RU232170U1 - DTSCAN ROLLING STOCK DIAGNOSTICS UNIT - Google Patents

Abstract

The utility model relates to the field of predictive diagnostics of the technical condition of rolling stock and transport infrastructure. The DTscan rolling stock diagnostics unit is placed on the rolling stock (RS) and collects, stores, processes and analyzes data to assess the current technical condition and predict the condition of the RS and infrastructure elements for a specified period of time or mileage, depending on the operating conditions. The DTscan rolling stock diagnostics unit is made in a single housing and includes measuring modules for assessing the parameters of the technical means of the RS (IM); a coordinate determination module (CDM) that determines the location of the RS on the track; a video data module (VDM) that records video from IP cameras and analyzes the condition of the track and infrastructure; a system analytics module (SAM) that processes and analyzes data from the IM, CDM, VDM and informs in the event of a critical condition being determined; a control module (CM) that coordinates the work of other modules and ensures the collection, storage and transmission of data via the wireless data transmission module (WDM); WDM for transmitting data to a remote server via Ethernet. All modules (components of the DTscan rolling stock diagnostics unit) are located on the rolling stock in a single housing, connected by harness wiring and fasteners, which ensures their structural unity and a single purpose of the DTscan rolling stock diagnostics unit. Increased diagnostic efficiency and reliability of the railway transport system are achieved.

Description

FIELD OF TECHNOLOGY TO WHICH THE UTILITY MODEL RELATS

The utility model relates to the field of predictive diagnostics of the technical condition of rolling stock and transport infrastructure in order to ensure the safety, reliability and efficiency of the functioning of the railway transport system.

LEVEL OF TECHNOLOGY

The railway industry is experiencing a growing need for tools and devices for diagnosing the technical condition of railway transport, providing real-time monitoring and timely detection of the occurrence and development of defects in order to eliminate them and prevent rolling stock failures.

The existing level of technology includes a microprocessor control and diagnostics system for a locomotive (MPCSiD), which includes a monitor unit, a central computer unit (CCU), contactor control units, control panel communication units, input signal units, an excitation control unit (ECU), voltage-to-code converters (VDC), pressure sensor communication units, current pressure sensor communication units, a rotation angle sensor communication unit, and a locomotive indicator unit. MPCSiD also includes a voice information console, a system for interaction with a locomotive via digital technological radio communication, and an electric brake regulator. All units and devices included in the MPSUiD are distributed among the locomotive compartments and are connected to each other in a network via a serial duplicate interface, while the PNKV units are connected to the BCV via the BUV via separate communication channels for collecting and transmitting data from the PNKV to the BCV (RU 116114 U1, IPC B61L 29/00, published 20.05.2012).

The disadvantages of the known technical solution are:

there is no analysis of the causes of failures;

there is no possibility of assessing the remaining resource of PS units;

the ability to perform descriptive and predictive analytics is limited as the solution does not include advanced technologies such as machine learning and neural networks;

the speed of information transfer and analysis is limited, which can lead to delays in identifying and responding to problems;

a wide range of monitoring of the locomotive and infrastructure condition is not provided, since a limited set of sensors is used, which can lead to underestimation of risks and problems;

the method does not provide for effective feedback mechanisms with control centers and drivers, there is no common line of communication with the security system, which can complicate prompt response to problems and emergency situations;

there is no possibility of application in a wide range of railway transport.

Also known is the microprocessor control and diagnostics system MPSUiD of an electric train, which provides control and diagnostics of the electric train, as well as data transfer between various devices and systems, organized at three levels of functionality (RU 2733594 C2, IPC B60L 15/32, published 05.10.2020). At the first level, there are subsystems for measuring various parameters, such as current, voltage, pressure and insulation resistance, an electricity meter. Also included are communication subsystems via CAN, RS485 and Ethernet lines for interaction with various systems of the electric train, including doors, a radio station, a brake system, an air conditioning system and a passenger information system. At the second level, there is a monitor, a communication unit with the console, an input signal unit, a central control unit and a contactor control unit. The third level includes subsystems for automatic train control, diagnostics, traffic safety and technological digital radio communication.

The disadvantages of the known technical solution are:

there is no analysis of the causes of failures;

there is no possibility of assessing the remaining resource of PS units;

The electric train's MPSUiD has limited capabilities compared to a more complete rolling stock diagnostic system, which includes a wide range of sensors and modules for monitoring various aspects of train operation;

the declared data processing tools are insufficient for the effective analysis of large volumes of information, which may reduce the effectiveness of diagnostics and management;

The ability to perform descriptive and predictive analytics is limited as the solution does not include advanced technologies such as machine learning and neural networks.

The existing level of technology also includes a comprehensive automated system for recording, monitoring, troubleshooting technical equipment failures and analyzing their reliability (KASANT), which automatically records the facts of technical equipment failure based on data entered by the train dispatcher into the automated schedule of completed train movements, and generates information on technical equipment failures from the railway transport infrastructure facilities. To ensure the correct recording of the fact of failure, the system implements a specialized mechanism for checking incoming data with the ability to subsequently combine them by users (KASANT System: Tasks, Possibilities, Development Prospects, E.N. Rozenberg, I.N. Rozenberg, A.M. Zamyshlyaev, G.B. Proshin, Zheleznodorozhny Transport, 2008, No. 9).

The known system has the following disadvantages:

analysis of the frequency of failures and the reasons for failures is impossible due to the fragmentation of the data obtained;

the system is not intended for analysis of technical aspects and causes of failures;

information is collected on various nodes separately and is not related to the state of the PS and the composition as a whole;

there is no possibility of assessing the remaining resource of PS units;

diagnostics cannot be performed in real time;

there is no possibility of descriptive and predictive analytics in diagnostic systems used in PS.

Statistical data on PS failures indicate that known systems for diagnostics and monitoring of failures have a number of shortcomings, often being unable to promptly identify failure situations and, thus, ensure reliability and increase the safety of both the unit and the PS fleet.

These shortcomings of existing diagnostic systems do not allow for a comprehensive analysis of the causes of failures and the implementation of necessary measures to prevent failures of individual units, and the implementation of a system that makes a decision on the possibility of operating the substation.

The proposed technical solution ensures the collection, processing and analysis of data to predict possible failures and a prognostic assessment of the condition of rolling stock and infrastructure, which reduces the time and costs of maintenance and repair and increases the level of safety and reliability of traffic.

DISCLOSURE OF THE ESSENCE OF THE UTILITY MODEL

The technical result is achieved in that the declared DTscan rolling stock diagnostic unit, installed on the rolling stock, collects, stores, processes and analyzes data, on the basis of which the current technical condition is assessed and a forecast is made of the condition of the rolling stock and infrastructure elements for a specified period of time or mileage depending on the operating conditions, and also carries out wireless data transmission to a remote server in real time in the presence of cellular communication.

The DTscan rolling stock diagnostic unit is made in a single housing and consists of:

measuring modules 1 for evaluating the parameters of technical means of the PS (IM), measuring the characteristics of the PS using current, acceleration and acoustic emission sensors and converting sensor signals into digital form;

coordinate determination module 2 (CDM), which determines the coordinates of the PS position on the route;

video data module 3 (VDM), which records video data, analyzes the presence of obstacles, people within the dimensions of the PS, as well as the state of the infrastructure, and evaluates the need for further response to the event;

control module 4 (CM), located in the on-board unit of the system 5 (OBS), and controlling the operation of the remaining modules of the rolling stock diagnostic unit DTscan, data collection and storage, data transmission via the MBPD, providing power supply to the remaining modules of the rolling stock diagnostic unit DTscan, while the elements of the module intended for receiving and digitizing primary data (ADC modules) can be located both in the BBS and on the elements of the rolling stock;

system analytics module 6 (SAM), located in the BBS and providing filtering and processing of primary data from the IM, IOC and MVD, selection from the on-board data base and analytics algorithms of the required processing functions and criteria, data analysis, conclusions about the state of the train in real time, as well as in the future development of failures, informing the driver and dispatcher when determining a critical state;

wireless data transmission module 7 (information exchange) (WDM), which provides wireless data transmission over the network to a remote server directly via Ethernet and data reception from a remote server, and can be implemented as a Wi-Fi router with an antenna located in the BBS. If transmission is impossible, the data is accumulated and transmitted when a connection appears.

The MSA can be designed with the ability to analyze the state of the PS and infrastructure in real time and predict possible failures based on data received from the IM, IOC and MVD, while the analysis can be carried out using machine learning algorithms and neural networks.

The Ministry of Internal Affairs can be equipped with machine vision algorithms to analyze the state of infrastructure and identify obstacles in the path of the PS.

All modules (components of the DTscan rolling stock diagnostics unit) are located on the rolling stock in a single housing: connected by harness wiring and fasteners, which ensures their structural unity and the single purpose of the DTscan rolling stock diagnostics unit.

BRIEF DESCRIPTION OF DRAWINGS AND OTHER GRAPHIC MATERIALS

The essence of the utility model is explained in Fig. 1, which displays a diagram of the DTscan rolling stock diagnostic unit, where:

1 - measuring modules,

2 - coordinate determination module,

3 - video data module,

4 - control module,

5 - on-board unit of the system,

6 - system analytics module,

7 - wireless data transmission module,

IMPLEMENTATION OF A UTILITY MODEL

The implementation of the DTscan rolling stock diagnostics unit, designed for remote monitoring of the rolling stock technical condition, forecasting the possibility of operation and making a decision on its movement, is expected to be modular, which allows for the formation of the necessary configuration taking into account its operation on various types of rolling stock.

For rolling stock equipped with motorized wheel pairs, the DTscan rolling stock diagnostics unit may include IM, represented by current sensors and accelerometers, MOC, MVD and BBS, containing MU, MSA, power supply, filter, switch, switches and connectors, MBPD, containing an antenna and a router with a GPS receiver.

For rolling stock whose bogies do not have traction motors, the DTscan rolling stock diagnostic unit may include IM, represented by accelerometers, MOC, MVD and BBS, containing MU, MSA, power supply, filter, switch, switches and connectors, MBPD, containing an antenna and a router with a GPS receiver.

The DTscan rolling stock diagnostics unit can be expanded with additional equipment and include IM, represented by current sensors, accelerometers, acoustic sensors with amplifiers and matching devices, MOC, MVD, BBS, distinguished by the fact that it includes a CAN bus converter and a switch to increase the inputs for connecting additional devices.

To achieve the technical result within the framework of the proposed utility model, the following operations are carried out.

The DTscan rolling stock diagnostics unit collects information from connected sensors (accelerometers, acoustic sensors, current sensors). Data from the sensors allows for continuous analysis of the rolling stock technical condition, predicting faults and determining the need for preventive maintenance. The DTscan rolling stock diagnostics unit provides for recording signals from installed sensors for diagnostics of the rolling stock structure condition during movement, including during passenger transportation.

Accelerometers are installed on at least one axle box of each axle of the PS bogie, on the bogie frame above the outer equipped axles, on the side of the equipped axle box, and also on the housings of traction motors and traction gearboxes, if any.

To diagnose the technical condition of traction electric motors installed at substations, current sensors are installed at the input of each phase of the stator winding.

The current position of the PS is determined using the IOC in real time.

Signals are received from IP cameras, the Ministry of Internal Affairs analyzes the presence of obstacles, people and the state of infrastructure using machine vision technologies.

Data processing and analysis in the BBS is carried out by the MSA and MU. The MSA filters and processes the collected data, analyzes the state of the rolling stock and infrastructure in real time, predicts possible failures for the next 4 hours, while the analysis can be carried out using machine learning algorithms and neural networks; MU coordinates the work of all modules of the DTscan rolling stock diagnostics unit, ensures the collection and storage of data, and their transmission to a remote server.

Transfer of collected and processed data from the PS to the remote server is provided by the MBPD via Ethernet. The router and antenna in the MBPD organize data transfer in several ranges and standards. In the absence of direct communication, the MBPD can operate in the mode of temporary data accumulation in the absence of communication for subsequent data transfer to the remote server via Ethernet.

Based on the analysis of data and forecasts, recommendations are developed for drivers, dispatchers and technical personnel to prevent possible failures and optimize maintenance and repairs.

The relevant recommendations and warnings are transmitted to drivers and dispatchers in real time so that necessary measures can be taken.

Thus, the DTscan rolling stock diagnostics unit records data from sensors connected to the measuring module for recording measured values, collecting, transmitting, processing, analyzing and storing data, converting sensor signals into digital form, generating data for indicating the state of monitored units, assessing the current state and trends in changes in the structural elements of the rolling stock based on calculations and modeling, and generating reports. The automated data analysis process does not require operator participation, which reduces the number of errors associated with the human factor.

The use of the DTscan rolling stock diagnostic unit helps to increase the safety and availability of railway tracks and rolling stock (locomotives, electric trains, track equipment) during operation due to continuous diagnostics of parameters.

Experimental data have been obtained confirming the industrial applicability and the possibility of obtaining a technical result when implementing a utility model, on the operation of the DTscan rolling stock diagnostic unit on such rolling stock as the TEM7 and TE18 diesel locomotives, the Sapsan and Lastochka passenger electric trains, and the Malakhit freight electric locomotive.

Claims (3)

1. The DTscan rolling stock diagnostics unit, located on the rolling stock, collects, processes and analyzes data in real time to predict the state of the rolling stock and infrastructure elements, as well as wirelessly transmits data to a remote server for data processing and real-time recommendation generation, equipped with measuring modules for collecting data on the technical state of the rolling stock using sensors, a coordinate determination module for determining the position of the rolling stock, a video data module for recording and analyzing video images from IP cameras, a control module in the on-board unit of the system for coordinating the operation of all modules included in the collection, storage and transmission of data, a system analytics module in the on-board unit of the system for processing and analyzing data, a wireless data transmission module in the on-board unit of the system for transmitting data to a remote server via Ethernet, wherein all modules of the DTscan rolling stock diagnostics unit are located in a single housing, connected by harness wiring and fasteners, which ensures their structural unity and a single purpose of the DTscan rolling stock diagnostics unit. 2. The unit according to item 1, characterized in that the system analytics module (SAM) is designed with the ability to analyze the state of the PS and infrastructure in real time and predict possible failures based on data received from the measuring modules, the coordinate determination module and the video data module, wherein the analysis is carried out using machine learning algorithms and neural networks. 3. The unit according to paragraph 1 or 2, characterized in that the video data module (VDM) is equipped with machine vision algorithms for analyzing the state of the infrastructure and identifying obstacles in the path of the PS.

Images