Track temperature acquisition, analysis and early warning system

Abstract

The invention relates to the technical field of railway engineering, in particular to a rail temperature acquisition, analysis and early warning system which obtains data transmission quality evaluation coefficients of sampling frequencies according to analysis of transmission parameters of the sampling frequencies so as to determine the optimal sampling frequency and screen out time points. The temperature coincidence degree of each time point of the track is obtained according to the temperature of each sampling point of the track, the snow melting influence coefficient is obtained according to the snow melting parameters of the track, then the snow melting effect evaluation index of each time point of the track is obtained through analysis, each regulation and control time point is screened out according to the number, and then temperature regulation and control are conducted on each regulation and control time point. Meanwhile, a time point-snow melting effect evaluation index curve is constructed, snow melting effect evaluation indexes of future time points are obtained from the time point-snow melting effect evaluation index curve and fed back to the system, key information of track temperature changes can be captured in time, snow melting measures can be implemented when needed, excessive or insufficient snow melting operation is avoided, and the overall snow melting efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of railway engineering, and in particular to a track temperature collection, analysis and early warning system. Background Art

[0002] With the rapid development of modern rail transit, the safety and stable operation of the rail system has become a vital issue. Under different environmental conditions, especially under the influence of temperature changes, the physical properties and structural state of the rail will change significantly. For example, in cold weather, the rail may be affected by snow and ice, which may affect the normal operation of the train. When the snow melts, poor drainage may also cause corrosion of the rail components.

[0003] At present, the traditional track maintenance method is mostly regular inspections. This method makes it difficult to grasp the track temperature status and its potential risks in real time and accurately. Therefore, effective collection, in-depth analysis and timely warning of track temperature are urgent needs to ensure the efficient and safe operation of the rail transit system.

[0004] For example, the existing Chinese patent application number 201520508572.0 discloses a track temperature monitoring system. This solution measures the track temperature through a nail-type temperature sensor, determines its position according to the positioning module to obtain positioning data, and sends the temperature data together with the positioning data through a communication module after amplification and calculation processing. The trackside terminal is powered by a solar power generation device, and the workstation receives and stores the temperature data. If the temperature exceeds the range, a prompt signal is issued. It is connected to the remote monitoring center through an interface to accurately locate the track area with abnormal temperature.

[0005] However, this solution has the following shortcomings: it only focuses on the measurement, transmission and monitoring of current temperature, and does not involve the use of historical temperature data and related environmental factors to predict future trends in track temperature. It is impossible to carry out preventive maintenance in advance for possible track problems, and can only carry out repairs after problems occur, which increases maintenance costs and interference with railway operations.

[0006] For example, the existing Chinese patent application number 201910319449.7 discloses a fluid-heated snow-melting pavement temperature strain monitoring system. This solution controls the electric heating pipe in the heating water tank to heat the fluid through the distribution box, and the circulating pump works. Under the control of the control valve, the heated fluid flows into the S-shaped pipe in the cement concrete pavement of the pavement system through the connecting pipe. The temperature sensor measurement component collects temperature data through the temperature sensor inside the cement concrete pavement, and transmits it to the computer through the collector. The collection device in the digital speckle meter measurement component collects data and then transmits it to the external digital speckle meter and then to the computer. The resistance strain gauge measurement component collects data through the resistance strain gauge inside the cement concrete pavement, and transmits it to the computer through the collector, thereby realizing the monitoring of the pavement temperature strain.

[0007] However, this scheme has the following shortcomings: This scheme focuses on the monitoring of two physical quantities, temperature and strain. For snow-melting pavements, other influencing factors may need to be considered, such as the water content and density of the accumulated snow. Snow-melting schemes designed only based on temperature and strain may not provide enough heat to quickly and effectively melt the wet snow, resulting in the snow remaining on the pavement for too long, affecting the normal use of the pavement. Summary of the invention

[0008] In order to overcome the shortcomings of the background technology, an embodiment of the present invention provides a track temperature collection, analysis and early warning system, which can effectively solve the problems involved in the above-mentioned background technology.

[0009] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a track temperature collection, analysis and early warning system, including: a temperature sampling point division module, which is used to select each rail monitoring point and each switch monitoring point on the track, collectively referred to as each sampling point.

[0010] The data transmission quality analysis module is used to obtain the transmission parameters of each sampling frequency through communication transmission detection, and then evaluate the data transmission quality evaluation coefficient of each sampling frequency, determine the optimal sampling frequency, and screen out each time point.

[0011] The snowmelt effect analysis module is used to obtain the temperature of each sampling point on the track and the snowmelt parameters of the track, evaluate the temperature compliance and snowmelt influence coefficient at each time point on the track, and thus evaluate the snowmelt effect evaluation index at each time point on the track.

[0012] The temperature control module is used to select each control time point according to the snow melting effect evaluation index at each time point of the track, and then perform temperature control at each control time point.

[0013] The snowmelt effect prediction module is used to construct a time point-snowmelt effect evaluation index curve according to the snowmelt effect evaluation index at each time point of the track, from which the snowmelt effect evaluation index at the future time point is obtained and fed back to the system.

[0014] The management database is used to store preset data, estimated transmission time, reference value of transmission delay time, transmission parameters of each sampling frequency, temperature of each rail monitoring point at each time point, each switch monitoring point, snow melting parameters of the track, optimal sampling frequency and each time point.

[0015] Preferably, the specific operation method of the temperature sampling point division module is: divide the track into a rail part and a switch part, select a number of monitoring points in the rail part and the switch part of the track according to the settings, respectively record them as rail monitoring points and switch monitoring points, collectively referred to as sampling points.

[0016] Preferably, the transmission parameters include transmission delay time and signal strength of the temperature data.

[0017] Preferably, the specific detection method of the communication transmission detection is: the first step, in a simulation environment, different acquisition frequencies are set according to the different acquisition interval durations that are initially set, recorded as each acquisition frequency, and at the same time, a fixed duration is used as an acquisition cycle, and each sampling time point is selected in the acquisition cycle according to each acquisition frequency, recorded as each sampling time point of each sampling frequency, and communication transmission detection is performed on the temperature data at each sampling time point of each sampling frequency, and the transmission delay duration of the temperature data of each sampling frequency is obtained by obtaining the temperature receiving time point and sampling time point of each sampling time point of each sampling frequency.

[0018] In the second step, several equally spaced detection points are selected on the communication cable according to the preset spacing, and the signal strength detection instrument is contacted with each detection point of the communication cable at each sampling frequency and each sampling time point through a specific interface to obtain the signal strength of each detection point corresponding to each sampling frequency and each time point, and the signal strength of each sampling frequency is obtained by average calculation.

[0019] Preferably, the specific analysis method of the data transmission quality analysis module is: based on the transmission delay duration of the temperature data of each sampling frequency and the signal strength of each sampling frequency, the data transmission quality evaluation coefficient of each sampling frequency is evaluated, and the data transmission quality evaluation coefficient of each sampling frequency is sorted in order from large to small, and the sampling frequency corresponding to the first data transmission quality evaluation coefficient is recorded as the optimal sampling frequency, and each sampling time point of the sampling frequency is recorded as each time point.

[0020] Preferably, the specific analysis method for the temperature compliance of the track at each time point is: obtaining the temperature of each rail monitoring point and each switch monitoring point at each time point of the track, and comparing them with the preset snowmelt temperature to obtain the temperature compliance of the rail part and the switch part of the track at each time point.

[0021] Based on the temperature compliance of the track rail part at each time point and the temperature compliance of the track switch part at each time point, the temperature compliance of the track at each time point is obtained by fusion calculation.

[0022] Preferably, the specific analysis method of the snowmelt influence coefficient is as follows: in the first step, set amounts of snow are taken from different positions near the track, and mixed to obtain snow samples, the mass of which is recorded as the initial mass of the snow sample, which is dried at a set constant temperature until the water in the snow sample is completely evaporated, and the remaining solid mass of the snow sample is weighed to obtain the residual mass of the snow sample, and the water content of the snow is obtained by comparing it with the initial mass of the snow sample.

[0023] In the second step, snow samples are collected at different locations near the track and filled into a container with a known volume scale to obtain a snow sample of known volume, which is recorded as the snow sampling sample. Its volume is recorded as the snow sampling sample volume. The snow sampling sample mass is obtained by weighing the snow sampling sample, and the snow density is calculated by the density formula.

[0024] The third step is to select several measurement points on the track surface, recorded as measurement points, and apply a stable heat flux source on one side of the track structure to transfer heat from one side to the other side. At the same time, a heat flux meter is tightly fitted on each measurement point, and a temperature sensor is installed near the heat flux meter. The heat flux density of each measurement point measured by the heat flux meter and the temperature of each measurement point measured by the temperature sensor are recorded, and the thermal conductivity of the track is calculated using Fourier's law.

[0025] The fourth step is to calculate the snowmelt influence coefficient based on the fusion of snow moisture content, snow density and thermal conductivity of the track.

[0026] Preferably, the specific operation method of each control time point is: based on the temperature compliance degree and snowmelt influence coefficient of each time point of the track, the snowmelt effect evaluation index of each time point of the track is evaluated and compared with the preset snowmelt effect evaluation index threshold value; if the snowmelt effect evaluation index of the track at a certain time point is greater than or equal to the preset snowmelt effect evaluation index threshold value, it means that the snowmelt effect of the track at that time point is qualified; if the snowmelt effect evaluation index of the track at a certain time point is less than the preset snowmelt effect evaluation index threshold value, it means that the snowmelt effect of the track at that time point is unqualified, and the temperature of the track at that time point needs to be controlled, and the time point is recorded as the control time point, thereby screening out each control time point.

[0027] Preferably, the specific operation method of the temperature control module is: read the temperature of each rail monitoring point and each switch monitoring point at each time point of the track, renumber them as the temperature of each sampling point at each time point of the track, screen out the temperature of each sampling point at each control time point of the track, and obtain the required control temperature of each sampling point at each control time point of the track by subtracting it from the preset snowmelt temperature respectively; if the required control temperature of a sampling point at a certain control time point of the track is a positive number, the temperature at the sampling point is correspondingly increased through the snowmelt equipment; if the required control temperature of a sampling point at a certain control time point of the track is a negative number, the temperature at the sampling point is correspondingly decreased.

[0028] After the snow-melting equipment regulates the temperature of each sampling point at each regulation time point, the snow-melting effect evaluation index of the track at each time point after regulation is analyzed again and recorded as the regulation snow-melting effect evaluation index of the track at each time point.

[0029] Preferably, the specific analysis method of the snowmelt effect prediction module is: reading the regulation snowmelt effect evaluation index of each time point of the track, taking the time point as the horizontal coordinate and the regulation snowmelt effect evaluation index as the vertical coordinate, constructing a two-dimensional coordinate system, and then marking several points in the constructed two-dimensional coordinate system for the regulation snowmelt effect evaluation index of each time point of the track to form a time point-regulation snowmelt effect evaluation index curve, substituting the future time point to be predicted into the time point-snowmelt effect evaluation index curve, obtaining the snowmelt effect evaluation index at the future time point, and feeding it back to the system.

[0030] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention obtains the data transmission quality evaluation coefficient of each sampling frequency according to the transmission parameter analysis of each sampling frequency, thereby determining the optimal sampling frequency and screening out each time point, which can accurately locate the optimal sampling frequency and improve data transmission efficiency and accuracy.

[0031] 2. The present invention obtains the temperature compliance degree of the track at each time point according to the temperature of each sampling point of the track, obtains the snowmelt influence coefficient according to the snowmelt parameters of the track, and then analyzes to obtain the snowmelt effect evaluation index at each time point of the track. Based on this number, each control time point is selected, and the snowmelt condition of the track is comprehensively evaluated to provide a basis for control.

[0032] 3. The present invention controls the temperature at each control time point, and at the same time constructs a time point-snow melting effect evaluation index curve, from which the snow melting effect evaluation index at a future time point is obtained and fed back to the system, thereby achieving effective temperature control and predicting future snow melting effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0034] Figure 1 This is a system module connection diagram of the present invention.

[0035] Figure 2 for Figure 1 Flowchart of communication transmission detection in the data transmission quality analysis module.

[0036] Figure 3 for Figure 1 Analysis flow chart of snowmelt influence coefficient in snowmelt effect analysis module. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] See also Figure 1 As shown, a track temperature collection, analysis and early warning system includes a temperature sampling point division module, a data transmission quality analysis module, a snow melting effect analysis module, a temperature control module, a snow melting effect prediction module, and a management database.

[0039] The management database is connected to the temperature sampling point division module, the data transmission quality analysis module, the snow melting effect analysis module, the temperature control module, and the snow melting effect prediction module; and the snow melting effect analysis module is connected to the temperature sampling point division module, the data transmission quality analysis module, and the temperature control module.

[0040] The temperature sampling point division module is used to select each rail monitoring point and each switch monitoring point on the track, collectively referred to as each sampling point.

[0041] The specific operation method of the temperature sampling point division module is as follows: the track is divided into a rail part and a switch part, and a number of monitoring points are selected from the rail part and the switch part of the track according to the settings, which are respectively recorded as rail monitoring points and switch monitoring points, collectively referred to as sampling points; the rail part and the switch part differ in structure and function, and the degree and manner in which they are affected by temperature may also be different. By setting sampling points separately, the temperature information of each part of the track can be obtained more accurately, providing a more accurate data basis for subsequent snow melting effect analysis and temperature control.

[0042] It should be noted that the selection method of each rail monitoring point and each turnout monitoring point is as follows: the first step is to select a number of monitoring points along the length direction of the rail at a fixed distance for the rail portion of the track, which are recorded as each rail head monitoring point. In the vertical direction, a number of monitoring points at different heights are selected at the rail waist height according to the set height difference, which are recorded as each rail waist monitoring point. At the same time, according to the selection method of each rail head monitoring point, a number of monitoring points are also selected at the edge position close to the side of the ballast, which are recorded as each rail bottom monitoring point. Each rail head monitoring point, each rail waist monitoring point, and each rail bottom monitoring point are numbered in the set order as each rail monitoring point. The overall status information of the rail can be fully obtained, and possible problems in various parts of the rail, such as deformation and damage, can be discovered in a timely manner.

[0043] The second step is to set several monitoring points on the point rail according to the set spacing for the turnout part of the track, which are recorded as each point rail monitoring point. Monitoring points are set one by one on the outer positions of the basic track corresponding to each point rail monitoring point, which are recorded as each basic track monitoring point. At the same time, several monitoring points are selected on the heart rail according to the different set positions, which are recorded as each heart rail monitoring point. Each point rail monitoring point, each basic track monitoring point, and each heart rail monitoring point are numbered in the set order as each turnout monitoring point. The point rail monitoring point can monitor the state of the point rail, the basic track monitoring point can cooperate with the point rail monitoring point to detect the relationship between the point rail and the basic rail, and the heart rail monitoring point helps to understand the state of the heart rail, which is very important for ensuring the normal operation of the turnout and preventing turnout failures.

[0044] The transmission parameters include the transmission delay time and signal strength of the temperature data.

[0045] The data transmission quality analysis module is used to obtain the transmission parameters of each sampling frequency through communication transmission detection, and then evaluate the data transmission quality evaluation coefficient of each sampling frequency, determine the optimal sampling frequency, and screen out each time point.

[0046] See also Figure 2 As shown, the specific detection method of the communication transmission detection is: the first step, in a simulation environment, different acquisition frequencies are set according to the different acquisition interval durations that are initially set, recorded as each acquisition frequency, and at the same time, a fixed duration is used as an acquisition cycle, and each sampling time point is selected in the acquisition cycle according to each acquisition frequency, recorded as each sampling time point of each sampling frequency, and communication transmission detection is performed on the temperature data at each sampling time point of each sampling frequency, and the transmission delay duration of the temperature data of each sampling frequency is obtained by obtaining the temperature receiving time point and sampling time point of each sampling time point of each sampling frequency; it is helpful to understand the time delay of temperature data transmission under different acquisition frequencies, and provide an important indicator for evaluating the quality of data transmission. By analyzing the transmission delay duration, it can be determined which acquisition frequency can minimize the impact of delay on subsequent analysis and decision-making under the premise of ensuring timely data transmission.

[0047] It should be noted that the specific analysis method for the transmission delay time of the temperature data of each sampling frequency is: monitor the temperature data at each sampling time point of each sampling frequency, convert it into electrical signals for packaging, send the data packet through wireless communication, and receive it through the communication interface corresponding to the receiving end, obtain the specific time point when the temperature data at each sampling time point of each sampling frequency arrives at the receiving end, record it as the temperature receiving time point of each sampling time point of each sampling frequency, and at the same time obtain the temperature sampling time point of each sampling time point of each sampling frequency, and obtain the transmission time of the temperature data at each sampling time point of each sampling frequency by subtracting the temperature receiving time point and the sampling time point of each sampling time point of each sampling frequency, and compare it with the preset data expected transmission time to obtain the transmission delay time of the temperature data of each sampling frequency.

[0048] In the second step, several equally spaced detection points are selected on the communication cable according to the preset spacing, and the signal strength detection instrument is contacted with each detection point of the communication cable at each sampling frequency and each sampling time point through a specific interface to obtain the signal strength of each detection point corresponding to each sampling frequency and each time point, and the signal strength of each sampling frequency is obtained by average calculation; signal strength is another important indicator to measure the quality of data transmission. By detecting and analyzing the signal strength, the stability and reliability of the signal during the transmission process at different acquisition frequencies can be understood, which is helpful to judge the transmission performance of the communication cable and the impact of different acquisition frequencies on signal transmission, thereby providing comprehensive data support for determining the optimal sampling frequency.

[0049] The specific analysis method of the data transmission quality analysis module is as follows: based on the transmission delay time of the temperature data of each sampling frequency and the signal strength of each sampling frequency, the data transmission quality evaluation coefficient of each sampling frequency is evaluated, and the data transmission quality evaluation coefficient of each sampling frequency is sorted in order from large to small, and the sampling frequency corresponding to the first data transmission quality evaluation coefficient is recorded as the optimal sampling frequency, and each sampling time point of the sampling frequency is recorded as each time point; selecting the optimal sampling frequency can ensure that during the data collection and transmission process, the temperature data can be acquired and transmitted at the optimal frequency, thereby improving the validity and reliability of the data and providing high-quality data support for subsequent snow melting effect analysis and other work.

[0050] In a preferred embodiment of the present invention, the specific method of evaluating the data transmission quality evaluation coefficient of each sampling frequency is as follows: extract the transmission delay time of the temperature data of each sampling frequency and the signal strength of each sampling frequency, and then sum them up according to the weight to obtain the data transmission quality evaluation coefficient of each sampling frequency.

[0051] Exemplarily, the weights corresponding to the transmission delay time and signal strength of the temperature data are 0.6 and 0.4.

[0052] The snowmelt effect analysis module is used to obtain the temperature of each sampling point on the track and the snowmelt parameters of the track, evaluate the temperature compliance and snowmelt influence coefficient at each time point on the track, and thus evaluate the snowmelt effect evaluation index at each time point on the track.

[0053] The specific analysis method for the temperature compliance of the track at each time point is: obtaining the temperature of each rail monitoring point and each switch monitoring point at each time point of the track, and comparing them with the preset snowmelt temperature to obtain the temperature compliance of the rail part and the switch part of the track at each time point; it can intuitively reflect the degree of proximity between the temperature of the track at different time points and the temperature required for snowmelt, and provide a direct temperature index for evaluating the snowmelt effect. By analyzing the temperature compliance of different parts of the track, the temperature changes of the rails and switches during the snowmelt process can be understood, which is helpful to evaluate the snowmelt effect of each part in a targeted manner, and to promptly discover abnormal temperature areas, so as to provide a basis for subsequent temperature regulation.

[0054] In a preferred embodiment of the present invention, the specific method of evaluating the temperature compliance of the track at each time point is as follows: extract the temperature of each sampling point of the track, compare it with the preset snowmelt temperature, and then calculate the average to obtain the temperature compliance of each time point of the track.

[0055] In a preferred embodiment of the present invention, the specific method of evaluating the snowmelt effect evaluation index of the track at each time point is as follows: extract the snowmelt parameters of the track, compare them with the preset snowmelt temperature, and then perform mean calculation to obtain the snowmelt effect evaluation index of the track at each time point.

[0056] Based on the temperature compliance of the track rail part at each time point and the temperature compliance of the track switch part at each time point, the temperature compliance of the track at each time point is obtained by fusion calculation.

[0057] In a preferred embodiment of the present invention, the specific method of the fusion calculation of the temperature compliance of the track at each time point is as follows: extract the temperature compliance of the track rail part at each time point and the temperature compliance of the track switch part at each time point, and then sum them up according to the weight to obtain the temperature compliance of the track at each time point.

[0058] Exemplarily, the weights corresponding to the temperature compliance degree of the track rail part and the temperature compliance degree of the track switch part are 0.7 and 0.3.

[0059] See also Figure 3As shown, the specific analysis method of the snowmelt influence coefficient is as follows: the first step is to take a set amount of snow from different positions near the track, mix them to obtain a snow sample, record the mass as the initial mass of the snow sample, dry it at a set constant temperature until the water in the snow sample is completely evaporated, weigh the remaining solid mass of the snow sample, obtain the residual mass of the snow sample, and compare it with the initial mass of the snow sample to obtain the water content of the snow; understanding the water content of the snow can help analyze the changes in the water content of the snow during the melting process, as well as the potential impact on track snowmelt.

[0060] It should be noted that the specific analysis method of the snow water content is: read the initial mass of the snow sample and the remaining mass of the snow sample respectively, and record them as , through the formula Get the moisture content of snow .

[0061] In the second step, snow samples are collected at different locations near the track and filled into a container with a known volume scale to obtain snow samples of known volume, which are recorded as snow sampling samples. The volume is recorded as snow sampling sample volume. The snow sampling sample mass is obtained by weighing the snow sampling sample, and the snow density is calculated by the density formula. Snow with different densities differs in the heat absorption and melting speed. By measuring the snow density, we can more accurately evaluate the hindering effect of snow on track snow melting and provide more comprehensive data for snow melting effect analysis.

[0062] It should be noted that the specific analysis method of the snow density is: the snow sampling sample volume and the snow sampling sample mass are respectively recorded as , substituting it into the formula Get snow density .

[0063] The third step is to select several measuring points on the track surface, recorded as each measuring point, and apply a stable heat flux source on one side of the track structure to transfer heat from one side to the other side. At the same time, the heat flux meter is tightly fitted on each measuring point, and a temperature sensor is installed near the heat flux meter. The heat flux density of each measuring point measured by the heat flux meter and the temperature of each measuring point measured by the temperature sensor are recorded, and the thermal conductivity of the track is calculated by Fourier's law. The thermal conductivity of the track reflects the thermal conductivity of the track material, which is crucial to understanding the heat transfer method and efficiency in the track. By measuring the thermal conductivity, the heat transfer of the track during the snow melting process can be better analyzed, providing important physical parameters for evaluating the snow melting effect.

[0064] The fourth step is to obtain the snowmelt influence coefficient based on the fusion calculation of snow moisture content, snow density and thermal conductivity of the track. This can accurately evaluate the impact of the interaction of various factors on the snowmelt effect during the snowmelt process, and provide a comprehensive quantitative indicator for accurately evaluating the snowmelt effect of the track.

[0065] In a preferred embodiment of the present invention, the snowmelt influence coefficient is specifically calculated as follows: extract the snow moisture content, snow density, and thermal conductivity of the track, and then sum them up according to the weights to obtain the snowmelt influence coefficient.

[0066] Exemplarily, the corresponding weights of snow moisture content, snow density, and thermal conductivity of the track are 0.4, 0.3, and 0.3.

[0067] The temperature control module is used to select each control time point according to the snow melting effect evaluation index at each time point of the track, and then perform temperature control at each control time point.

[0068] The specific operation method of each control time point is: based on the temperature compliance degree and snowmelt influence coefficient of each time point of the track, the snowmelt effect evaluation index of each time point of the track is evaluated and compared with the preset snowmelt effect evaluation index threshold. If the snowmelt effect evaluation index of the track at a certain time point is greater than or equal to the preset snowmelt effect evaluation index threshold, it means that the snowmelt effect of the track at that time point is qualified. If the snowmelt effect evaluation index of the track at a certain time point is less than the preset snowmelt effect evaluation index threshold, it means that the snowmelt effect of the track at that time point is unqualified, and the temperature of the track at that time point needs to be controlled, and the time point is recorded as the control time point, thereby screening out each control time point; by comparing the snowmelt effect evaluation index with the threshold, the time point at which the snowmelt effect is unqualified can be accurately identified, so that the temperature of the track at these time points can be controlled in a targeted manner, the snowmelt efficiency can be improved, and the safe operation of the track can be ensured.

[0069] In a preferred embodiment of the present invention, the specific calculation method of the snowmelt effect evaluation index at each time point of the track is as follows: extract the temperature compliance degree and snowmelt influence coefficient at each time point of the track, and then sum them up according to the weight to obtain the snowmelt influence coefficient.

[0070] Exemplarily, the corresponding weights of snow moisture content, snow density, and thermal conductivity of the track are 0.7 and 0.3.

[0071] The specific operation method of the temperature control module is as follows: read the temperature of each rail monitoring point and each switch monitoring point at each time point of the track, renumber them as the temperature of each sampling point at each time point of the track, screen out the temperature of each sampling point at each control time point of the track, and obtain the required control temperature of each sampling point at each control time point of the track by subtracting it from the preset snowmelt temperature. If the required control temperature of a sampling point at a certain control time point of the track is a positive number, the temperature at the sampling point is correspondingly increased through the snowmelt equipment; if the required control temperature of a sampling point at a certain control time point of the track is a negative number, the temperature at the sampling point is correspondingly lowered; by accurately controlling the temperature of each sampling point, the snow melting effect of the track can be effectively improved, ensuring that the snow on the track surface can melt in time, and reducing the impact of snow on track operation.

[0072] After the snow-melting equipment regulates the temperature of each sampling point at each regulation time point, the snow-melting effect evaluation index of the track at each time point after regulation is analyzed again and recorded as the regulation snow-melting effect evaluation index of the track at each time point.

[0073] The snowmelt effect prediction module is used to construct a time point-snowmelt effect evaluation index curve according to the snowmelt effect evaluation index at each time point of the track, from which the snowmelt effect evaluation index at the future time point is obtained and fed back to the system.

[0074] The specific analysis method of the snow-melting effect prediction module is as follows: reading the snow-melting effect evaluation index of the track at each time point, taking the time point as the horizontal coordinate and the snow-melting effect evaluation index as the vertical coordinate, constructing a two-dimensional coordinate system, and then marking a number of points in the constructed two-dimensional coordinate system for the snow-melting effect evaluation index of the track at each time point, forming a time point-snow-melting effect evaluation index curve, substituting the future time point to be predicted into the time point-snow-melting effect evaluation index curve, obtaining the snow-melting effect evaluation index at the future time point, and feeding it back to the system; it is helpful to understand the development trend of the snow-melting effect of the track in advance, and by predicting the snow-melting effect evaluation index at the future time point, it is possible to prepare in advance to deal with the possible poor snow-melting effect, thereby ensuring the safety and normal operation of the track.

[0075] The management database is used to store preset data, estimated transmission time, reference value of transmission delay time, transmission parameters of each sampling frequency, temperature of each rail monitoring point at each time point, each switch monitoring point, snow melting parameters of the track, optimal sampling frequency and each time point.

[0076] The present invention obtains the data transmission quality evaluation coefficient of each sampling frequency according to the transmission parameter analysis of each sampling frequency, thereby determining the optimal sampling frequency, and screening out each time point, obtaining the temperature compliance of the track at each time point according to the temperature of each sampling point of the track, obtaining the snowmelt influence coefficient according to the snowmelt parameter of the track, and then analyzing to obtain the snowmelt effect evaluation index of each time point of the track, thereby screening out each control time point, and then performing temperature control on each control time point, and at the same time constructing a time point-snowmelt effect evaluation index curve, from which the snowmelt effect evaluation index of the future time point is obtained and fed back to the system, so that the key information of the track temperature change can be captured in time, so that the snowmelt measures can be implemented when it is most needed, avoiding excessive or insufficient snowmelt operations, and improving the overall snowmelt efficiency.

[0077] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention and they are still covered by the protection scope of the present invention.

Claims

1. A track temperature collection, analysis and early warning system, characterized in that: The system specifically includes the following modules: The temperature sampling point division module is used to select each rail monitoring point and each switch monitoring point on the track, collectively referred to as each sampling point; The data transmission quality analysis module is used to obtain the transmission parameters of each sampling frequency through communication transmission detection, and then evaluate the data transmission quality evaluation coefficient of each sampling frequency, determine the optimal sampling frequency, and screen out each time point; Snowmelt effect analysis module, used to obtain the temperature of each sampling point on the track and the snowmelt parameters of the track, evaluate the temperature compliance and snowmelt influence coefficient at each time point on the track, and thus evaluate the snowmelt effect evaluation index at each time point on the track; The temperature control module is used to select each control time point according to the snow melting effect evaluation index at each time point of the track, and then perform temperature control at each control time point; The snowmelt effect prediction module is used to construct a time point-snowmelt effect evaluation index curve based on the snowmelt effect evaluation index at each time point of the track, from which the snowmelt effect evaluation index at the future time point is obtained and fed back to the system; The management database is used to store preset data, estimated transmission time, reference value of transmission delay time, transmission parameters of each sampling frequency, temperature of each rail monitoring point at each time point, each switch monitoring point, snow melting parameters of the track, optimal sampling frequency and each time point.

2. A track temperature collection, analysis and early warning system according to claim 1, characterized in that: The specific operation method of the temperature sampling point division module is: The track is divided into a rail part and a switch part. According to the settings, a number of monitoring points are selected from the rail part and the switch part of the track, which are respectively recorded as rail monitoring points and switch monitoring points, collectively referred to as sampling points.

3. A track temperature collection, analysis and early warning system according to claim 1, characterized in that: The transmission parameters include the transmission delay time and signal strength of the temperature data.

4. A track temperature collection, analysis and early warning system according to claim 3, characterized in that: The specific detection method of the communication transmission detection is: The first step is to set different acquisition frequencies in a simulation environment according to the different acquisition intervals that are initially set, which are recorded as acquisition frequencies. At the same time, a fixed duration is used as an acquisition cycle. According to each acquisition frequency, each sampling time point is selected in the acquisition cycle, which is recorded as each sampling time point of each sampling frequency. The temperature data of each sampling time point of each sampling frequency is tested for communication transmission. The transmission delay of the temperature data of each sampling frequency is obtained by obtaining the temperature receiving time point and sampling time point of each sampling time point of each sampling frequency. In the second step, several equally spaced detection points are selected on the communication cable according to the preset spacing, and the signal strength detection instrument is contacted with each detection point of the communication cable at each sampling frequency and each sampling time point through a specific interface to obtain the signal strength of each detection point corresponding to each sampling frequency and each time point, and the signal strength of each sampling frequency is obtained by average calculation.

5. A track temperature collection, analysis and early warning system according to claim 4, characterized in that: The specific analysis method of the data transmission quality analysis module is: The data transmission quality evaluation coefficient of each sampling frequency is evaluated based on the transmission delay time of the temperature data of each sampling frequency and the signal strength of each sampling frequency. The data transmission quality evaluation coefficient of each sampling frequency is sorted in order from large to small, and the sampling frequency corresponding to the first data transmission quality evaluation coefficient is recorded as the optimal sampling frequency, and the sampling time points of the sampling frequency are recorded as each time point.

6. A track temperature collection, analysis and early warning system according to claim 3, characterized in that: The specific analysis method of the temperature compliance degree of the track at each time point is: Obtain the temperature of each rail monitoring point and each switch monitoring point at each time point of the track, and compare them with the preset snowmelt temperature to obtain the temperature compliance degree of the rail part and the switch part at each time point; Based on the temperature compliance of the track rail part at each time point and the temperature compliance of the track switch part at each time point, the temperature compliance of the track at each time point is obtained by fusion calculation.

7. The track temperature collection, analysis and early warning system according to claim 1 is characterized in that: The specific analysis method of the snowmelt influence coefficient is as follows: In the first step, a set amount of snow is taken from different locations near the track, mixed to obtain a snow sample, and its mass is recorded as the initial mass of the snow sample. The snow sample is dried at a set constant temperature until the water in the snow sample is completely evaporated. The remaining solid mass of the snow sample is weighed to obtain the residual mass of the snow sample, and the water content of the snow is obtained by comparing it with the initial mass of the snow sample. The second step is to collect snow samples at different locations near the track, fill them into a container with a known volume scale, obtain a snow sample of known volume, record it as a snow sampling sample, record its volume as the snow sampling sample volume, weigh the snow sampling sample to obtain the snow sampling sample mass, and calculate the snow density by the density formula; The third step is to select several measurement points on the track surface, which are recorded as measurement points. A stable heat flux source is applied on one side of the track structure to transfer heat from one side to the other side. At the same time, a heat flux meter is tightly attached to each measurement point, and a temperature sensor is installed near the heat flux meter. The heat flux density of each measurement point measured by the heat flux meter and the temperature of each measurement point measured by the temperature sensor are recorded, and the thermal conductivity of the track is calculated by Fourier's law. The fourth step is to calculate the snowmelt influence coefficient based on the fusion of snow moisture content, snow density and thermal conductivity of the track.

8. A track temperature collection, analysis and early warning system according to claim 7, characterized in that: The specific operation method of each control time point is as follows: Based on the temperature compliance and snowmelt influence coefficient of the track at each time point, the snowmelt effect evaluation index of the track at each time point is evaluated and compared with the preset snowmelt effect evaluation index threshold. If the snowmelt effect evaluation index of the track at a certain time point is greater than or equal to the preset snowmelt effect evaluation index threshold, it means that the snowmelt effect of the track at that time point is qualified. If the snowmelt effect evaluation index of the track at a certain time point is less than the preset snowmelt effect evaluation index threshold, it means that the snowmelt effect of the track at that time point is unqualified, and the temperature of the track at that time point needs to be controlled. This time point is recorded as the control time point, thereby screening out various control time points.

9. A track temperature collection, analysis and early warning system according to claim 8, characterized in that: The specific operation method of the temperature control module is: Read the temperature of each rail monitoring point and each switch monitoring point at each time point of the track, renumber them as the temperature of each sampling point at each time point of the track, select the temperature of each sampling point at each control time point of the track, and obtain the required control temperature of each sampling point at each control time point of the track by subtracting it from the preset snow melting temperature. If the required control temperature of a sampling point at a certain control time point of the track is a positive number, the temperature at the sampling point is correspondingly increased through the snow melting equipment; if the required control temperature of a sampling point at a certain control time point of the track is a negative number, the temperature at the sampling point is correspondingly decreased; After the snow-melting equipment regulates the temperature of each sampling point at each regulation time point, the snow-melting effect evaluation index of the track at each time point after regulation is analyzed again and recorded as the regulation snow-melting effect evaluation index of the track at each time point.

10. A track temperature collection, analysis and early warning system according to claim 9, characterized in that: The specific analysis method of the snow melting effect prediction module is: The snow-melting effect evaluation index of the track at each time point is read, and a two-dimensional coordinate system is constructed with the time point as the horizontal coordinate and the snow-melting effect evaluation index as the vertical coordinate. Then, several points are marked in the constructed two-dimensional coordinate system according to the snow-melting effect evaluation index of the track at each time point to form a time point-snow-melting effect evaluation index curve. The future time point to be predicted is substituted into the time point-snow-melting effect evaluation index curve to obtain the snow-melting effect evaluation index at the future time point, which is then fed back to the system.

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