Automatic steel rail temperature remote monitor
Through automated rail temperature remote monitors, distributed temperature sensors and wireless transmission technology, real-time and accurate rail temperature monitoring and abnormal identification are achieved, solving the problems of low efficiency and insufficient response speed of traditional monitoring methods, and ensuring the real-time and accuracy of railway safety management.
Patent Information
- Application Number
- CN202510250667.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-04
- Publication Date
- 2025-05-30
AI Technical Summary
Traditional rail temperature monitoring relies on manual operation and is inefficient and difficult to meet the real-time temperature change monitoring needs. Especially during train operation, the rail temperature cannot be detected in real time and accurately, resulting in insufficient response speed to abnormal temperatures.
It adopts automated rail temperature remote monitor, including distributed temperature sensors and wireless transmission technology, to detect rail temperature in real time, and perform data analysis and remote identification of abnormal points through data storage, transmission and abnormal marking modules.
The contactless all-weather rail temperature monitoring is realized, which solves the problem that temperature data cannot be obtained in real time during train operation, improves the ability to accurately capture and identify abnormalities of rail temperature changes, and ensures the real-time and accuracy of safety management.
Smart Images
Figure CN120057057A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of rail monitoring, and more particularly to an automated remote rail temperature monitor. Background Art
[0002] With the rapid development of high-speed railways, intercity railways, and subways, the railway industry, with its advantages of safety, punctuality, comfort, low carbon, and environmental protection, has currently become the preferred mode of travel for passengers.
[0003] Rail is the basic equipment to ensure the smooth and safe operation of railway trains. Due to the influence of low temperature in winter and high temperature in summer, there is a large temperature stress inside the rail. The large temperature stress poses a safety risk of rail breakage in winter and rail expansion in summer, affecting the safe operation of trains.
[0004] Traditional rail temperature monitoring mostly relies on manual operation, and technicians need to regularly enter the track area for manual detection. Although this method can directly collect data, due to the long operation cycle and low efficiency, it is difficult to meet the monitoring requirements of real-time temperature changes. Especially during train operation, in order to ensure the safety management concept of "no operation during train running and no train running during operation", operators cannot enter the track area to work, resulting in difficulties in obtaining temperature data during train operation. This time-lagged detection method seriously lacks the response speed to temperature anomalies.
[0005] Most of the current temperature monitors on the market adopt a single-point acquisition mode. Although they can obtain temperature data in a certain area, it is difficult to comprehensively cover the entire rail when facing a long-distance track system. The single-point monitoring method is prone to overlooking local temperature changes, resulting in difficulty in timely warning of systemic risks. In addition, due to the limitations of the installation environment and monitoring method, the monitoring equipment can often only cover certain key sections and cannot effectively analyze the overall temperature distribution of the rail. Summary of the Invention
[0006] In view of the deficiencies of the prior art, the present invention provides an automated remote rail temperature monitor, which solves the problems of being unable to detect the rail temperature in real time and accurately during train operation due to operation restrictions, and remotely identifying and warning abnormal temperature points.
[0007] To achieve the above object, the present invention is realized through the following technical solutions: an automated remote rail temperature monitor, including an equipment box, the lower surface of the equipment box is fixedly connected with a plug rod, the outer wall of the equipment box is fixedly connected with a first connecting frame, a limiting rod is slidably connected inside the first connecting frame, one end of the limiting rod is threadedly connected with a second connecting frame, the outer wall of the second connecting frame is slidably connected to the inner wall of the first connecting frame, the outer wall of the second connecting frame is fixedly connected with a temperature sensor, the outer wall of the temperature sensor is slidably connected inside the first connecting frame, and the upper surface of the equipment box is fixedly connected with an alarm.
[0008] Preferably, the upper surface of the equipment box is fixedly connected with a support rod, the upper surface of the support rod is fixedly connected with a second baffle, the outer wall of the second baffle is slidably connected with a first baffle, the inner wall of the first baffle is fixedly connected with a limiting block, and the outer wall of the limiting block is slidably connected to the outer wall of the second baffle.
[0009] An automated remote rail temperature monitoring system, including; A temperature detection module for detecting the temperature of the rail in real time; A data storage module for storing the detected temperature data; A data transmission module for wirelessly transmitting the temperature data; An anomaly marking module for analyzing the temperature data and marking anomaly data points; A data receiving terminal for receiving, displaying, and analyzing the temperature data and the anomaly marked data.
[0010] Preferably, the temperature detection module includes; A temperature data acquisition unit for detecting the real-time temperature of the rail; An ambient temperature acquisition unit for detecting the real-time temperature of the environment around the rail.
[0011] Preferably, the data storage module includes; A short-term storage unit for storing the real-time temperature data in the short term; A long-term storage unit for storing the historical temperature data for subsequent analysis.
[0012] Preferably, the data transmission module includes; A real-time transmission unit for transmitting the real-time data when the rail temperature changes; A batch transmission unit for batch transmitting the historical temperature data in a non-emergency state; A redundancy unit for reattempting to transmit in case of data transmission failure to ensure data integrity.
[0013] Preferably, the anomaly marking module includes; A threshold model detection unit for marking abnormal data points according to a preset temperature stress threshold; A dynamic threshold adjustment unit for dynamically adjusting the detection threshold based on ambient temperature changes and historical data; A machine learning unit for analyzing historical data and optimizing the accuracy of abnormal marking.
[0014] Preferably, the data receiving terminal includes; A display unit for real-time displaying of rail temperature data and abnormal points; An analysis unit for generating a rail temperature change trend graph and a prediction report; An alarm unit for emitting an audible and visual alarm signal when the temperature stress reaches a dangerous value; A historical data query unit for retrieving and displaying rail temperature data for a specific time period.
[0015] Preferably, the change trend of the temperature stress is calculated based on the following functional relationship; Rail temperature stress = coefficient of thermal expansion of rail material × (real-time rail temperature - line-locked rail temperature) × elastic modulus of rail; Wherein, the line-locked rail temperature is the actual rail-locking temperature during rail laying, and the coefficient of thermal expansion and the elastic modulus are determined according to the characteristics of the rail material.
[0016] Preferably, the dynamic threshold adjustment unit is used to adjust the temperature stress threshold in real time according to the following parameters: The change trend of the ambient temperature in the area where the rail is located; The change rule of the rail historical temperature data; The coefficient of thermal expansion and the elastic modulus of the rail material; Wherein, the dynamic threshold adjustment unit can calculate and generate a new temperature stress threshold through the above parameters to meet the rail stress change requirements in different operating environments and time periods.
[0017] The present invention provides an automated remote rail temperature monitor. It has the following beneficial effects: 1. By pushing the limit rod to drive the second connecting frame to move, the limit rod slides on the first connecting frame. The movement of the second connecting frame drives the temperature sensor to move, so that the temperature sensor slides within the first connecting frame, and the movement of the temperature sensor contacts the rail. By rotating the limit rod within the second connecting frame, the second connecting frame is limited, thereby achieving the effect of fixing the temperature sensor to prevent it from falling.
[0018] 2. By adopting the technical solution of combining distributed temperature sensors with wireless transmission, the present invention achieves the technical effect of non-contact all-weather monitoring of rail temperature. In the prior art, traditional rail temperature measurement equipment requires on-site operation and cannot meet the safety management requirements of "no operation during train operation". However, the present invention successfully solves the problem of being unable to accurately obtain temperature data at any time during train operation by installing fixed sensors on the rail and combining remote monitoring.
[0019] 3. By adopting the technical solution of real-time temperature acquisition and dynamic threshold adjustment, the present invention achieves the technical effect of accurately capturing rail temperature changes and identifying abnormalities. Compared with the monitoring scheme relying on fixed thresholds in the prior art, which is difficult to adapt to environmental temperature fluctuations, the present invention solves the problem of frequent false alarms and missed alarms in extreme climates by combining real-time temperature difference and historical data trend analysis.
[0020] 4. By adopting the technical solution of combining data compression storage and hierarchical storage, the present invention realizes the efficient utilization of storage space and ensures data security. Different from the prior art where directly storing large-scale real-time data leads to rapid exhaustion of storage capacity, the present invention solves the problem of low data management efficiency during long-term operation through hierarchical management of short-term and long-term data. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] Figure 1 is a perspective view of the present invention; Figure 2 is a sectional view of the first connecting frame of the present invention; Figure 3 is an exploded view of the second baffle of the present invention; Figure 4 is a schematic diagram of the system framework of the present invention; Figure 5 is a schematic diagram of the temperature detection module of the present invention; Figure 6 is a schematic diagram of the data storage module of the present invention; Figure 7 is a schematic diagram of the data transmission module of the present invention; Figure 8 is a schematic diagram of the anomaly marking module of the present invention; Figure 9 is a schematic diagram of the data receiving terminal of the present invention.
[0022] Among them, 1. Equipment box; 2. Insert rod; 3. First connecting frame; 4. Support rod; 5. First baffle; 6. Alarm; 7. Limit rod; 8. Temperature sensor; 9. Second connecting frame; 10. Second baffle; 11. Limit block. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.
[0024] Please refer to the attached Figure 1 - attached Figure 3 , the embodiment of the present invention provides an automatic remote monitoring instrument for rail temperature, including an equipment box 1. A plug rod 2 is fixedly connected to the lower surface of the equipment box 1. A first connecting frame 3 is fixedly connected to the outer wall of the equipment box 1. A limiting rod 7 is slidably connected inside the first connecting frame 3. One end of the limiting rod 7 is threadedly connected to a second connecting frame 9. The outer wall of the second connecting frame 9 is slidably connected to the inner wall of the first connecting frame 3. A temperature sensor 8 is fixedly connected to the outer wall of the second connecting frame 9. The outer wall of the temperature sensor 8 is slidably connected inside the first connecting frame 3. An alarm 6 is fixedly connected to the upper surface of the equipment box 1; Specifically, by placing the equipment box 1 beside and pressing the equipment box 1 to insert the plug rod 2 into the ground, the equipment box 1 is installed on the ground. By pushing the limiting rod 7 to drive the second connecting frame 9 to move, the limiting rod 7 slides on the first connecting frame 3. By the movement of the second connecting frame 9, the temperature sensor 8 is driven to move, so that the temperature sensor 8 slides inside the first connecting frame 3 and contacts the rail through the movement of the temperature sensor 8. By rotating the limiting rod 7 inside the second connecting frame 9, the second connecting frame 9 is limited, thereby achieving the effect of fixing the temperature sensor 8 to prevent it from falling. When the temperature is abnormal, the alarm 6 emits sound and light to achieve a warning effect.
[0025] A support rod 4 is fixedly connected to the upper surface of the equipment box 1. A second baffle 10 is fixedly connected to the upper surface of the support rod 4. A first baffle 5 is slidably connected to the outer wall of the second baffle 10. A limiting block 11 is fixedly connected to the inner wall of the first baffle 5. The outer wall of the limiting block 11 is slidably connected to the outer wall of the second baffle 10; Specifically, by pulling the first baffle 5 to slide on the second baffle 10 and driving the limiting block 11 to slide on the second baffle 10 through the movement of the first baffle 5, the first baffle 5 is unfolded to one side, and the first baffle 5 and the second baffle 10 achieve the effect of protecting the equipment.
[0026] Please refer to the attached Figure 4 - attached Figure 9 , an automatic remote monitoring system for rail temperature, including; A temperature detection module for real-time detection of the temperature of the rail; Specifically, in this embodiment, the temperature detection module is responsible for real-time detection of the rail temperature, and provides basic data support for subsequent data analysis, anomaly marking, and temperature stress calculation by performing high-precision acquisition of the temperature changes of the rail and its surrounding environment; Specifically, the temperature data acquisition unit is used to detect the real-time temperature of the rail surface. A contact temperature sensor is adopted. By closely adhering to the rail surface, the contact sensor can accurately sense the instantaneous temperature change of the rail; The ambient temperature acquisition unit is combined with the temperature data acquisition unit to record the ambient temperature around the rail simultaneously. Specifically, this unit uses a non-contact sensor to measure the ambient temperature remotely, avoiding measurement errors caused by the direct exposure of the sensor to the outside. The data acquired for the ambient temperature provides the basic input for the temperature difference calculation unit and can support the analysis of the temperature difference between the rail and the environment; In this embodiment, the temperature difference calculation unit calculates the temperature gradient between the rail and the environment according to the following formula;
[0027] where, represents the temperature gradient between the rail and the environment; represents the real-time temperature of the rail, which is obtained by the temperature data acquisition unit; represents the real-time temperature of the environment, which is obtained by the ambient temperature acquisition unit; The temperature difference calculation unit uses the temperature gradient as an input parameter for the anomaly marking module. If the temperature difference exceeds the set threshold, the system will activate the anomaly marking mechanism and notify the data receiving terminal. The temperature detection module can also perform real-time calibration in combination with the data storage module to eliminate possible deviations during long-term operation. Specifically, the system analyzes the historical temperature data and dynamically adjusts the measurement parameters of the temperature sensor, thereby further improving the measurement accuracy; The temperature detection module can be expanded to add multiple sensor nodes, and perform multi-point temperature detection on long-distance rails through a distributed architecture. The overall temperature change trend of the rail is calculated by the weighted average method for the results of multi-point detection, and its formula is;
[0028] where, represents the average temperature of the rail; represents the th temperature value of the sensor node; represents the th weight of the sensor node; represents the total number of sensor nodes; The weights of the sensors are dynamically adjusted according to their positions and detection conditions to ensure the accuracy of the average temperature calculation; By simultaneously collecting the rail temperature and the ambient temperature and using the temperature difference calculation unit for data processing, this module can not only provide basic data for subsequent anomaly marking.
[0029] Data storage module, used to store the detected temperature data; Specifically, in this implementation, the data collected by the rail temperature detection module is classified, stored, managed, and backed up. In the data storage module, the temperature data for different time periods need to be managed separately. Real-time data is usually preferentially stored in the short-term storage unit, while historical data is stored in the long-term storage unit in a compressed form. Through the classification storage method, the efficiency of data storage can be effectively improved, and the pressure on the use of storage space can be reduced; Specifically, the short-term storage unit is used to store the real-time temperature data collected by the rail temperature detection module. The unit stores the data in units of time slices, and stores the rail temperature and ambient temperature data for 1 minute as one entry; The short-term storage unit can initially classify the collected temperature data, and mark the time periods with large temperature differences as "high stress risk data". This classification information can be directly transmitted to the anomaly marking module to provide prior support for the anomaly recognition of the system; The long-term storage unit is used to save the processed historical data. This unit uses a compression storage algorithm to downsample and compress the storage of temperature data. The average temperature data for one hour can be calculated by the following formula
[0030] where, represents the average temperature within one hour; represents the th sampled rail temperature within this hour; represents the number of samplings within this hour; In the long-term storage unit, not only the average value is stored, but also the maximum and minimum values of the temperature can be recorded. The maximum temperature is determined by the following formula:
[0031] where, represents the highest value of the rail temperature within this hour; The meanings of other symbols are the same as those in the above formula; By storing the average value and extreme value information, the long-term storage unit can provide complete data support for historical trend analysis; The data storage module adopts a dual-backup mechanism to improve the security and integrity of data storage. When the main storage unit fails, the redundant storage unit can be immediately activated to ensure that data is not lost. When the storage capacity is approaching the upper limit, the system can choose to deeply compress some low-priority data and only retain key statistical information. This method can maximize the storage capacity of historical data within a limited storage space; Specifically, when abnormal data is detected, the system will first write the abnormal data into the long-term storage unit and attach marker information, which may include the time point when the abnormality occurred, the temperature value and its corresponding temperature difference; Through the hierarchical storage of short-term and long-term data, the system can not only meet the needs of real-time monitoring but also provide support for long-term trend analysis.
[0032] The data transmission module is used to wirelessly transmit the temperature data; Specifically, in this implementation, the data transmission module timely transmits the data obtained by the temperature detection module and the data storage module to the data receiving terminal to support real-time monitoring and subsequent analysis. The data transmission module needs to ensure the integrity and accuracy of the data while guaranteeing the transmission speed; Specifically, the real-time transmission unit is responsible for immediately transmitting the data to the data receiving terminal when the rail temperature data is abnormal or undergoes a significant change. The unit triggers the transmission mechanism through a preset threshold. When the rail temperature gradient exceeds the critical value, the system automatically sends the data entry to the terminal. The threshold can be calculated based on the following formula;
[0033] where, represents the critical temperature difference value for triggering real-time transmission is the real-time rail temperature; is the real-time ambient temperature; The real-time transmission unit packs the abnormal temperature data and its additional information such as time and location and sends it in the form of a data packet; The data packet is transmitted to the terminal in real time through a wireless communication protocol (such as 4G / 5G, LoRa or Wi-Fi) to ensure that technicians can obtain abnormal information in a timely manner; The receiving terminal feeds back the transmission completion status to the sending end after successfully receiving the data packet. If the confirmation information is not received, the real-time transmission unit will repeat the transmission until successful; The batch transfer unit is used to periodically transfer historical stored data. The batch transfer unit packs the historical data in the data storage module according to a preset time interval and sends it to the terminal. The main feature of the batch transfer mode is high transfer efficiency and low occupancy of network bandwidth; Specifically, during the batch transfer process, the system compresses the data and calculates the compression ratio using the following formula;
[0034] represents the data compression ratio; is the size of the data before compression; is the size of the data after compression; Batch transfer usually uses a transfer protocol with low bandwidth requirements (such as TCP / IP or UDP) to ensure stable transfer even in a poor communication environment; After the batch transfer is completed, the system verifies the transferred data (such as CRC verification) to ensure that the data is not damaged during the transfer process; In this embodiment, the data transfer module further includes a redundancy unit for enhancing the reliability of the transfer. Specifically, when the real-time transfer unit or the batch transfer unit fails to transfer due to poor network signal or communication interruption, the redundancy unit will start a retransmission mechanism. The redundancy unit automatically detects the data entries that have failed to transfer and repeats the transfer until the transfer is successful. For data that still cannot be transferred after multiple attempts, the system will temporarily store it locally and give it priority for transfer when the next communication is restored; The data transfer module also supports collaborative work with distributed storage nodes. Specifically, when data needs to be synchronized between storage nodes, the module can efficiently complete data interaction through packet transfer. The specific logic of packet transfer can be optimized according to the following formula;
[0035] Among them, is the total transfer time is the size of the is the bandwidth of the is the total number of packets; By dynamically allocating the transfer paths, the system can maximize the data transfer efficiency; The data transmission module of this embodiment ensures the timely transmission of data and also improves the reliability and flexibility of transmission through various mechanisms. Whether in real-time transmission or batch transmission scenarios, this module can adapt to complex and changing communication environments. Through redundant design and packet optimization, this module can effectively cope with communication failures or insufficient network resources. These technical features enable the present invention to exhibit excellent stability and reliability in the railway operation environment.
[0036] Anomaly marking module, used to analyze temperature data and mark abnormal data points; Specifically, the anomaly marking module of this embodiment analyzes the temperature data transmitted by the data storage module, identifies potential abnormal points, and provides a basis for subsequent alarms and decisions. The anomaly marking module combines real-time data and historical data, and dynamically adjusts the judgment criteria through the analysis of temperature change rules; Specifically, the threshold model detection unit preliminarily screens abnormal data points through a preset temperature stress threshold, and the system calculates the temperature stress according to the following formula;
[0037] Where, represents the temperature stress of the rail; represents the coefficient of thermal expansion of the rail material; represents the elastic modulus of the rail; represents the real-time temperature of the rail; represents the reference temperature of the rail, usually the initial temperature at the time of installation; When the temperature stress exceeds the preset threshold, the system will mark this data point as abnormal, and the threshold can be adjusted according to seasonal changes or regional climate conditions; The dynamic threshold adjustment unit optimizes the above threshold to cope with the complex fluctuations caused by environmental temperature changes. Specifically, this unit combines the real-time environmental temperature and the historical data trend to dynamically generate a new threshold. The formula for dynamic threshold adjustment is;
[0038] Where, represents the temperature stress threshold after dynamic adjustment represents the adjustment coefficient, which is automatically fitted from historical data Represents the temperature difference between the current rail and the ambient temperature; Represents the historical average temperature difference within the corresponding time period; Through this dynamic adjustment method, false alarms caused by external environmental fluctuations can be significantly reduced; The machine learning unit conducts in-depth analysis on historical data and optimizes the anomaly marking strategy by combining real-time collected data. The machine learning unit trains the anomaly classification model through a supervised learning algorithm. The training data includes normal data points and marked anomaly data points. After the model training is completed, it can be used to identify anomaly patterns in temperature data in real time; Specifically, the input feature vector of the machine learning unit contains the following parameters; Is the real-time temperature of the rail; Is the real-time ambient temperature; Is the real-time temperature difference; Is the historical average temperature; Is the temperature stress calculated based on the formula; The model output is the classification result, marking whether the current data point is an anomaly point. The machine learning unit can continuously iterate and optimize the model to make its identification of anomaly points under complex conditions more accurate; The anomaly marking module also includes an anomaly classification function. Specifically, the system classifies the marked anomaly data points into two categories according to the type: rail break risk points and rail buckling risk points. Rail break risk points usually correspond to anomalies under low temperature conditions, while rail buckling risk points mostly appear in high temperature weather. The classification basis can be judged by combining the following formula; Rail break risk;
[0039] Rail buckling risk;
[0040] Where; And Are the temperature thresholds under the corresponding conditions, set based on historical climate data and rail material properties; The anomaly marking module significantly improves the identification accuracy of rail temperature anomaly points through a multi-level judgment and dynamic adjustment mechanism. Combined with the intelligent analysis of the machine learning unit, this module can not only accurately capture potential risk points, but also adapt to different operating environments and complex temperature change patterns.
[0041] The data receiving terminal is used to receive, display and analyze temperature data and anomaly marking data; Specifically, in this embodiment, the data receiving terminal receives the rail temperature data sent from the data transmission module, and processes, analyzes, and displays the data in various ways. The data receiving terminal closely cooperates with other modules of the system to ensure that technicians can grasp the changes in rail temperature in real time. Through intuitive displays and multi-dimensional analysis functions, the terminal can quickly locate abnormal points and generate relevant reports to provide support for subsequent decision-making. The terminal is equipped with a high-resolution display screen to display the temperature change curve, abnormal point markings, and comparison data of the temperature difference between the environment and the rail in real time. Technicians can directly view various analysis results on the screen. When the data transmission module sends an abnormal temperature alarm, technicians carry mobile devices to observe and go to the abnormal location to ensure a quick response; Specifically, the display unit is the core part of the data receiving terminal and is responsible for displaying the rail temperature data in a graphical manner. The display unit uses a high-resolution screen and presents the real-time temperature change trend in the form of a line chart or a bar chart. The display unit can also superimpose and compare the real-time temperature of the rail with the ambient temperature to directly reflect the difference between the two. The display content usually includes the following main information; Real-time rail temperature ; Real-time ambient temperature ; Temperature difference ; Abnormal point marking information; The analysis unit is used to deeply analyze the received temperature data. Specifically, this unit calculates the rail temperature stress through a built-in algorithm model and generates a corresponding change trend chart. The calculation formula for temperature stress is as follows;
[0042] Where, represents the rail temperature stress; is the coefficient of thermal expansion of the rail material; is the elastic modulus of the rail; is the real-time rail temperature; is the reference temperature when the rail is installed; The analysis unit will generate a real-time curve of stress change according to the above formula and predict the future temperature stress trend in combination with historical data. When the prediction result shows that the temperature stress approaches or exceeds the safety threshold, the system will prompt technicians to take necessary measures; After the data receiving terminal completes the temperature change analysis and abnormal point marking, it outputs the analysis results to the display module, and at the same time clears the temporary cache data during the analysis process. After the analysis is completed, it records the corresponding data analysis time, results, and whether an alarm is triggered in the terminal log module for subsequent review. In this embodiment, the alarm unit is responsible for sending an alarm signal when the temperature stress reaches a dangerous value. The alarm unit adopts an integrated design of sound and light, and uses a buzzer and an indicator light to prompt technicians of abnormal situations. The alarm threshold is dynamically adjusted by the abnormal marking module. When the temperature difference exceeds the critical value calculated by the following formula, an alarm is triggered;
[0043] represents the alarm temperature difference threshold; is the adjustment coefficient; and are the historical maximum temperature difference and the historical average temperature difference respectively; The alarm unit supports a hierarchical alarm mechanism. Specifically, when the number of abnormal points is small, the system will give a low-priority prompt; when a large number of abnormal points are detected, the system will issue a high-priority alarm; When an abnormal point triggers an alarm signal, the terminal will record the alarm event and issue an alarm according to the number and level of abnormal points. After the technician manually confirms a known abnormality through the terminal interface, the system records the confirmation time and ends the alarm prompt. If there is no human intervention, the alarm signal will automatically end after a set delay time, recorded as an unconfirmed status, and at the same time the alarm information will be stored in the log for subsequent query.
[0044] The historical data query unit is used to retrieve and display the rail temperature data for a specific time period. Users can retrieve historical records by entering query conditions. The query results are presented in a list form and accompanied by corresponding statistical analysis; Real-time temperature change curve; Maximum temperature 、Minimum temperature and average temperature ; Abnormal point distribution and classification results; The historical data query unit also supports an export function. Users can export the query results to external devices in the form of tables or graphs for further report generation; The data receiving terminal can give full play to the role of data processing and display. Whether it is real-time monitoring or historical query, users can obtain key information in a simple way. Combining the functions of the analysis unit and the alarm unit, the terminal can provide comprehensive support for railway maintenance and safe operation.
[0045] Working principle: Place the equipment box 1 beside and press the equipment box 1 to insert the insertion rod 2 into the ground, and install the equipment box 1 on the ground. Drive the second connecting frame 9 to move by pushing the limit rod 7, so that the limit rod 7 slides on the first connecting frame 3. Drive the temperature sensor 8 to move by the movement of the second connecting frame 9, so that the temperature sensor 8 slides inside the first connecting frame 3, and contact the rail through the movement of the temperature sensor 8. Rotate the limit rod 7 to rotate inside the second connecting frame 9 to limit the second connecting frame 9, and further achieve the effect of fixing the temperature sensor 8 to prevent it from falling. Pull the first baffle 5 to slide on the second baffle 10, and drive the limit block 11 to slide on the second baffle 10 by the movement of the first baffle 5, so that the first baffle 5 unfolds to one side. Achieve the effect of protecting the equipment through the first baffle 5 and the second baffle 10, and prevent rainwater from affecting the equipment box 1. When the temperature sensor 8 detects abnormal temperature, make a sound and emit light through the alarm 6 to achieve a warning effect.
[0046] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.
Claims
1. An automated rail temperature remote monitoring device, comprising an equipment box (1), characterized in that: The lower surface of the equipment box (1) is fixedly connected to a plug rod (2); the outer wall of the equipment box (1) is fixedly connected to a first connecting frame (3); the interior of the first connecting frame (3) is slidably connected to a limit rod (7); one end of the limit rod (7) is threadedly connected to a second connecting frame (9); the outer wall of the second connecting frame (9) is slidably connected to the inner wall of the first connecting frame (3); the outer wall of the second connecting frame (9) is fixedly connected to a temperature sensor (8); the outer wall of the temperature sensor (8) is slidably connected to the interior of the first connecting frame (3); and the upper surface of the equipment box (1) is fixedly connected to an alarm (6).
2. The automated rail temperature remote monitoring device according to claim 1, characterized in that: The upper surface of the equipment box (1) is fixedly connected to a support rod (4), the upper surface of the support rod (4) is fixedly connected to a second baffle (10), the outer wall of the second baffle (10) is slidably connected to the first baffle (5), the inner wall of the first baffle (5) is fixedly connected to a limit block (11), and the outer wall of the limit block (11) is slidably connected to the outer wall of the second baffle (10).
3. An automated rail temperature remote monitoring system, according to the automated rail temperature remote monitoring instrument of claims 1-2, characterized in that: include; Temperature detection module, used to detect the temperature of the rail in real time; A data storage module, used for storing the detected temperature data; A data transmission module, used for wirelessly transmitting the temperature data; Anomaly marking module, used to analyze temperature data and mark abnormal data points; The data receiving terminal is used to receive, display and analyze temperature data and abnormal marking data.
4. The automated rail temperature remote monitoring system according to claim 3, characterized in that: The temperature detection module comprises: Temperature data acquisition unit, used to detect the real-time temperature of the rail; The ambient temperature acquisition unit is used to detect the real-time temperature of the environment around the rail.
5. The automated rail temperature remote monitoring system according to claim 3, characterized in that: The data storage module comprises: A short-term storage unit is used to store real-time temperature data in a short period of time; Long-term storage unit for storing historical temperature data for subsequent analysis.
6. The automated rail temperature remote monitoring system according to claim 3, characterized in that: The data transmission module comprises: A real-time transmission unit for transmitting real-time data when the rail temperature changes; Batch transmission unit, used for batch transmission of historical temperature data in non-emergency state; Redundancy unit to retry transmission when data transmission fails to ensure data integrity.
7. The automated rail temperature remote monitoring system according to claim 3, characterized in that: The abnormal marking module includes: A threshold model detection unit, used to mark abnormal data points according to a preset temperature stress threshold; A dynamic threshold adjustment unit, used to dynamically adjust the detection threshold based on ambient temperature changes and historical data; A machine learning unit that analyzes historical data and optimizes the accuracy of anomaly labeling.
8. The automated rail temperature remote monitoring system according to claim 3, characterized in that: The data receiving terminal comprises: Display unit, used to display rail temperature data and abnormal points in real time; Analysis unit, used to generate rail temperature trend graph and forecast report; An alarm unit, used to send out an audible and visual alarm signal when the temperature stress reaches a dangerous value; The historical data query unit is used to retrieve and display the rail temperature data for a specific time period.
9. The automated rail temperature remote monitoring system according to claim 8, characterized in that: The variation trend of the temperature stress is calculated based on the following functional relationship: Rail temperature stress = rail material thermal expansion coefficient × (rail real-time temperature - line locking rail temperature) × rail elastic modulus; Among them, the line locking rail temperature is the actual locking rail temperature when the rail is laid, and the thermal expansion coefficient and elastic modulus are determined according to the material properties of the rail.
10. The automated rail temperature remote monitoring system according to claim 7, characterized in that: The dynamic threshold adjustment unit is used to adjust the temperature stress threshold in real time according to the following parameters: The changing trend of ambient temperature in the area where the rails are located; The changing pattern of rail historical temperature data; The coefficient of thermal expansion and modulus of elasticity of the rail material; Among them, the dynamic threshold adjustment unit can generate a new temperature stress threshold through the above-mentioned parameter calculation to adapt to the rail stress change requirements in different operating environments and time periods.