CN118936747A - A hydraulic pump leakage status identification system - Google Patents
A hydraulic pump leakage status identification system Download PDFInfo
- Publication number
- CN118936747A CN118936747A CN202411419907.1A CN202411419907A CN118936747A CN 118936747 A CN118936747 A CN 118936747A CN 202411419907 A CN202411419907 A CN 202411419907A CN 118936747 A CN118936747 A CN 118936747A
- Authority
- CN
- China
- Prior art keywords
- hydraulic pump
- data
- real
- leakage
- time
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/002—Investigating fluid-tightness of structures by using thermal means
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B51/00—Testing machines, pumps, or pumping installations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
- G01M3/04—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
- G01M3/24—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
- G01M3/26—Investigating fluid-tightness of structures by using fluid or vacuum by measuring rate of loss or gain of fluid, e.g. by pressure-responsive devices, by flow detectors
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
- G06F18/2131—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on a transform domain processing, e.g. wavelet transform
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Mechanical Engineering (AREA)
- Fluid-Pressure Circuits (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
本发明涉及液压泵状态识别技术领域，且公开了一种液压泵泄漏状态识别系统。该液压泵泄漏状态识别系统，通过对采集液压泵工作过程中的实时振动数据、实时声音数据、实时流量数据以及实时温度数据，并对这些数据进行特征提取，得出振动数据特征、声音数据特征、流量数据特征以及温度数据特征，并将得出的这些特征组成组成综合特征向量，并将其带入预设的模型进行进行计算当前液压泵的状态值，并将其与状态阈值对比，判定液压泵是否出现泄漏，当出现泄漏时，发出预警警报，从而可以在液压泵工作过程中，实时对其检测，避免液压泵在工作过程中发生泄漏，无法及时的发现，进而导致液压泵损坏程度加深，增加液压泵维护成本。
The present invention relates to the technical field of hydraulic pump state recognition, and discloses a hydraulic pump leakage state recognition system. The hydraulic pump leakage state recognition system collects real-time vibration data, real-time sound data, real-time flow data and real-time temperature data during the operation of the hydraulic pump, extracts features from these data, obtains vibration data features, sound data features, flow data features and temperature data features, and combines these features into a comprehensive feature vector, which is then brought into a preset model to calculate the current state value of the hydraulic pump. , and compare it with the status threshold to determine whether the hydraulic pump is leaking. When a leak occurs, a warning alarm is issued, so that the hydraulic pump can be detected in real time during its operation to avoid leakage of the hydraulic pump during operation. The failure to detect it in time will lead to further damage to the hydraulic pump and increase the maintenance cost of the hydraulic pump.
Description
Technical Field
The invention relates to the technical field of hydraulic pump state identification, in particular to a hydraulic pump leakage state identification system.
Background
A hydraulic pump is a device that converts mechanical energy into hydraulic energy, which is a core component in a hydraulic system. The hydraulic pump enables a hydraulic cylinder or a hydraulic motor in the hydraulic system to perform various mechanical actions by providing a flow of pressurized oil. The types of hydraulic pumps are numerous, including gear pumps, vane pumps, plunger pumps, etc.;
At present, the hydraulic pump leakage identification usually depends on observing the state of hydraulic oil, monitoring the temperature of a hydraulic system, visually checking or using a detecting instrument, and the identification mode usually needs to stop the hydraulic pump for checking, so that the hydraulic pump cannot be detected and identified in the working process, when the hydraulic pump leaks in the working process, the hydraulic pump cannot be timely found, the damage degree of the hydraulic pump is deepened, and the maintenance cost of the hydraulic pump is increased.
Disclosure of Invention
(One) solving the technical problems
Aiming at the defects of the prior art, the invention provides a hydraulic pump leakage state identification system, which has the advantages of detecting the hydraulic pump in real time in the working process of the hydraulic pump, avoiding the leakage of the hydraulic pump in the working process, being incapable of finding in time and the like, and solves the problems.
(II) technical scheme
In order to achieve the above purpose, the present invention provides the following technical solutions: a hydraulic pump leakage state identification system comprises a hydraulic pump data collection module, a hydraulic pump data processing module, a hydraulic pump data analysis module and a hydraulic pump leakage alarm module;
the hydraulic pump data collection module is used for collecting real-time vibration data of the hydraulic pump during working in real time Real-time sound dataReal-time flow dataReal-time temperature dataThe hydraulic pump data collection module sends the collected real-time data to a hydraulic pump data processing module connected with the hydraulic pump data collection module;
the hydraulic pump data processing module respectively processes real-time vibration data Real-time sound dataReal-time flow dataReal-time temperature dataExtracting features to obtain vibration data featuresSound data characteristicsFlow data characterizationTemperature data characterizationAnd characterizing vibration dataSound data characteristicsFlow data characterizationTemperature data characterizationComposition of the integrated feature vectorAnd integrates the feature vectorsIs carried into a linear discriminant model, and a state value is calculatedWhen the hydraulic pump data processing module calculates a state valueThen, the data is sent to a hydraulic pump data analysis module;
The hydraulic pump data analysis module analyzes the state value And a state thresholdComparing to obtain whether the hydraulic pump leaks, generating a leakage signal when the hydraulic pump data analysis module judges that the hydraulic pump leaks, and sending the leakage signal to the hydraulic pump leakage alarm module;
And the hydraulic pump leakage alarm module sends out an alarm after receiving the leakage signal.
Preferably, the vibration data featureThe computational expression is as follows:
In the formula (i), Representing the fast fourier transform extracted spectral features,Representing spectral features of real-time vibration data extracted by fast fourier changes, i.e. vibration data features。
Preferably, the sound data featureThe computational expression is as follows:
In the formula (i), Representing the fast fourier transform extracted spectral features,Representing spectral features of real-time sound data extracted by fast fourier transform, i.e. sound data features。
Preferably, the flow data featuresThe computational expression is as follows:
In the formula (i), Representing the fast fourier transform extracted spectral features,Representing spectral features of real-time flow data extracted by fast fourier changes, i.e. flow data features。
Preferably, the temperature data featuresThe computational expression is as follows:
In the formula (i), Representing the fast fourier transform extracted spectral features,Representing spectral features of real-time temperature data extracted by fast fourier changes, i.e. temperature data features。
Preferably, the integrated feature vectorThe computational expression is as follows:
In the formula (i), Representing different types of data characteristics of the hydraulic pump during operation, for describing various states of the hydraulic pump during operation.
Preferably, the state valueThe computational expression is as follows:
In the formula (i), Model parameters representing a linear discriminant model,Representing the bias, and obtaining the model parameters and the bias through training iteration of the model in an experimental environment,A weighted sum of the input features is represented,And adjusting the output of the linear discriminant model for the bias term.
Preferably, the state valueAnd a state thresholdThe expression for comparison is as follows:
In the formula (i), The decision is represented by a representation of the decision,Indicating whenWhen=1, the state value is representedGreater than the state thresholdThe hydraulic pump is leaked, and the leakage occurs,Indicating whenWhen=0, the state value is representedLess than the state thresholdIndicating that no leakage has occurred in the hydraulic pump.
Preferably, when the hydraulic pump data analysis module is presentWhen the hydraulic pump data analysis module is in the condition of being=1, the hydraulic pump data analysis module judges that the hydraulic pump leaks, generates a leakage signal and sends the leakage signal to the hydraulic pump leakage alarm module.
Preferably, the hydraulic pump leakage alarm module further comprises a display screen and a buzzer, when the hydraulic pump leakage alarm module receives a leakage signal, the display displays leakage information, and the buzzer sends out warning sound.
Compared with the prior art, the invention provides a hydraulic pump leakage state identification system, which has the following beneficial effects:
the invention collects real-time vibration data in the working process of the hydraulic pump Real-time sound dataReal-time flow dataReal-time temperature dataAnd extracting features of the data to obtain vibration data featuresSound data characteristicsFlow data characterizationTemperature data characterizationAnd combining the obtained features into a comprehensive feature vectorAnd the hydraulic pump is brought into a preset model to calculate the state value of the current hydraulic pumpAnd comparing the detection result with the state threshold value to judge whether the hydraulic pump leaks, and when the hydraulic pump leaks, sending out an early warning alarm, so that the detection can be carried out on the hydraulic pump in real time in the working process of the hydraulic pump, the hydraulic pump is prevented from leaking in the working process, the hydraulic pump cannot be found timely, the damage degree of the hydraulic pump is deepened, and the maintenance cost of the hydraulic pump is increased.
Drawings
FIG. 1 is a schematic flow chart of the system of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a hydraulic pump leakage state recognition system includes a hydraulic pump data collection module, a hydraulic pump data processing module, a hydraulic pump data analysis module, and a hydraulic pump leakage alarm module;
The hydraulic pump data collection module is used for collecting real-time vibration data of the hydraulic pump during working in real time Real-time sound dataReal-time flow dataReal-time temperature dataThe hydraulic pump data collection module sends the collected real-time data to a hydraulic pump data processing module connected with the hydraulic pump data collection module;
The hydraulic pump data processing module is used for real-time vibration data Feature extraction is performed, and the expression of the extraction is as follows:
In the formula (i), Representing the fast fourier transform extracted spectral features,Representing spectral features of real-time vibration data extracted by fast fourier changes, i.e. vibration data features。
The hydraulic pump data processing module processes real-time sound dataFeature extraction is performed, and the expression of the extraction is as follows:
In the formula (i), Representing the fast fourier transform extracted spectral features,Representing spectral features of real-time sound data extracted by fast fourier transform, i.e. sound data features。
The hydraulic pump data processing module is used for processing real-time flow dataFeature extraction is performed, and the expression of the extraction is as follows:
In the formula (i), Representing the fast fourier transform extracted spectral features,Representing spectral features of real-time flow data extracted by fast fourier changes, i.e. flow data features。
Hydraulic pump data processing module versus temperature data characteristicsFeature extraction is performed, and the extraction expression is as follows:
In the formula (i), Representing the fast fourier transform extracted spectral features,Representing spectral features of real-time temperature data extracted by fast fourier changes, i.e. temperature data features。
The frequency spectrum characteristics are extracted by using the fast Fourier change, so that corresponding characteristics of corresponding data generated by the hydraulic pump in the working process can be obtained, and the working state of the hydraulic pump can be analyzed according to the characteristics;
The hydraulic pump data processing module characterizes the vibration data Sound data characteristicsFlow data characterizationTemperature data characterizationComposition of the integrated feature vectorThe expression is as follows:
In the formula (i), Data characteristics representing different types of hydraulic pumps in the working process are used for describing various states of the hydraulic pumps in the working process;
the hydraulic pump data processing module is also provided with a linear discrimination model, and when the hydraulic pump data processing module obtains the comprehensive feature vector Then, the obtained product is put into a linear discriminant model to calculate a state valueThe calculation expression is as follows:
In the formula (i), Model parameters representing a linear discriminant model,Representing the bias, and obtaining the model parameters and the bias through training iteration of the model in an experimental environment,A weighted sum of the input features is represented,As a bias term, adjusting the output of the linear discriminant model;
Calculating to obtain state value After that, the hydraulic pump data processing module sends the data to the hydraulic pump data analysis module, and the hydraulic pump data analysis module sends the state valueAnd a state thresholdAnd comparing to obtain whether the hydraulic pump leaks or not, wherein the specific comparison mode is as follows:
In the formula (i), The decision is represented by a representation of the decision,Indicating whenWhen=1, the state value is representedGreater than the state thresholdThe hydraulic pump is leaked, and the leakage occurs,Indicating whenWhen=0, the state value is representedLess than the state thresholdIndicating that no leakage has occurred in the hydraulic pump;
It should be noted that the number of the components, Representing if state valueGreater than the state thresholdWhen in use, then=1，Indicating, if the state valueLess than or equal to the state thresholdWhen in use, then=0；
When the hydraulic pump data analysis module is relative to the state valueAfter analysis, the result isThe hydraulic pump data analysis module judges that the hydraulic pump leaks at the moment, and then generates a leakage signal and sends the leakage signal to the hydraulic pump alarm module;
The hydraulic pump alarm module consists of a display screen and a buzzer, when the hydraulic pump leakage alarm module receives a leakage signal, the display displays leakage information, the buzzer gives out alarm sound, and an operator timely closes the hydraulic pump according to the leakage information displayed by the display and the audible alarm sound and maintains the hydraulic pump to avoid further expansion of leakage;
It should be noted that the fast fourier transform extraction of spectral features mentioned above is an existing well-established algorithm model, which is an important signal processing tool for converting a time domain signal into a frequency domain signal, and the spectral features of the signal can be extracted by FFT, which has many advantages in the analysis of vibration data, sound data, flow data and temperature data, in particular as follows:
vibration data characteristics, through FFT, can decompose the vibration signal into different frequency components, help discern the unusual vibration source in the hydraulic pump;
the characteristic of sound data, through FFT, can separate different frequency components in the sound signal, thus confirm whether the hydraulic pump appears the unusual noise;
The flow data features can analyze the periodic fluctuation in the fluid flow in the hydraulic pump through FFT, and are used for identifying the working state of the hydraulic pump, and when abnormal fluctuation occurs, the phenomenon of blockage or leakage of the surface hydraulic pump is likely to occur;
The temperature data features can identify the periodic variation in the temperature signal through FFT, can carry out spectral analysis and identification on the periodic heat generated by the hydraulic pump in the operation process, and when a hot spot or an overheat area is formed, the heat dissipation abnormality of the part of the hydraulic pump is indicated, and the fault possibly occurs;
After the hydraulic pump leaks, the temperature of the leaking part of the hydraulic pump can be obviously increased to form local hot spots, and meanwhile, the phenomenon of flow reduction can occur, so that the actual output flow of the hydraulic pump can be smaller than a preset value, irregular fluctuation of hydraulic pressure can be caused, the vibration can be increased, the reason of the vibration increase comprises that the internal pressure of the hydraulic pump leaks is changed, the vibration data can be abnormal, the leakage can also cause the hydraulic oil to generate bubbles, cavitation phenomenon occurs, the vibration of the hydraulic pump is increased, the leakage of the hydraulic pump can also cause the increase of noise, and a large amount of abnormality is caused.
By collecting real-time vibration data in the working process of the hydraulic pumpReal-time sound dataReal-time flow dataReal-time temperature dataAnd extracting features of the data to obtain vibration data featuresSound data characteristicsFlow data characterizationTemperature data characterizationAnd combining the obtained features into a comprehensive feature vectorAnd the hydraulic pump is brought into a preset model to calculate the state value of the current hydraulic pumpAnd comparing the detection result with the state threshold value to judge whether the hydraulic pump leaks, and when the hydraulic pump leaks, sending out an early warning alarm, so that the detection can be carried out on the hydraulic pump in real time in the working process of the hydraulic pump, the hydraulic pump is prevented from leaking in the working process, the hydraulic pump cannot be found timely, the damage degree of the hydraulic pump is deepened, and the maintenance cost of the hydraulic pump is increased.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411419907.1A CN118936747A (en) | 2024-10-12 | 2024-10-12 | A hydraulic pump leakage status identification system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411419907.1A CN118936747A (en) | 2024-10-12 | 2024-10-12 | A hydraulic pump leakage status identification system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN118936747A true CN118936747A (en) | 2024-11-12 |
Family
ID=93346794
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411419907.1A Pending CN118936747A (en) | 2024-10-12 | 2024-10-12 | A hydraulic pump leakage status identification system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118936747A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119688191A (en) * | 2025-02-21 | 2025-03-25 | 国家管网集团北方管道有限责任公司 | Pump unit sealing fault detection method and system based on voiceprint characterization |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20210026321A1 (en) * | 2019-07-26 | 2021-01-28 | Fluid Power AI Inc. | System and method for evaluating hydraulic system events and executing responses |
| CN112943595A (en) * | 2021-02-07 | 2021-06-11 | 三一重工股份有限公司 | Hydraulic pump fault prediction method, hydraulic pump fault prediction device, electronic equipment and storage medium |
| CN114048786A (en) * | 2021-11-23 | 2022-02-15 | 联陆智能交通科技(上海)有限公司 | Method and system for identifying leakage state of hydraulic pump based on feature optimization |
| CN115822943A (en) * | 2022-11-18 | 2023-03-21 | 太原理工大学 | Hydraulic Pump Leakage Fault Diagnosis Method |
| CN116882164A (en) * | 2023-07-07 | 2023-10-13 | 郑州轻工业大学 | Valve cooling equipment fault diagnosis method based on Fisher ratio and improved LSSVM algorithm |
| CN118669317A (en) * | 2024-06-24 | 2024-09-20 | 苏州铼洛威液压泵有限公司 | Hydraulic pump fault detection system and method |
-
2024
- 2024-10-12 CN CN202411419907.1A patent/CN118936747A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20210026321A1 (en) * | 2019-07-26 | 2021-01-28 | Fluid Power AI Inc. | System and method for evaluating hydraulic system events and executing responses |
| CN112943595A (en) * | 2021-02-07 | 2021-06-11 | 三一重工股份有限公司 | Hydraulic pump fault prediction method, hydraulic pump fault prediction device, electronic equipment and storage medium |
| CN114048786A (en) * | 2021-11-23 | 2022-02-15 | 联陆智能交通科技(上海)有限公司 | Method and system for identifying leakage state of hydraulic pump based on feature optimization |
| CN115822943A (en) * | 2022-11-18 | 2023-03-21 | 太原理工大学 | Hydraulic Pump Leakage Fault Diagnosis Method |
| CN116882164A (en) * | 2023-07-07 | 2023-10-13 | 郑州轻工业大学 | Valve cooling equipment fault diagnosis method based on Fisher ratio and improved LSSVM algorithm |
| CN118669317A (en) * | 2024-06-24 | 2024-09-20 | 苏州铼洛威液压泵有限公司 | Hydraulic pump fault detection system and method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119688191A (en) * | 2025-02-21 | 2025-03-25 | 国家管网集团北方管道有限责任公司 | Pump unit sealing fault detection method and system based on voiceprint characterization |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Al-Obaidi | Detection of cavitation phenomenon within a centrifugal pump based on vibration analysis technique in both time and frequency domains | |
| McKee et al. | A vibration cavitation sensitivity parameter based on spectral and statistical methods | |
| CN118410389B (en) | Intelligent monitoring system for faults of intelligent clothes equipment | |
| GB2619825A (en) | A fault diagnosis method of blast blower and apparatus, electronic device thereof | |
| CN107461342A (en) | A kind of centrifugal pump fault inline diagnosis method and system | |
| CN118936747A (en) | A hydraulic pump leakage status identification system | |
| CN111365083A (en) | Thermal parameter-based turbine through-flow part fault diagnosis method | |
| CN117879168A (en) | Real-time early warning system of thermal power station based on multimode fuses | |
| CN118885947B (en) | Pressure detection early warning system and method based on pipeline network collection data | |
| CN111811820A (en) | A method for evaluating the vibration state of steam turbine main engine based on multi-parameter comparison | |
| CN118243200A (en) | Gas turbine flowmeter fault diagnosis method and system | |
| CN116617616B (en) | A fire protection pipeline monitoring method, system, terminal equipment and storage medium | |
| CN119669991A (en) | A rotor surface magnetic field characteristics real-time monitoring and damage assessment system and method | |
| CN118549780B (en) | Transformer partial discharge sensing system | |
| CN202661269U (en) | Compound fault diagnosis test platform of diesel engine | |
| Cai et al. | A data-driven early micro-leakage detection and localization approach of hydraulic systems | |
| CN116071053B (en) | Reciprocating compressor state early warning system based on digital twinning | |
| CN112711850A (en) | Unit online monitoring method based on big data | |
| Al-Obaidi et al. | Experimental investigation to utilize Low-cost sensors of early cavitation prediction in axial pump based on acoustic and vibration approaches | |
| CN120384882A (en) | A slurry circulation pump state monitoring method and related equipment | |
| KR20150119563A (en) | Fault diagnosis system and method for hydraulic breaker | |
| CN102967420A (en) | On-line leak detection device and method for heat exchanger | |
| CN118565742A (en) | Online early warning method and system for water cooling system | |
| Goel et al. | Exploring the diagnostic potential of infrared thermography for experimental assessment of cavitation and air entrainment-induced faults in centrifugal pumps | |
| Zhang et al. | Development of low-cost air-based hydraulic leakage detection system through real-time pressure decay data acquisition technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20241112 |