, a coupling risk assessment module and a grading early warning module; the sensor network deployment module is used for collecting multi-parameter data, the dynamic baseline analysis module is used for calculating the dynamic baseline range of each parameter, the multi-source data space-time calibration module is used for eliminating space-time deviation among sensor nodes and outputting space-time calibration data, the coupling risk assessment module is used for calculating the soil liquefaction slippage risk coefficient, and the grading early warning module is used for triggering early warning. According to the invention, through the combination of multi-parameter sensing, space-time calibration and risk fusion evaluation, accurate monitoring and grading early warning of submarine pipeline soil liquefaction slippage are realized, and monitoring continuity and early warning timeliness are improved.
Description
Technical Field
The invention relates to the technical field of ocean engineering safety monitoring, in particular to a submarine pipeline soil liquefaction slip real-time monitoring system based on a sensor network.
Background
In the submarine oil gas resource exploitation and cross-sea conveying engineering, a submarine pipeline is used as a key infrastructure, the running stability of the submarine pipeline is directly related to the safety and sustainability of marine energy transportation, however, in a complex marine geological environment, the submarine pipeline is easily subjected to liquefaction and slippage phenomena under the influence of multiple factors such as seismic disturbance, tidal current flushing, sediment layer structure change and the like, so that the pipeline is concentrated in strain, misplaced and even unstable integrally to form serious engineering disaster risks, and in order to ensure the safety of the submarine pipeline structure, a real-time monitoring system with high precision, continuity and multi-parameter sensing capability is needed to be established, and early identification and grading response on potential liquefaction slippage events are realized.
The existing monitoring technology mainly adopts single sensing type or data point monitoring, lacks comprehensive analysis mechanism for vibration, pressure, displacement and strain, is easy to be interfered by submarine environment in actual deployment, causes data distortion, delay or loss, and cannot construct continuous and reliable early warning chains, meanwhile, most of the current methods do not form an effective multi-source data space-time fusion and risk quantization model, and are difficult to meet the dynamic evaluation and response requirements of the sliding process. Therefore, it is needed to provide a submarine pipeline soil liquefaction slip real-time monitoring system based on a sensor network to improve the monitoring precision and early warning timeliness of the submarine pipeline soil liquefaction slip whole process.
Disclosure of Invention
Based on the purpose, the invention provides a submarine pipeline soil liquefaction slip real-time monitoring system based on a sensor network.
The submarine pipeline soil liquefaction slip real-time monitoring system based on the sensor network comprises a sensor network deployment module, a dynamic baseline analysis module, a multi-source data space-time calibration module, a coupling risk assessment module and a grading early warning module, wherein:
The sensor network deployment module is used for circumferentially arranging a plurality of groups of sensor nodes along the submarine pipeline and acquiring soil vibration acceleration data, pore water pressure data, soil displacement data and pipeline strain data and outputting multi-parameter data;
The dynamic baseline analysis module is used for receiving the multi-parameter data output by the sensor network deployment module, calculating the dynamic baseline range of each parameter based on the sliding time window and generating real-time dynamic reference data;
the multi-source data space-time calibration module is used for receiving the real-time dynamic reference data output by the dynamic baseline analysis module, eliminating space-time deviation among sensor nodes through a time stamp alignment and spatial interpolation algorithm, and outputting space-time calibration data;
The coupling risk assessment module is used for receiving the space-time calibration data output by the space-time calibration module, and fusing the vibration acceleration, the pore water pressure, the soil displacement and the pipeline strain data according to weights to generate a soil liquefaction slippage risk coefficient;
The grading early warning module is used for receiving the soil liquefaction slippage risk coefficient output by the coupling risk assessment module, triggering primary early warning, secondary early warning or tertiary early warning according to a preset threshold value, and outputting an early warning signal to the monitoring terminal.
Optionally, the sensor network deployment module comprises a circumferential layout unit, a multi-parameter acquisition unit, a data preprocessing unit and a time synchronization unit, wherein:
The circumferential layout unit is used for arranging a group of sensor nodes at intervals of 10 meters along the axial direction of the submarine pipeline, wherein each group of sensor nodes comprises a vibration acceleration sensor, a pore water pressure sensor, a soil mass displacement sensor and a pipeline strain sensor which are respectively arranged at the positions of 0 degree, 90 degree, 180 degree and 270 degree in the circumferential direction of the pipeline;
The multi-parameter acquisition unit is used for acquiring soil vibration acceleration data, pore water pressure data, soil displacement data and pipeline strain data through each group of sensor nodes;
the data preprocessing unit is used for performing time domain filtering, dimension normalization and outlier rejection on the acquired soil vibration acceleration data, pore water pressure data, soil mass displacement data and pipeline strain data to generate multi-parameter data;
And the time synchronization unit is used for receiving the NTP protocol clock signal issued by the water surface repeater, performing millisecond time synchronization on each sensor node, and ensuring consistency of a plurality of groups of data time stamps.
Optionally, the dynamic baseline analysis module comprises a parameter grouping processing unit, a sliding window construction unit, an anomaly filtering calculation unit and a dynamic reference generation unit, wherein:
the parameter grouping processing unit is used for receiving the multi-parameter data output by the sensor network deployment module and respectively classifying the vibration acceleration data, the pore water pressure data, the soil mass displacement data and the pipeline strain data according to the data sources;
The sliding window construction unit is used for constructing a sliding time window with fixed time length aiming at each type of parameter data, wherein the window length is set to be T seconds, the step length is deltat seconds, and a continuous historical data sequence in the current window is extracted at each moment;
The abnormal filtering calculation unit is used for carrying out steady-state fluctuation analysis on the historical data in each sliding window, eliminating data points with the amplitude exceeding the set standard deviation multiple, and generating a steady interval of the parameter in the current window by adopting a median filtering method;
and the dynamic reference generating unit is used for respectively defining the upper and lower boundaries of the stable interval of each type of parameter in the sliding window as dynamic base line ranges of the corresponding parameters after the abnormal filtering is completed, and outputting the dynamic base line ranges by taking the range average value as real-time dynamic reference data at the current moment.
Optionally, the anomaly filtering calculation unit includes:
a volatility evaluation subunit, configured to perform volatility evaluation on the received historical data sequence in each sliding window, and calculate a mean value M and a standard deviation S of the sequence;
An abnormal point eliminating subunit, configured to eliminate the meeting condition according to the set deviation threshold multiple a Generating a rejected data set;
a median filtering subunit, configured to perform median filtering processing on the removed data set, calculate a median P of the ordered sequence as a reference value of the current parameter steady-state level, and extract upper and lower quartiles at the same time ,Determining a stability interval。
Optionally, the multi-source data space-time calibration module comprises a time alignment unit, a spatial position registration unit and an interpolation calculation unit, wherein:
the time alignment unit is used for receiving the real-time dynamic reference data of each sensor node output by the dynamic baseline analysis module, extracting corresponding time stamps according to a system master clock signal, uniformly reconstructing a data time axis taking uniform reference time as a reference, eliminating data frames with time drift, and ensuring that all node data have comparability at the same time point;
The spatial position registration unit is used for constructing a sensor spatial position mapping table according to geographic coordinates or relative position labels preset when each sensor node is circumferentially arranged in the pipeline, and carrying out spatial indexing on data according to the distribution relation of the nodes in a three-dimensional coordinate system;
And the interpolation calculation unit is used for carrying out numerical interpolation reconstruction on the missing or abnormal data nodes according to the dynamic reference values of the spatial adjacent nodes on the basis of completing time alignment and spatial position registration, and carrying out fine adjustment on the adjacent node data with consistent time sequence variation trend at the same time to generate space-time calibration data.
Optionally, the spatial position registration unit includes:
the node information extraction subunit is used for extracting the unique identifier of each sensor node and the initial position information recorded during deployment of each sensor node from the sensor network deployment module, wherein the initial position information comprises a pipeline segment number, a circumferential angle and an installation depth;
the three-dimensional coordinate modeling subunit is used for calculating rectangular coordinates (X, Y, Z) of each node in space according to the extracted pipeline segment number, the circumferential angle and the installation depth and by combining a pipeline center line three-dimensional track model, and storing the rectangular coordinates (X, Y, Z) in a space position mapping table of a corresponding sensor;
And the space index coding subunit is used for carrying out space level coding on all nodes according to node distribution in the three-dimensional coordinate system and constructing a rapid space query index structure by adopting a hash mode.
Optionally, the interpolation calculation unit includes:
The adjacent node searching subunit is used for searching an adjacent node set of the target missing node in the three-dimensional coordinate space from the space position mapping table, adopting a fixed searching radius R to carry out spherical neighborhood matching, outputting all nodes with the spatial distance not greater than R from the target node as interpolation reference sets, and recording the interpolation reference sets as a node set N;
a spatial interpolation reconstruction subunit, configured to perform weighted average on a current time dynamic reference value of each node in the node set N according to the euclidean distance between the current time dynamic reference value and the target node, and generate an interpolation estimation value of the target node ;
A time sequence trend reconciliation subunit for performing spatial interpolation on the estimated valuePerforming time trend fine adjustment, and calculating reference value sequence of adjacent nodes at the previous momentWith the current sequenceMean change difference of (2)Then the difference is addedWeighting actionGenerating final output spatio-temporal calibration dataThe calculation formula is as follows: , wherein, The harmonic weight factor is expressed as a temporal trend harmonic coefficient.
Optionally, the coupled risk assessment module includes a normalization unit, a weight fusion unit and a risk generation unit, where:
The parameter normalization unit is used for receiving the vibration acceleration data A, the pore water pressure data P, the soil body displacement data D and the pipeline strain data E output by the space-time calibration module, and normalizing the vibration acceleration data A, the pore water pressure data P, the soil body displacement data D and the pipeline strain data E to intervals [0,1] by adopting a maximum and minimum normalization method respectively to obtain normalized parameters ,,,To eliminate scale differences between different physical quantities;
the weight distribution unit is used for setting the fusion weight of each type of standardized parameters according to the analysis of the historical slippage event and the regional geological weight factor, and setting the weight set as The influence degrees of vibration acceleration, pore water pressure, soil displacement and pipeline strain are respectively corresponding to the constraint conditions:;
the risk coefficient calculating unit is used for calculating a comprehensive soil liquefaction sliding risk coefficient R based on the standardized parameters and the weight set, wherein the calculation formula is as follows: 。
optionally, the hierarchical early warning module comprises a threshold judging unit, an early warning message generating unit and a signal transmission unit, wherein:
The threshold value judging unit is used for receiving the soil liquefaction slippage risk coefficient output by the coupling risk assessment module and comparing the soil liquefaction slippage risk coefficient with three preset risk coefficient thresholds, triggering a third-level early warning at the moment, triggering a second-level early warning at the moment, and triggering a first-level early warning at the moment, wherein the risk thresholds respectively correspond to the local slippage, regional liquefaction and pipeline instability;
The pre-alarm message generating unit is used for constructing a structured pre-alarm message based on the triggered pre-alarm level;
the signal transmission unit is used for transmitting the structured early warning message to the monitoring terminal through a wired or wireless communication network.
Optionally, the early warning message generating unit includes:
The early warning level mapping subunit is used for determining a corresponding early warning level identification code according to the early warning level triggered by the risk level result output by the threshold value judging unit, wherein the primary early warning mapping is W1 and represents local slippage, the secondary early warning mapping is W2 and represents regional liquefaction, and the tertiary early warning mapping is W3 and represents pipeline instability;
The message segment filling unit is used for constructing the structural content containing the following fields for each triggering early warning event:
1. Early warning level identification;
2. Triggering time;
3. early warning center coordinates;
4. corresponding to the risk coefficient value;
5. Suggested treatment instructions;
And the structured format coding subunit is used for coding the field content which is built according to a preset format to generate a unified message format.
The invention has the beneficial effects that:
According to the invention, through the arrangement and data collaborative sensing of the multi-type sensor nodes, key parameters such as vibration acceleration, pore water pressure, soil displacement, pipeline strain and the like can be synchronously acquired, and a dynamic baseline analysis and multi-source data space-time calibration method is utilized, so that high stability processing of monitoring data is realized, the accuracy and continuity of slip risk identification are remarkably improved, and the problems of parameter drift and abnormal point interference in a seabed complex environment are solved.
According to the invention, a coupling risk assessment mechanism is constructed, multiple parameters are fused according to weights to calculate the liquefaction slippage risk coefficient, and hierarchical early warning is executed by combining with a preset threshold value, and the liquefaction slippage risk coefficient is automatically pushed to the monitoring terminal through the structured message, so that the quick response and treatment suggestion output of different slippage severity degrees are effectively realized, and the safety guarantee capability and the early warning intelligent level in the whole life cycle operation process of the submarine pipeline are improved.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only of the invention and that other drawings can be obtained from them without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a real-time monitoring system for soil liquefaction slippage according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a multi-source data space-time calibration module according to an embodiment of the invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and to specific embodiments. While the invention has been described herein in detail in order to make the embodiments more detailed, the following embodiments are preferred and can be embodied in other forms as well known to those skilled in the art, and the accompanying drawings are only for the purpose of describing the embodiments more specifically and are not intended to limit the invention to the specific forms disclosed herein.
1-2, The submarine pipeline soil liquefaction slip real-time monitoring system based on the sensor network comprises a sensor network deployment module, a dynamic baseline analysis module, a multi-source data space-time calibration module, a coupling risk assessment module and a hierarchical early warning module, wherein:
The sensor network deployment module is used for circumferentially arranging a plurality of groups of sensor nodes along the submarine pipeline and acquiring soil vibration acceleration data, pore water pressure data, soil displacement data and pipeline strain data and outputting multi-parameter data;
The dynamic baseline analysis module is used for receiving the multi-parameter data output by the sensor network deployment module, calculating the dynamic baseline range of each parameter based on the sliding time window and generating real-time dynamic reference data;
the multi-source data space-time calibration module is used for receiving the real-time dynamic reference data output by the dynamic baseline analysis module, eliminating space-time deviation among sensor nodes through a time stamp alignment and spatial interpolation algorithm, and outputting space-time calibration data;
The coupling risk assessment module is used for receiving the space-time calibration data output by the space-time calibration module, and fusing the vibration acceleration, the pore water pressure, the soil displacement and the pipeline strain data according to weights to generate a soil liquefaction slippage risk coefficient;
The grading early warning module is used for receiving the soil liquefaction slippage risk coefficient output by the coupling risk assessment module, triggering primary early warning (local slippage), secondary early warning (regional liquefaction) or tertiary early warning (pipeline instability) according to a preset threshold value, and outputting an early warning signal to the monitoring terminal.
The sensor network deployment module comprises a circumferential layout unit, a multi-parameter acquisition unit, a data preprocessing unit and a time synchronization unit, wherein:
The circumferential layout unit is used for arranging a group of sensor nodes along the axial direction of the submarine pipeline at intervals of 10 meters, wherein each group of sensor nodes comprises a vibration acceleration sensor, a pore water pressure sensor, a soil mass displacement sensor and a pipeline strain sensor which are respectively arranged at the positions of 0 DEG, 90 DEG, 180 DEG and 270 DEG in the circumferential direction of the pipeline;
The multi-parameter acquisition unit is used for acquiring soil vibration acceleration data, pore water pressure data, soil displacement data and pipeline strain data through each group of sensor nodes;
The multi-parameter acquisition unit comprises:
the vibration acceleration sensing subunit adopts an MEMS triaxial accelerometer which is arranged on the contact surface of the outer wall of the pipeline and the soil, the measuring range is +/-5 g, the sampling frequency is 100Hz, and the vibration acceleration sensing subunit is used for collecting vibration acceleration data of the pipeline-soil interface;
the pore water pressure sensing subunit adopts a piezoresistive sensor with a permeable stone protective film, is embedded in the position 20cm away from the outer wall of the pipeline at the tail end of the anchoring rod, has sampling frequency of 1Hz, and measures pore water pressure data in the soil liquefaction process;
A soil body displacement sensing subunit, namely adopting a laser ranging sensor to face soil outside the pipeline at a 45-degree inclination angle, and acquiring circumferential soil body displacement data of the pipeline in real time within a measuring range of 0-30 cm;
The pipeline strain sensing subunit adopts a fiber grating sensor to be welded on the outer surface along the axial direction of the pipeline, and one measuring point is arranged at each interval of 1 meter to monitor the pipeline strain data;
the data preprocessing unit is used for performing time domain filtering, dimension normalization and outlier rejection on the acquired soil vibration acceleration data, pore water pressure data, soil mass displacement data and pipeline strain data to generate multi-parameter data;
And the time synchronization unit is used for receiving an NTP (network time) protocol clock signal issued by the water surface repeater, performing millisecond time synchronization on each sensor node, and ensuring that a plurality of groups of data time stamps are consistent.
The dynamic baseline analysis module comprises a parameter grouping processing unit, a sliding window construction unit, an anomaly filtering calculation unit and a dynamic reference generation unit, wherein:
The parameter grouping processing unit is used for receiving the multi-parameter data output by the sensor network deployment module, classifying the vibration acceleration data, the pore water pressure data, the soil mass displacement data and the pipeline strain data according to data sources, and ensuring that each type of data keeps an independent processing path in subsequent analysis;
The sliding window construction unit is used for constructing a sliding time window with fixed time length aiming at each type of parameter data, wherein the window length is set to be T seconds, the step length is deltat seconds, and a continuous historical data sequence in the current window is extracted at each moment;
The abnormal filtering calculation unit is used for carrying out steady-state fluctuation analysis on the historical data in each sliding window, eliminating data points with the amplitude exceeding the set standard deviation multiple, and generating a steady interval of the parameter in the current window by adopting a median filtering method;
The dynamic reference generation unit is used for respectively defining the upper and lower boundaries of the stable interval of each type of parameter in the sliding window as dynamic base line ranges of corresponding parameters after the abnormal filtering is completed, and taking the average value of the ranges as real-time dynamic reference data of the current moment to output.
The anomaly filtering calculation unit includes:
And the fluctuation evaluation subunit is used for carrying out fluctuation evaluation on the received historical data sequence in each sliding window, and calculating the mean value M and the standard deviation S of the sequence, wherein the calculation formula is as follows: , wherein, Representing an ith historical sampling value, and n represents the total number of data points in the sliding window;
An abnormal point eliminating subunit, configured to eliminate the meeting condition according to the set deviation threshold multiple a Generating a rejected data set;
a median filtering subunit, configured to perform median filtering processing on the removed data set, calculate a median P of the ordered sequence as a reference value of the current parameter steady-state level, and extract upper and lower quartiles at the same time ,Determining a stability intervalBy introducing standard deviation elimination and median filtering, the influence of extreme points such as seismic wave disturbance and local water burst on the data stability can be effectively eliminated, the reliability of the parameter dynamic reference in the sliding window is improved, and more robust reference data support is provided for subsequent coupling risk assessment.
The multi-source data space-time calibration module comprises a time alignment unit, a spatial position registration unit and an interpolation calculation unit, wherein:
the time alignment unit is used for receiving the real-time dynamic reference data of each sensor node output by the dynamic baseline analysis module, extracting corresponding time stamps according to a system master clock signal, uniformly reconstructing a data time axis taking uniform reference time as a reference, eliminating data frames with time drift, and ensuring that all node data have comparability at the same time point;
The spatial position registration unit is used for constructing a sensor spatial position mapping table according to geographic coordinates or relative position labels preset when each sensor node is circumferentially distributed in the pipeline, and carrying out spatial indexing on data according to the distribution relation of the nodes in a three-dimensional coordinate system so as to ensure that the subsequent interpolation operation is based on the geometric distribution of a real sensor;
The interpolation calculation unit is used for carrying out numerical interpolation reconstruction according to dynamic reference values of spatial adjacent nodes of missing or abnormal data nodes on the basis of completing time alignment and spatial position registration, and carrying out fine adjustment on adjacent node data with consistent time sequence variation trend to generate continuous, complete and space-time calibration data.
The spatial position registration unit includes:
The node information extraction subunit is used for extracting the unique identifier of each sensor node and the initial position information recorded during deployment of each sensor node from the sensor network deployment module, wherein the initial position information comprises a pipeline segment number, a circumferential angle and an installation depth and is used for subsequent coordinate modeling;
the three-dimensional coordinate modeling subunit is used for calculating rectangular coordinates (X, Y, Z) of each node in space according to the extracted pipeline segment number, the circumferential angle and the installation depth and by combining a pipeline center line three-dimensional track model, and storing the rectangular coordinates (X, Y, Z) in a space position mapping table of a corresponding sensor;
the specific calculation formula of the coordinates is as follows:
;
;
Wherein, the method comprises the steps of, ,,The central coordinate of the starting point of the current pipeline section is represented and preset by a pipeline layout path, and L represents the longitudinal distance (along the direction of a central line) of the pipeline section where the current node is located; representing the inclination angle of the extending direction of the current section on the horizontal plane, if the current section is a horizontal section R represents the radius distance of the sensor node installation, i.e., the pipe radius, set to constant; The method comprises the steps of representing circumferential angles of sensor nodes relative to the center of the cross section of a pipeline, wherein the units are degrees, D represents the installation depth (unit: meters) of the sensor nodes vertically downwards, and X, Y and Z represent three-dimensional space rectangular coordinates obtained through final conversion.
The spatial index coding subunit is used for carrying out spatial hierarchy coding on all nodes according to node distribution in a three-dimensional coordinate system, constructing a rapid spatial query index structure by adopting a hash mode so as to support rapid search of a spatial point set of any node adjacent area in interpolation operation, and realizing rapid search and accurate expression of the spatial relationship of the nodes by standardizing sensor installation information into the three-dimensional coordinate form and introducing a spatial index mechanism, thereby supporting high-precision spatial interpolation and coupling calculation and providing spatial continuity guarantee for subsequent slippage risk assessment.
Table 1 sensor spatial location map structure example
| Node numbering | Pipeline section numbering | Circumferential angle | Depth of installation | X coordinates | Y coordinates | Z coordinate |
| N001 | S01 | 0 | 2 | 100 | 50 | -2 |
| N002 | S01 | 90 | 2 | 100 | 52 | -2 |
| N003 | S01 | 180 | 2 | 100 | 50 | -4 |
| N004 | S01 | 270 | 2 | 100 | 48 | -2 |
| N005 | S02 | 0 | 2 | 102 | 50 | -2 |
In table1, the node number is a unique number allocated to each sensor node, the pipe section number represents the pipe section number where the sensor is located, the circumferential angle represents the angle of the node relative to the center of the pipe cross section, the installation depth represents the depth of the node below the seabed, and X, Y, Z coordinates are actual space positions obtained by modeling and transforming according to the section positions, the circumferential angles and the installation depths through three-dimensional coordinates, and are used for subsequent interpolation calculation.
The interpolation calculation unit includes:
The adjacent node searching subunit is used for searching an adjacent node set of the target missing node in the three-dimensional coordinate space from the space position mapping table, adopting a fixed searching radius R to carry out spherical neighborhood matching, outputting all nodes with the spatial distance not greater than R from the target node as interpolation reference sets, and recording the interpolation reference sets as a node set N;
a spatial interpolation reconstruction subunit, configured to perform weighted average on a current time dynamic reference value of each node in the node set N according to the euclidean distance between the current time dynamic reference value and the target node, and generate an interpolation estimation value of the target node The calculation formula is as follows: , wherein, Representing an interpolated estimate of the missing node,Representing the dynamic reference value of the i-th neighbor node,Representing the Euclidean distance between the node and the target node, wherein k is the number of adjacent nodes;
a time sequence trend reconciliation subunit for performing spatial interpolation on the estimated value Performing time trend fine adjustment, and calculating reference value sequence of adjacent nodes at the previous momentWith the current sequenceMean change difference of (2)Then the difference is addedWeighting actionGenerating final output spatio-temporal calibration dataThe calculation formula is as follows: , wherein, The subunit realizes interpolation reconstruction based on the distance weighted average of the space adjacent nodes, and then combines the time sequence trend to carry out trend fine adjustment, thereby effectively solving the problem of data missing caused by node faults or signal interference, ensuring the continuity and consistency of calibration data in two dimensions of time and space, and further ensuring the accuracy and stability of the subsequent coupling evaluation result.
The coupled risk assessment module comprises a normalization unit, a weight fusion unit and a risk generation unit, wherein:
The parameter normalization unit is used for receiving the vibration acceleration data A, the pore water pressure data P, the soil body displacement data D and the pipeline strain data E output by the space-time calibration module, and normalizing the vibration acceleration data A, the pore water pressure data P, the soil body displacement data D and the pipeline strain data E to intervals [0,1] by adopting a maximum and minimum normalization method respectively to obtain normalized parameters ,,,To eliminate scale differences between different physical quantities;
the weight distribution unit is used for setting the fusion weight of each type of standardized parameters according to the analysis of the historical slippage event and the regional geological weight factor, and setting the weight set as The influence degrees of vibration acceleration, pore water pressure, soil displacement and pipeline strain are respectively corresponding to the constraint conditions:;
the weight setting method in the weight distribution unit includes the steps of:
Step one, firstly, collecting the target sea area and the similar geological units Each event records the corresponding standardized parameter and actual slip strength indexThen construct the history response matrix H and the observation result vectorThe expressions are respectively:
;
;
step two, adopting a linear least square method to invert and solve the optimal weight vector To predict risk coefficientAs close as possible to the observed valueThen solving an objective function: The constraint conditions are as follows: thereby obtaining a group of uniquely determined fusion weights The method is used for subsequent real-time monitoring of the scene;
the risk coefficient calculating unit is used for calculating a comprehensive soil liquefaction sliding risk coefficient R based on the standardized parameters and the weight set, wherein the calculation formula is as follows: the method comprises the steps of establishing a standardized and weighted fusion risk quantization flow, uniformly integrating multisource heterogeneous parameters into a uniform evaluation frame, improving objectivity and instantaneity of soil liquefaction slip risk judgment, having good region adaptability and providing a quantized input basis for downstream grading early warning.
The hierarchical early warning module comprises a threshold judging unit, an early warning message generating unit and a signal transmission unit, wherein:
The threshold value judging unit is used for receiving the soil liquefaction slippage risk coefficient output by the coupling risk assessment module and comparing the soil liquefaction slippage risk coefficient with three preset risk coefficient thresholds, triggering a third-level early warning at the moment, triggering a second-level early warning at the moment, and triggering a first-level early warning at the moment, wherein the risk thresholds respectively correspond to the local slippage, regional liquefaction and pipeline instability;
The pre-alarm message generating unit is used for constructing a structured pre-alarm message based on the triggered pre-alarm level, wherein the message comprises a pre-alarm level identifier, and generating information such as a time stamp, a pre-alarm area position and the like so as to enable the monitoring terminal to accurately analyze;
the signal transmission unit is used for transmitting the structured early warning message to the monitoring terminal through a wired or wireless communication network to ensure the real-time performance of early warning information, and the structured message and the transmission are combined through multi-level threshold judgment, so that the accurate distinction and instant notification of the slippage risks with different severity degrees are realized, and the response speed and the early warning accuracy of the system to the submarine pipeline soil liquefaction slippage event are improved.
The pre-alarm text generation unit includes:
The early warning level mapping subunit is used for determining a corresponding early warning level identification code according to the early warning level triggered by the risk level result output by the threshold value judging unit, wherein the primary early warning mapping is W1 and represents local slippage, the secondary early warning mapping is W2 and represents regional liquefaction, and the tertiary early warning mapping is W3 and represents pipeline instability;
The message segment filling unit is used for constructing the structural content containing the following fields for each triggering early warning event:
1. Early warning level identification (W1/W2/W3);
2. Trigger time (system standard timestamp);
3. Early warning center coordinates (represented by node numbers of trigger points and three-dimensional positions thereof);
4. corresponding to the risk coefficient value R;
5. suggested treatment instruction (with an operation instruction number according to the early warning level);
The structured format coding subunit is used for coding the field content which is built according to a preset format to generate a unified message format;
Specific examples are as follows:
[ LEVEL=W2 ], [ TIME=2025-04-25T 10:33:10], [ NODE=N 037], [ POS= (102.3,48.7, -3.2) ], [ R=0.68 ], [ ACTION=A02 ], wherein the field sequence is fixed, the separator uniformly adopts a half-angle semicolon to facilitate subsequent analysis and execution, and through standardized mapping and encoding of the early warning LEVEL and the structured content field, uniform expression and rapid transmission of early warning information are realized, the message analysis efficiency is improved, the response measures under different early warning LEVELs are ensured to be accurately corresponding, and the response normalization and automation LEVEL of the system to sudden sliding events are enhanced.
The invention is intended to cover any alternatives, modifications, equivalents, and variations that fall within the spirit and scope of the invention. In the following description of preferred embodiments of the invention, specific details are set forth in order to provide a thorough understanding of the invention, and the invention will be fully understood to those skilled in the art without such details. In other instances, well-known methods, procedures, flows, components, circuits, and the like have not been described in detail so as not to unnecessarily obscure aspects of the present invention.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (10)
1. The submarine pipeline soil liquefaction slip real-time monitoring system based on the sensor network is characterized by comprising a sensor network deployment module, a dynamic baseline analysis module, a multi-source data space-time calibration module, a coupling risk assessment module and a grading early warning module, wherein:
The sensor network deployment module is used for circumferentially arranging a plurality of groups of sensor nodes along the submarine pipeline and acquiring soil vibration acceleration data, pore water pressure data, soil displacement data and pipeline strain data and outputting multi-parameter data;
The dynamic baseline analysis module is used for receiving the multi-parameter data output by the sensor network deployment module, calculating the dynamic baseline range of each parameter based on the sliding time window and generating real-time dynamic reference data;
the multi-source data space-time calibration module is used for receiving the real-time dynamic reference data output by the dynamic baseline analysis module, eliminating space-time deviation among sensor nodes through a time stamp alignment and spatial interpolation algorithm, and outputting space-time calibration data;
The coupling risk assessment module is used for receiving the space-time calibration data output by the space-time calibration module, and fusing the vibration acceleration, the pore water pressure, the soil displacement and the pipeline strain data according to weights to generate a soil liquefaction slippage risk coefficient;
The grading early warning module is used for receiving the soil liquefaction slippage risk coefficient output by the coupling risk assessment module, triggering primary early warning, secondary early warning or tertiary early warning according to a preset threshold value, and outputting an early warning signal to the monitoring terminal.
2. The sensor network-based submarine pipeline soil liquefaction slip real-time monitoring system according to claim 1, wherein the sensor network deployment module comprises a circumferential layout unit, a multi-parameter acquisition unit, a data preprocessing unit and a time synchronization unit, wherein:
The circumferential layout unit is used for arranging a group of sensor nodes at intervals of 10 meters along the axial direction of the submarine pipeline, wherein each group of sensor nodes comprises a vibration acceleration sensor, a pore water pressure sensor, a soil mass displacement sensor and a pipeline strain sensor which are respectively arranged at the positions of 0 degree, 90 degree, 180 degree and 270 degree in the circumferential direction of the pipeline;
The multi-parameter acquisition unit is used for acquiring soil vibration acceleration data, pore water pressure data, soil displacement data and pipeline strain data through each group of sensor nodes;
the data preprocessing unit is used for performing time domain filtering, dimension normalization and outlier rejection on the acquired soil vibration acceleration data, pore water pressure data, soil mass displacement data and pipeline strain data to generate multi-parameter data;
And the time synchronization unit is used for receiving the NTP protocol clock signal issued by the water surface repeater, performing millisecond time synchronization on each sensor node, and ensuring consistency of a plurality of groups of data time stamps.
3. The sensor network-based submarine pipeline soil liquefaction slip real-time monitoring system according to claim 1, wherein the dynamic baseline analysis module comprises a parameter grouping processing unit, a sliding window construction unit, an anomaly filtering calculation unit and a dynamic reference generation unit, wherein:
the parameter grouping processing unit is used for receiving the multi-parameter data output by the sensor network deployment module and respectively classifying the vibration acceleration data, the pore water pressure data, the soil mass displacement data and the pipeline strain data according to the data sources;
The sliding window construction unit is used for constructing a sliding time window with fixed time length aiming at each type of parameter data, wherein the window length is set to be T seconds, the step length is deltat seconds, and a continuous historical data sequence in the current window is extracted at each moment;
The abnormal filtering calculation unit is used for carrying out steady-state fluctuation analysis on the historical data in each sliding window, eliminating data points with the amplitude exceeding the set standard deviation multiple, and generating a steady interval of the parameter in the current window by adopting a median filtering method;
and the dynamic reference generating unit is used for respectively defining the upper and lower boundaries of the stable interval of each type of parameter in the sliding window as dynamic base line ranges of the corresponding parameters after the abnormal filtering is completed, and outputting the dynamic base line ranges by taking the range average value as real-time dynamic reference data at the current moment.
4. The sensor network-based submarine pipeline soil liquefaction slip real-time monitoring system according to claim 3, wherein the anomaly filtering calculation unit comprises:
a volatility evaluation subunit, configured to perform volatility evaluation on the received historical data sequence in each sliding window, and calculate a mean value M and a standard deviation S of the sequence;
An abnormal point eliminating subunit, configured to eliminate the meeting condition according to the set deviation threshold multiple a Generating a rejected data set;
a median filtering subunit, configured to perform median filtering processing on the removed data set, calculate a median P of the ordered sequence as a reference value of the current parameter steady-state level, and extract upper and lower quartiles at the same time ,Determining a stability interval。
5. The sensor network-based submarine pipeline soil liquefaction slip real-time monitoring system according to claim 1, wherein the multi-source data space-time calibration module comprises a time alignment unit, a spatial position registration unit and an interpolation calculation unit, wherein:
the time alignment unit is used for receiving the real-time dynamic reference data of each sensor node output by the dynamic baseline analysis module, extracting corresponding time stamps according to a system master clock signal, uniformly reconstructing a data time axis taking uniform reference time as a reference, eliminating data frames with time drift, and ensuring that all node data have comparability at the same time point;
The spatial position registration unit is used for constructing a sensor spatial position mapping table according to geographic coordinates or relative position labels preset when each sensor node is circumferentially arranged in the pipeline, and carrying out spatial indexing on data according to the distribution relation of the nodes in a three-dimensional coordinate system;
And the interpolation calculation unit is used for carrying out numerical interpolation reconstruction on the missing or abnormal data nodes according to the dynamic reference values of the spatial adjacent nodes on the basis of completing time alignment and spatial position registration, and carrying out fine adjustment on the adjacent node data with consistent time sequence variation trend at the same time to generate space-time calibration data.
6. The sensor network-based submarine pipeline soil liquefaction slip real-time monitoring system according to claim 5, wherein the spatial location registration unit comprises:
the node information extraction subunit is used for extracting the unique identifier of each sensor node and the initial position information recorded during deployment of each sensor node from the sensor network deployment module, wherein the initial position information comprises a pipeline segment number, a circumferential angle and an installation depth;
the three-dimensional coordinate modeling subunit is used for calculating rectangular coordinates (X, Y, Z) of each node in space according to the extracted pipeline segment number, the circumferential angle and the installation depth and by combining a pipeline center line three-dimensional track model, and storing the rectangular coordinates (X, Y, Z) in a space position mapping table of a corresponding sensor;
And the space index coding subunit is used for carrying out space level coding on all nodes according to node distribution in the three-dimensional coordinate system and constructing a rapid space query index structure by adopting a hash mode.
7. The sensor network-based submarine pipeline soil liquefaction slip real-time monitoring system according to claim 6, wherein the interpolation calculation unit comprises:
The adjacent node searching subunit is used for searching an adjacent node set of the target missing node in the three-dimensional coordinate space from the space position mapping table, adopting a fixed searching radius R to carry out spherical neighborhood matching, outputting all nodes with the spatial distance not greater than R from the target node as interpolation reference sets, and recording the interpolation reference sets as a node set N;
a spatial interpolation reconstruction subunit, configured to perform weighted average on a current time dynamic reference value of each node in the node set N according to the euclidean distance between the current time dynamic reference value and the target node, and generate an interpolation estimation value of the target node ;
A time sequence trend reconciliation subunit for performing spatial interpolation on the estimated valuePerforming time trend fine adjustment, and calculating reference value sequence of adjacent nodes at the previous momentWith the current sequenceMean change difference of (2)Then the difference is addedWeighting actionGenerating final output spatio-temporal calibration dataThe calculation formula is as follows: , wherein, The harmonic weight factor is expressed as a temporal trend harmonic coefficient.
8. The sensor network-based submarine pipeline soil liquefaction slip real-time monitoring system according to claim 1, wherein the coupled risk assessment module comprises a normalization unit, a weight fusion unit and a risk generation unit, wherein:
The parameter normalization unit is used for receiving the vibration acceleration data A, the pore water pressure data P, the soil body displacement data D and the pipeline strain data E output by the space-time calibration module, and normalizing the vibration acceleration data A, the pore water pressure data P, the soil body displacement data D and the pipeline strain data E to intervals [0,1] by adopting a maximum and minimum normalization method respectively to obtain normalized parameters ,,,To eliminate scale differences between different physical quantities;
the weight distribution unit is used for setting the fusion weight of each type of standardized parameters according to the analysis of the historical slippage event and the regional geological weight factor, and setting the weight set as The influence degrees of vibration acceleration, pore water pressure, soil displacement and pipeline strain are respectively corresponding to the constraint conditions:;
the risk coefficient calculating unit is used for calculating a comprehensive soil liquefaction sliding risk coefficient R based on the standardized parameters and the weight set, wherein the calculation formula is as follows: 。
9. the sensor network-based submarine pipeline soil liquefaction slip real-time monitoring system according to claim 1, wherein the grading early warning module comprises a threshold judgment unit, an early warning message generation unit and a signal transmission unit, wherein:
The threshold value judging unit is used for receiving the soil liquefaction slippage risk coefficient output by the coupling risk assessment module and comparing the soil liquefaction slippage risk coefficient with three preset risk coefficient thresholds, triggering a third-level early warning at the moment, triggering a second-level early warning at the moment, and triggering a first-level early warning at the moment, wherein the risk thresholds respectively correspond to the local slippage, regional liquefaction and pipeline instability;
The pre-alarm message generating unit is used for constructing a structured pre-alarm message based on the triggered pre-alarm level;
the signal transmission unit is used for transmitting the structured early warning message to the monitoring terminal through a wired or wireless communication network.
10. The sensor network-based submarine pipeline soil liquefaction slip real-time monitoring system according to claim 9, wherein the early warning message generating unit comprises:
The early warning level mapping subunit is used for determining a corresponding early warning level identification code according to the early warning level triggered by the risk level result output by the threshold value judging unit, wherein the primary early warning mapping is W1 and represents local slippage, the secondary early warning mapping is W2 and represents regional liquefaction, and the tertiary early warning mapping is W3 and represents pipeline instability;
The message segment filling unit is used for constructing the structural content containing the following fields for each triggering early warning event:
1) Early warning level identification;
2) Triggering time;
3) Early warning center coordinates;
4) Corresponding to the risk coefficient value;
5) Suggested treatment instructions;
And the structured format coding subunit is used for coding the field content which is built according to a preset format to generate a unified message format.
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