Multi-dimensional electrical parameter monitoring method and system

Abstract

The present application relates to the technical field of thermal fault monitoring, and in particular to a multi-dimensional electrical parameter monitoring method and system, which solves the technical problem of high false alarm rate of electrical equipment thermal fault monitoring under the double interference of dynamic load and static structure difference in the prior art. The method comprises: obtaining the loop current and temperature of each phase monitoring point of a three-phase electrical equipment, and the ambient temperature of the three-phase electrical equipment; generating a theoretical temperature rise contribution value with thermal time delay characteristics according to the loop current of each phase; obtaining the corrected contact deviation of each phase according to the temperature of each phase, the ambient temperature, the theoretical temperature rise contribution value, and the predetermined inherent static temperature difference reference of each phase; and outputting the corresponding electrical parameter monitoring result according to the cumulative result of the corrected contact deviation of each phase within a preset time window.

Description

Technical Field

[0001] This invention relates to the field of thermal fault monitoring technology, specifically to a multi-dimensional electrical parameter monitoring method and system. Background Technology

[0002] Core power equipment in power systems, such as high-voltage switchgear and gas-insulated switchgear (GIS) switchgear, contains a large number of electrical connection points, including busbar lap surfaces and contact surfaces. These connection points are in a complex operating environment of vibration, oxidation, and corrosion for a long time, and the contact resistance is very likely to gradually increase, which can lead to local overheating of the equipment and even burn-out accidents in severe cases. To avoid such safety hazards, the industry currently widely uses infrared temperature measurement or wireless passive temperature measurement technology to monitor the temperature of critical electrical connection points of the equipment in real time.

[0003] Currently, for thermal fault monitoring of electrical connection points in power equipment, the industry generally uses infrared temperature measurement or wireless passive temperature measurement technology to monitor key connection points in real time, and determines whether the equipment has an overheating fault by setting a fixed temperature threshold or relative temperature rise threshold.

[0004] Existing monitoring methods based on fixed temperature thresholds or relative temperature rise thresholds suffer from a high false alarm rate in practical engineering applications. This problem mainly stems from two interference factors. First, there is thermal inertia interference under dynamic loads. The metal material of high-voltage conductors has a large heat capacity, causing its temperature rise to lag significantly behind current changes in the time dimension. When the load current fluctuates rapidly and significantly, the instantaneous temperature rise cannot respond to the current change in time, resulting in a deviation between the theoretical temperature rise derived from the instantaneous current and the actual measured temperature rise, ultimately leading to false alarms. Second, there is static interference caused by structural differences. Three-phase equipment is often arranged in parallel in space within the switchgear. Due to the design of the heat dissipation duct and the influence of heat radiation from adjacent phases, the middle phase inherently exhibits a higher temperature rise under normal equipment conditions. Existing technologies often ignore this fixed temperature difference caused by the equipment structure, making it difficult to set a uniform fault alarm threshold under unbalanced three-phase equipment structures, further exacerbating the false alarm problem. Summary of the Invention

[0005] To address the high false alarm rate in existing technologies for monitoring thermal faults in electrical equipment under the dual interference of dynamic load and static structural differences, the present invention aims to provide a multi-dimensional electrical parameter monitoring method and system. The specific technical solution adopted is as follows: Firstly, a multi-dimensional electrical parameter monitoring method is provided, comprising: acquiring the loop current and temperature of each phase monitoring point of a three-phase electrical device, as well as the ambient temperature of the three-phase electrical device; generating a theoretical temperature rise contribution value with thermal time delay characteristics based on the loop current of each phase; the theoretical temperature rise contribution value is used to characterize the proportion of each phase's heating excitation in the total heating excitation under the influence of conductor thermal capacity; obtaining the corrected contact deviation of each phase based on the temperature of each phase, the ambient temperature, the theoretical temperature rise contribution value, and a pre-determined inherent static temperature difference benchmark for each phase; the contact deviation is used to characterize the abnormal temperature rise characteristics caused by changes in contact resistance; and outputting the corresponding electrical parameter monitoring results based on the cumulative result of the corrected contact deviation of each phase within a preset time window.

[0006] Based on the above technical solution, in the multi-dimensional electrical parameter monitoring method provided by this invention, by introducing a theoretical temperature rise contribution value with thermal time delay characteristics, the temperature rise lag effect caused by conductor thermal capacity is effectively simulated, eliminating the instantaneous temperature rise deviation caused by sudden current changes under dynamic load fluctuations. At the same time, by introducing a pre-determined inherent static temperature difference benchmark for each phase, the non-fault inherent temperature difference caused by spatial structural differences in three-phase equipment is eliminated, achieving accurate extraction of abnormal temperature rise characteristics caused by changes in contact resistance. On this basis, combined with the cumulative judgment mechanism within a preset time window, weak and continuous fault signals can be amplified and transient noise interference can be filtered out, thereby significantly reducing the false alarm rate of fault monitoring under complex operating conditions, improving the sensitivity of early hidden danger identification, and providing a reliable decision-making basis for condition-based maintenance of electrical equipment.

[0007] In conjunction with the first aspect above, in one possible implementation, the method for generating a theoretical temperature rise contribution value with thermal time delay characteristics based on the loop current of each phase specifically includes: determining the heat generation power ratio of each phase based on the ratio of the square value of the loop current of each phase to the sum of the square values ​​of the loop currents of the three phases; performing a first-order recursive filtering on the heat generation power ratio to generate the theoretical temperature rise contribution value of each phase; the smoothing coefficient of the first-order recursive filtering is determined based on the thermal time constant and sampling period of the three-phase electrical equipment.

[0008] In conjunction with the first aspect above, in one possible implementation, the method for obtaining the corrected contact deviation for each phase specifically includes: comparing the temperature of each phase with the ambient temperature to determine the net temperature rise of each phase, and taking the ratio of the net temperature rise of each phase to the total net temperature rise of the three phases as the actual temperature rise percentage of each phase; comparing the actual temperature rise percentage of each phase with the theoretical temperature rise contribution value to determine the original temperature rise deviation of each phase; and subtracting the inherent static temperature difference reference from the original temperature rise deviation of each phase to obtain the contact deviation of each phase.

[0009] In conjunction with the first aspect above, in one possible implementation, the method further includes: when the three-phase electrical equipment is in a healthy steady state and the load fluctuation meets the preset stability conditions, obtaining the original temperature rise deviation between the actual temperature rise percentage and the theoretical temperature rise contribution value of each phase; and updating the average value of the original temperature rise deviation of each phase within a preset learning period to the inherent static temperature difference benchmark of the corresponding phase.

[0010] In conjunction with the first aspect above, in one possible implementation, the method further includes: before updating the inherent static temperature difference benchmark, verifying the dispersion of each phase candidate benchmark in the current learning cycle; if the dispersion exceeds the preset structural difference limit, refusing to update the inherent static temperature difference benchmark determined in the current learning cycle, and outputting an abnormal prompt message.

[0011] In conjunction with the first aspect above, in one possible implementation, the method further includes: performing nonlinear dead-zone processing on the contact deviation to obtain a corrected contact deviation; the nonlinear dead-zone processing includes: setting contact deviations less than or equal to a preset noise threshold to zero, and performing nonlinear amplification on contact deviations greater than the preset noise threshold.

[0012] In conjunction with the first aspect above, in one possible implementation, the method for outputting the corresponding electrical parameter monitoring result based on the cumulative result of the corrected contact deviation of each phase within a preset time window specifically includes: accumulating the product of the corrected contact deviation of each phase and the sampling period within the preset time window to obtain the cumulative contact deviation of each phase; a preset time window includes multiple sampling periods; if the cumulative contact deviation of any phase is greater than or equal to a preset first threshold and less than a preset second threshold, outputting a first-level warning signal for the corresponding phase; if the cumulative contact deviation of any phase is greater than or equal to the second threshold, outputting a second-level alarm signal for the corresponding phase.

[0013] In conjunction with the first aspect above, in one possible implementation, the method further includes: when it is detected that the corrected contact deviation of any phase is continuously zero over multiple consecutive sampling periods, the cumulative contact deviation of the corresponding phase is cleared to zero.

[0014] In conjunction with the first aspect above, in one possible implementation, after obtaining the loop current and temperature of each phase, as well as the ambient temperature, the method further includes: comparing the temperature of each phase with the ambient temperature to determine the net temperature rise of each phase, and calculating the total net temperature rise of the three phases; calculating the average current of the three phases based on the loop current of each phase; if the average current of the three phases is less than or equal to a preset current threshold, or the total net temperature rise of the three phases is less than or equal to a preset temperature rise threshold, then the sampled data is determined to be invalid, and the subsequent processing steps are terminated.

[0015] Secondly, a multi-dimensional electrical parameter monitoring system is provided, comprising: a data acquisition module for acquiring the loop current and temperature of each phase monitoring point of the three-phase electrical equipment, as well as the ambient temperature of the three-phase electrical equipment; a theoretical response generation module for generating a theoretical temperature rise contribution value with thermal time delay characteristics based on the loop current of each phase; the theoretical temperature rise contribution value is used to characterize the proportion of each phase's heating excitation in the total heating excitation under the influence of conductor heat capacity; a deviation correction module for obtaining the corrected contact deviation of each phase based on the temperature of each phase, the ambient temperature, the theoretical temperature rise contribution value, and a pre-determined inherent static temperature difference benchmark for each phase; the contact deviation is used to characterize the abnormal temperature rise characteristics caused by changes in contact resistance; and a fault determination module for outputting the corresponding electrical parameter monitoring results based on the cumulative result of the corrected contact deviation of each phase within a preset time window.

[0016] The present invention has the following beneficial effects: By introducing a theoretical temperature rise contribution value with thermal time delay characteristics, the temperature rise lag effect caused by conductor thermal capacity is effectively simulated, eliminating the instantaneous temperature rise deviation caused by sudden current changes under dynamic load fluctuations. Simultaneously, by introducing a pre-determined inherent static temperature difference benchmark for each phase, the non-fault-related inherent temperature difference caused by spatial structural differences in three-phase equipment is eliminated, enabling accurate extraction of abnormal temperature rise characteristics caused by changes in contact resistance. Based on this, combined with an accumulation judgment mechanism within a preset time window, weak, persistent fault signals can be amplified and transient noise interference filtered out, thereby significantly reducing the false alarm rate of fault monitoring under complex operating conditions, improving the sensitivity of early-stage hazard identification, and providing a reliable decision-making basis for condition-based maintenance of electrical equipment. Attached Figure Description

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a system structure diagram of a multi-dimensional electrical parameter monitoring system provided in one embodiment of the present invention; Figure 2 This is a flowchart illustrating a multi-dimensional electrical parameter monitoring method according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the hardware structure of a multi-dimensional electrical parameter monitoring device provided in one embodiment of the present invention. Detailed Implementation

[0019] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a multi-dimensional electrical parameter monitoring method and system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0021] The following description, in conjunction with the accompanying drawings, details a specific scheme for a multi-dimensional electrical parameter monitoring method and system provided by the present invention.

[0022] Please see Figure 1 The diagram shows a system structure diagram of a multi-dimensional electrical parameter monitoring system provided by an embodiment of the present invention. The multi-dimensional electrical parameter monitoring system includes: a data acquisition module 1, a theoretical response generation module 2, a deviation correction module 3, and a fault determination module 4.

[0023] This multi-dimensional electrical parameter monitoring system comprises four core functional modules: data acquisition module 1, theoretical response generation module 2, deviation correction module 3, and fault determination module 4. Each module achieves its function through the collaborative cooperation of hardware circuits, embedded programs, and industrial control software. A hierarchical data transmission relationship is formed between modules, with the valid data and calculation results output by preceding modules serving as the core input basis for subsequent modules. The system is comprehensively adapted to the electrical parameter monitoring needs of three-phase electrical equipment such as high-voltage switchgear and GIS combined electrical appliances. It can accurately extract temperature rise characteristics caused by abnormal equipment contact resistance, enabling graded judgment and early warning of equipment faults. The following provides a detailed introduction to each module and its sub-modules: Data acquisition module 1 is the basic input module of the entire monitoring system. It is responsible for the synchronous acquisition and validity screening of the original data related to the three-phase electrical equipment, providing high-quality basic data for subsequent modules. This module can be built using various sensing and detection devices and embedded control boards. It contains two core sub-modules: data synchronization acquisition sub-module 11 and data validity verification sub-module 12.

[0024] The data synchronization acquisition submodule 11 acquires the circuit current of each phase monitoring point of the three-phase electrical equipment through a current transformer installed on the electrical circuit, acquires the temperature of each phase monitoring point through temperature sensors (fiber optic temperature sensors or wireless passive temperature sensors) deployed at key locations such as equipment contacts and busbar lap surfaces, and acquires the ambient temperature of the equipment through an ambient temperature sensor placed in the cold air vent of the cabinet and away from the heat source. This submodule will complete the synchronous acquisition of the above three types of data according to the preset sampling period. The acquired raw data will be synchronously transmitted to the data validity verification submodule 12.

[0025] The data validity verification submodule 12 performs data screening through the algorithm program in the embedded control board. First, it calculates the net temperature rise of each phase based on the temperature of each phase monitoring point and the ambient temperature, and then calculates the total net temperature rise of the three phases. Next, it calculates the average current of the three phases based on the loop current of each phase. Then, it compares the average current of the three phases with the preset current threshold and the total net temperature rise of the three phases with the preset temperature rise threshold. If the judgment result of any comparison condition is that the data is invalid, then all subsequent processing steps are terminated directly, and only the sampled data that is determined to be valid is transmitted to the theoretical response generation module 2 and the deviation correction module 3 respectively as the basis for subsequent calculations.

[0026] The theoretical response generation module 2 is the core module for realizing dynamic hysteresis compensation. It is specifically designed to receive the effective loop current data output by the data acquisition module 1 and generate a theoretical temperature rise contribution value that conforms to the thermal capacity characteristics of the conductor through algorithm calculation. This module can be implemented by the program calculation unit of a microcontroller or industrial computer. It contains two core sub-modules: a heat generation power ratio calculation sub-module 21 and a first-order recursive filtering processing sub-module 22.

[0027] The heat generation power ratio calculation submodule 21 completes the calculation through the built-in algorithm program. Based on the ratio of the square value of the current in each phase loop to the sum of the square values ​​of the current in the three phase loops, it accurately calculates the heat generation power ratio of each phase. The calculated heat generation power ratio data of each phase is transmitted to the first-order recursive filtering processing submodule 22 in real time as the core basic data for generating the theoretical temperature rise contribution value.

[0028] The first-order recursive filtering submodule 22 first determines the smoothing coefficient of the first-order recursive filter based on the thermal time constant of the three-phase electrical equipment and the system's preset sampling period. Then, it performs first-order recursive filtering on the proportion of received heat power and finally generates a theoretical temperature rise contribution value with thermal time delay characteristics. This value is used to characterize the proportion of each phase's heat excitation in the total heat excitation under the influence of conductor heat capacity. The generated theoretical temperature rise contribution value will be transmitted to the deviation correction module 3 to provide a key basis for the subsequent calculation of the original temperature rise deviation.

[0029] Deviation correction module 3 is the core module for stripping away static structural deviations of equipment and extracting real fault characteristics. It also receives effective temperature and ambient temperature data output by data acquisition module 1 and theoretical temperature rise contribution value output by theoretical response generation module 2. Through multi-step calculations, it obtains the corrected contact deviation that only represents the change in contact resistance. This module can be built using the computing and storage units of an industrial computer. It contains four core sub-modules: actual temperature rise ratio calculation sub-module 31, original temperature rise deviation calculation sub-module 32, static reference correction sub-module 33, and nonlinear dead zone processing sub-module 34.

[0030] The actual temperature rise percentage calculation submodule 31 completes the calculation through the built-in algorithm program. First, it compares the temperature of each phase monitoring point with the ambient temperature to calculate the net temperature rise value of each phase. Then, it takes the ratio of the net temperature rise value of each phase to the total net temperature rise of the three phases as the actual temperature rise percentage of each phase. The calculated actual temperature rise percentage data will be transmitted to the original temperature rise deviation calculation submodule 32.

[0031] The original temperature rise deviation calculation submodule 32 compares the actual temperature rise percentage of each phase with the theoretical temperature rise contribution value, and obtains the original temperature rise deviation of each phase through difference calculation. This deviation data is transmitted to the static reference correction submodule 33 in real time.

[0032] The static reference correction submodule 33 has a built-in inherent static temperature difference reference for each phase of the three-phase electrical equipment under a healthy steady state. It first subtracts the inherent static temperature difference reference of the corresponding phase from the original temperature rise deviation of each phase to obtain the preliminary contact deviation. At the same time, this submodule can also realize the self-learning and updating of the inherent static temperature difference reference. When the equipment is in a healthy steady state and the load fluctuation meets the preset stability conditions, it continuously obtains the original temperature rise deviation between the actual temperature rise ratio and the theoretical temperature rise contribution value of each phase. The average value of the original temperature rise deviation of each phase within the preset learning period is used as the candidate reference for the corresponding phase. Before updating the inherent static temperature difference reference, this submodule will also verify the dispersion of each phase candidate reference within the current learning period. If the dispersion exceeds the preset structural difference limit, the inherent static temperature difference reference determined this time will be rejected and an abnormal prompt message will be output through the system communication unit. If the verification is successful, the reference update is completed. The contact deviation calculated by this submodule will be transmitted to the nonlinear dead zone processing submodule 34.

[0033] The nonlinear dead zone processing submodule 34 performs nonlinear dead zone processing on the received contact deviation through an algorithm program. Contact deviations less than or equal to the preset noise threshold are directly set to zero, while contact deviations greater than the preset noise threshold are nonlinearly amplified to obtain the corrected contact deviation. This deviation only represents the abnormal temperature rise characteristics caused by the change in contact resistance and will be fully transmitted to the fault determination module 4 to provide clean fault characteristic data for equipment fault determination.

[0034] The fault determination module 4 is the core module of the entire monitoring system for fault classification and early warning. It is specifically designed to receive the corrected contact deviation output by the deviation correction module 3. Through cumulative calculation and comparison with the threshold, it determines the equipment fault status and outputs early warning signals. This module can be built collaboratively by an industrial control computer, alarm indicator device and communication module. It contains three core sub-modules: cumulative contact deviation calculation sub-module 41, graded early warning output sub-module 42, and integral reset sub-module 43.

[0035] The cumulative contact deviation calculation submodule 41 implements its function through the built-in first-in-first-out data storage queue and calculation program. It continuously accumulates the corrected contact deviation of each phase within a preset time window to obtain the cumulative contact deviation of each phase. The preset time window includes multiple sampling periods set by the system. The calculated cumulative contact deviation data of each phase is transmitted to the graded early warning output submodule 42 in real time.

[0036] The graded early warning output submodule 42 has two preset judgment thresholds: a first threshold and a second threshold. It compares the received cumulative contact deviation of each phase with the two thresholds. If the cumulative contact deviation of any phase is greater than or equal to the first threshold and less than the second threshold, the submodule will output a first-level early warning signal for the corresponding phase through an alarm indicator, an industrial control computer display unit, or a remote communication module. If the cumulative contact deviation of any phase is greater than or equal to the second threshold, it will output a second-level alarm signal for the corresponding phase, thereby realizing graded judgment and early warning of equipment faults.

[0037] The integral reset submodule 43 monitors the corrected contact deviation of each phase output by the deviation correction module 3 in real time through program logic. When it is detected that the corrected contact deviation of any phase is continuously zero for multiple consecutive sampling periods, the submodule will automatically clear the cumulative contact deviation of the corresponding phase to zero, so as to avoid the interference of historical invalid data on the subsequent fault judgment results and ensure the accuracy of the system's early warning judgment.

[0038] Please see Figure 2 The diagram illustrates a flowchart of a multi-dimensional electrical parameter monitoring method according to an embodiment of the present invention. This multi-dimensional electrical parameter monitoring method includes: S1. Obtain the loop current and temperature of each phase monitoring point of the three-phase electrical equipment, as well as the ambient temperature of the three-phase electrical equipment.

[0039] In some implementations, firstly, the system establishes a unified time reference and sets a preset sampling period. This sampling period must be less than 1 / 10 of the equipment's thermal response time (typically 20-60 minutes for conventional high-voltage switchgear and GIS combined electrical equipment), for example, 10 seconds, to meet the requirements of Shannon's sampling theorem for thermal process reconstruction. Then, the data synchronization acquisition process is initiated: using current transformers installed on the electrical circuits, the loop current values ​​of each phase monitoring point of the three-phase electrical equipment are synchronously collected according to the preset sampling period, and recorded as the loop current acquisition data for phase A, phase B, and phase C, respectively. Temperature sensors installed at key connection points of the electrical equipment, including contacts and busbar lap surfaces, are used to synchronously collect the temperature values ​​of each phase monitoring point. Simultaneously, ambient temperature sensors deployed inside the electrical equipment cabinet at cold air vents or away from heat sources are used to collect the ambient reference temperature of the three-phase electrical equipment, ensuring the accuracy of the ambient temperature acquisition and avoiding interference from the equipment's own thermal radiation.

[0040] After data collection is complete, the system automatically performs a data validity verification process to eliminate interference from invalid data such as low load and slight temperature rise in subsequent calculations. First, the temperature difference between each phase monitoring point and the ambient temperature is determined as the net temperature rise of each phase. Then, the net temperature rises of the three phases are accumulated and statistically analyzed to obtain the total net temperature rise of the three phases. At the same time, based on the collected circuit current of each phase, the average value of the three-phase circuit current is calculated, i.e., the three-phase average current.

[0041] Next, the system compares the statistically obtained three-phase average current with a preset current threshold, which in this embodiment is 20% of the rated current. Simultaneously, it compares the statistically obtained total net temperature rise of the three phases with a preset temperature rise threshold, which in this embodiment is 3°C.

[0042] If the determination result is that the three-phase average current is less than or equal to the preset current threshold, it indicates that the current load of the electrical equipment is insufficient and cannot generate an effective thermal effect; or if the sum of the three-phase net temperature rises is less than or equal to the preset temperature rise threshold, it indicates that the temperature rise signal is weak and the equipment as a whole has no effective thermal effect (such as low load, no load, power failure). Under these conditions, the equipment does not generate Joule heating or heat accumulation, and there is no risk of thermal failure. To avoid the system state from losing synchronization with the physical cooling process (for example, after the equipment is suddenly powered off from a high load, the conductor is still actually dissipating heat and cooling, but the system cannot update its internal state because the data is shielded, causing historical fault information to be retained), the system will handle it as follows: The process of generating the theoretical temperature rise contribution value (S2) continues to run, in which the current of each phase loop is set to zero at the current moment, so that the first-order recursive filter can iterate normally, simulating the exponential cooling process of the conductor under no current excitation, and ensuring that the internal state of the thermal time delay filter is synchronized with the physical world. Skip the contact deviation calculation (S3) and fault determination (S4) steps, that is, do not perform original temperature rise deviation, inherent static temperature difference correction, nonlinear dead zone processing, and accumulation and alarm output of cumulative contact deviation; When the average current of the three phases is greater than the preset current threshold and the total net temperature rise of the three phases is greater than the preset temperature rise threshold in subsequent sampling cycles, the complete S3 and S4 processing flow will be automatically restored. At this time, the internal thermal accumulation state of the system has been continuously updated to be consistent with the actual cooling process, avoiding serious false alarms caused by the residue of historical fault states after power-on.

[0043] If the sampled data passes the above validity check, the system will transmit the effective loop current, effective temperature and effective ambient temperature data collected this time to the subsequent theoretical response generation stage and deviation correction stage, respectively. This provides reliable basic data for generating the theoretical temperature rise contribution value that matches the thermal capacity characteristics of the conductor and calculating the corrected contact deviation that characterizes the change in contact resistance, thus ensuring the accuracy and effectiveness of the entire monitoring system's calculation process.

[0044] S2. Based on the loop current of each phase, generate the theoretical temperature rise contribution value with thermal time delay characteristics.

[0045] The theoretical temperature rise contribution value is used to characterize the proportion of each phase's heating excitation in the total heating excitation under the influence of the conductor's heat capacity.

[0046] In some implementations, firstly, based on the physical law of Joule's law that the heating power of a conductor is proportional to the square of the current, the proportion of heating power in each phase is calculated to eliminate common-mode interference from changes in the absolute amplitude of the current, retaining only the characteristics of relative imbalance between the three phases. During the calculation, the square of the loop current in each phase is first taken to characterize the heating excitation intensity of that phase. Then, the squares of the three-phase loop currents are summed to obtain the total heating excitation intensity. Finally, the proportion of heating power in each phase is determined based on the ratio of the square of the loop current in each phase to the sum of the squares of the three-phase loop currents. Specifically, if the squares of all three phase currents are zero, it indicates that the three-phase electrical equipment is operating under zero load or in a power-off shutdown state, with no current flowing in the electrical circuit. In this case, there is no Joule heating excitation, and the proportion of heating power in each phase can be directly assigned to 0.

[0047] Subsequently, the system executes cold start and interrupt reset logic checks to avoid transient errors caused by the recursive algorithm's reliance on historical states. The system records the timestamp of the last valid calculation moment, calculates the time interval between the current valid moment and the previous valid moment, and compares this interval with three times the device's thermal time constant (e.g., 30 minutes). If the time interval is greater than three times the thermal time constant, the system is determined to be in a cold start state. At this time, the conductor's thermal equilibrium has been rebuilt, historical temperature rise information has been exhausted, and the current heat generation power ratio is directly assigned as the theoretical temperature rise contribution value, serving as a new starting point for recursive iteration. If the time interval is less than or equal to three times the thermal time constant, the system is determined to be in a continuous operation state, maintaining the recursive iteration logic.

[0048] Next, a first-order recursive filter is applied to the proportion of heating power to generate a theoretical temperature rise contribution value with thermal time delay characteristics. The smoothing coefficient of this filter is... From the thermal time constant of the equipment With sampling period Determined jointly, and expressed as: In the formula, The ratio of the sampling period to the thermal time constant is a dimensionless parameter that reflects the degree of matching between the sampling frequency and the thermal inertia of the equipment. exp is the natural exponential function, which is calculated by subtracting the negative ratio from the natural exponent, thus establishing the correlation between the smoothing coefficient and thermal inertia, and obtaining the smoothing coefficient. , is a dimensionless scalar with values ​​between (0, 1), representing the update weight of the current heating power ratio in the first-order recursive filter, reflecting the system's response speed to new heating excitation.

[0049] In recursive calculations, the theoretical temperature rise contribution value from the previous moment represents the influence of historical heat accumulation, while the current moment's heat generation power ratio represents the new heat generation excitation. A weighted summation is used to obtain the current moment's theoretical temperature rise contribution value, ensuring that the theoretical temperature rise contribution value exhibits an exponential hysteresis characteristic consistent with the actual temperature rise. This achieves phase alignment between the heat generation excitation and the thermal response on the time axis, expressed as: In the formula, This represents the theoretical temperature rise contribution value of the k-th phase at the nth sampling time. The theoretical temperature rise contribution value of the k-th phase at the n-1 sampling time represents the influence of historical heat accumulation; For smoothing coefficients; The percentage of heat generation power in the k-th phase at the n-th sampling time represents the current new heat generation excitation; The historical theoretical contribution value of temperature rise is weighted to represent the retained portion of historical heat accumulation; The weighted average of the current heat generation power percentage represents the portion of the new heat generation excitation introduced.

[0050] S3. Based on the temperature of each phase, ambient temperature, theoretical temperature rise contribution value, and the predetermined inherent static temperature difference benchmark of each phase, obtain the corrected contact deviation of each phase.

[0051] Contact deviation is used to characterize the abnormal temperature rise caused by changes in contact resistance.

[0052] In some implementations, firstly, based on the temperature at each phase monitoring point and the ambient temperature, the net temperature rise of each phase is calculated. The net temperature rise is the difference between the temperature at the corresponding phase monitoring point and the ambient temperature, representing the actual thermal response intensity of that phase relative to the environment. Subsequently, the actual temperature rise percentage of each phase is calculated, and the net temperature rise of each phase is compared with the sum of the net temperature rises of the three phases (cases with a denominator of zero are filtered out in S1). Finally, a dimensionless actual temperature rise percentage with a value between [0, 1] is obtained, which is used to represent the actual temperature rise contribution ratio presented at that time, eliminating the combined influence of overall ambient temperature fluctuations and overall load increases and decreases on the three-phase temperature rise, and making the monitoring data under different operating conditions comparable.

[0053] Next, the initial temperature rise deviation for each phase is calculated. The difference between the actual temperature rise percentage and the theoretical temperature rise contribution is taken. The resulting initial temperature rise deviation combines abnormal deviations caused by contact faults and fixed deviations caused by differences in equipment structure. To eliminate non-fault deviations caused by structural differences, a pre-determined inherent static temperature difference benchmark for each phase is introduced. The inherent static temperature difference benchmark for the corresponding phase is subtracted from the initial temperature rise deviation to obtain the preliminary contact deviation. This deviation has eliminated structural biases under healthy equipment conditions and retains only abnormal characteristics related to changes in contact resistance.

[0054] The inherent static temperature difference reference is determined through a self-learning process under healthy conditions: When the three-phase electrical equipment is in a healthy steady state with good contact after commissioning and acceptance or maintenance, and the three-phase load current fluctuation is stable (for example, the preset fluctuation stability condition is that the current change rate is less than 5% / min), the original temperature rise deviation between the actual temperature rise ratio and the theoretical temperature rise contribution value of each phase is continuously obtained, and the arithmetic mean of the original temperature rise deviation of each phase is calculated within a preset learning period (such as 24 hours) as a candidate benchmark.

[0055] Before updating the inherent static temperature difference reference, the dispersion of the three-phase candidate references is verified. In this embodiment, a minimum reference value is preset (far smaller than the noise threshold, but larger than the calculation precision, used for safety identification of the reference as zero, such as 0.001), and a structural difference limit is preset to ±10%. If the absolute value of the candidate reference is greater than the preset minimum reference value, the difference between the maximum and minimum values ​​of the original temperature rise deviation is calculated for each phase, and then the ratio of the difference to the candidate reference is used as the dispersion. If the dispersion exceeds the preset structural difference limit, it is determined that the current data has an installation hazard or wiring error, the inherent static temperature difference reference is rejected, and an abnormal prompt message is output; if the absolute value of the candidate reference is less than or equal to the preset minimum reference value, it means that the inherent static temperature difference reference of that phase under healthy operating conditions is close to zero (common in equipment with symmetrical structure and ideal heat dissipation conditions). At this time, the absolute fluctuation amplitude is used directly for judgment: if the difference between the maximum and minimum values ​​of the original temperature rise deviation is greater than the preset absolute deviation threshold (e.g., 1 / 4 of the noise threshold, reflecting the upper limit of absolute fluctuation allowed by healthy equipment), it is considered that the dispersion is too large, the verification fails, and the update is rejected.

[0056] If the verification passes, the candidate reference will be fixed as the inherent static temperature difference reference for the corresponding phase until the next reset.

[0057] Subsequently, nonlinear dead-zone processing is performed on the initial contact deviation to filter out non-fault-related fluctuations such as sensor noise and electromagnetic interference. The system has a preset noise filtering threshold. For example, if the value is 0.02 (i.e., a 2% percentage deviation), and the contact deviation is less than or equal to the noise threshold... If the current deviation is within the normal noise fluctuation range or is a negative deviation indicating good heat dissipation and no fault characteristics, set it to zero; if the contact deviation is greater than the noise threshold, it indicates that the current deviation is within the normal noise fluctuation range or is a negative deviation indicating good heat dissipation and no fault characteristics. This indicates the existence of a positive temperature rise deviation exceeding the noise range. The portion exceeding the threshold is squared to achieve non-linear amplification, yielding the corrected contact deviation. This deviation is a non-negative value, representing only the abnormal temperature rise characteristics caused by changes in contact resistance, and is expressed as: In the formula, The initial contact deviation of the k-th phase at the nth sampling time; The preset noise filtering threshold is dimensionless and represents the upper limit of normal noise fluctuations. The contact deviation (i.e., effective contact deviation) is the k-th phase after nonlinear dead zone processing at the n-th sampling time.

[0058] If the deviation is a negative deviation indicating noise fluctuation or good heat dissipation, and there are no fault characteristics, it is directly set to zero to suppress non-fault interference.

[0059] The positive deviation exceeding the noise threshold is extracted and amplified quadratically. Slightly exceeding the threshold results in a smaller amplified value, suppressing repeated alarms in critical states; severely exceeding the threshold results in a rapidly increasing amplified value, enhancing sensitivity to serious faults. This yields the effective abnormal temperature rise characteristics of the k-th phase caused by changes in contact resistance. It only includes positive fault deviations that are outside the noise range.

[0060] S4. Based on the cumulative result of the corrected contact deviation of each phase within the preset time window, output the corresponding electrical parameter monitoring results.

[0061] In some implementations, the system presets a time window width (e.g., 60 sampling periods) based on the design requirement of 1 / 3 to 1 / 2 of the equipment's thermal time constant. For each phase, the system maintains a first-in-first-out (FIFO) data queue with a length equal to the preset time window width to store the most recent valid contact deviations within the preset time window. At the current sampling moment, the system accumulates the product of all valid contact deviations in the queue and the sampling period to obtain the cumulative contact deviation for that phase.

[0062] Since the effective contact deviations are all non-negative after nonlinear dead-zone processing, the cumulative contact deviations have monotonic accumulation characteristics: if a phase is only affected by transient interference (such as a single-point jump caused by an electromagnetic pulse), the effective contact deviation is only positive at individual moments, and the cumulative contact deviation will remain at a low level, without triggering false alarms; if a phase has continuous poor contact, the effective contact deviation will remain positive, and the cumulative result will increase rapidly. Even if the deviation at a single moment is small, the cumulative contact deviation can significantly exceed the threshold, thus achieving sensitive detection of weak early faults.

[0063] Subsequently, the integral reset and zeroing logic is executed to prevent historical fault information from causing the integral value to remain for a long time. The automatic reset logic is as follows: the system monitors the effective contact deviation of each phase in real time. If the effective contact deviation of a phase remains at 0 for several consecutive sampling periods (e.g., two preset time windows, 120 periods), it indicates that the phase has returned to normal or is in a heat dissipation state. The system automatically clears the cumulative contact deviation of that phase to zero and emptys the corresponding data queue, preparing for the reception of new data. Additionally, the manual / command reset logic is as follows: when the system receives a fault confirmation or system reset command from maintenance personnel, it forcibly clears the cumulative contact deviation and historical queues of all phases to zero, releases the alarm lockout state, and ensures that the system can quickly respond to manual intervention.

[0064] Finally, the system performs a graded threshold determination and alarm output. The system presets two graded thresholds: the first threshold is the attention threshold, which is set as the cumulative contact deviation value generated when the contact deviation is continuously equal to twice the noise threshold and the duration reaches half of the preset time window; the second threshold is the critical threshold, which is set as the cumulative contact deviation value generated when the contact deviation is continuously equal to five times the noise threshold and the duration reaches half of the preset time window.

[0065] For each phase, the system compares the cumulative contact deviation with two thresholds: if the cumulative contact deviation is greater than or equal to the first threshold and less than the second threshold, it determines that the phase has an early contact hazard (such as initial oxidation or loosening of the contact surface), outputs a yellow first-level warning signal, and suggests increasing the frequency of inspections or arranging non-emergency troubleshooting; if the cumulative contact deviation is greater than or equal to the second threshold, it determines that the phase has a serious contact fault (significantly increased contact resistance and continuous heating), outputs a red second-level alarm signal, which can trigger an emergency shutdown or trip command to prevent overheating and burnout accidents. This hierarchical logic follows the inverse-time principle of power protection: the more severe the fault, the greater the effective contact deviation, the faster the integral growth, and the shorter the duration required to trigger the warning, thus capturing both minor early hazards and accurately identifying urgent and dangerous faults.

[0066] Based on the above technical solution, by introducing a theoretical temperature rise contribution value with thermal time delay characteristics, the temperature rise lag effect caused by conductor thermal capacity is effectively simulated, eliminating the instantaneous temperature rise deviation caused by sudden current changes under dynamic load fluctuations. At the same time, by introducing a pre-determined inherent static temperature difference benchmark for each phase, the non-fault-related inherent temperature difference caused by spatial structural differences in three-phase equipment is eliminated, enabling accurate extraction of abnormal temperature rise characteristics caused by changes in contact resistance. On this basis, combined with an accumulation judgment mechanism within a preset time window, weak and persistent fault signals can be amplified and transient noise interference can be filtered out, thereby significantly reducing the false alarm rate of fault monitoring under complex operating conditions, improving the sensitivity of early hidden danger identification, and providing a reliable decision-making basis for condition-based maintenance of electrical equipment.

[0067] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0068] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0069] In this embodiment of the invention, the multi-dimensional electrical parameter monitoring device can be divided into functional units according to the above method example. For example, each function can be divided into its own functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0070] This invention also provides a hardware structure diagram of a multi-dimensional electrical parameter monitoring device, see [link / reference]. Figure 3 The multi-dimensional electrical parameter monitoring device 300 includes a processor 301, and optionally, a memory 302 connected to the processor 301.

[0071] In the first possible implementation, see Figure 3 The multi-dimensional electrical parameter monitoring device 300 also includes a transceiver 303. The processor 301, memory 302, and transceiver 303 are connected via a bus. The transceiver 303 is used to communicate with other devices or communication networks. Optionally, the transceiver 303 may include a transmitter and a receiver. The device in the transceiver 303 that implements the receiving function can be considered as a receiver, and the receiver is used to perform the receiving steps in the embodiments of the present invention. The device in the transceiver 303 that implements the transmitting function can be considered as a transmitter, and the transmitter is used to perform the transmitting steps in the embodiments of the present invention.

[0072] Based on the first possible implementation method Figure 3 The structural diagram shown can be used to illustrate the structure of the multi-dimensional electrical parameter monitoring device involved in the above embodiments.

[0073] in, Figure 3 The system chip in the multi-dimensional electrical parameter monitoring device can also be illustrated. In this case, the actions performed by the aforementioned multi-dimensional electrical parameter monitoring device can be implemented by this system chip. The specific actions performed can be found above and will not be repeated here.

[0074] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings and the disclosure, will understand and implement other variations of the disclosed embodiments in carrying out the claimed invention. In this invention, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit can implement several of the functions listed in this invention.

[0075] Although the invention has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made therein without departing from the scope of the invention. Accordingly, this specification and drawings are merely illustrative of the invention and are to be considered as covering any and all modifications, variations, combinations, or equivalents within the scope of the invention. Clearly, those skilled in the art can make various alterations and modifications to the invention without departing from its scope. Thus, if such modifications and modifications of the invention fall within the scope of the invention and its equivalents, the invention is also intended to include such modifications and modifications.

Claims

1. A method for monitoring multi-dimensional electrical parameters, characterized in that, include: The loop current and temperature of each phase monitoring point of the three-phase electrical equipment, as well as the ambient temperature of the three-phase electrical equipment, are obtained. The heat generation power percentage of each phase is determined by the ratio of the square of the current in each phase loop to the sum of the squares of the currents in the three phase loops. A first-order recursive filter is applied to this heat generation power percentage to generate the theoretical temperature rise contribution value for each phase. The smoothing coefficient of the first-order recursive filter is determined based on the thermal time constant and sampling period of the three-phase electrical equipment. The theoretical temperature rise contribution value is used to characterize the proportion of each phase's heat generation excitation in the total heat generation excitation under the influence of the conductor's thermal capacity. By comparing the temperature of each phase with the ambient temperature, the net temperature rise of each phase is determined, and the ratio of the net temperature rise of each phase to the total net temperature rise of the three phases is taken as the actual temperature rise percentage of each phase. By comparing the actual temperature rise percentage of each phase with the theoretical temperature rise contribution value, the original temperature rise deviation of each phase is determined. The contact deviation of each phase is obtained by subtracting the predetermined inherent static temperature difference reference of each phase from the original temperature rise deviation of each phase; the contact deviation is used to characterize the abnormal temperature rise characteristics caused by changes in contact resistance. The contact deviation is processed by nonlinear dead zone treatment to obtain the corrected contact deviation; The nonlinear dead zone processing includes: setting contact deviations less than or equal to a preset noise threshold to zero, and nonlinearly amplifying contact deviations greater than the preset noise threshold. Based on the cumulative result of the corrected contact deviation of each phase within a preset time window, the corresponding electrical parameter monitoring results are output.

2. The multi-dimensional electrical parameter monitoring method according to claim 1, characterized in that, Also includes: When the three-phase electrical equipment is in a healthy steady state and the load fluctuation meets the preset stability conditions, the original temperature rise deviation between the actual temperature rise percentage of each phase and the theoretical temperature rise contribution value is obtained. The average value of the original temperature rise deviation of each phase within a preset learning period is updated to the inherent static temperature difference reference of the corresponding phase.

3. The multi-dimensional electrical parameter monitoring method according to claim 2, characterized in that, Also includes: Before updating the inherent static temperature difference benchmark, the dispersion of each phase candidate benchmark within the current learning cycle is verified. If the dispersion exceeds the preset structural difference limit, the inherent static temperature difference benchmark determined in the current learning cycle will not be updated, and an abnormal prompt message will be output.

4. The multi-dimensional electrical parameter monitoring method according to claim 1, characterized in that, Based on the cumulative result of the corrected contact deviation for each phase within a preset time window, the corresponding electrical parameter monitoring results are output, including: The product of the corrected contact deviation for each phase and the sampling period is accumulated within a preset time window to obtain the cumulative contact deviation for each phase; a preset time window includes multiple sampling periods. If the cumulative contact deviation of any phase is greater than or equal to the preset first threshold and less than the preset second threshold, the corresponding phase's first-level warning signal will be output. If the cumulative contact deviation of any phase is greater than or equal to the second threshold, a secondary alarm signal for the corresponding phase is output.

5. The multi-dimensional electrical parameter monitoring method according to claim 4, characterized in that, Also includes: When the corrected contact deviation of any phase remains zero for multiple consecutive sampling periods, the cumulative contact deviation of the corresponding phase is cleared to zero.

6. A multi-dimensional electrical parameter monitoring system, characterized in that, include: The data acquisition module is used to acquire the loop current and temperature of each phase monitoring point of the three-phase electrical equipment, as well as the ambient temperature of the three-phase electrical equipment. The theoretical response generation module is used to determine the heat generation power ratio of each phase based on the ratio of the square value of the current in each phase loop to the sum of the square values ​​of the currents in the three phase loops; the heat generation power ratio is subjected to first-order recursive filtering to generate the theoretical temperature rise contribution value of each phase; the smoothing coefficient of the first-order recursive filter is determined based on the thermal time constant and sampling period of the three-phase electrical equipment; the theoretical temperature rise contribution value is used to characterize the proportion of each phase's heat generation excitation in the total heat generation excitation under the influence of the conductor's heat capacity; The deviation correction module is used to compare the temperature of each phase with the ambient temperature to determine the net temperature rise of each phase, and to take the ratio of the net temperature rise of each phase to the total net temperature rise of the three phases as the actual temperature rise percentage of each phase; to compare the actual temperature rise percentage of each phase with the theoretical temperature rise contribution value to determine the original temperature rise deviation of each phase; and to subtract the predetermined inherent static temperature difference benchmark of each phase from the original temperature rise deviation of each phase to obtain the contact deviation of each phase; the contact deviation is used to characterize the abnormal temperature rise characteristics caused by changes in contact resistance. The contact deviation is processed by nonlinear dead zone treatment to obtain the corrected contact deviation; The nonlinear dead zone processing includes: setting contact deviations less than or equal to a preset noise threshold to zero, and nonlinearly amplifying contact deviations greater than the preset noise threshold. The fault determination module is used to output the corresponding electrical parameter monitoring results based on the cumulative result of the corrected contact deviation of each phase within a preset time window.

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