CN112014593B - Device and method for monitoring and evaluating quality condition of railway track basic equipment - Google Patents
Device and method for monitoring and evaluating quality condition of railway track basic equipment Download PDFInfo
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- G—PHYSICS
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- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
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Abstract
The invention relates to a device and a method for monitoring and evaluating the quality condition of basic equipment of a railway track, which are characterized in that after a signal diagram of the basic equipment of the railway track in working is drawn, the signal diagram is subjected to region division, then a plurality of signal sensors are arranged on the basic equipment of the railway track, the signal value of the basic equipment of the railway track in working is monitored in real time and compared with a signal frequency domain diagram obtained in the last step, so as to judge the region of the signal value of the real-time monitoring on the signal frequency domain diagram, and finally, the working condition of the basic equipment of the railway track is predicted and judged according to the region of the signal value of the basic equipment of the railway track in real time monitoring in the last step in the signal frequency domain diagram, so that the real-time on-line monitoring of the track and the prediction, judgment, evaluation and analysis of the working condition of the basic equipment of the railway track are realized.
Description
Technical Field
The invention relates to the technical field of safety monitoring of railway track basic equipment components, in particular to a device and a method for monitoring and evaluating quality conditions of railway track basic equipment.
Background
At present, railway track basic equipment and relevant track auxiliary components such as turnouts, frog and the like in China can generate potential safety hazards such as abrasion, cracking, corrosion and even peeling in the long-time running and using processes, for the operation management part of the railway track basic equipment, the railway track basic equipment and the relevant auxiliary components thereof need to be regularly checked, the safety check needs to be carried out on the whole road network, a large amount of manpower and material resources are consumed, and the railway track basic equipment and the relevant auxiliary components thereof can only be checked when no train passes through, so that the checking efficiency is very low, and the ever-increasing railway track basic equipment transportation capacity requirement in China can not be completely met. Therefore, a new method for analyzing, monitoring and early warning the quality condition of the basic equipment of the railway track is developed to meet the requirement of transportation of the basic equipment of the modern railway track, the working state of the basic equipment of the railway track is combined with a sensor and the Internet of things to carry out unmanned remote system monitoring, evaluation and prediction judgment in the running process of a vehicle of the basic equipment of the railway track, the fault and the potential safety hazard of the basic equipment of the railway track are found in time, corresponding measures are taken, the accident is avoided, the monitoring efficiency is improved, and the monitoring cost is reduced.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide a method for analyzing the quality condition of railway track basic equipment, so as to realize unmanned remote system monitoring, evaluation and prediction judgment of the working state of the railway track basic equipment by combining a sensor and the Internet of things.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a quality condition monitoring and evaluating device for railway track basic equipment comprises a data acquisition module, a data communication module and a data processing and displaying module, wherein the data acquisition module is used for monitoring and acquiring signals generated by the railway track basic equipment during working; the data communication module is used for transmitting the signal value acquired by the data acquisition module to the data processing display module; and the data processing and displaying module is used for carrying out data analysis and graph conversion on the signal data transmitted by the data communication module to generate and display a data schematic diagram.
Furthermore, the device also comprises a power supply module, wherein the data communication module adopts a wired or wireless data communication mode; the data processing and displaying module also comprises a data storage device.
Further, the invention also relates to a quality condition monitoring and evaluating method of the railway track basic equipment of any one device, which comprises the following steps:
1) arranging a plurality of sensors on the railway track basic equipment, wherein the sensors are used for acquiring signals generated when the railway track basic equipment works; collecting signals according to a certain rule or interval time, summarizing the signals into time domain data according to recording time, and storing the time domain data;
2) drawing the signal data acquired in the step 1) to obtain a signal diagram; the method comprises the steps of drawing a graph according to a time axis corresponding to signal data, recording signal values on a time domain graph along with the time, obtaining a signal data time domain graph by taking a horizontal axis as time and taking a vertical axis as the signal value, and obtaining a frequency correlation graph of the signal values, namely a signal frequency domain graph, by carrying out Fourier transform on the time domain data.
3) Selecting signals generated when the actual measurement quality conditions of a plurality of railway track basic equipment have characteristics, and recording the signals as characteristic signal values; and the larger the measured data amount is, the more stable and accurate the result is, so that the big data acquires the relevant measured data and the corresponding records are stored one by one.
4) Substituting the characteristic signal value measured in the step 3) into the signal diagram obtained by drawing in the step 2), and carrying out region division on the signal diagram according to the position of the characteristic signal value on the signal diagram; after a large amount of actually measured data is used for marking the corresponding actually measured quality conditions, the region distribution on the signal diagram is primarily divided, and the regions are respectively regions of corresponding signal values of various quality conditions, such as a general normal signal value corresponding region, a tiny crack region which can be tolerated and a crack region which exceeds a tolerance range; small peeling intervals that can still be tolerated, peeling intervals that are outside the tolerance range, and the like.
5) Carrying out signal acquisition on the railway track basic equipment to be analyzed for the quality condition, and bringing the acquired signals into the map subjected to area division to obtain an analysis result corresponding to the quality condition; the more underlying data acquisition markers, the more accurate the corresponding quality status analysis will be.
6) Arranging a plurality of sensors on the railway track basic equipment, carrying out statistical analysis on historical measured signal values to obtain a signal value variation trend, and using the signal value variation trend as a basis for predicting and judging the quality condition development trend of the railway track basic equipment; after the historical actual measurement signals are collected, fitting the collected historical actual measurement signals into a change trend curve according to signal value distribution, wherein the horizontal axis of the curve represents a time axis, and the vertical axis of the curve is the change of the signal value, so that the change trend to be developed and the residual life prediction of the current actual measurement railway track basic equipment can be predicted and judged as long as the railway track basic equipment working signals needing prediction and judgment are actually measured, the corresponding values of the corresponding frequency domain diagram are compared, and the quality condition development prediction can be carried out according to the historical data change rule of the values on the frequency domain diagram; moreover, each different quality condition has a change trend corresponding to each other, and can be statistically analyzed and fitted from historical data to be used as a judgment basis for online prediction. .
7) After the signal diagram quality condition area is divided, the signal diagram with the divided area is compared, historical measured data are referred, corresponding quality condition characteristics and corresponding characteristic signals collected by the signal diagram are respectively included, the corresponding area is divided into a plurality of evaluation intervals according to the degree of the poor degree of each quality condition, such as excellent, good, medium and poor intervals or small, medium and large evaluation intervals, in the evaluation intervals, the collected measured data are artificially utilized to be collected and sorted in a big data marking mode, then quality condition standard signal values of all degrees are substituted into the signal diagram, and the evaluation intervals of the quality condition area in the diagram are divided.
8) Carrying out signal acquisition on the railway track basic equipment to be analyzed for the quality condition, and bringing the acquired signals into the map subjected to interval division to obtain an evaluation result corresponding to the quality condition degree; for example, if a certain characteristic signal value is collected and falls in a high-class signal interval according to comparison with a signal diagram, the equipment can be judged that no poor quality condition exists at present; when the signal value falls into the crack quality condition characteristic region, judging whether the quality condition degree of the currently measured equipment is a micro crack, a medium crack or a large crack according to the position of the signal value in the small, medium and large intervals, and immediately evaluating the judgment of the corresponding processing means required to be made, wherein the division of the specific degree is determined according to the regulations of different line countries and governing departments and the railway maintenance regulations of related laws and regulations.
The signal diagram in step 2) includes, but is not limited to, a time domain diagram of the signal data corresponding to a time axis, and a signal frequency domain diagram obtained by performing fourier transform on the signal time domain data.
When the quality condition is characterized in step 3), the characteristics include, but are not limited to, the following: normal, fracture, abrasion, cracking, spalling, corrosion, deformation, crushing, nuclear damage, and the like.
Furthermore, the signal time domain data needs to be denoised, and the processing methods include low-pass filtering, correlation filtering, time domain average filtering and wavelet filtering.
Furthermore, after the signal frequency domain diagram is drawn in the step 2), the signal frequency domain diagram needs to be standardized, the standardization is to perform fitting correction processing on the signal data, and the parameters participating in the fitting correction include weather, air temperature, train load weight and train speed.
Further, in the step 3), a plurality of railway track basic devices with characteristics of the quality conditions are actually measured under the actual working conditions, different weather conditions, different air temperatures, different train load weights and different train speeds, and the railway track basic devices correspond to corresponding characteristic signal values respectively.
Further, the signal diagram is divided into different intervals corresponding to the quality condition characteristics according to the different positions of the characteristic signal values in the signal diagram.
Further, the railway track infrastructure is a rail traffic infrastructure including, but not limited to, rails, ties, track plates, tie plates, fasteners, switch rails, frog, guard rails, guide rails, stock rails, splice clips, and fasteners.
The invention relates to a quality condition monitoring and evaluating device for railway track basic equipment, which comprises a data acquisition module, a data communication module and a data processing and displaying module, wherein the data acquisition module is used for monitoring and acquiring signals generated by the railway track basic equipment during working, the sensors can adopt mature signal sensors in the prior art, and the sensors are arranged on the railway track basic equipment to monitor the signal values in real time.
The data communication module is used for transmitting the signal value acquired by the data acquisition module to the data conversion module, and the data communication module is responsible for transmitting the signal value acquired by the signal sensor.
The data processing and displaying module is used for carrying out data analysis and graph conversion on the signal data transmitted by the data communication module to generate and display a data schematic diagram, the data processing and displaying module is used for processing and analyzing the transmitted signal values, the data processing and displaying module comprises Fourier transform and fitting correction processing, after a signal frequency domain diagram is generated, the frequency domain diagram is divided into regions according to the actually measured signal values of different track working conditions, and finally the frequency domain diagram with the divided regions is used for comparing the signal data transmitted by real-time monitoring, so that the real-time monitoring and the evaluation additional prediction of the working condition of the railway track basic equipment are realized.
The device also comprises a power supply module, wherein the data communication module adopts a wired or wireless data communication mode; the data processing and displaying module also comprises a data storage device.
The invention monitors and obtains the signal generated when the railway track basic equipment works by the signal sensor arranged on the railway track basic equipment, the quality condition of the railway track basic equipment is divided into a plurality of types, and the signals sent by the working under different quality conditions are obviously different, so the quality condition of the railway track basic equipment at the moment can be accurately obtained according to different actually measured signal values; after a signal change signal diagram of the railway track basic equipment in working is drawn, the signal diagram is subjected to quality condition area division, then a plurality of sensors are arranged on the railway track basic equipment, signal values generated when the railway track basic equipment works are monitored in real time, and the signal values are used for predicting the development trend of the quality condition of the current railway track basic equipment according to the change trend of historical data on a frequency domain diagram; dividing the corresponding signal diagram into a plurality of judgment intervals according to the quality condition of the railway track basic equipment on the corresponding quality condition signal diagram and the requirements of quality technical standards and line specifications; the working signal of the railway track basic equipment at a certain position is actually measured and substituted into the judgment interval to judge the quality condition of the current railway track basic equipment, so that a series of practical functions of real-time online monitoring of the railway track basic equipment, prediction and judgment of the quality condition of the railway track basic equipment and the like are realized.
The method comprises the steps that firstly, data collected by sensors arranged at each position of railway track basic equipment are collected and transmitted, the original data are collectively called signal time domain data, the signal time domain data have a lot of noises, in order to reduce the interference of the noises, the signal time domain data also need to be subjected to noise removal processing, and a noise reduction method comprises low-pass filtering, related filtering, time domain average filtering and wavelet filtering, the signal time domain data subjected to noise reduction are subjected to Fourier transform, and a signal frequency domain graph is obtained by drawing; the frequency domain graph is influenced by weather, temperature, train load weight and speed, the frequency domain graph needs to be standardized, the standardization processing is to carry out fitting correction processing on the frequency domain graph, parameters participating in fitting correction comprise weather, temperature, train load weight and train speed, the common influence factors are taken as influence factors and are brought into a fitting algorithm to carry out fitting correction standardization processing on the frequency domain graph, and the fitting correction algorithm used by the invention belongs to a common and common fitting correction algorithm in the prior art, and is one of correction algorithms which are commonly used in the field of data processing. The signal curve after fitting and correction is a standard frequency domain diagram under various working conditions on the railway track basic equipment, and in order to divide the region of the frequency domain diagram, the invention also carries out field measurement on various quality conditions on the railway track basic equipment. According to the existing industry standard for judging the quality condition of railway track basic equipment, a track area which normally works, an abnormal track area with tiny flaws needing early warning and a track area which exceeds a tolerance range and needs to be replaced immediately are actually selected on the railway track basic equipment, a large number of actual signal measurements are respectively carried out on the various track areas to respectively obtain various signal characteristic values corresponding to the quality condition, then the obtained signal frequency domain diagrams are compared to determine the sections of the signal frequency domain diagrams where the actually measured normal working signal values, the signal values needing early warning and the signal values needing to be replaced immediately are respectively located, the sections on the frequency domain diagrams where the various signal characteristic values are located are the signal sections which normally work, the tiny quality condition signal sections needing early warning and the signal sections which exceed the tolerance range and need to be replaced immediately, this allows to divide the entire frequency domain map into different regions, the signal values in the different regions reflecting different actual quality conditions and specific quality conditions of the track. The frequency domain graph which completes the area division can be used for real-time monitoring and track quality condition early warning analysis of railway track basic equipment, only a signal sensor is required to be arranged on the railway track basic equipment, data obtained by monitoring the signal sensor is compared with the frequency domain graph after being processed and analyzed in real time, and the signal value is determined to fall into which interval, namely the quality condition of the track at the moment in which interval, for example: if the real-time signal value of the railway track basic equipment falls into the signal interval of normal work, the railway track basic equipment is in a normal quality condition at the moment; if the actual signal value of the track falls into an abnormal signal interval needing early warning, the basic equipment of the railway track at the moment is the abnormal quality condition needing early warning, and can point to which specific abnormal quality condition and subdivide to which specific one, which is the representation of tiny fracture, abrasion, crack, spalling, corrosion, deformation, crushing and nuclear damage; if the signal value of the railway track basic equipment falls into the signal interval which is required to be replaced immediately and exceeds the tolerance range, the quality condition of the railway track basic equipment at the moment is the state required to be replaced immediately, and specifically, the quality condition can be directly judged according to which one of fracture, abrasion, crack, peeling, corrosion, deformation, crushing and damage, so that the real-time online monitoring and analysis of the railway track basic equipment are realized.
Meanwhile, after a signal diagram of the railway track basic equipment in operation is drawn, evaluation interval division is carried out on the poor quality condition area of the signal diagram again, namely: a high-grade signal interval of normal work, a tiny poor quality condition signal interval needing early warning and a large poor quality condition signal interval needing immediate processing; then, arranging a plurality of signal sensors on the railway track basic equipment, monitoring a signal value of the railway track basic equipment during working in real time and comparing the signal value with the signal diagram obtained in the previous step to judge the region of the signal value monitored in real time on the signal diagram, and finally evaluating and judging the quality condition of the actually-measured railway track basic equipment according to the position condition of the signal value of the railway track basic equipment monitored in real time in the previous step on the signal diagram; if the actual signal value of the railway track basic equipment falls into the micro signal interval, the railway track basic equipment at the moment is the quality condition needing early warning, and micro defects such as fracture, abrasion, cracks, peeling, corrosion, deformation, crushing, nuclear damage and the like in a tolerable range already occur; if the signal value of the railway track basic equipment falls into a large poor quality condition signal interval, the railway track basic equipment has the characteristics of intolerable fracture, abrasion, crack, spalling, corrosion, deformation, crushing and nuclear damage at the moment, and needs to be immediately processed, namely: the quality condition signal diagram areas of the railway track basic equipment can be a good area, a middle area and a poor area, or a bad quality condition, a middle area and a small area, so that the real-time online monitoring of the railway track basic equipment and the evaluation and judgment of the track quality condition are realized.
After the quality condition area division is completed and the historical measured signals are gathered, any quality condition characteristic represents a corresponding signal value, and a curve with a variation trend can be formed after the signal value is fitted according to a time axis line; in practical application, when real-time data of railway track basic equipment at a certain position is measured, the future development trend and the upcoming state of the railway track basic equipment at the position can be predicted by using the corresponding change trend curve, so that the real-time online prediction and judgment method for the railway track basic equipment is realized, a large amount of manpower and material resources are saved, and the prediction efficiency is high.
The device has high monitoring efficiency, is convenient to set, does not damage the original equipment installation form of railway track foundation equipment, saves a large amount of manpower and material resources, and has high market popularization value.
Detailed Description
For further understanding of the present invention, embodiments of the present invention will be described in further detail below with reference to examples and comparative examples, but embodiments of the present invention are not limited thereto.
In order to make the purpose and technical solution of the present invention more apparent, the present invention is further described in detail with reference to the following examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. The following describes the application of the present invention in detail.
A monitoring and evaluating device for frog quality conditions comprises a data acquisition module, a data communication module and a data processing and displaying module, wherein the data acquisition module is used for monitoring and acquiring acceleration signals generated by a frog when a train passes through the data acquisition module; the data communication module is used for transmitting the acceleration signal value acquired by the data acquisition module to the data processing display module; and the data processing and displaying module is used for carrying out data analysis and graph conversion on the acceleration signal data transmitted by the data communication module to generate and display a data schematic diagram.
The device also comprises a power supply module, wherein the data communication module adopts a wired or wireless data communication mode; the data processing and displaying module also comprises a data storage device.
The frog quality condition monitoring and evaluating method of the device comprises the following steps:
1) arranging a plurality of sensors on the frog, wherein the sensors are used for acquiring acceleration signals generated by vibration impact of the frog when a train passes through the frog; acquiring acceleration signals according to a certain rule or interval time, summarizing the acceleration signals into time domain data according to recording time, and storing the time domain data;
2) drawing the acceleration signal data acquired in the step 1) to obtain an acceleration signal diagram; the acceleration signal data is plotted according to a time axis corresponding to the acceleration signal data, the horizontal axis is time, the acceleration signal values are recorded on a time domain graph along with the time, the vertical axis is the magnitude of the acceleration signal values, the acceleration signal data time domain graph can be obtained, and the frequency correlation graph of the acceleration signal values, namely the acceleration signal frequency domain graph, can be obtained by carrying out Fourier transform on the time domain data.
3) Selecting acceleration signals generated when the actually measured quality conditions of a plurality of frog are characterized, and recording the acceleration signals as characteristic acceleration signal values; and the larger the measured data amount is, the more stable and accurate the result is, so that the big data acquires the relevant measured data and the corresponding records are stored one by one.
4) Substituting the characteristic acceleration signal value measured in the step 3) into the acceleration signal diagram obtained by drawing in the step 2), and carrying out area division on the acceleration signal diagram according to the position of the characteristic acceleration signal value on the acceleration signal diagram; after a large amount of actually measured data is used for marking the actually measured corresponding quality conditions, the area distribution on the acceleration signal diagram is primarily divided, and the areas are respectively intervals of the acceleration signal values corresponding to various quality conditions, such as the ordinary normal acceleration signal value corresponding interval, a tiny crack interval which can be tolerated and a crack interval which exceeds a tolerance range; small peeling intervals that can still be tolerated, peeling intervals that are outside the tolerance range, and the like.
5) Acquiring acceleration signals of the frog to be analyzed for the quality condition, and bringing the acquired acceleration signals into the map subjected to area division to obtain an analysis result corresponding to the quality condition; the more underlying data acquisition markers, the more accurate the corresponding quality status analysis will be.
6) Arranging a plurality of sensors on the frog, carrying out statistical analysis on historical measured acceleration signal values to obtain the variation trend of the acceleration signal values, and taking the variation trend of the acceleration signal values as the basis for predicting and judging the development trend of the quality condition of the frog; after the historical measured acceleration signals are collected, a change trend curve can be formed by fitting according to the distribution of the acceleration signal values, the horizontal axis of the curve represents the time axis, and the vertical axis of the curve is the change of the acceleration signal values, so that the change trend to be developed and the residual life prediction of the current measured frog and the quality condition development prediction can be predicted by only actually measuring the working acceleration signals of the frog needing prediction and judging and comparing the values corresponding to the corresponding frequency domain graph according to the historical data change rule of the values on the frequency domain graph; moreover, each different quality condition has a change trend corresponding to each other, and can be statistically analyzed and fitted from historical data to serve as a judgment basis for online prediction. .
7) After the quality condition area of the acceleration signal diagram is divided, comparing the acceleration signal diagram with the divided area, referring to historical measured data, respectively comprising corresponding quality condition characteristics and collected corresponding characteristic acceleration signals, dividing the corresponding area into a plurality of evaluation intervals according to the degree of the badness of each quality condition, such as excellent, good, medium and poor intervals or small, medium and large evaluation intervals, wherein the collected measured data is artificially collected and sorted by using a big data marking mode, and then quality condition standard acceleration signal values of all degrees are substituted into the acceleration signal diagram to divide the evaluation intervals of the quality condition area in the diagram.
8) Acquiring acceleration signals of the frog to be analyzed for the quality condition, and bringing the acquired acceleration signals into the graph subjected to interval division to obtain an evaluation result corresponding to the quality condition degree; for example, a certain characteristic acceleration signal value is collected, and the characteristic acceleration signal value is compared with an acceleration signal diagram and falls into a superior acceleration signal interval, so that the equipment can be judged that no poor quality condition exists at present; when the measured acceleration signal value falls into the crack quality condition characteristic region, judging whether the quality condition degree of the currently measured equipment is a micro crack, a medium crack or a large crack according to the position of the acceleration signal value in the small, medium and large intervals, and immediately evaluating the judgment of the corresponding processing means required to be made, wherein the division of the specific degree is determined according to the regulations of different line countries and governing departments and the railway maintenance regulations of related laws and regulations.
The acceleration signal diagram in step 2) includes, but is not limited to, a time domain diagram of the acceleration signal data corresponding to a time axis, and an acceleration signal frequency domain diagram obtained by performing fourier transform on the acceleration signal time domain data.
When the quality condition is characterized in step 3), the characteristics that occur include, but are not limited to, the following: normal, fracture, abrasion, cracking, spalling, corrosion, deformation, crushing, nuclear damage, and the like.
And denoising the acceleration signal time domain data, wherein the processing methods comprise low-pass filtering, correlation filtering, time domain average filtering and wavelet filtering.
After the acceleration signal frequency domain diagram is drawn in the step 2), the acceleration signal frequency domain diagram needs to be standardized, the standardization is to perform fitting correction processing on the acceleration signal data, and parameters participating in the fitting correction include weather, air temperature, train load weight and train speed.
And 3) in the step 3), a plurality of frog with characteristics are respectively corresponding to corresponding characteristic acceleration signal values when the actual working condition, different weather, air temperature, train load weight and train speed are measured to obtain the quality condition.
And dividing the acceleration signal diagram into different intervals corresponding to the quality condition characteristics according to the different positions of the characteristic acceleration signal values in the acceleration signal diagram.
The invention discloses a frog quality condition monitoring and evaluating device, which comprises a data acquisition module, a data communication module and a data processing and displaying module, wherein the data acquisition module is used for monitoring and acquiring acceleration signals generated by a frog when a train passes through, the sensor can adopt a mature acceleration signal sensor in the prior art, and the sensor is arranged on the frog to monitor the value of the acceleration signals in real time.
The data communication module is used for transmitting the acceleration signal value acquired by the data acquisition module to the data conversion module, and the data communication module is responsible for transmitting the acceleration signal value acquired by the acceleration signal sensor.
The data processing and displaying module is used for carrying out data analysis and graph conversion on the acceleration signal data transmitted by the data communication module to generate and display a data schematic diagram, the data processing and displaying module is used for processing and analyzing the acceleration signal values transmitted by the data communication module, the data processing and displaying module comprises Fourier transform and fitting correction processing, after an acceleration signal frequency domain diagram is generated, the frequency domain diagram is divided into regions according to actually measured acceleration signal values of different frog working conditions, and finally the frequency domain diagram with the divided regions is used for comparing the acceleration signal data transmitted by real-time monitoring, so that the real-time monitoring and the evaluation and additional prediction of the frog working condition are realized.
The device also comprises a power supply module, wherein the data communication module adopts a wired or wireless data communication mode; the data processing and displaying module also comprises a data storage device.
The invention monitors and obtains the acceleration signal generated when the frog works by the acceleration signal sensor arranged on the frog, the quality conditions of the frog are divided into a plurality of types, and the acceleration signals generated when the frog works under different quality conditions are obviously different, so that the quality condition of the frog at the moment can be accurately obtained according to different actually measured acceleration signal values; after an acceleration signal change acceleration signal graph is drawn when a frog passes by a train, the acceleration signal graph is subjected to quality condition area division, then a plurality of sensors are arranged on the frog, the acceleration signal value generated when the frog works is monitored in real time, and the acceleration signal value is used for predicting the development trend of the quality condition of the current frog according to the change trend of historical data on a frequency domain graph; dividing the corresponding acceleration signal diagram into a plurality of judgment intervals on the corresponding quality condition acceleration signal diagram according to the quality condition of the frog and the requirements of quality technical standards and line specifications; actually measuring the working acceleration signal of a certain frog, substituting the working acceleration signal into an evaluation interval to evaluate the quality condition of the current frog, thereby realizing a series of practical functions of real-time online monitoring of the frog, prediction and judgment of the quality condition of the frog and the like.
Firstly, summarizing and transmitting data collected by sensors arranged at each position of a frog, using the original data to collectively refer to acceleration signal time domain data, wherein the acceleration signal time domain data also has a lot of noises, and in order to reduce the interference of the noises, the acceleration signal time domain data also needs to be subjected to noise removal processing; because the frequency domain graph can be influenced by weather, temperature, train load weight and speed, the frequency domain graph also needs to be standardized, the standardization is to carry out fitting correction processing on the frequency domain graph, parameters participating in fitting correction comprise weather, temperature, train load weight and train speed, the common influence factors are taken as influence factors and are brought into a fitting algorithm to carry out fitting correction standardization processing on the frequency domain graph, and the fitting correction algorithm used by the invention belongs to a common and common fitting correction algorithm in the prior art, and is one of correction algorithms commonly used in the field of data processing. The acceleration signal curve after fitting and correction is a standard frequency domain diagram under various working conditions on the frog, and in order to divide the frequency domain diagram into areas, the invention also carries out field measurement on various quality conditions on the frog. According to the existing industry standard for judging the quality condition of the frog, a frog area which works normally, an abnormal frog area which needs early warning and a frog area which exceeds a tolerance range and needs to be replaced immediately are selected actually on the frog, the acceleration signals are measured actually and massively on the multiple frog areas respectively to obtain multiple acceleration signal characteristic values corresponding to the quality condition, then the obtained acceleration signal frequency domain diagrams are compared to determine the normal working acceleration signal values which are obtained by actual measurement, the acceleration signal values which need early warning and the acceleration signal values which need to be replaced immediately are respectively located in which sections of the acceleration signal frequency domain diagram, and the sections on the frequency domain diagram where the multiple acceleration signal characteristic values are located are the acceleration signal sections which work normally, the acceleration signal sections which need to be replaced immediately, and the like, The acceleration signal interval of the small quality condition which needs early warning and the acceleration signal interval which needs to be replaced immediately and exceeds the tolerance range can be divided into different areas, and the acceleration signal values in the different areas reflect different actual quality conditions and specific quality conditions of the frog. The frequency domain graph of accomplishing regional division can be used for the real-time supervision and the early warning analysis of frog quality situation to the frog, only need set up acceleration signal sensor on the frog can, compare with the frequency domain graph after the data real-time processing analysis that obtains acceleration signal sensor monitoring, confirm that this acceleration signal value falls into in which interval, be the quality situation of frog this moment in which interval, for example: if the real-time acceleration signal value of the frog falls into the acceleration signal interval of normal work, the frog at the moment is in a normal quality condition; if the actual acceleration signal value of the frog falls into an abnormal acceleration signal interval needing early warning, the frog at the moment is an abnormal quality condition needing early warning, and can point to which specific abnormal quality condition and subdivide to which specific abnormal quality condition is represented by tiny fracture, abrasion, crack, spalling, corrosion, deformation, crushing and nuclear injury; if the acceleration signal value of the frog falls into the acceleration signal interval which exceeds the tolerance range and needs to be replaced immediately, the quality condition of the frog at the moment is the state needing to be replaced immediately, and specifically, the quality condition of the frog, namely which one of fracture, abrasion, crack, peeling, corrosion, deformation, crushing and nuclear injury can be directly judged, so that the real-time online monitoring and analysis of the frog are realized.
And simultaneously, after an acceleration signal diagram of the frog passing by the train is drawn, evaluating interval division is carried out on the poor quality condition area of the acceleration signal diagram again, namely: the method comprises the following steps that (1) a high-grade acceleration signal interval of normal work, a small bad quality condition acceleration signal interval needing early warning and a large bad quality condition acceleration signal interval needing immediate processing are carried out; then, arranging a plurality of acceleration signal sensors on the frog, monitoring the acceleration signal value of the frog during working in real time, comparing the acceleration signal value with the acceleration signal diagram obtained in the previous step, judging the region of the acceleration signal value monitored in real time on the acceleration signal diagram, and finally evaluating and judging the quality condition of the actually-measured frog according to the position condition of the acceleration signal value of the frog monitored in real time in the acceleration signal diagram in the previous step; if the actual acceleration signal value of the frog falls into a tiny acceleration signal interval, the frog at the moment is the quality condition needing early warning, and tiny flaws such as fracture, abrasion, crack, peeling, corrosion, deformation, crushing, nuclear damage and the like in a tolerable range already appear; if the acceleration signal value of the frog falls into the acceleration signal interval of the large poor quality condition, the frog has the characteristics of intolerable fracture, abrasion, crack, peeling, corrosion, deformation, crushing and nuclear damage at the moment, and needs to be immediately processed, namely: the multiple evaluation intervals of the quality condition acceleration signal diagram area of the frog can be excellent, good, medium and poor intervals, and also can be large, medium and small intervals of poor quality conditions, so that real-time online monitoring of the frog and evaluation and judgment of the quality condition of the frog are realized.
After the quality condition area division is completed and the historical measured acceleration signals are gathered, any quality condition characteristic represents the corresponding acceleration signal value, and a curve with a change trend can be formed after the acceleration signal value is fitted according to a time axis line; in practical application, when real-time data of a frog at a certain position is measured, the future development trend and the impending state of the frog at the position can be predicted by using the corresponding change trend curve, so that the real-time online prediction and judgment method of the frog is realized, a large amount of manpower and material resources are saved, and the prediction efficiency is high.
The device has the advantages of high monitoring efficiency, convenient arrangement, no damage to the original equipment installation form of the frog, saving of a large amount of manpower and material resources and high market popularization value.
The foregoing is a preferred embodiment of the present invention, and is not intended to limit the invention in any way, so that any modifications or equivalents made in accordance with the teachings of the present invention will still fall within the scope of the claims appended hereto.
Claims (8)
1. The method for monitoring and evaluating the quality condition of the railway track basic equipment is characterized by comprising a device, wherein the device comprises a data acquisition module, a data communication module and a data processing and displaying module, and the data acquisition module is used for acquiring signals of the railway track basic equipment during working; the data communication module is used for transmitting the signal value acquired by the data acquisition module to the data processing display module; the data processing and displaying module is used for carrying out data analysis and graph conversion on the signal data transmitted by the data communication module to generate and display a data schematic diagram;
the method comprises the following steps:
1) arranging a plurality of sensors on the railway track basic equipment, wherein the sensors are used for acquiring signals generated when the railway track basic equipment works;
2) drawing the signal data acquired in the step 1) to obtain a signal diagram;
3) selecting signals generated when the actual measurement quality conditions of a plurality of railway track basic equipment have characteristics, and recording the signals as characteristic signal values;
4) substituting the characteristic signal value measured in the step 3) into the signal diagram obtained by drawing in the step 2), and carrying out region division on the signal diagram according to the position of the characteristic signal value on the signal diagram;
5) carrying out signal acquisition on the railway track basic equipment to be analyzed for the quality condition, and bringing the acquired signals into the map subjected to area division to obtain an analysis result corresponding to the quality condition;
6) arranging a plurality of sensors on the railway track basic equipment, carrying out statistical analysis on historical measured signal values to obtain a signal value variation trend, and using the signal value variation trend as a basis for predicting and judging the quality condition development trend of the railway track basic equipment;
7) after the signal diagram quality condition areas are divided, dividing the corresponding areas into a plurality of evaluation intervals according to the degree of the poor quality conditions, such as excellent, good, medium and poor areas or small, medium and large evaluation intervals;
8) and carrying out signal acquisition on the railway track basic equipment to be analyzed for the quality condition, and bringing the acquired signals into the map subjected to interval division to obtain an evaluation result corresponding to the quality condition degree.
2. The method for monitoring and evaluating the quality condition of the basic equipment of the railway track as claimed in claim 1, wherein the device further comprises a power module, and the data communication module adopts a wired or wireless data communication mode; the data processing and displaying module also comprises a data storage device.
3. The method for monitoring and evaluating the quality condition of the railway track basic equipment as claimed in claim 1, wherein the signal diagram in the step 2) includes but is not limited to a time domain diagram of the signal data corresponding to a time axis and a signal frequency domain diagram obtained by Fourier transforming the signal time domain data.
4. The method for monitoring and evaluating the quality condition of the railway track basic equipment as claimed in claim 1, wherein when the quality condition is characterized in the step 3), the characteristics include but are not limited to the following conditions: normal, fracture, abrasion, crack, spalling, corrosion, deformation, crushing, nuclear damage.
5. The method for monitoring and evaluating the quality condition of the basic equipment of the railway track as claimed in claim 3, wherein the signal time domain data is subjected to noise reduction processing by low-pass filtering, correlation filtering, time domain average filtering and wavelet filtering.
6. The method for monitoring and evaluating the quality condition of the basic equipment of the railway track as claimed in claim 1, wherein the signal frequency domain graph is normalized after being drawn in the step 2), the normalization is to perform fitting correction processing on the signal data, and the parameters participating in the fitting correction include weather, air temperature, train load weight and train speed.
7. The method for monitoring and evaluating the quality condition of the basic equipment of the railway track as claimed in claim 1, wherein the step 3) comprises the step of carrying out actual measurement on a plurality of basic equipment of the railway track with the quality condition characteristic under the actual working condition, different weather, air temperature, train load weight and train speed, wherein the actual measurement corresponds to the corresponding characteristic signal values respectively.
8. The method as claimed in claim 7, wherein the signal diagram is divided into different sections corresponding to the quality status characteristics according to the characteristic signal values at different positions of the signal diagram.
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