Portable switch cabinet temperature rise on-line monitoring system
By combining a portable high-frequency high-current power supply and a multi-channel temperature acquisition module with a hierarchical thermal resistance-thermal capacity prediction model, the problems of bulky and long testing cycles of traditional switchgear temperature rise test equipment are solved, achieving rapid and accurate temperature rise prediction and improving testing efficiency and flexibility.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUBEI JINLANG HI TECH DEV CO LTD
- Filing Date
- 2025-10-09
- Publication Date
- 2026-08-04
AI Technical Summary
In the existing technology, traditional switchgear temperature rise test equipment is bulky, has poor mobility, and has a long test cycle, which cannot meet the needs of on-site testing and rapid diagnosis.
It employs a portable high-frequency high-current power supply module, a multi-channel temperature acquisition module, an initial temperature rise calculation module, a parameter identification module, a temperature rise correction module, and a state determination module. Combined with a hierarchical thermal resistance-thermal capacity prediction model and the nonlinear least squares method, it achieves rapid and accurate temperature rise prediction.
The testing cycle has been significantly shortened from several hours to about 1 hour, improving testing efficiency, enhancing the portability and flexibility of the system, and ensuring the accuracy and reliability of the prediction results.
Smart Images
Figure CN121253945B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of power equipment testing technology, and more specifically, to a portable online temperature rise monitoring system for switchgear. Background Technology
[0002] In power systems, switchgear is a key power transmission and distribution control device, and its safety and reliability are of paramount importance. To ensure equipment safety, a rigorous temperature rise test must be conducted before leaving the factory or being put into operation to verify its thermal stability under rated load current. This test monitors the temperature of key parts until thermal stability is achieved, which is a necessary step to ensure that the switchgear meets design and safety standards. Traditional temperature rise test methods, while following established standards, have revealed a series of deep-seated technical and engineering problems in practical applications. Existing technologies mainly rely on large, fixed power frequency high current generating devices. Such devices are bulky and have poor mobility, which restricts experimental activities to professional high-voltage laboratories and cannot meet the growing demand for on-site testing and flexible deployment. Existing technologies for temperature rise testing inherently have limitations. The core issue is that achieving thermal stability of the equipment often requires a testing process lasting 5 to 8 hours. This lengthy testing cycle significantly extends product development and production delivery time, resulting in a waste of expensive experimental resources and time. Furthermore, when faced with quality inspections during production or unexpected on-site troubleshooting tasks, the lengthy testing cycle of traditional methods makes it impossible to provide rapid diagnostic results, hindering its adaptation to the demands of modern production and efficient operation and maintenance.
[0003] Therefore, how to develop a portable monitoring system that can break free from the constraints of large fixed equipment, shorten the testing cycle of several hours, and achieve rapid and accurate prediction of the steady-state temperature rise of switchgear is a technical problem that urgently needs to be solved in the field of power equipment testing.
[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention
[0005] To overcome the above-mentioned deficiencies of the prior art, embodiments of the present invention provide a portable online temperature rise monitoring system for switchgear. The technical solution is as follows: The portable online temperature rise monitoring system for switchgear includes: Portable high-frequency high-current power supply module for generating test current and applying it to switch cabinet; A multi-channel temperature acquisition module is used to synchronously acquire the measurement point temperature data and ambient temperature data of the switch cabinet within a preset initial time period in response to the application of the test current, so as to generate the measurement point temperature data sequence and the ambient temperature data sequence. The initial temperature rise calculation module is used to calculate and generate an initial measured temperature rise data sequence based on the temperature data sequence of the measuring point and the ambient temperature data sequence. The parameter identification module is used to identify parameters based on the initial measured temperature rise data sequence and using a preset layered thermal resistance-thermal capacity prediction model, so as to calculate a set of dynamic model parameters and determine the predicted steady-state temperature rise value under the test current from the dynamic model parameters. The temperature rise correction module is used to combine the predicted steady-state temperature rise value under the test current, the preset current correction coefficient, the test current and the preset rated current, and calculate the final steady-state temperature rise value under the rated operating conditions according to the preset nonlinear relationship conversion formula. The status determination module is used to compare the final steady-state temperature rise value under the rated operating conditions with the preset temperature rise threshold to determine the temperature rise status of the switchgear.
[0006] Preferably, the initial temperature rise calculation module is specifically used to: subtract the temperature value in the corresponding ambient temperature data sequence from the temperature value at each moment in the temperature data sequence of the measuring point within the preset initial time period, so as to generate the initial measured temperature rise data sequence.
[0007] Preferably, the parameter identification module is specifically used to: fit the layered thermal resistance-heat capacity prediction model using the nonlinear least squares method to find a set of optimal dynamic model parameters, such that the sum of the variances between the predicted temperature rise curve calculated by the model and the initial measured temperature rise data sequence is minimized.
[0008] Preferably, the layered thermal resistance-heat capacity prediction model describes the temperature rise process as a linear superposition of multiple exponential components; wherein, the number of exponential components is determined by a preset model order, and the dynamic model parameters include a weighting coefficient and a time constant defining each exponential component.
[0009] Preferably, the model order is predetermined based on experimental data analysis of typical switchgear.
[0010] Preferably, the state determination module is specifically used to: determine that the temperature rise state is abnormal when the final steady-state temperature rise value under the rated operating conditions is higher than the preset temperature rise threshold; and determine that the temperature rise state is normal when the final steady-state temperature rise value under the rated operating conditions is not higher than the preset temperature rise threshold.
[0011] Preferably, the preset current correction coefficient is generated by applying multiple test currents of different levels to a standard model switchgear and completing a full temperature rise experiment, and then fitting the obtained steady-state temperature rise and test current data.
[0012] Preferably, the portable high-frequency high-current power supply module adopts a high-frequency switching power supply topology and third-generation semiconductor power devices to achieve miniaturization.
[0013] Preferably, the portable switchgear temperature rise online monitoring system further includes: a human-machine interface for displaying the temperature rise status.
[0014] Compared with the prior art, the portable switchgear temperature rise online monitoring system provided by the present invention has the following advantages: 1. By adopting high-frequency switching power supply technology and third-generation semiconductor power devices, the system significantly reduces the size and weight of the testing equipment, solving the problems of bulky and poor mobility of traditional devices. This makes it possible to conduct on-site testing in places such as production lines and substations, enhancing the flexibility of the application.
[0015] 2. By using a layered thermal resistance-thermal capacity prediction model and parameter identification algorithm, the system changes the traditional testing mode that requires waiting for the equipment to reach a thermally stable state, shortening the experimental cycle of several hours to a prediction process of about one hour, which greatly improves testing efficiency and reduces time and resource costs.
[0016] 3. The system calibrates the nonlinear relationship between temperature rise and current by introducing a current correction coefficient and deducts the influence of ambient temperature fluctuations in real time, ensuring the accuracy of the prediction results. At the same time, the use of a multi-order exponential model can more realistically fit the complex temperature rise process of the switchgear and improve the reliability of the prediction.
[0017] 4. The system integrates a fully automated process from data acquisition and model calculation to status determination, and displays the final pass / fail conclusion intuitively through a human-machine interface, reducing the professional skill requirements for operators, avoiding human error, and improving the convenience and standardization of equipment acceptance and maintenance. Attached Figure Description
[0018] Figure 1 This is a system flowchart of the present invention. Detailed Implementation
[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example
[0020] A portable online temperature rise monitoring system for switchgear includes: a portable high-frequency high-current power supply module for generating a test current and applying it to the switchgear; a multi-channel temperature acquisition module for synchronously acquiring temperature data at measuring points of the switchgear and ambient temperature data within a preset initial time period in response to the application of the test current, to generate a measuring point temperature data sequence and an ambient temperature data sequence; an initial temperature rise calculation module for calculating and generating an initial measured temperature rise data sequence based on the measuring point temperature data sequence and the ambient temperature data sequence; and a parameter identification module for... The system employs a pre-defined layered thermal resistance-thermal capacity prediction model for parameter identification to calculate a set of dynamic model parameters and determine the predicted steady-state temperature rise value under the test current from these parameters. A temperature rise correction module combines the predicted steady-state temperature rise value under the test current, a pre-defined current correction coefficient, the test current, and the pre-defined rated current, and calculates the final steady-state temperature rise value under rated operating conditions based on a pre-defined nonlinear relationship conversion formula. A status determination module compares the final steady-state temperature rise value under rated operating conditions with a pre-defined temperature rise threshold to determine the temperature rise status of the switchgear. This embodiment discloses a portable online temperature rise monitoring system for switchgear. The system aims to solve the technical problems of bulky temperature rise test equipment, long test cycles of 5-8 hours, and inability to perform rapid on-site testing in the prior art. By adopting lightweight high-frequency power supply technology, multi-channel synchronous data acquisition, and innovative temperature rise prediction algorithm, this invention can accurately predict the final steady-state temperature rise of the switchgear under rated operating conditions after an initial test of about 1 hour, thereby improving the test efficiency by several times and significantly improving the portability of the entire system. Within a complete technological closed loop, the system of this embodiment specifically includes the following collaboratively working modules: The core purpose of this portable high-frequency, high-current power supply module is to apply a stable and controllable test current to the internal conductive circuit of the switchgear under test, serving as the excitation source for the entire temperature rise experiment. In this embodiment, the module applies a preset test current. For example, a convenient current value of 630A or selected according to site conditions can be used to simulate the load-bearing heating process of the switchgear; The multi-channel temperature acquisition module aims to accurately and synchronously capture the dynamic thermal response of the switchgear during the initial heating phase. In this embodiment, the module deploys multiple temperature sensors, such as K-type thermocouples or PT100 platinum resistance thermometers, at key heating points within the switchgear and in the surrounding environment. Responding to the test current applied by a portable high-frequency, high-current power supply module, it synchronously and frequently acquires temperature data from each measuring point and ambient temperature data within a preset initial duration, for example, 60 minutes. This process generates time-dependent temperature data sequences for each measuring point. and ambient temperature data series ; The initial temperature rise calculation module aims to preprocess the collected raw temperature data to eliminate interference from ambient temperature fluctuations and extract the net temperature rise caused by the device's own heating. In this embodiment, the module receives two sets of data sequences generated by the multi-channel temperature acquisition module, performs calculations, and finally generates the initial measured temperature rise data sequence. This sequence is the direct input to subsequent prediction algorithms; The parameter identification module aims to use limited initial temperature rise data to solve for the intrinsic thermodynamic characteristic parameters of the switchgear under test through a mathematical model, and predict its final temperature rise state accordingly. In this embodiment, the module uses a preset layered thermal resistance-thermal capacity prediction model based on the initial measured temperature rise data sequence generated in the previous stage for parameter identification. Through identification, the module can calculate a set of dynamic model parameters, which can accurately describe the heat transfer and heat dissipation characteristics of the current tested object. Subsequently, the module directly determines the temperature rise state at the current test current from this set of dynamic model parameters. Predicted steady-state temperature rise value ; The temperature rise correction module aims to convert predicted results under specific test conditions to industry-recognized standard operating conditions, ensuring the universality and comparability of the results; taking into account the test current used in field testing... It may not be equal to the preset rated current of the switchgear. Furthermore, there is a complex nonlinear relationship between temperature rise and current. In this embodiment, the module combines the predicted steady-state temperature rise value output by the parameter identification module. Preset current correction factor Test current and the preset rated current Based on a preset nonlinear relationship conversion formula, the final steady-state temperature rise under rated operating conditions is accurately calculated. ; The purpose of the status determination module is to provide a clear and intuitive conclusion on the operational safety of the switchgear based on the final calculation results. In this embodiment, this module will use the final steady-state temperature rise value calculated by the temperature rise correction module under rated operating conditions. The temperature rise status of the switchgear is compared with a preset temperature rise threshold to determine whether the temperature rise status is normal or abnormal. The preset temperature rise threshold is determined based on the temperature rise limits for different components of the switchgear according to national or industry standards. This embodiment, through the organic combination of the above modules, constitutes a complete automated and intelligent testing process from excitation application, data acquisition, model identification, nonlinear correction to state determination. It changes the traditional temperature rise test mode, shortening the passive waiting process that takes 5-8 hours to an active prediction process of about 1 hour, greatly improving testing efficiency and reducing testing costs. At the same time, the highly integrated portable design enables it to be applied to scenarios that traditional equipment cannot reach, such as production sites and substations, significantly enhancing the flexibility and practical value of the application, and realizing the functional upgrade from traditional experimental equipment to intelligent diagnostic instruments. Example
[0021] The initial temperature rise calculation module is specifically used to: subtract the temperature value in the corresponding ambient temperature data sequence from the temperature value of each moment in the measured temperature data sequence within the preset initial time period, so as to generate an initial measured temperature rise data sequence. This embodiment further defines the specific implementation of the initial temperature rise calculation module in Embodiment 1; The initial temperature rise calculation module's specific calculation logic is as follows: it calculates the temperature data sequence of measurement points collected within a preset initial time period. The temperature value at each moment in the data, minus the ambient temperature data sequence. The temperature value at the corresponding moment; the mathematical expression of this calculation process is:
[0022] in: For a moment The initial measured temperature rise values constitute the initial measured temperature rise data sequence, with the units being K or °C; For a moment At the measuring point The temperature values collected are sourced from real-time data acquired by the multi-channel temperature acquisition module. For a moment The collected ambient temperature values are sourced from real-time data collected by the multi-channel temperature acquisition module. By using this point-by-point, real-time subtraction method, the interference caused by natural fluctuations in ambient temperature during the experiment can be effectively eliminated. This ensures that the generated initial measured temperature rise data sequence can more accurately reflect the net temperature rise of the equipment caused by the test current, providing a reliable data foundation for the subsequent parameter identification module to perform high-precision model fitting, thereby improving the accuracy of the entire system's prediction. Example
[0023] The parameter identification module is specifically used to: fit the layered thermal resistance-heat capacity prediction model using the nonlinear least squares method in order to find a set of optimal dynamic model parameters that minimize the sum of variances between the predicted temperature rise curve calculated by the model and the initial measured temperature rise data sequence. This embodiment further defines the specific algorithm implementation of the parameter identification module in Embodiment 1; The parameter identification module is implemented by using a nonlinear least squares method to curve fit the layered thermal resistance-heat capacity prediction model. In this embodiment, a mature iterative algorithm such as the Levenberg-Marquardt algorithm can be used. The goal of this algorithm is to find a set of optimal dynamic model parameters that make the predicted temperature rise curve calculated by the model... Compared with the initial measured temperature rise data sequence The objective function for optimization is to minimize the sum of variances between the two variances; it can be expressed as:
[0024] in: The initial time is the endpoint; the algorithm iteratively adjusts the model parameters and calculates the sum of squared residuals between the predicted and measured values until the value converges to the minimum, at which point the parameters are determined as the optimal solution. The nonlinear least squares method provides an automated and standardized mathematical tool for solving complex, nonlinear layered thermal resistance-heat capacity prediction model parameters. Compared with simple linear fitting or manual trial and error, this method can find the optimal parameter solution more robustly and accurately, thus ensuring that the identified dynamic model parameters can reproduce the true thermodynamic behavior of the device under test in the initial stage to the greatest extent. This is a key prerequisite for achieving high-precision steady-state temperature rise prediction. Example
[0025] The layered thermal resistance-heat capacity prediction model describes the temperature rise process as a linear superposition of multiple exponential components; the number of exponential components is determined by the preset model order, and the dynamic model parameters include the weighting coefficient and time constant for each exponential component. The model order was predetermined based on the analysis of experimental data from typical switchgear. This embodiment further defines the source of the hierarchical thermal resistance-heat capacity prediction model itself and the order of its key hyperparameter model in Embodiment 1; The hierarchical thermal resistance-heat capacity prediction model works by treating the complex thermal system of a switchgear cabinet as a linear superposition of multiple sub-processes with different thermal response rates, rather than roughly considering it as a single homogeneous body. This model describes the temperature rise process as a linear superposition of multiple exponential components; its specific mathematical expression is as follows:
[0026] in: For at any time The predicted temperature rise is the output of the model, and its dimensions are K or °C. The predicted final steady-state temperature rise is one of the key dynamic model parameters identified by the model. It directly reflects the thermal equilibrium state of the equipment under the current test current, and its dimension is K or °C. The model order represents the number of main heat capacity components used to equivalently describe the system's thermal dynamics. It is an integer, a preset value determined by analyzing complete data collected from a traditional temperature rise experiment on a typical switchgear. Typical switchgear models such as KYN28 and MNS, through modal analysis or exponential decomposition of the measured curves, show that the temperature rise process is typically composed of the superposition of two to three dominant exponential components. Therefore, in this embodiment... The default value is usually 2 or 3, in order to balance accuracy with computational efficiency. For the first The weight coefficient of the first exponential component is one of the dynamic model parameters identified by the model, reflecting the weight of the first exponential component. The contribution of each equivalent heat capacity component to the total temperature rise is a dimensionless parameter, and the sum of all weight coefficients is always 1. ; For the first The time constant of the exponential component is one of the dynamic model parameters identified by the model, representing the time constant of the exponential component. The thermal response rate of an equivalent component is expressed as a value. The smaller the value, the faster the part heats up. The unit of measurement is seconds or minutes. Compared to the traditional single-exponential model, the multi-order model of this invention can more accurately fit the complex temperature rise curve under the combined effect of different materials and different heat dissipation paths inside the switch cabinet. By decomposing the temperature rise process into multiple exponential components with different time constants, the model can better capture the rapid temperature rise in the initial stage and the slow stabilization process in the later stage, making the physical meaning clearer and thus significantly improving the prediction accuracy. The model order was determined by pre-analyzing experimental data from typical switchgear. This approach avoids the complexities of model selection and order determination during on-site testing, simplifying the complexity of on-site calculations. This prior knowledge-based approach ensures that the structure of the model used matches the general physical characteristics of the object being tested, guaranteeing the effectiveness of the model while improving the efficiency and convenience of testing. Example
[0027] The status determination module is specifically used to: determine the temperature rise status as abnormal when the final steady-state temperature rise value under rated operating conditions is higher than the preset temperature rise threshold; and determine the temperature rise status as normal when the final steady-state temperature rise value under rated operating conditions is not higher than the preset temperature rise threshold. This embodiment further defines the specific judgment logic of the state determination module in claim 1; The status determination module works as follows: When the temperature rise correction module calculates the final steady-state temperature rise value under rated operating conditions When the temperature rise exceeds the preset threshold, the status determination module determines that the temperature rise status of the switch cabinet is abnormal. When the final steady-state temperature rise under rated operating conditions When the temperature rise is not higher than the preset temperature rise threshold, the status determination module determines that the temperature rise status of the switch cabinet is normal. As mentioned earlier, the source of the preset temperature rise threshold is definite; it is strictly set according to the maximum allowable temperature rise limit for different parts in the relevant power industry safety standards. This judgment logic is clear and explicit, providing an automated, industry-standard pass / fail determination. It directly transforms complex temperature rise prediction values into a binary conclusion on the safety status of the equipment, reducing the professional requirements for on-site operators. This allows them to make quick and accurate judgments without needing to deeply understand temperature rise data and standard details, effectively avoiding safety hazards caused by human error and improving the standardization level of equipment acceptance and maintenance. Example
[0028] The preset current correction coefficient is generated by applying multiple test currents of different levels to a standard model switchgear and completing a full temperature rise experiment, and then fitting the obtained steady-state temperature rise with the test current data. This embodiment further defines the calibration method for the preset current correction coefficient in claim 1; The preset current correction factor is expressed as a parameter in this technical solution. This is intended to quantify and correct the nonlinear change in heat dissipation efficiency caused by changes in current; the calibration and generation process of this coefficient is as follows: Select calibration object: Select a standard model switch cabinet as the calibration sample; Conducting multi-level current tests: In a controlled experimental environment, multiple test currents of different levels were applied sequentially to the standard switchgear. For example, apply multiple current values such as 60%, 80%, and 100% of its rated current respectively; Complete a full temperature rise test: For each current level, conduct a complete traditional temperature rise test, i.e., continuously power on the device until it reaches a thermally stable state, and accurately record each current. The corresponding final steady-state temperature rise ; Data fitting and calibration: This involves combining multiple sets of data points (...) , Perform nonlinear fitting on the following semi-empirical formula:
[0029] The optimal current correction coefficient was obtained by fitting algorithm. This was generated after calibration. The value was then preset into the temperature rise correction module of the monitoring system; The technical basis of this calibration method lies in the fact that the temperature rise is not simply proportional to the square of the current, especially under high current, the efficiency of heat dissipation mechanisms such as natural convection and radiation will change; through a one-time, rigorous multi-point calibration experiment, this invention can accurately capture this nonlinear effect and quantify it into a correction coefficient. This allows the system to accurately convert the results to the temperature rise value under the rated current in subsequent daily use, regardless of the convenient test current used for short-term testing, through the conversion formula in the temperature rise correction module. This greatly improves the flexibility of testing and the accuracy and reliability of the results, ensuring a high degree of consistency between the predicted results and the standard requirements. Example
[0030] The portable high-frequency high-current power supply module adopts a high-frequency switching power supply topology and third-generation semiconductor power devices to achieve miniaturization; This embodiment further defines the specific technical path for miniaturizing the portable high-frequency high-current power supply module in Embodiment 1; To achieve miniaturization and weight reduction—for example, keeping the overall weight under 20kg—the portable high-frequency, high-current power module employs the following key technologies in its internal circuit design: It adopts a high-frequency switching power supply topology: it abandons the bulky power frequency transformer in the traditional power frequency high current generator and instead adopts an advanced high-frequency switching power supply topology, such as full-bridge LLC resonant converter, etc. Third-generation semiconductor power devices are used: Third-generation semiconductor power devices, represented by silicon carbide or gallium nitride, are used in the key switching elements of the circuit. The synergistic effect of these two technologies is that silicon carbide or gallium nitride devices have higher withstand voltage, lower on-resistance, and extremely fast switching speed, which allows the switching frequency of the power supply to be significantly increased to tens or even hundreds of kilohertz, for example, >50kHz; according to the principles of electromagnetics, the volume of magnetic components such as transformers and filter inductors is inversely proportional to the operating frequency; therefore, the significant increase in switching frequency directly leads to a significant reduction in the volume and weight of these core energy storage components, thereby realizing the miniaturization of the entire power supply module; By employing a combination of high-frequency topology and third-generation semiconductor devices, this embodiment effectively solves the problem of the large size and weight of traditional high-current power supplies. This design is the key to achieving high system portability, allowing it to be carried by a single person to various work sites, such as switchgear production lines, substations, and power distribution rooms. This is something that existing technologies cannot achieve. This portability is the core physical basis for the application scenarios of this invention, such as online monitoring and rapid troubleshooting. Example
[0031] A portable online temperature rise monitoring system for switchgear also includes: a human-machine interface for displaying the temperature rise status; This embodiment is a further supplement to the system of Embodiment 1 at the user interaction level; The system also includes a human-computer interaction interface; in this embodiment, the interface may be a high-resolution touch screen integrated on the host device, or a dedicated application running on an external device, communicating with the host system wirelessly or via wired means. The core function of this human-computer interaction interface is to display the temperature rise status finally output by the status determination module; for example, the interface will directly inform the user of the test results in a prominent manner; in addition, this interface can also be used to display other relevant information, such as: The specific value of the final steady-state temperature rise under rated operating conditions; A complete predicted temperature rise curve is provided, and it is compared with the initial measured data curve. Real-time temperature data at each measuring point; Test the input and setting of configuration parameters, such as rated current, temperature rise threshold, etc. The addition of a human-computer interaction interface enhances the system's usability and ease of operation; it presents complex background calculation processes and data results to operators in an intuitive and easy-to-understand form, achieving a seamless connection from raw data to final conclusions; this makes the system an instrument integrating measurement and intelligent diagnostic functions, allowing operators to make quick decisions, thereby improving work efficiency and safety.
[0032] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A portable switchgear temperature rise online monitoring system, characterized in that, include: Portable high-frequency high-current power supply module for generating test current and applying it to switch cabinet; A multi-channel temperature acquisition module is used to synchronously acquire the measurement point temperature data and ambient temperature data of the switch cabinet within a preset initial time period in response to the application of the test current, so as to generate the measurement point temperature data sequence and the ambient temperature data sequence. The initial temperature rise calculation module is used to calculate and generate an initial measured temperature rise data sequence based on the temperature data sequence of the measuring point and the ambient temperature data sequence. The parameter identification module is used to identify parameters based on the initial measured temperature rise data sequence and using a preset layered thermal resistance-thermal capacity prediction model, so as to calculate a set of dynamic model parameters and determine the predicted steady-state temperature rise value under the test current from the dynamic model parameters. The temperature rise correction module is used to combine the predicted steady-state temperature rise value under the test current, the preset current correction coefficient, the test current and the preset rated current, and calculate the final steady-state temperature rise value under the rated operating conditions according to the preset nonlinear relationship conversion formula. The status determination module is used to compare the final steady-state temperature rise value under the rated operating conditions with the preset temperature rise threshold to determine the temperature rise status of the switchgear. The layered thermal resistance-heat capacity prediction model describes the temperature rise process as a linear superposition of multiple exponential components; its specific mathematical expression is as follows: ； wherein: is a predicted temperature rise value at time , is a predicted final steady state temperature rise value, is a model order, is a weight coefficient of the th exponential component, is a time constant of the th exponential component; The number of exponential components is determined by a preset model order, and the dynamic model parameters include the weighting coefficient and time constant for each exponential component. The preset current correction coefficient is generated by applying multiple test currents of different levels to a standard model switchgear and completing a full temperature rise experiment, and then fitting the obtained steady-state temperature rise with the test current data.
2. The portable switchgear cabinet temperature rise online monitoring system according to claim 1, characterized in that, The initial temperature rise calculation module is specifically used to: subtract the temperature value in the corresponding ambient temperature data sequence from the temperature value at each moment in the measured point temperature data sequence within the preset initial time period, so as to generate the initial measured temperature rise data sequence.
3. The system of claim 1, wherein, The parameter identification module is specifically used to: fit the layered thermal resistance-heat capacity prediction model using the nonlinear least squares method to find a set of optimal dynamic model parameters, such that the sum of the variances between the predicted temperature rise curve calculated by the model and the initial measured temperature rise data sequence is minimized.
4. The portable switchgear cabinet temperature rise online monitoring system according to claim 3, characterized in that, The model order was predetermined based on experimental data analysis of typical switchgear.
5. The portable switchgear cabinet temperature rise online monitoring system according to claim 1, characterized in that, The state determination module is specifically used to: determine that the temperature rise state is abnormal when the final steady-state temperature rise value under the rated operating conditions is higher than the preset temperature rise threshold; and determine that the temperature rise state is normal when the final steady-state temperature rise value under the rated operating conditions is not higher than the preset temperature rise threshold.
6. The portable switchgear cabinet temperature rise online monitoring system according to claim 1, characterized in that, The portable high-frequency high-current power supply module adopts a high-frequency switching power supply topology and third-generation semiconductor power devices to achieve miniaturization.
7. The portable switchgear cabinet temperature rise online monitoring system according to claim 1, characterized in that, Also includes: A human-computer interaction interface is used to display the temperature rise status.