Temperature monitoring system and method based on surface acoustic wave technology

Abstract

The invention relates to the technical field of temperature monitoring, and discloses a surface acoustic wave technology-based temperature monitoring system and method, and the system comprises a temperature collection module, a data processing module and a temperature monitoring module which are in communication connection in sequence. The method corresponds to the system. According to the application, the temperature acquisition module solves the problems of complex wiring and electromagnetic interference by using a passive and wireless surface acoustic wave sensor; a temperature distribution coordinate system constructed by the data processing module fuses three-dimensional data of time, space and temperature, so that the temperature field distribution of the equipment is reflected more comprehensively; the temperature monitoring module realizes dynamic early warning of abnormal temperature; through the surface acoustic wave sensor, the anti-interference capability and the measurement precision are improved, the temperature change trend and early warning can be generated in real time, the equipment overheating accident risk is effectively reduced, and a solution with universality and intelligence is provided for intelligent power equipment state monitoring.

Description

Technical Field

[0001] The present application relates to the field of temperature monitoring technology, and specifically to a temperature monitoring system and method based on surface acoustic wave technology. Background Art

[0002] During the operation of power equipment, abnormal temperatures are a significant factor leading to failures. This is especially true for fully enclosed electrical cabinets, which place higher demands on temperature monitoring due to their confined space and electromagnetic radiation. Conventional infrared thermometers cannot penetrate the cabinet for internal monitoring, temperature patches require manual observation for color changes and cannot provide online warnings, and wired temperature measurement systems suffer from complex wiring and susceptibility to electromagnetic interference. Furthermore, existing monitoring systems are often limited to single-point measurement, making it difficult to construct comprehensive temperature distribution models and achieve real-time collection, processing, and dynamic warning of multi-location temperature data. This results in inefficient monitoring of potential equipment overheating risks.

[0003] Chinese invention patent application publication number CN104406710A discloses an online monitoring system and method for the operating temperature of GIS internal disconnectors based on surface acoustic wave technology. However, this invention focuses on monitoring the operating temperature of GIS internal disconnectors, and its application scenario is limited to GIS equipment, with a relatively limited monitoring object and scope. Chinese invention patent application publication number CN114739531A discloses a gas-fired hot air unit temperature monitoring system based on surface acoustic wave technology. However, this invention focuses on gas-fired hot air unit temperature monitoring, targeting only specific equipment types, and has shortcomings in terms of functional expansion and compatibility of the monitoring system.

[0004] In summary, a new technical solution for temperature monitoring based on surface acoustic wave technology is urgently needed. Summary of the Invention

[0005] The purpose of this application is to provide a temperature monitoring system and method based on surface acoustic wave technology to solve the technical problems raised in the above background technology.

[0006] To achieve the above objectives, this application discloses the following technical solutions:

[0007] In a first aspect, the present application discloses a temperature monitoring system based on surface acoustic wave technology, the system comprising a temperature acquisition module, a data processing module, and a temperature monitoring module that are sequentially communicatively connected; wherein the temperature acquisition module is disposed in the monitored object, and the data processing module and the temperature monitoring module are disposed on a monitoring platform;

[0008] The temperature acquisition module is configured to: place multiple surface acoustic wave sensors at different locations of the monitored object, collect corresponding target temperature data, and upload the target temperature data; wherein the target temperature data includes the target temperature and its corresponding collection time and collection location;

[0009] The data processing module is configured to: receive and process the target temperature data, generate and transmit a temperature distribution coordinate system, wherein the temperature distribution coordinate system is constructed based on the target temperature data and stores the target temperature data;

[0010] The temperature monitoring module is configured to receive and monitor the temperature distribution coordinate system and generate a corresponding temperature change warning.

[0011] Preferably, the monitored object includes at least a fully enclosed electrical cabinet.

[0012] Preferably, the step of arranging a plurality of surface acoustic wave sensors at different positions of the monitored object specifically includes:

[0013] The surface acoustic wave sensors are respectively arranged at multiple contacts and multiple outgoing wire connectors of the fully enclosed electrical cabinet; wherein the surface acoustic wave sensors are selected based on parameter disturbances during the operation of the fully enclosed electrical cabinet, and the parameters are used to characterize the changes in temperature, pressure, strain and mass of the operating environment of the surface acoustic wave sensors caused by the operation of the fully enclosed electrical cabinet.

[0014] Preferably, the construction of the temperature distribution coordinate system specifically includes:

[0015] Analyzing the target temperature to obtain a temperature axis;

[0016] Analyzing the acquisition time corresponding to the target temperature, and mapping the target temperature to the same time axis;

[0017] parsing the acquisition position corresponding to the target temperature, spatially assigning the acquisition position based on its corresponding spatial position in the fully enclosed electrical cabinet to obtain a corresponding position axis, and mapping the target temperature onto the position axis;

[0018] The temperature distribution coordinate system is obtained by taking the time axis as the x-axis of the temperature distribution coordinate system, taking the position axis as the y-axis of the temperature distribution coordinate system, and taking the temperature axis as the z-axis of the temperature distribution coordinate system.

[0019] Preferably, the generation of the temperature change warning specifically includes:

[0020] Run the temperature distribution monitoring model, monitor the temperature distribution coordinate system, and generate the corresponding temperature change warning; wherein, the temperature distribution monitoring model is used to monitor the deviation between the temperature distribution coordinate system and the critical temperature distribution coordinate system, and generate the corresponding temperature change warning, the critical temperature distribution coordinate system is used to characterize the critical state of the normal temperature distribution, and the critical temperature distribution coordinate system is composed of critical temperature data corresponding to the target temperature data, and the critical temperature data includes the critical temperature and its corresponding collection time and collection position.

[0021] Preferably, the temperature distribution monitoring model specifically includes:

[0022] Obtain a historical temperature distribution coordinate system and its corresponding historical temperature change warning, and select the historical temperature distribution coordinate system when the historical temperature change warning was generated;

[0023] Performing fitting based on the screened historical temperature distribution coordinate system, determining the critical temperatures at different acquisition moments and their corresponding acquisition positions, generating corresponding critical temperature data based on the acquisition moments, the acquisition positions, and the critical temperatures, and generating the critical temperature distribution coordinate system based on the critical temperature data;

[0024] After the critical temperature distribution coordinate system is stored in the temperature distribution monitoring model, it is used for comparison monitoring with the temperature distribution coordinate system.

[0025] Preferably, the monitoring of the deviation between the temperature distribution coordinate system and the critical temperature distribution coordinate system and generating the corresponding temperature change warning specifically includes:

[0026] Analyze the first deviations between the target temperature data of the temperature distribution coordinate system and the critical temperature data of the corresponding critical temperature distribution coordinate system, count the number of first anomalies in each first deviation that do not meet the preset temperature deviation threshold, and generate the corresponding first temperature change warning based on the ratio of the number of first anomalies to the total number of first deviations. The first temperature change warning belongs to the temperature change warning.

[0027] Preferably, the monitoring of the deviation between the temperature distribution coordinate system and the critical temperature distribution coordinate system and generating the corresponding temperature change warning further includes:

[0028] analyzing each deviation between each target temperature data in the temperature distribution coordinate system and each critical temperature data in the corresponding critical temperature distribution coordinate system, counting the number of anomalies in each deviation that do not meet a preset temperature deviation threshold, and generating the corresponding first temperature change warning based on a ratio of the number of anomalies to the total number of each deviation, where the first temperature change warning belongs to the temperature change warning;

[0029] Extracting critical distribution characteristics of the critical temperature between different acquisition positions corresponding to the same acquisition time in the critical temperature distribution coordinate system;

[0030] extracting target distribution characteristics of the target temperature between different acquisition positions corresponding to the acquisition time in the temperature distribution coordinate system;

[0031] Analyze the second deviations between the target temperature data of the target distribution feature and the critical temperature data of the critical distribution feature corresponding to the acquisition time of the target distribution feature, count the number of second anomalies that do not meet the preset temperature deviation threshold in each second deviation, and generate a corresponding second temperature change warning based on the ratio of the number of second anomalies to the total number of each second deviation, where the second temperature change warning belongs to the temperature change warning.

[0032] Preferably, the temperature deviation threshold specifically includes:

[0033] Based on the target temperature data and its corresponding critical temperature data, a temperature deviation threshold value for different collection moments and corresponding different collection positions is determined. The temperature deviation threshold value is used to characterize the allowable deviation in the difference between the target temperature and the critical temperature at different collection moments and corresponding different collection positions.

[0034] In a second aspect, the present application discloses a temperature monitoring method based on surface acoustic wave technology, which is applicable to the temperature monitoring system based on surface acoustic wave technology as described above, and comprises:

[0035] S1: placing multiple surface acoustic wave sensors at different locations of the monitored object, collecting corresponding target temperature data, and uploading the target temperature data; wherein the target temperature data includes the target temperature and its corresponding collection time and collection location;

[0036] S2: Receive and process the target temperature data, generate and transmit a temperature distribution coordinate system, wherein the temperature distribution coordinate system is constructed based on the target temperature data and stores the target temperature data;

[0037] S3: Receive and monitor the temperature distribution coordinate system, and generate a corresponding temperature change warning.

[0038] Beneficial effects: The temperature monitoring system and method based on surface acoustic wave technology of the present application realizes high-precision temperature monitoring of scenarios such as fully enclosed electrical cabinets through the collaborative design of surface acoustic wave technology and multiple modules; the temperature acquisition module uses passive wireless surface acoustic wave sensors distributed at key positions such as contacts and outlet connectors, which solves the problems of complex wiring and electromagnetic interference of traditional wired temperature measurement, and improves environmental adaptability by selecting sensors based on parameter disturbance; the temperature distribution coordinate system constructed by the data processing module integrates three-dimensional data of time, space and temperature, and reflects the temperature field distribution of the equipment more comprehensively than single-point measurement; the temperature monitoring module realizes dynamic early warning of abnormal temperature through critical temperature comparison and multi-dimensional deviation analysis, which is more accurate than traditional threshold alarm; through surface acoustic wave sensors, the anti-interference ability and measurement accuracy are improved, and temperature change trends and early warnings can be generated in real time, effectively reducing the risk of equipment overheating accidents, and providing a universal and intelligent solution for smart power equipment status monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 A structural block diagram of a temperature monitoring system based on surface acoustic wave technology provided in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of the arrangement of a surface acoustic wave sensor for a temperature monitoring system based on surface acoustic wave technology provided in an embodiment of the present application;

[0042] Figure 3 This is a flowchart of a temperature monitoring method based on surface acoustic wave technology provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The following is a clear and complete description of the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0044] In this document, the term "comprising" is intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0045] This embodiment is applied to temperature monitoring. Surface acoustic wave sensors are installed at key locations of the monitored object to collect temperature data with time stamps and position information in real time. The data processing module constructs a three-dimensional distribution coordinate system of time, space, and temperature. The monitoring module generates early warnings by comparing critical temperature models to achieve dynamic monitoring of the equipment temperature field.

[0046] Specifically, the first aspect of this embodiment discloses Figure 1 A temperature monitoring system based on surface acoustic wave technology is shown, which includes a temperature acquisition module, a data processing module, and a temperature monitoring module that are communicatively connected in sequence; wherein the temperature acquisition module is disposed in the monitored object, and the data processing module and the temperature monitoring module are disposed on a monitoring platform; it should be noted that the monitoring platform of this embodiment can be any existing data platform that implements integrated temperature monitoring of the monitored object;

[0047] The temperature acquisition module is configured to: place multiple surface acoustic wave sensors at different locations of the monitored object, collect corresponding target temperature data, and upload the target temperature data; wherein the target temperature data includes the target temperature and its corresponding collection time and collection location;

[0048] The data processing module is configured to: receive and process target temperature data, generate and transmit a temperature distribution coordinate system, wherein the temperature distribution coordinate system is constructed based on the target temperature data and stores the target temperature data;

[0049] The temperature monitoring module is configured to receive and monitor the temperature distribution coordinate system and generate corresponding temperature change warnings.

[0050] In this embodiment, the following monitoring is performed based on the monitoring platform:

[0051] 1. Centralized Monitoring: After entering the system, enter the centralized monitoring interface. The directory on the left side of the interface is the directory structure of the switch cabinet. The right side shows the temperature of the current measurement point in the switch cabinet.

[0052] Every ten seconds, it will automatically switch to the next switch cabinet and display its measuring point temperature.

[0053] When the temperature of a measuring point exceeds the upper limit, the switch cabinet and measuring point information are displayed in yellow.

[0054] When the temperature exceeds the upper limit, the switch cabinet and measuring point information will be displayed in red, and an audible and visual alarm will sound. The switch cabinet will also freeze and will no longer switch automatically.

[0055] You can view the temperature history curve of each measuring point for one week

[0056] 2. Temperature curve: If you need to view the temperature change trend, you can click "One Week Historical Temperature Curve" on the interface to enter the temperature curve interface. The temperature curve color of each sensor is different.

[0057] 3. Real-time alarm and notification: Set the temperature threshold. Once the temperature exceeds the preset range, the system will trigger an alarm in real time and warn relevant personnel through sound and light alarms.

[0058] 4. Historical data: Click the "History Browsing" button on the interface to enter the historical data browsing interface. You can also select "Data Export" to export historical data to a table for subsequent processing.

[0059] 5. Alarm threshold setting: In the threshold setting, you can manually set the upper limit of the alarm temperature. When the temperature reaches the upper limit, an audible and visual alarm will be issued.

[0060] Through the above, through module collaborative design, the passive wireless characteristics of surface acoustic wave sensors are used to solve the problems of traditional wired temperature measurement wiring and electromagnetic interference. Multi-location data acquisition is combined with a three-dimensional temperature distribution coordinate system to achieve comprehensive characterization and real-time monitoring of the equipment temperature field. Compared with single-point measurement, it more accurately reflects the temperature change trend and improves the timeliness and reliability of abnormal temperature warnings.

[0061] In specific implementation, the temperature monitoring system based on the surface acoustic wave technology of this embodiment is applied to a fully enclosed electrical cabinet, and the temperature of internal contacts, outlet connectors and other locations thereof is monitored.

[0062] Specifically, the monitored object includes at least a fully enclosed electrical cabinet. The cause analysis of overheating failure of a fully enclosed electrical cabinet can be summarized as follows:

[0063] 1. The equipment in the cabinet is abnormally hot

[0064] Under the action of current and voltage, the equipment will produce normal heat loss. However, when the resistance of a certain joint in the current loop is too large, discharge will occur in the gap at that part, and the heat generation will increase sharply. If the normal heat dissipation of the switch cabinet cannot dissipate the heat quickly, the temperature of that part will rise abnormally. The parts of the switch cabinet that are prone to overheating failure are as follows:

[0065] ① The busbar and knife switch on the 10kV side are both installed in the narrow space of the switch cabinet. Insulating heat shrink tubing is often used on the busbar to increase insulation. If the copper quality of the busbar is not up to standard or the connection points are not tightened, the contact resistance will increase.

[0066] ② The static and dynamic contacts of the switch cabinet isolation knife switch are not tightly engaged, and the contact is poor, resulting in a corresponding gap. The current forms a partial discharge here, causing a sharp rise in temperature. The probability of such thermal failures occurring during operation is high;

[0067] ③ The current transformer (CT) in the cabinet generally adopts a fully sealed epoxy resin cast structure. The heat dissipation effect of the primary winding and iron core of this structure is poor, and two connecting joints are generally added in the high current circuit. Heat sources lead to serious internal CT heating problems when high current is running.

[0068] 2. Poor heat dissipation caused by protection level factors

[0069] To prevent accidental human contact with high-voltage live parts and foreign matter from entering the switchgear and causing equipment short circuits, switchgear currently utilizes fully enclosed metal enclosures. Common standards require metal enclosures to meet IP4X protection levels, significantly limiting the switchgear's heat dissipation efficiency. When equipment within the cabinet overheats abnormally, relying solely on the cabinet's internal natural ventilation or forced exhaust system will not be enough to dissipate heat. This will cause the insulation performance of the cabinet components to gradually deteriorate in the high-temperature environment without sufficient heat dissipation, creating a potential risk of overheating.

[0070] 3. Environmental conditions

[0071] The outdoor temperature plus the heat emitted by the equipment itself will cause the ambient temperature in the distribution room to be too high. If the electrical cabinet adopts traditional heat dissipation methods and lacks ventilation facilities, it will indirectly increase the amount of dust and moisture entering the room, putting the electrical cabinet in a relatively harsh operating environment. This will intensify the heating of the primary components in the electrical cabinet and cause abnormal heating of the electrical cabinet.

[0072] Specifically, for the above analysis, Figure 2 As shown in the schematic diagram of the surface acoustic wave sensor setting, multiple surface acoustic wave sensors are set at different positions of the monitored object, specifically including:

[0073] Surface acoustic wave sensors are respectively arranged at multiple contacts and multiple outgoing line connectors of a fully enclosed electrical cabinet; wherein, the surface acoustic wave sensors are selected based on parameter disturbances during the operation of the fully enclosed electrical cabinet. The parameters are used to characterize the changes in temperature, pressure, strain and mass of the operating environment of the surface acoustic wave sensors caused by the operation of the fully enclosed electrical cabinet.

[0074] In this embodiment, the three contacts and three outgoing wire connectors within the switchgear are most susceptible to heat buildup, with the three contacts experiencing the highest failure rate. Therefore, most switchgear temperature measurement requirements require six points: one temperature sensor is installed on each of the three phase contacts and three outgoing wires of the circuit breaker. The plate antenna is attached to the inner wall of the power switchgear, and the temperature reader is installed in the switchgear's instrument compartment and secured by rails.

[0075] Through the above, by placing surface acoustic wave sensors in key heat-prone areas such as contacts and outlet connectors of fully enclosed electrical cabinets, accurate temperature measurement of the core areas of the equipment can be achieved; sensors are selected based on parameter disturbances such as temperature, pressure, strain and mass in the operating environment to enhance the system's anti-interference ability and environmental adaptability, and ensure the reliability and stability of temperature measurement data under complex working conditions.

[0076] In a specific implementation, the data processing module parses the target temperature data collected by the sensor, extracts the temperature value, collection time and spatial position in the electrical cabinet, and constructs a three-dimensional temperature distribution coordinate system.

[0077] Specifically, the construction of the temperature distribution coordinate system includes:

[0078] Analyze the target temperature to obtain the temperature axis;

[0079] Analyze the acquisition time corresponding to the target temperature and map the target temperature to the same time axis;

[0080] Analyze the acquisition position corresponding to the target temperature, assign a spatial value to the acquisition position based on its corresponding spatial position in the fully enclosed electrical cabinet, obtain the corresponding position axis, and map the target temperature onto the position axis;

[0081] The temperature distribution coordinate system is obtained by taking the time axis as the x-axis of the temperature distribution coordinate system, the position axis as the y-axis of the temperature distribution coordinate system, and the temperature axis as the z-axis of the temperature distribution coordinate system.

[0082] It should be noted that this embodiment utilizes existing data processing technology to realize the construction of the temperature distribution coordinate system and the corresponding data processing.

[0083] In a simple example, in a fully enclosed electrical cabinet, contact A collects temperature T1 at time t1, maps T1 to the temperature axis, t1 corresponds to the time axis, and the spatial position of contact A is assigned to the position axis. The three constitute the point (t1, contact A position, T1) in the coordinate system.

[0084] Through the above, by constructing a three-dimensional distribution coordinate system of time, space and temperature, the discrete temperature data is converted into a visual three-dimensional temperature field model, which realizes the dynamic representation of the temperature distribution in the electrical cabinet, facilitates the intuitive analysis of temperature change trends and spatial abnormal distribution, and improves the comprehensiveness of temperature monitoring and the accuracy of early warning.

[0085] In specific implementation, the temperature distribution monitoring model is run to compare the real-time temperature distribution coordinate system with the preset critical temperature distribution coordinate system, and a temperature change warning is generated based on the deviation.

[0086] Specifically, the generation of temperature change warnings includes:

[0087] Run the temperature distribution monitoring model, monitor the temperature distribution coordinate system, and generate corresponding temperature change warnings; wherein, the temperature distribution monitoring model is used to monitor the deviation between the temperature distribution coordinate system and the critical temperature distribution coordinate system, and generate corresponding temperature change warnings. The critical temperature distribution coordinate system is used to characterize the critical state of the normal temperature distribution, and the critical temperature distribution coordinate system is composed of critical temperature data corresponding to the target temperature data. The critical temperature data includes the critical temperature and its corresponding collection time and collection position.

[0088] It should be noted that, in this embodiment, the construction of the temperature distribution monitoring model is realized by using existing machine learning technology, for example, deep learning technology.

[0089] In a simple example, the measured temperature of contact A in a fully enclosed electrical cabinet at time t1 is 65°C, while the critical temperature of this position at time t1 in the critical temperature distribution coordinate system is 60°C. If the deviation exceeds the threshold, a temperature anomaly warning is generated.

[0090] Through the above, by constructing a critical temperature distribution coordinate system and comparing it with the real-time temperature field, dynamic threshold monitoring of the temperature distribution of the electrical cabinet can be achieved. Compared with a single temperature threshold alarm, it can more accurately identify temperature anomalies in spatial and temporal dimensions, thereby improving the timeliness and accuracy of early warning.

[0091] In specific implementation, the temperature distribution monitoring model obtains the historical temperature distribution coordinate system, screens the historical data that has triggered early warnings, and fits and generates a critical temperature distribution coordinate system for comparison.

[0092] Specifically, the temperature distribution monitoring model includes:

[0093] Obtain a historical temperature distribution coordinate system and its corresponding historical temperature change warning, and select the historical temperature distribution coordinate system when generating the historical temperature change warning;

[0094] Fitting is performed based on the screened historical temperature distribution coordinate system to determine the critical temperatures at different acquisition moments and their corresponding acquisition positions, generating corresponding critical temperature data based on the acquisition moments, the acquisition positions, and the critical temperatures, and generating a critical temperature distribution coordinate system based on the critical temperature data;

[0095] After the critical temperature distribution coordinate system is stored in the temperature distribution monitoring model, it is used for comparative monitoring with the temperature distribution coordinate system.

[0096] In a simple example, the system extracts the coordinate system data of contact A triggering temperature warning in historical operation in a fully enclosed electrical cabinet. For example, if the temperature at time t1 is ≥ 60°C, the critical temperature of contact A at time t1 is fitted to be 60°C, and a critical temperature distribution coordinate system is constructed.

[0097] Through the above, by self-learning and generating a critical temperature distribution coordinate system based on historical warning data, the system can adapt to the equipment operating status and environmental changes, and dynamically adjust the temperature monitoring threshold. Compared with fixed threshold settings, it can more accurately match the actual operating characteristics of the equipment and improve the accuracy and adaptability of temperature anomaly warnings.

[0098] In a specific implementation, the temperature deviation between the temperature distribution coordinate system and the critical coordinate system is analyzed, the proportion of abnormalities that do not meet the threshold is counted, and the first temperature change warning is generated.

[0099] Specifically, the deviation between the monitoring temperature distribution coordinate system and the critical temperature distribution coordinate system is generated to generate a corresponding temperature change warning, which specifically includes:

[0100] Analyze the first deviations between the target temperature data of the temperature distribution coordinate system and the critical temperature data of the corresponding critical temperature distribution coordinate system, count the number of first anomalies in each first deviation that do not meet the preset temperature deviation threshold, and generate the corresponding first temperature change warning based on the ratio of the number of first anomalies to the total number of first deviations. The first temperature change warning belongs to the temperature change warning.

[0101] In a simple example, contacts A, B, and C of a fully enclosed electrical cabinet are monitored. At time t1, the measured temperatures at these three locations are 65°C, 62°C, and 57°C, respectively. The corresponding critical temperatures are all 60°C, with a deviation threshold of ±2°C. At this point, there are two single-point temperature anomalies (A and C), accounting for 66.7% of the total number of abnormalities (the preset warning threshold is 40%). The system generates a first temperature change warning based on the abnormal proportion of the overall temperature field.

[0102] By counting the abnormal temperature deviation ratios of multiple monitoring points at the same time, dynamic monitoring of the overall temperature field of the electrical cabinet can be achieved. Even if a single contact is locally overheated, an early warning can be triggered by the abnormal ratio, avoiding misjudgment or omission of potential overheating risks of the equipment due to a single data point. Multi-dimensional dynamic monitoring of the temperature distribution coordinate system is achieved. Compared with a single threshold alarm, it can more comprehensively reflect the degree of equipment temperature abnormality, improve the accuracy and reliability of the early warning, and avoid misjudgment of a single data point.

[0103] In a specific implementation, while analyzing the single-point deviation of the temperature data to generate the first temperature change warning, the temperature distribution characteristics of different positions at the same moment are extracted, and the critical distribution characteristics are compared to generate the second temperature change warning.

[0104] Specifically, monitoring the deviation between the temperature distribution coordinate system and the critical temperature distribution coordinate system and generating corresponding temperature change warnings also includes:

[0105] Analyze each deviation between each target temperature data of the temperature distribution coordinate system and each critical temperature data of its corresponding critical temperature distribution coordinate system, count the number of anomalies in each deviation that do not meet a preset temperature deviation threshold, and generate a corresponding first temperature change warning based on the ratio of the number of anomalies to the total number of each deviation. The first temperature change warning belongs to the temperature change warning;

[0106] Extracting the critical distribution characteristics of the critical temperature between different acquisition positions corresponding to the same acquisition time in the critical temperature distribution coordinate system;

[0107] Extracting target distribution characteristics of target temperatures between different acquisition positions corresponding to acquisition moments in a temperature distribution coordinate system;

[0108] Analyze the second deviations between the target temperature data of the target distribution feature and the critical temperature data of the critical distribution feature corresponding to the acquisition time of the target distribution feature, count the number of second anomalies in each second deviation that do not meet the preset temperature deviation threshold, and generate the corresponding second temperature change warning based on the ratio of the number of second anomalies to the total number of each second deviation. The second temperature change warning belongs to the temperature change warning.

[0109] In a simple example, contacts A, B, and C of a fully enclosed electrical cabinet are monitored. The critical temperature distribution characteristic at time t1 is "contact A (load end) ≥ B ≥ C" (the critical temperatures are 70°C, 65°C, and 60°C, respectively, with a deviation threshold of ±5°C). The measured target temperatures are A = 65°C, B = 67°C, and C = 58°C. At this time:

[0110] Single point deviation analysis:

[0111] Deviation of A: 65℃-70℃=-5℃ (just equal to the lower limit of the threshold, within the tolerance); Deviation of B: 67℃-65℃=+2℃ (within the range of ±5℃); Deviation of C: 58℃-60℃=-2℃ (within the range of ±5℃); The number of single-point anomalies is 0, and the first temperature change warning is not generated.

[0112] Comparison of spatial distribution characteristics:

[0113] The critical distribution characteristic requires A ≥ B ≥ C, while the measured distribution is B (67°C) > A (65°C) > C (58°C). The temperature at load end A is lower than that at B, violating the thermodynamic principle that the load end should be hottest during normal operation. This distribution order deviation was analyzed and suggested a possible contact resistance anomaly (e.g., contact oxidation) at point B. Although the current temperature did not exceed the critical value, the abnormal distribution characteristic indicated a potential overheating risk. The system counted the number of secondary anomalies as 1 / 1, representing a 100% abnormality, and generated a secondary temperature change warning.

[0114] By strictly limiting single-point deviations to within the threshold range, utilizing the sequential anomalies of spatial distribution characteristics (B>A) to trigger early warnings, and realizing forward-looking fault identification through logical analysis of temperature field distribution, this technology can locate hidden problems such as poor contact and abnormal load distribution before the equipment temperature exceeds the limit, thus avoiding the lag of single threshold judgment.

[0115] In the specific implementation, based on the target temperature and critical temperature data at each collection time and location, differentiated temperature deviation thresholds are determined to achieve accurate monitoring at different times and locations.

[0116] Specifically, the temperature deviation threshold includes:

[0117] Based on the target temperature data and its corresponding critical temperature data, the temperature deviation thresholds at different collection moments and their corresponding different collection positions are determined. The temperature deviation thresholds are used to characterize the allowable deviation in the difference between the target temperature and the critical temperature at different collection moments and their corresponding different collection positions.

[0118] Taking a fully enclosed electrical cabinet as an example, when contact A is running at full load at time t1, the temperature deviation threshold is set to ±3°C; when the outlet connector B is running at low load at time t2, the threshold is relaxed to ±5°C, both of which are dynamically set based on historical data.

[0119] Through the above, by dynamically setting the temperature deviation threshold at different time and position, the system can adapt to the differences in temperature characteristics at different collection times (such as load fluctuations) and positions (such as contacts / connectors). Compared with the unified threshold setting, it can more accurately match the actual operating conditions of the equipment, reduce false alarms and missed alarms, and improve the adaptability and reliability of temperature warnings.

[0120] The second aspect of this embodiment discloses Figure 3 A temperature monitoring method based on surface acoustic wave technology is shown, which is applicable to the temperature monitoring system based on surface acoustic wave technology as described above. The method includes:

[0121] S1: multiple surface acoustic wave sensors are placed at different locations of the monitored object, and corresponding target temperature data is collected and uploaded; wherein the target temperature data includes the target temperature and its corresponding collection time and collection location;

[0122] S2: Receive and process target temperature data, generate and transmit a temperature distribution coordinate system, where the temperature distribution coordinate system is constructed based on the target temperature data and stores the target temperature data;

[0123] S3: Receive and monitor the temperature distribution coordinate system and generate corresponding temperature change warnings.

[0124] It should be noted that the surface acoustic wave (SAW)-based temperature monitoring method of this embodiment corresponds to the aforementioned SAW-based temperature monitoring system. Therefore, any details not specifically described in the SAW-based temperature monitoring method of this embodiment, including but not limited to functional definitions, operating principles, and technical effects, can be referenced in the aforementioned SAW-based temperature monitoring system and are not further elaborated herein.

[0125] In summary, the temperature monitoring system and method based on surface acoustic wave technology in this embodiment realizes high-precision temperature monitoring in scenarios such as fully enclosed electrical cabinets through the collaborative design of surface acoustic wave technology and multiple modules; the temperature acquisition module uses passive wireless surface acoustic wave sensors distributed at key positions such as contacts and outlet connectors, which solves the problems of complex wiring and electromagnetic interference of traditional wired temperature measurement, and improves environmental adaptability by selecting sensors based on parameter perturbations; the temperature distribution coordinate system constructed by the data processing module integrates three-dimensional data of time, space, and temperature, and more comprehensively reflects the temperature field distribution of the equipment than single-point measurement; the temperature monitoring module realizes dynamic early warning of abnormal temperature through critical temperature comparison and multi-dimensional deviation analysis, which is more accurate than traditional threshold alarms; through surface acoustic wave sensors, the anti-interference ability and measurement accuracy are improved, and temperature change trends and early warnings can be generated in real time, effectively reducing the risk of equipment overheating accidents, and providing a universal and intelligent solution for smart power equipment status monitoring.

[0126] In the embodiments provided herein, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to implement the functions described herein, or a combination thereof. For software implementation, part or all of the processes of the embodiments can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein the communication media include any medium that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that a computer can access. The computer-readable storage medium can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer.

[0127] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent replacements for some of the technical features therein. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A temperature monitoring system based on surface acoustic wave technology, characterized in that: The system comprises a temperature acquisition module, a data processing module and a temperature monitoring module which are sequentially connected in communication; wherein the temperature acquisition module is arranged in the monitored object, and the data processing module and the temperature monitoring module are arranged on the monitoring platform; The temperature acquisition module is configured to: place multiple surface acoustic wave sensors at different locations of the monitored object, collect corresponding target temperature data, and upload the target temperature data; wherein the target temperature data includes the target temperature and its corresponding collection time and collection location; The data processing module is configured to: receive and process the target temperature data, generate and transmit a temperature distribution coordinate system, wherein the temperature distribution coordinate system is constructed based on the target temperature data and stores the target temperature data; The temperature monitoring module is configured to receive and monitor the temperature distribution coordinate system and generate a corresponding temperature change warning.

2. The temperature monitoring system based on surface acoustic wave technology according to claim 1, characterized in that: The monitored object at least includes a fully enclosed electrical cabinet.

3. The temperature monitoring system based on surface acoustic wave technology according to claim 2, characterized in that: The step of placing a plurality of surface acoustic wave sensors at different locations of the monitored object specifically includes: The surface acoustic wave sensors are respectively arranged at multiple contacts and multiple outgoing wire connectors of the fully enclosed electrical cabinet; wherein the surface acoustic wave sensors are selected based on parameter disturbances during the operation of the fully enclosed electrical cabinet, and the parameters are used to characterize the changes in temperature, pressure, strain and mass of the operating environment of the surface acoustic wave sensors caused by the operation of the fully enclosed electrical cabinet.

4. The temperature monitoring system based on surface acoustic wave technology according to claim 3, characterized in that: The construction of the temperature distribution coordinate system specifically includes: Analyzing the target temperature to obtain a temperature axis; Analyzing the acquisition time corresponding to the target temperature, and mapping the target temperature to the same time axis; parsing the acquisition position corresponding to the target temperature, spatially assigning the acquisition position based on its corresponding spatial position in the fully enclosed electrical cabinet to obtain a corresponding position axis, and mapping the target temperature onto the position axis; The temperature distribution coordinate system is obtained by taking the time axis as the x-axis of the temperature distribution coordinate system, taking the position axis as the y-axis of the temperature distribution coordinate system, and taking the temperature axis as the z-axis of the temperature distribution coordinate system.

5. The temperature monitoring system based on surface acoustic wave technology according to claim 1, characterized in that: The generation of the temperature change warning specifically includes: Run the temperature distribution monitoring model, monitor the temperature distribution coordinate system, and generate the corresponding temperature change warning; wherein, the temperature distribution monitoring model is used to monitor the deviation between the temperature distribution coordinate system and the critical temperature distribution coordinate system, and generate the corresponding temperature change warning, the critical temperature distribution coordinate system is used to characterize the critical state of the normal temperature distribution, and the critical temperature distribution coordinate system is composed of critical temperature data corresponding to the target temperature data, and the critical temperature data includes the critical temperature and its corresponding collection time and collection position.

6. The temperature monitoring system based on surface acoustic wave technology according to claim 5, characterized in that: The temperature distribution monitoring model specifically includes: Obtain a historical temperature distribution coordinate system and its corresponding historical temperature change warning, and select the historical temperature distribution coordinate system when the historical temperature change warning was generated; Performing fitting based on the screened historical temperature distribution coordinate system, determining the critical temperatures at different acquisition moments and their corresponding acquisition positions, generating corresponding critical temperature data based on the acquisition moments, the acquisition positions, and the critical temperatures, and generating the critical temperature distribution coordinate system based on the critical temperature data; After the critical temperature distribution coordinate system is stored in the temperature distribution monitoring model, it is used for comparison monitoring with the temperature distribution coordinate system.

7. The temperature monitoring system based on surface acoustic wave technology according to claim 5, characterized in that: The monitoring of the deviation between the temperature distribution coordinate system and the critical temperature distribution coordinate system and generating the corresponding temperature change warning specifically includes: Analyze the first deviations between the target temperature data of the temperature distribution coordinate system and the critical temperature data of the corresponding critical temperature distribution coordinate system, count the number of first anomalies in each first deviation that do not meet the preset temperature deviation threshold, and generate the corresponding first temperature change warning based on the ratio of the number of first anomalies to the total number of first deviations. The first temperature change warning belongs to the temperature change warning.

8. The temperature monitoring system based on surface acoustic wave technology according to claim 5, characterized in that: The monitoring of the deviation between the temperature distribution coordinate system and the critical temperature distribution coordinate system and generating the corresponding temperature change warning further includes: analyzing each deviation between each target temperature data in the temperature distribution coordinate system and each critical temperature data in the corresponding critical temperature distribution coordinate system, counting the number of anomalies in each deviation that do not meet a preset temperature deviation threshold, and generating the corresponding first temperature change warning based on a ratio of the number of anomalies to the total number of each deviation, where the first temperature change warning belongs to the temperature change warning; Extracting critical distribution characteristics of the critical temperature between different acquisition positions corresponding to the same acquisition time in the critical temperature distribution coordinate system; extracting target distribution characteristics of the target temperature between different acquisition positions corresponding to the acquisition time in the temperature distribution coordinate system; Analyze the second deviations between the target temperature data of the target distribution feature and the critical temperature data of the critical distribution feature corresponding to the acquisition time of the target distribution feature, count the number of second anomalies that do not meet the preset temperature deviation threshold in each second deviation, and generate a corresponding second temperature change warning based on the ratio of the number of second anomalies to the total number of each second deviation, where the second temperature change warning belongs to the temperature change warning.

9. The temperature monitoring system based on surface acoustic wave technology according to claim 7 or 8, characterized in that: The temperature deviation threshold specifically includes: Based on the target temperature data and its corresponding critical temperature data, a temperature deviation threshold value for different collection moments and corresponding different collection positions is determined. The temperature deviation threshold value is used to characterize the allowable deviation in the difference between the target temperature and the critical temperature at different collection moments and corresponding different collection positions.

10. A temperature monitoring method based on surface acoustic wave technology, the method being applicable to the temperature monitoring system based on surface acoustic wave technology according to any one of claims 1 to 9, characterized in that: The method includes: S1: placing multiple surface acoustic wave sensors at different locations of the monitored object, collecting corresponding target temperature data, and uploading the target temperature data; wherein the target temperature data includes the target temperature and its corresponding collection time and collection location; S2: Receive and process the target temperature data, generate and transmit a temperature distribution coordinate system, wherein the temperature distribution coordinate system is constructed based on the target temperature data and stores the target temperature data; S3: Receive and monitor the temperature distribution coordinate system, and generate a corresponding temperature change warning.

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