A high-voltage electrical appliance temperature rise on-line monitoring system

Abstract

The application relates to the technical field of electrical equipment state monitoring, and discloses a high-voltage electrical appliance temperature rise online monitoring system, which comprises a data synchronization module, a static calibration module, a working condition routing module, a parameter calibration module and a deduction and early warning module. The system re-samples equipment operation data to generate a synchronous vector group, and calibrates an equivalent heat capacity constant and an initial heat dissipation coefficient in an initial operation period. The working condition routing module cuts the system into a power-off cooling mode, a low valley quasi-steady state mode or an online deduction mode according to a load characteristic boundary. In a specific mode, the system regularly updates a dynamic comprehensive heat dissipation coefficient by solving an integral equation; in the online deduction mode, the system inverses a dynamic resistance equivalent factor based on time domain integration, and calculates a relative degradation multiple to output a graded early warning. The application corrects heat dissipation parameters through working condition matching self-adaptation, weakens the interference of transient sampling noise and environmental factors, and improves the accuracy of internal contact degradation state evaluation of high-voltage electrical appliances.

Description

Technical Field

[0001] This invention relates to the field of electrical equipment condition monitoring technology, specifically to an online monitoring system for the temperature rise of high-voltage electrical appliances. Background Technology

[0002] During operation, high-voltage electrical equipment generates Joule heat as the internal contact current flows through the contact resistance, leading to a temperature rise. When mechanical wear or microscopic oxidation occurs in the contacts, the contact resistance increases, causing an abnormal increase in heat generation. Therefore, online monitoring of the temperature rise of high-voltage electrical equipment is a fundamental means to ensure safe operation.

[0003] Existing temperature rise monitoring technologies mostly rely on sensors to collect node temperatures and combine them with fixed thresholds for judgment. For example, Chinese patent application document CN110514306A discloses a method and system for monitoring the temperature of high-voltage switchgear based on pyroelectric sensors. This system uses pyroelectric sensors to collect temperature data of internal components of the switchgear and monitors abnormal heating of the equipment by comparing it with preset temperature thresholds.

[0004] However, high-voltage electrical equipment operates under alternating loads for extended periods after being put into operation, with its heat generation and environmental heat dissipation conditions constantly changing. Existing technologies rely directly on real-time temperature sampling points or fixed parameter models for condition assessment, failing to consider the degradation of macroscopic heat dissipation capacity caused by factors such as surface dust accumulation and metal component oxidation after long-term operation. When external heat dissipation conditions weaken, leading to temperature increases, existing monitoring methods are prone to misinterpreting this as a contact fault within the contacts. Furthermore, calculation methods relying directly on transient temperature data are susceptible to fluctuations due to sensor sampling noise and internal airflow disturbances. This approach, which fails to isolate external environmental heat dissipation interference and lacks adaptability to different operating conditions, prevents existing systems from accurately calculating the true degradation state of the contact resistance within the contacts, easily leading to calculation errors and false alarms under complex load conditions. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an online temperature rise monitoring system for high-voltage electrical appliances. This system solves the problems of existing high-voltage electrical appliance temperature rise monitoring methods accumulating measurement errors under long-term variable load operation, and failing to effectively isolate the interference of external heat dissipation degradation on temperature data, resulting in inaccurate assessment of the internal micro-deterioration state of the contacts and triggering false alarms.

[0006] To address the above problems, the present invention provides the following technical solution: The first aspect of this invention provides an online temperature rise monitoring system for high-voltage electrical appliances, comprising: The data synchronization module is used to establish a unified clock reference, perform resampling operations on discrete contact temperature data and ambient temperature data to generate a continuous temperature sequence, and integrate the continuous temperature sequence with phase current data and opening / closing status data to construct a synchronization vector group. The static calibration module is used to read the synchronization vector group in the initial stage of equipment commissioning, and to calculate and store the equivalent heat capacity constant and the initial comprehensive heat dissipation coefficient based on the lumped parameter thermodynamic model when the high voltage electrical equipment is in an ideal healthy steady-state condition according to the load stability condition and temperature gradient condition. The operating condition routing module is used to monitor the synchronization vector group and extract the opening and closing status data and phase current data. Based on the preset boundary judgment threshold, it switches the system state machine into the power-off natural cooling mode, the valley quasi-steady state observation mode, or the online monitoring and simulation mode. The parameter calibration module is used to extract the synchronization vector group within the corresponding time window in the power outage natural cooling mode or the low-temperature quasi-steady-state observation mode, calculate the current dynamic comprehensive heat dissipation coefficient by solving the thermal balance integral equation, and write the updated dynamic comprehensive heat dissipation coefficient into the system global cache. The simulation and early warning module is used to extract the synchronization vector group based on the sliding time window in the online monitoring and simulation mode. Based on the equivalent heat capacity constant and dynamic comprehensive heat dissipation coefficient in the system global cache, it calculates the dynamic resistance equivalent factor through time domain integration inversion, and calculates the relative degradation ratio based on this to perform graded early warning operations.

[0007] Furthermore, the data synchronization module extracts the timestamp sequence of the phase current data as a reference time axis and calculates the time interval between two adjacent actual received temperature data. If the time interval is greater than the set packet loss tolerance threshold, the system marks the data quality bits within that time period as invalid; for time segments where data quality verification is valid, the system uses an interpolation algorithm or a zero-order hold to map the sparse temperature timestamps onto the dense reference time axis.

[0008] Furthermore, the load stability condition and temperature gradient condition are defined as follows: within a preset observation time window, the variance of the phase current data fluctuation is continuously less than a set current fluctuation threshold, and the derivative of the continuous contact temperature with respect to time at the end of the observation time window is less than a set minimum temperature change rate threshold. The static calibration module reads the pre-entered reference contact resistance, multiplies the square of the mean effective value of the phase current within the steady-state time window by the reference contact resistance, and divides by the difference between the mean continuous contact temperature and the mean continuous ambient temperature to calculate the initial comprehensive heat dissipation coefficient. Subsequently, the system backtracks and extracts historical synchronous vector group data within the transient heating period, calculates the difference between the time-domain integral of the internal Joule heating and the time-domain integral of the external heat dissipation within the transient heating period, and divides this difference by the contact temperature rise amplitude to deduce the equivalent heat capacity constant.

[0009] Furthermore, the preset boundary judgment thresholds include a zero current dead zone threshold, a low-valley stable load threshold, a steady-state current fluctuation variance threshold, and a quasi-steady-state temperature change rate minimum threshold. When the circuit breaker status data is detected as being in an open state or the phase current data is less than the zero current dead zone threshold, the operating condition routing module switches the system to a power-off natural cooling mode. When the circuit breaker status data is detected as being in a closed state and the phase current data is within the range greater than the zero current dead zone threshold and less than or equal to the low-valley stable load threshold, and the fluctuation variance of the phase current data and the absolute value of the derivative of the continuous contact temperature with respect to time are both continuously less than the corresponding thresholds, the system switches to a low-valley quasi-steady-state observation mode. If the above judgment conditions are not met, the system switches to an online monitoring and simulation mode. This routing mechanism can effectively avoid calculation errors caused by boundary condition mismatches and improve the reliability of the system.

[0010] Furthermore, in the power-off natural cooling mode, after verifying that the temperature drop of the continuous contact is greater than the set effective cooling threshold, the parameter calibration module performs a natural cooling integral inversion calculation based on the area integral of the real-time temperature difference between the contact and the environment using the equivalent heat capacity constant, under the boundary condition of no internal heat source. In the low-valley quasi-steady-state observation mode, the reference contact resistance is introduced as a known parameter to calculate the time-domain integral of the internal Joule heating, and the heat capacity integral compensation term is retained to perform heat storage compensation inversion calculation. After the calculation is completed, the parameter calibration module uses a first-order low-pass filtering algorithm to assign corresponding smoothing filter coefficient weights to the newly calculated dynamic comprehensive heat dissipation coefficient and the existing historical dynamic comprehensive heat dissipation coefficient, and performs weighted summation and fusion to generate a smooth updated dynamic comprehensive heat dissipation coefficient that is overwritten to the system global cache.

[0011] Furthermore, the deduction and early warning module calculates the time-domain integral of the square of the effective value of the phase current within the sliding time window. After determining that it is greater than the effective work threshold, it establishes a discretized thermodynamic time-domain integral equation based on the law of conservation of energy to solve for the dynamic resistance equivalence factor. The deduction and early warning module then retrieves the reference contact resistance, calculates the ratio of the current dynamic resistance equivalence factor to the reference contact resistance to generate a relative degradation ratio, and compares the relative degradation ratio with a health status threshold matrix that includes mild degradation, moderate alarm, and critical fault. Based on the exceeding of limits, it generates an early warning data packet with the corresponding priority.

[0012] The second aspect of this invention provides a method for online monitoring of temperature rise in high-voltage electrical appliances. This method is based on the online monitoring system for temperature rise in high-voltage electrical appliances described in the first aspect above, and includes: generating a vector group of synchronous contact temperature, ambient temperature, and electrical operating status; statically calibrating the equivalent heat capacity constant and initial comprehensive heat dissipation coefficient under steady-state and transient conditions during the initial operation of the equipment; identifying the current load characteristic boundary of the equipment in real time and directing the computational flow to the corresponding physical model; performing integral inversion and low-pass filtering under power-off cooling or low-load conditions to adaptively correct heat dissipation parameters; and inverting the contact resistance equivalent factor based on the corrected heat dissipation parameters and the time-domain integral equation under normal operating conditions, and outputting multi-level deterioration warnings.

[0013] This invention provides an online temperature rise monitoring system for high-voltage electrical appliances. It has the following beneficial effects: 1. This invention, by setting up a working condition routing module, switches the system into power-off natural cooling, low-peak quasi-steady-state observation, or online monitoring and simulation modes based on preset boundary judgment thresholds. This mechanism can call up a matching physical model according to the actual load characteristics and opening / closing status of high-voltage electrical appliances, avoiding calculation errors caused by the inapplicability of boundary conditions to a single thermodynamic equation under complex working conditions, and improving the reliability of system state assessment.

[0014] 2. Under the power outage natural cooling and low-temperature quasi-steady-state observation modes, this invention updates the dynamic comprehensive heat dissipation coefficient by solving the thermal balance integral equation and uses a low-pass filtering algorithm for global parameter fusion. This processing method can periodically correct the degradation of heat dissipation capacity caused by surface dust or metal oxidation during equipment operation, reduce the interference of external environmental factors on temperature rise monitoring, and provide an accurate parameter basis for subsequent analysis of the heating status. Attached Figure Description

[0015] Figure 1 This is a diagram of an online temperature rise monitoring system for high-voltage electrical appliances according to an embodiment of the present invention; Figure 2 This is a flowchart of the online temperature rise monitoring method for high-voltage electrical appliances according to an embodiment of the present invention; Figure 3 This is a topology diagram of multi-source hardware data acquisition in an embodiment of the present invention; Figure 4 This is a timing diagram of the heterogeneous data clock synchronization and resampling logic in an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the static calibration principle of thermodynamic reference parameters according to an embodiment of the present invention. Figure 6 This is a flowchart of the working condition identification and routing control based on three-state logic according to an embodiment of the present invention; Figure 7 This is a flow diagram of the adaptive integral calibration logic for heat dissipation parameters in an embodiment of the present invention. Figure 8 This is a time-domain integral derivation and early warning logic diagram of the dynamic resistance equivalent factor in an embodiment of the present invention.

[0016] Among them, 100, high-voltage electrical appliance temperature rise online monitoring system; 101, temperature measurement node; 102, ambient temperature node; 103, measurement and control device; 104, data synchronization module; 105, static calibration module; 106, operating condition routing module; 107, parameter calibration module; 108, simulation and early warning module; 109, processing gateway. Detailed Implementation

[0017] 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.

[0018] See attached document Figure 1 , Figure 1 This is a diagram of an online temperature rise monitoring system for high-voltage electrical appliances according to an embodiment of the present invention. The present invention provides an online temperature rise monitoring system 100 for high-voltage electrical appliances, including a temperature measuring node 101, an ambient temperature node 102, a monitoring and control device 103, and a processing gateway 109.

[0019] The processing gateway 109 is equipped with a data synchronization module 104, a static calibration module 105, a working condition routing module 106, a parameter calibration module 107, and a prediction and early warning module 108.

[0020] Temperature measuring node 101 is installed on the surface of the high-voltage electrical contact to acquire contact temperature data.

[0021] The ambient temperature node 102 is installed in the space area where the high-voltage electrical appliances are located to acquire ambient temperature data.

[0022] The measurement and control device 103 is connected to the current transformer and circuit breaker auxiliary nodes of the high-voltage electrical equipment to acquire phase current data and opening and closing status data.

[0023] Temperature measurement node 101, ambient temperature node 102 and measurement and control device 103 send the acquired data to processing gateway 109 via communication bus.

[0024] See attached document Figure 2 , Figure 2 This is a flowchart of a method for online monitoring of temperature rise in high-voltage electrical appliances according to an embodiment of the present invention. The present invention provides a method for online monitoring of temperature rise in high-voltage electrical appliances, comprising the following steps: S10, the data synchronization module 104 receives data uploaded by the temperature measurement node 101, the ambient temperature node 102 and the measurement and control device 103; S20, the data synchronization module 104 establishes a clock reference, performs resampling operations on the contact temperature data and ambient temperature data, generates a continuous temperature sequence that is clock-aligned with the phase current data, and encapsulates the continuous temperature sequence, phase current data and opening / closing status data into a synchronization vector group and outputs it. S30, the static calibration module 105 reads the synchronization vector group and the pre-entered reference contact resistance during the initial stage of equipment commissioning, calculates and stores the reference contact resistance, equivalent heat capacity constant and initial comprehensive heat dissipation coefficient. S40, the working condition routing module 106 monitors the synchronization vector group, extracts the opening and closing status data and phase current data, and determines whether the equipment is in the power-off cooling working condition, the low-valley stable load working condition, or the normal operation and alternating simulation working condition. S50, when it is determined that the equipment is in a power-off cooling condition or a low-load stable condition, the parameter calibration module 107 receives the synchronization vector group, calculates the current dynamic comprehensive heat dissipation coefficient by solving the thermal balance integral equation, and writes the dynamic comprehensive heat dissipation coefficient into the system cache. S60, when it is determined that the equipment is in normal operation and alternating simulation conditions, the simulation early warning module 108 reads the latest dynamic comprehensive heat dissipation coefficient from the system cache; S70, the simulation and early warning module 108 performs definite integral operation on the synchronization vector group within the set sliding time window, and calculates the dynamic resistance equivalent factor by combining the dynamic comprehensive heat dissipation coefficient and through integral normalization. S80, the simulation and early warning module 108 compares the dynamic resistance equivalent factor sequence with the reference contact resistance, and outputs an early warning command for deterioration of contact resistance when the comparison deviation reaches the set threshold.

[0025] See attached document Figure 3 , Figure 3 This is a multi-source hardware data acquisition topology diagram according to an embodiment of the present invention. The method for the data synchronization module 104 of the present invention to receive data uploaded by the temperature measurement node 101, the ambient temperature node 102, and the monitoring and control device 103 specifically includes the following operations: S101, temperature sensing node 101 and ambient temperature node 102 collect thermodynamic parameters of their spatial locations and generate discrete temperature data. Temperature sensing node 101 is fixedly connected to the surface of the conductive contacts of the high-voltage electrical equipment. Due to the technical requirements of high-potential insulation isolation for high-voltage contacts in actual operation, as a preferred approach, temperature sensing node 101 can use a passive wireless architecture surface acoustic wave temperature sensor or radio frequency identification temperature sensor. Ambient temperature node 102 is arranged on the wall of the enclosed switchgear where the high-voltage electrical equipment is located and in the indoor space of the substation. It can typically use a thermistor probe or an infrared temperature probe to obtain the ambient reference temperature. To ensure the rigor of the thermodynamic model derivation, this ambient reference temperature is preferably one that can accurately reflect the local enclosed microenvironment where the equipment is located, such as the air temperature inside the enclosed switchgear. Based on this, since passive devices rely on external electromagnetic field excitation to accumulate working energy, temperature sensing node 101 and ambient temperature node 102 trigger sampling actions according to irregular wake-up time intervals, outputting non-continuous data packets with timestamps. For the hardware working principles of radio frequency energy acquisition, temperature-sensitive medium physical property conversion, and wireless signal modulation inside surface acoustic wave sensors or passive radio frequency identification sensors, those skilled in the art can refer to existing mature industrial sensing technology literature for implementation. The underlying physical conversion process of temperature sensing is a well-known technology in this field and will not be elaborated here.

[0026] While acquiring the thermodynamic parameters of the environment and equipment, the system also needs to simultaneously acquire the electrical status of the equipment to construct a complete monitoring data dimension. Therefore, step S102 is executed, and the measurement and control device 103 acquires the electrical operating parameters of the high-voltage electrical equipment in real time. In this embodiment, the analog input channel of the measurement and control device 103 is connected to the secondary side conductor of the current transformer configured in the high-voltage electrical circuit to acquire the real-time analog current signal. Subsequently, the analog-to-digital conversion circuit inside the measurement and control device 103 performs continuous high-frequency discrete sampling on the analog current signal. The microprocessor of the measurement and control device 103 calculates and generates phase current data on a continuous time series according to a preset time window. In this technical solution, the phase current data summarized in the claims is specifically embodied as the root mean square value within the power frequency cycle. This effective value objectively reflects the comprehensive heating effect of the power frequency alternating current within a complete fluctuation cycle in a physical sense, and is the theoretical basis for subsequent deduction of the Joule heat inside the system. Its discretization calculation formula is: ; In the formula, For the first The effective value of the phase current output in each calculation cycle; This represents the total number of sampling points in the analog-to-digital converter circuit within a single power frequency cycle. This is to balance the computational load of the microprocessor with the accuracy of AC waveform restoration. The value range is usually set to 64 to 256 points per power frequency cycle; This represents the instantaneous current amplitude from a single sampling. Simultaneously, the digital input channel of the measurement and control device 103 is connected via hardwiring to the auxiliary contacts within the mechanical mechanism of the high-voltage circuit breaker, acquiring the high and low level states of the circuit and generating Boolean-type opening and closing status data.

[0027] After the aforementioned nodes and devices perform pre-processing, the process proceeds to step S103, where the underlying sensing devices unidirectionally transmit heterogeneous datasets to the processing gateway 109. Temperature measurement node 101 and ambient temperature node 102 transmit discrete temperature data to the wireless aggregation receiving module configured at the front end of the processing gateway 109 via a short-range wireless radio frequency communication channel. Meanwhile, the measurement and control device 103 periodically uploads phase current data and circuit breaker status data to the processing gateway 109 via a local Ethernet bus, based on standard power communication protocols such as IEC61850 or Modbus. The data synchronization module 104 opens a receiving buffer in the operating system of the processing gateway 109, classifying and storing asynchronous data streams from various interfaces into a hardware memory queue. To prevent system memory overflow due to prolonged operation, the receive buffer is configured with a circular queue management mechanism. When the data volume reaches the preset storage capacity limit, newly written data will automatically overwrite the oldest data with the oldest timestamp. To ensure the integrity of historical data required during the initial calibration phase of equipment commissioning, the system suspends the circular queue overwriting mechanism or allocates a dedicated long-cycle buffer during this initial phase to ensure that the transient full data from cold start to steady state is not overwritten. In this step, the data synchronization module 104 only performs message parsing and value extraction, forming an initial data pool with the extracted timestamps and physical quantity values, establishing a preliminary data source for subsequent mathematical alignment and physical parameter calibration.

[0028] See attached document Figure 4 , Figure 4 This is a timing diagram of heterogeneous data clock synchronization and resampling logic according to an embodiment of the present invention. The data synchronization module 104 provided by the present invention establishes a clock reference, performs resampling operations on contact temperature data and ambient temperature data to generate a continuous temperature sequence aligned with the phase current data clock, and encapsulates the continuous temperature sequence, phase current data, and opening / closing status data into a synchronization vector group and outputs it. Specifically, the method includes the following operations: S201, the data synchronization module 104 establishes a unified clock reference within the computational domain of the processing gateway 109. The underlying sensing data received by the system has different time attributes: the phase current data has dense timestamps and a fixed sampling period, while the temperature data has sparse and random timestamps due to the wireless sensor wake-up mechanism. To meet the mathematical continuity condition for solving the subsequent thermal balance integral equation in a discrete digital system, it is usually necessary to integrate the various data sources into a unified time dimension. In this embodiment, the data synchronization module 104 extracts the timestamp sequence of the phase current data sent by the measurement and control device 103 as the system's reference time axis, denoted as... All the irregular timestamp sequences corresponding to the acquired discrete temperature data are uniformly denoted as... The data synchronization module 104 uses the sampling period of the phase current data as a fixed discrete step length to provide an aligned time coordinate system for heterogeneous data.

[0029] S202, the data synchronization module 104 performs data alignment verification and abnormal period removal operations.

[0030] Due to electromagnetic interference in industrial environments, data loss is possible during wireless transmission. To ensure the validity of subsequent calculation results, the data synchronization module 104 monitors the timestamp sequence. The update status is calculated to determine the time interval between two consecutive actual temperature data receptions. .like Greater than the set packet loss tolerance threshold If the data quality bit for that time period is not specified, then the data quality bit for that period is marked as invalid. This packet loss tolerance threshold... The configuration can be based on the thermal inertia of the high-voltage electrical appliances and the nominal transmission frequency of the sensor. As a preferred approach, the value is typically set to three to five times the rated transmission period of the sensor. In practice, if the data quality bits for a certain time period are marked as invalid, the system will automatically skip the time period containing invalid data or reset the starting point of the integration sliding time window to after the invalid time period when performing subsequent time-domain integration derivation. This prevents distorted constant temperature values ​​from being directly substituted into the thermodynamic equations, thus causing divergence in the integration calculation.

[0031] S203, the data synchronization module 104 performs a resampling operation on the discrete contact temperature data and ambient temperature data.

[0032] For the time period where data quality verification is valid, to address the issue of mismatched sampling rates in heterogeneous data, specifically, the data synchronization module 104 will synchronize sparse temperature timestamps. Mapped to a dense reference time axis The above process generates a continuous temperature sequence. The physical essence of the resampling operation is to reconstruct the temperature evolution state at intermediate moments using known discrete temperature observation points within a reasonable error range. In this embodiment, a zero-order hold or a linear interpolation algorithm can be used to achieve the above continuous mapping. If a linear interpolation algorithm is used, this algorithm assumes that the temperature of the high-voltage contact changes uniformly and linearly within a short sampling interval. For any point within the interval... Reference time axis moments within Continuous contact temperature after resampling The calculation formula is: ; In the formula, and At time respectively and The actual collected discrete contact temperature data. Following the same mapping rule, the continuous ambient temperature... The resampling calculation formula is expressed as: ; In the formula, and At time respectively and The actual collected discrete ambient temperature data. Through the above algebraic mapping process, the low-frequency and irregular discrete temperature data is transformed into a continuous variable with the same time density as the high-frequency phase current data.

[0033] The principle of the zero-order hold is to maintain the temperature value of the previous sampling point constant between two effective temperature sampling points until the next sampling point arrives, thereby generating a step-like continuous temperature sequence. For the specific engineering implementation of the zero-order hold in digital signal processing, those skilled in the art can refer to existing mature discrete signal reconstruction theories. Its signal holding and mapping process is a well-known technique in the field and will not be elaborated upon here.

[0034] S204, the data synchronization module 104 will synchronize the timelines of the same reference time axis. The various physical quantities below are combined and packaged.

[0035] After resampling preprocessing, the heterogeneous data now has the foundation for coupled computation within the same physical space-time. The data synchronization module 104 will continuously synchronize the contact temperature... Continuous ambient temperature Phase current data and opening / closing status data Extract and arrange the data in a fixed order, then integrate them to construct a multi-dimensional data structure, thereby generating a synchronization vector group. The mathematical expression for this synchronization vector group is: ; The generated synchronization vector set serves as the basic input source for the standardization within the processing gateway 109. It is continuously pushed into the system's memory queue, providing time-consistent data support for subsequent condition determination and various parameter evaluation calculations.

[0036] See attached document Figure 5 , Figure 5This is a schematic diagram illustrating the static calibration principle of thermodynamic reference parameters according to an embodiment of the present invention. The static calibration module 105 provided by the present invention reads the synchronization vector group, calculates and stores the reference contact resistance, equivalent heat capacity constant, and initial comprehensive heat dissipation coefficient during the initial stage of equipment commissioning. Specifically, the method includes the following operations: S301, the static calibration module 105 determines whether the high-voltage electrical equipment has entered the ideal healthy steady-state operating condition during the initial commissioning stage based on the synchronization vector group. When the high-voltage electrical equipment is newly commissioned or energized for the first time after maintenance, the mechanical contact state and microscopic conductive spot distribution on the contact surface are usually within the initial design standard range. At this time, the physical parameters characterize the health reference state of the equipment. To obtain accurate thermodynamic reference parameters, the system sets dual boundary conditions for steady-state determination, namely, load stability condition and temperature gradient condition. Specifically, the static calibration module 105 continuously calculates the fluctuation variance of the phase current data within a preset observation time window. When the fluctuation variance is continuously less than the set current fluctuation threshold, and the derivative of the continuous contact temperature with respect to time at the end of the observation time window is less than the set minimum temperature change rate threshold, the equipment is determined to have entered the ideal healthy steady-state operating condition. As a preferred approach, to ensure a dynamic balance between internal heat generation and external heat dissipation in the contacts, the current fluctuation threshold is typically set to within 5% of the rated current, the observation time window length is set to three to five times the equivalent thermal time constant of the equipment, and the minimum temperature change rate threshold is typically set to 0.1℃ / h to 0.5℃ / h, for example, 0.5℃ / h. If the above conditions are not met, the static calibration module 105 will continue monitoring by sliding along the time axis until it captures a synchronization vector group data segment that meets the boundary conditions.

[0037] S302, the static calibration module 105 extracts initial physical constants based on the lumped parameter thermodynamic model.

[0038] After the system successfully captures a steady-state data segment that meets the boundary conditions, the physical constants can be extracted. From the perspective of heat transfer principles, since high-pressure contacts are typically made of copper or aluminum alloys with high thermal conductivity and relatively small volume, their internal thermal resistance is much smaller than their surface convective thermal resistance. Therefore, according to the lumped parameter method, the high-pressure contact can be reasonably considered as a single-node thermodynamic system with a uniform internal temperature distribution. Its standard unsteady-state thermal equilibrium differential equation is expressed as: ; In the formula, It is the equivalent heat capacity constant; Contact resistance; The overall heat dissipation coefficient; This is a sequence of effective values ​​of phase currents; and These are the continuous contact temperature and continuous ambient temperature sequences, respectively.

[0039] Under ideal, healthy, and steady-state operating conditions, the heat storage term approaches zero, i.e., the temperature derivative term. The original unsteady-state thermal equilibrium differential equation is simplified into a steady-state algebraic equation. In this embodiment, The interface reads the pre-recorded reference contact resistance. In actual engineering implementation, this reference contact resistance... The static contact absolute resistance value, measured by a loop resistance tester before equipment commissioning, is used as a known constant input to the equation, reducing the uncertainty caused by the coupling of multiple unknowns in the solution. Substituting the reference contact resistance... In addition to the phase current data and ambient temperature difference data under steady-state operating conditions, the static calibration module 105 calculates the initial comprehensive heat dissipation coefficient. The solution formula is: ; In the formula, The average effective value of the phase current within the steady-state time window; and These are the average continuous contact temperature and the average continuous ambient temperature within the steady-state time window, respectively.

[0040] To construct a complete transient thermodynamic derivation model, the system also needs to extract the equivalent heat capacity constant. The static calibration module 105 backtracks and extracts the transient temperature rise time period from cold start-up to reaching the aforementioned steady-state operating condition. The system uses historical synchronized vector group data. To avoid dead zones in division-to-zero operations caused by excessively small integral temperature differences, the system verifies the temperature rise before performing calculations. Does it exceed the set effective temperature rise threshold, such as 5°C? If this condition is met, the calculated initial comprehensive heat dissipation coefficient will be used. By performing time-domain definite integral calculations on the original unsteady-state thermal equilibrium differential equation, the equivalent heat capacity constant is derived in reverse. : ; Through the above physical mechanism calculation process, the system completes the extraction and quantification of core thermodynamic reference parameters using its own collected routine operating data without introducing external complex temperature measurement and calibration equipment.

[0041] S303, the static calibration module 105 persistently stores the extracted reference physical parameters and binds them to memory variables.

[0042] After obtaining the above basic physical parameters, the system needs to solidify them to support subsequent long-term monitoring. The static calibration module 105 will use the reference contact resistance. Equivalent heat capacity constant and initial overall heat dissipation coefficient The health baseline feature set of this specific high-voltage electrical appliance is written into a non-volatile storage medium. To meet the high-frequency real-time call requirements of the subsequent dynamic monitoring algorithm, the static calibration module 105 allocates a dedicated shared memory area in the system global cache and sets the initial comprehensive heat dissipation coefficient. The numerical value is assigned to the dynamic integrated heat dissipation coefficient variable. This dynamic comprehensive heat dissipation coefficient variable As the basic input parameters characterizing the microscopic heat dissipation environment, the operating condition routing module 106 and the parameter calibration module 107 are granted read access, thus establishing the initial boundary conditions of the online temperature rise simulation system.

[0043] See attached document Figure 6 , Figure 6 This is a flowchart of a three-state logic-based operating condition identification and routing control according to an embodiment of the present invention. The operating condition routing module 106 provided by the present invention monitors the synchronization vector group, extracts opening and closing status data and phase current data, determines whether the equipment is in a power-off cooling condition, a low-valley stable load condition, or an alternating load operating condition, and executes corresponding routing actions. Specifically, the method includes the following operations: S401, the operating condition routing module 106 reads the engineering threshold parameters used to define the operating condition boundaries from the system configuration file of the processing gateway 109.

[0044] High-voltage electrical equipment operates under complex conditions such as frequent operation, long-term overload, or long-term light load during its actual operating cycle. Single thermodynamic algebraic calculations are prone to accumulating errors under long-term variable load operation. To achieve reasonable switching between heterogeneous physical calculation models, the system pre-defines four boundary judgment thresholds, specifically including a zero-current dead zone threshold. Low-valley stable load threshold Steady-state current fluctuation variance threshold and the threshold value of the minimum rate of change of quasi-steady-state temperature In this embodiment, the zero-current dead zone threshold... To shield the underlying electromagnetic background noise and measurement zero drift of current transformers, a preferred method is to set the value to 1% to 2% of the rated current of the high-voltage electrical equipment. Low-valley stable load threshold. The value of l is used to define the light-load stable section during off-peak hours at night, and is typically configured as 20% to 40% of the rated current. Steady-state current fluctuation variance threshold. Used to quantify the stability of the load, typically taken as less than 5% of the variance corresponding to the rated current. Minimum threshold for quasi-steady-state temperature change rate. The maximum tolerable fluctuation rate characterizes the dynamic micro-equilibrium between heat generation from the contact and heat dissipation from the environment. Depending on the thermal conductivity of the contact material, it is usually set to 0.1℃ / h to 0.5℃ / h.

[0045] S402, the operating condition routing module 106 determines whether the device has entered the power-off cooling operating condition.

[0046] After establishing the various boundary judgment thresholds, the operating condition routing module 106 extracts the opening and closing status data from the synchronization vector group in real time. Phase current data This leads to the execution of state branch logic for judgment and flow splitting. When the open / close status data is detected... 0 or phase current data Less than zero current dead zone threshold At this point, the system determines that the Joule heating effect inside the contacts has essentially ceased. This logic treats the physical disconnection of the switch and the no-load closing as equivalent to the same thermodynamic boundary. Under this physical boundary condition, the operating condition routing module 106 switches the system state machine to the power-off natural cooling mode and routes the synchronization vector group data stream containing the continuous contact temperature and the continuous ambient temperature to the parameter calibration module 107. This routing operation aims to provide the data source triggering condition for subsequent adaptive correction calculation of heat dissipation parameters based on the natural physical decay process.

[0047] S403, the operating condition routing module 106 determines whether the device has entered a low-load stable operating condition.

[0048] In practical engineering, some high-voltage equipment in key substations operate without power for extended periods, making it difficult for the system to capture power outage cooling conditions for months or even years. To prevent the heat dissipation parameters from remaining uncalibrated due to changes in the microenvironment such as dust accumulation and metal oxidation on the contact surface, the system is designed with an alternative compensation calibration channel. When the opening / closing status data is detected... The phase current data is 1. In Within the preset observation time window, the variance of the phase current data fluctuation is consistently less than the steady-state current variance threshold. Meanwhile, the absolute value of the derivative of the continuous contact temperature with respect to time during this period. The temperature remains below the minimum threshold value of the quasi-steady-state temperature change rate. When the equipment meets the low-temperature quasi-steady-state observation conditions, it is determined that the equipment is operating under these conditions. Under this condition, although the equipment is powered on, its internal heat generation and external heat dissipation are in a constant equilibrium quasi-steady-state, and the heat storage term in the thermodynamic equation is approximately zero. The operating condition routing module 106 then switches the system state machine to the low-temperature quasi-steady-state observation mode and routes the synchronization vector group to the parameter calibration module 107, thereby performing heat dissipation parameter drift compensation calculations under uninterrupted power supply conditions.

[0049] S404, when the operating condition routing module 106 determines that the data characteristics of the current synchronization vector group do not meet the judgment conditions for either the power outage cooling condition or the low-valley stable load condition, the system identifies the equipment as being in a normal operation and alternating simulation condition. This condition covers the high-load stable operation period exceeding the low-valley load threshold and the period of dynamic load fluctuation. The time-domain integral simulation model used has universal compatibility with both steady-state and dynamic fluctuations.

[0050] After excluding the two specific operating conditions mentioned above for basic parameter calibration, the equipment operates under this routine monitoring condition for most of its lifecycle. During this period, the equipment is in a regular online monitoring and simulation phase. The operating condition routing module 106 switches the system state machine to online monitoring and simulation mode and transfers the continuously generated synchronization vector group data to the simulation and early warning module 108. Through the aforementioned mutually exclusive control routing mechanism, the system can autonomously perceive the alternating evolution of the high-voltage electrical load characteristics and map the current data input sequence to the designated computational core, thus avoiding the mathematical divergence caused by the forced solution of the heat balance equation under unsuitable operating conditions from the underlying architecture.

[0051] See attached document Figure 7 , Figure 7 This is a logic flow diagram for adaptive integral calibration of heat dissipation parameters according to an embodiment of the present invention. When the parameter calibration module 107 provided by the present invention determines that the device is in a power-off cooling condition or a low-load stable condition, it receives a synchronization vector group, calculates the current dynamic comprehensive heat dissipation coefficient by solving the heat balance integral equation, and writes the dynamic comprehensive heat dissipation coefficient into the system cache. The method specifically includes the following operations: When the operating condition routing module 106 triggers the power-off natural cooling mode switching command, it enters step S501, and the parameter calibration module 107 performs power-off natural cooling integral inversion calculation based on the boundary condition of no internal heat source. During long-term operation, the contact surfaces and heat dissipation fins of high-voltage electrical appliances often accumulate dust or undergo metal oxidation due to prolonged exposure to air, resulting in a slow decrease in overall convective and radiative heat transfer capacity. Under power-off cooling conditions, the phase current heating term returns to zero, and the temperature change of the contacts is mainly dominated by natural heat dissipation from the metal body to the external environment. In this embodiment, to reduce the interference of transient temperature noise in numerical calculations, the parameter calibration module 107 performs calculations within a set cooling time window. Internally, utilizing the equivalent heat capacity constant The heat balance equation is performed using a time-domain definite integral. The length of this cooling time window is typically set based on the equipment's natural cooling time constant, and as a preferred approach, its value ranges from 30 minutes to 2 hours.

[0052] To avoid the contact temperature from getting too close to the ambient temperature during the later stages of cooling, which could cause an algorithm dead zone where the denominator approaches zero, the parameter calibration module 107 pre-verifies the cooling temperature drop before performing integration. Whether the temperature exceeds the set effective cooling threshold, which is typically set to 3°C to 5°C as a preferred method. If the temperature does not reach this threshold, the system determines that the characteristics of the current cooling process are insufficient to support parameter calibration, and will actively terminate the current inversion and maintain the original dynamic comprehensive heat dissipation coefficient in the system cache unchanged. Under the premise of satisfying this physical constraint, the parameter calibration module 107 inverts the current dynamic comprehensive heat dissipation coefficient using the following definite integral formula. : ; In the formula, and These represent the continuous contact temperatures at the end and beginning of the cooling time window, respectively; the integrand of the integral term is the real-time temperature difference between the contact and the environment within this time window. By integrating the area over time, this algorithm effectively smooths transient sampling jitter, thereby obtaining more accurate macroscopic heat dissipation physical quantities.

[0053] Considering that a large number of devices in the power grid are in a state of continuous energization and lack the opportunity for cooling during power outages, the system provides a parameter compensation path under uninterrupted power supply conditions. When the operating condition routing module 106 triggers the off-peak quasi-steady-state observation mode, S502 is executed, and the parameter calibration module 107 calculates the dynamic comprehensive heat dissipation coefficient based on the off-peak quasi-steady-state heat storage compensation inversion mechanism. During the off-peak light load period at night, due to the extremely small load current and low heat generation, the abnormal temperature rise effect caused by contact resistance degradation has not yet become significant. At this time, the reference contact resistance obtained during the static calibration stage is introduced. As known parameters, they typically do not cause significant calculation deviations. Based on this, since the equipment temperature is in a quasi-steady state with slight fluctuations, the thermal storage term is not completely zero. The parameter calibration module 107 extracts the low-temperature observation window. The synchronization vector group sequence within the array, retaining the heat capacity integral compensation term, is calculated using the following formula: ; In the formula, the first term in the numerator is the time-domain integral of the Joule heating amount during the low-temperature period, and the second term is the minute amount of heat absorbed or released by the device body during that period. To avoid the risk of division by zero in algebraic calculations, the system sets a temperature difference significance verification logic, which requires that the average temperature difference between the contact and the environment within the observation time window must be greater than the set steady-state temperature difference lower limit threshold. As a preferred approach, this threshold can be set to 10℃; if this condition is not met, the compensation calculation is abandoned. This low-temperature compensation algorithm enables the system to periodically eliminate the heat dissipation performance degradation caused by environmental factors during the normal operation cycle of the device without power interruption.

[0054] After completing the algebraic calculation of the dynamic integrated heat dissipation coefficient, the system needs to globalize this underlying physical parameter to support subsequent core inference calculations. Entering S503, the parameter calibration module 107 executes a global parameter cache update mechanism based on exponential smoothing. Since a single inversion calculation may be affected by occasional sensor drift or extreme local airflow disturbances, directly overwriting the original parameters can easily lead to oscillations in subsequent warning logic. In this embodiment, the parameter calibration module 107 uses a first-order low-pass filtering algorithm to update the newly calculated values. Combined with existing historical dynamic thermal coefficients in the system cache Perform a smooth fusion. The mathematical expression for its update rule is: ; In the formula, To smooth the updated dynamic overall heat dissipation coefficient; The smoothing filter coefficient is typically set to a value between 0.1 and 0.3, with a preferred value of 0.2. The specific value is negatively correlated with the sensor sampling noise level. The higher the noise, the smaller α should be to enhance the weight of historical data. This coefficient setting gives historical data a greater weight, ensuring the engineering continuity of the evolution of physical parameters.

[0055] After completing the smoothing calculation, the parameter calibration module 107 will... The value of the global variable is overwritten into the shared memory area of ​​the processing gateway 109. The updated dynamic comprehensive heat dissipation coefficient is readily available for reading by the simulation and early warning module 108, establishing the latest and most accurate external heat dissipation boundary conditions for the next cycle of alternating load calculation, thereby effectively suppressing the problem of false alarms in temperature rise warnings caused by the decline in environmental cooling capacity.

[0056] See attached document Figure 8 , Figure 8 This is a time-domain integral derivation and early warning logic diagram of the dynamic resistance equivalence factor according to an embodiment of the present invention. The derivation and early warning module 108 provided by the present invention calculates the dynamic resistance equivalence factor through time-domain integral inversion based on the thermodynamic parameters of the synchronization vector group and global cache under alternating load operation conditions, and uses this as a basis for equipment health status assessment and graded early warning. Specifically, it includes the following operations: S601, the simulation and early warning module 108 constructs an integral simulation mechanism based on a sliding time window.

[0057] When the system is in normal operation and alternating simulation conditions, the heat generation and dissipation of the equipment are in dynamic change or in a high-level dynamic equilibrium. Traditional transient algebraic calculations are easily affected by sensor sampling noise or local airflow disturbances, resulting in drastic fluctuations. To obtain stable physical characteristics characterizing the true degree of degradation of the high-voltage contacts, the system allocates a circular buffer in memory based on a first-in-first-out (FIFO) mechanism to hold the data sequence. The simulation and early warning module 108 extracts a fixed-length sliding time window on the time axis. The system simultaneously extracts phase current data, continuous contact temperature, and continuous ambient temperature within this time window. The length of this sliding time window determines the algorithm's ability to smooth transient noise and its real-time fault response. As a preferred approach, the sliding time window length can be set to 10 to 30 minutes, taking into account the actual thermal time constant of the high-voltage electrical equipment, and incrementing in preset steps as the system clock advances. Swipe forward to update and overwrite outdated data.

[0058] After extracting the data sequence within the time window, to ensure the subsequent inversion has reliable physical meaning, the deduction and early warning module 108 needs to rigorously verify the validity of the data to avoid dead zones in the underlying mathematical calculations. Considering that there may still be extremely short-term current drops under this operating condition, the deduction and early warning module 108 calculates the time-domain integral of the square of the effective value of the phase current within the sliding time window. In digital microprocessors, the aforementioned continuous time-domain integral is typically obtained numerically using the discrete trapezoidal integration algorithm or the summation method, which are well-known techniques in the field and will not be elaborated upon here. The system determines whether the current integral term is greater than the set effective work threshold. The effective work threshold Typically, the integral of the square of the current generated by the continuous constant operation of the device within this time window is set to 5% of the rated current of the equipment. If the calculated result is less than this threshold, the system determines that the current-induced heating effect within the current window is too weak, and the signal-to-noise ratio of the reverse-calculated contact resistance is extremely low. At this time, the deduction warning module 108 will abandon the deduction action of the current time window, and the window will continue to slide backward; if this condition is met, the actual integral inversion process will be entered.

[0059] Under the premise of meeting the effective work conditions, the deduction and early warning module 108 reads the equivalent heat capacity constant from the global shared memory of the processing gateway 109. and the dynamic overall heat dissipation coefficient updated in real time. Based on the law of conservation of energy, the Joule heating within the time window equals the sum of the heat absorbed by the equipment body during heating and the heat lost to the environment. The deduction and early warning module 108 establishes a discretized thermodynamic time-domain integral equation and solves for the dynamic resistance equivalence factor characterizing the current contact state of the contacts. The specific mathematical derivation and solution formula is as follows: ; In the formula, and These represent the continuous contact temperatures at the end and beginning of the sliding time window, respectively; the integral term... This is the area integral of the real-time temperature difference between the contact and the environment within this time window; It is a time variable.

[0060] To prevent calculation results from deviating from physical principles due to occasional extreme measurement data, the system will also adjust the calculated dynamic resistance equivalence factor. Perform boundary limit verification. In this embodiment, if If a value is negative or exceeds the preset physical extreme value limit, such as 10 times the reference contact resistance, the calculation result is deemed invalid and discarded, and the result from the previous time window is maintained. Through the above time-domain integral model, the system effectively reduces the interference of external heat dissipation degradation and the thermal inertia heat storage of the equipment itself, and obtains the equivalent thermal resistance characteristics mainly affected by the internal mechanical wear and micro-oxidation degree of the contacts.

[0061] The system executes S602, namely the simulation and early warning module 108, to calculate the relative degradation rate.

[0062] The simulation and early warning module 108 retrieves the reference contact resistance recorded during the initial commissioning of the equipment. To prevent the risk of division-by-zero overflow caused by underlying hardware or software failures, the system pre-processes the read data. Perform a validity check; if a validity check is detected... If the value is zero or the data is missing, the default factory reference value of the same model of equipment will be automatically invoked to maintain the simulation process, and the parameter anomaly log will be triggered simultaneously. After confirming that the reference value is valid, the current dynamic resistance equivalence factor will be calculated. relative to reference contact resistance The ratio of the two values ​​generates the relative degradation rate. The mathematical definition of this parameter is: ; Due to the reduction of baseline drift effects from ambient temperature and load fluctuations, the relative degradation rate... It can effectively reflect the attenuation state of the contact spots inside the high-voltage contacts.

[0063] Based on the quantified relative degradation ratio, the system triggers the terminal fault alarm and strategy output logic. Corresponding to main method step S80, the system executes S701, where the deduction and early warning module 108 performs state assessment and hierarchical early warning operations based on multi-level thresholds. The deduction and early warning module 108 calculates the relative degradation ratio... Compare with the preset health status threshold matrix.

[0064] In this example, the health status threshold matrix typically includes a mild degradation threshold, such as 1.2, a moderate alarm threshold, such as 1.5, and a critical failure threshold, such as 2.0. When the relative degradation ratio... When the temperature is below the mild degradation threshold, the equipment is considered to be in a healthy state. When it falls between the mild degradation threshold and the moderate alarm threshold, the system generates a warning message to prompt maintenance personnel to pay attention during subsequent inspections. If the temperature exceeds the moderate alarm threshold, the inference and early warning module 108 will immediately generate a high-priority early warning data packet and send it to the dispatch master station to request maintenance intervention. By constructing the above-mentioned monitoring path with complete closed loop and physical meaning, the system has achieved a technological improvement from single temperature alarm to proactive inference of contact microscopic pathological characteristics.

[0065] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A high-voltage electrical appliance temperature rise online monitoring system, characterized in that, include: The data synchronization module is used to establish a unified clock reference, perform resampling operations on discrete contact temperature data and ambient temperature data to generate a continuous temperature sequence, and integrate the continuous temperature sequence with phase current data and opening / closing status data to construct a synchronization vector group. The static calibration module is used to read the synchronization vector group at the initial stage of equipment commissioning, and to calculate and store the equivalent heat capacity constant and the initial comprehensive heat dissipation coefficient based on the lumped parameter thermodynamic model when the high voltage electrical appliance is in an ideal healthy steady-state condition according to the load stability condition and temperature gradient condition. The operating condition routing module is used to monitor the synchronization vector group and extract the opening and closing status data and phase current data. Based on the preset boundary judgment threshold, it switches the system state machine into the power-off natural cooling mode, the valley quasi-steady state observation mode, or the online monitoring and deduction mode. The parameter calibration module is used to extract the synchronization vector group within the corresponding time window in the power outage natural cooling mode or the valley quasi-steady state observation mode, calculate the current dynamic comprehensive heat dissipation coefficient by solving the thermal balance integral equation, and write the updated dynamic comprehensive heat dissipation coefficient into the system global cache. The simulation and early warning module is used to extract the synchronization vector group based on the sliding time window in the online monitoring and simulation mode, calculate the dynamic resistance equivalent factor through time domain integration inversion based on the equivalent heat capacity constant and dynamic comprehensive heat dissipation coefficient in the system global cache, and calculate the relative degradation ratio based on this and then perform graded early warning operation.

2. The online temperature rise monitoring system for high-voltage electrical appliances according to claim 1, characterized in that, The data synchronization module is specifically used for: The timestamp sequence of the extracted phase current data is used as the reference time axis. The time interval between two adjacent actual received temperature data is calculated. If the time interval is greater than the set packet loss tolerance threshold, the data quality bits in that time period are marked as invalid. For the time segment where the data quality verification is valid, an interpolation algorithm or a zero-order hold is used to map the sparse temperature timestamps onto the dense reference time axis to generate a continuous contact temperature sequence and a continuous ambient temperature sequence.

3. The online temperature rise monitoring system for high-voltage electrical appliances according to claim 1, characterized in that, The specific load stability condition and temperature gradient condition are as follows: Within a preset observation time window, the variance of the phase current data fluctuation is consistently less than the set current fluctuation threshold, and the derivative of the continuous contact temperature with respect to time at the end of the observation time window is less than the set minimum temperature change rate threshold.

4. The online temperature rise monitoring system for high-voltage electrical appliances according to claim 3, characterized in that, The static calibration module is specifically used for: The reference contact resistance is read through an external interactive interface. The square of the average effective value of the phase current within the steady-state time window is multiplied by the reference contact resistance and divided by the difference between the average continuous contact temperature and the average continuous ambient temperature to calculate the initial comprehensive heat dissipation coefficient. Historical synchronous vector group data within the transient heating period are retrieved retrospectively. Using the calculated initial comprehensive heat dissipation coefficient, the time-domain integral of the internal Joule heat generation and the time-domain integral of the external heat dissipation within the transient heating period are calculated. This difference is then divided by the contact temperature rise amplitude within the transient heating period to deduce the equivalent heat capacity constant.

5. The online temperature rise monitoring system for high-voltage electrical appliances according to claim 1, characterized in that, The preset boundary judgment thresholds include a zero current dead zone threshold, a low-valley stable load threshold, a steady-state current fluctuation variance threshold, and a quasi-steady-state temperature change rate minimum threshold; the operating condition routing module is specifically used for: When the circuit breaker status data is detected as being in the open state, or the phase current data is less than the zero current dead zone threshold, the system state machine will switch to the power-off natural cooling mode. When the opening and closing status data is detected to be in the closing state and the phase current data is in the range of greater than the zero current dead zone threshold and less than or equal to the valley stable load threshold, and the fluctuation variance of the phase current data is continuously less than the steady-state current fluctuation variance threshold, and the absolute value of the derivative of the continuous contact temperature with respect to time is continuously less than the minimum value threshold of the quasi-steady-state temperature change rate, the system state machine is switched to the valley quasi-steady-state observation mode. When the conditions for determining the above two modes are not met, the system state machine will switch to online monitoring and simulation mode.

6. The online temperature rise monitoring system for high-voltage electrical appliances according to claim 5, characterized in that, In the power-off natural cooling mode, the parameter calibration module is specifically used for: Within the set cooling time window, it is verified whether the temperature drop of the continuous contact is greater than the set effective cooling threshold. If it is satisfied, then based on the boundary condition of no internal heat source, the natural cooling integral inversion calculation is performed on the area integral of the real-time temperature difference between the contact and the environment using the equivalent heat capacity constant, so as to obtain the dynamic comprehensive heat dissipation coefficient of the calculation state.

7. The online temperature rise monitoring system for high-voltage electrical appliances according to claim 5, characterized in that, In the aforementioned quasi-steady-state observation mode during the trough, the parameter calibration module is specifically used for: Extract the synchronous vector group sequence within the low observation time window, and verify whether the average temperature difference between the contact and the environment within the time window is greater than the set steady-state temperature difference lower limit threshold. If it is satisfied, the reference contact resistance is introduced as a known parameter to calculate the time domain integral of the internal Joule heat generation, and the heat capacity integral compensation term is retained. The low quasi-steady-state heat storage compensation inversion calculation is performed to obtain the dynamic comprehensive heat dissipation coefficient of the calculation state.

8. The online temperature rise monitoring system for high-voltage electrical appliances according to claim 1, characterized in that, After calculating the current dynamic comprehensive heat dissipation coefficient, the parameter calibration module executes a global parameter cache update mechanism based on exponential smoothing; specifically used for: A first-order low-pass filtering algorithm is used to assign corresponding smoothing filter coefficient weights to the newly calculated dynamic integrated heat dissipation coefficient and the existing historical dynamic integrated heat dissipation coefficient in the system cache, and then perform weighted summation and fusion to generate a smooth updated dynamic integrated heat dissipation coefficient. The smooth updated dynamic integrated heat dissipation coefficient is then overwritten into the system global cache of the processing gateway.

9. The online temperature rise monitoring system for high-voltage electrical appliances according to claim 1, characterized in that, The inference and early warning module is specifically used before performing time-domain integral inversion calculation: Calculate the time-domain integral of the square of the effective value of the phase current within the sliding time window, and determine whether the integral value is greater than the set effective work threshold. If it is satisfied, then establish the discretized thermodynamic time-domain integral equation based on the law of conservation of energy to solve the dynamic resistance equivalent factor. If the solved dynamic resistance equivalent factor is negative or exceeds the preset physical extreme value upper limit, then the calculation result is determined to be invalid and discarded, and the derivation result of the previous sliding time window is maintained.

10. The online temperature rise monitoring system for high-voltage electrical appliances according to claim 9, characterized in that, The inference and early warning module performs tiered early warning operations specifically for: The reference contact resistance recorded during the initial operation of the equipment is retrieved, and the ratio of the current dynamic resistance equivalence factor to the reference contact resistance is calculated to generate a relative degradation ratio. The relative degradation ratio is compared with a health status threshold matrix that includes a mild degradation threshold, a moderate alarm threshold, and a critical fault threshold. When the relative degradation ratio exceeds the moderate alarm threshold, a high-priority early warning data packet is generated and sent to the dispatch master station.

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