A method for monitoring electrical variables for operation of a ring main unit

Abstract

The application relates to the technical field of power distribution network automation, and discloses an electric variable monitoring method for the operation of a ring network cabinet, which comprises the following steps: in response to a load current change rate exceeding a preset micro-motion excitation threshold, acquiring three-phase electric variable data; calculating a reference voltage based on a circuit state equation containing a mutual inductance coupling term; constructing a rotating coordinate system with a current vector as a reference axis, performing vector decomposition on a voltage deviation vector, separating out a resistive temperature drift voltage component parallel to the reference axis, and taking a nonlinear impedance voltage component perpendicular to the reference axis as a monitoring parameter to determine a contact state; through a vector orthogonal decomposition mechanism, the application effectively decouples linear resistance drift caused by conductor temperature rise, eliminates baseline interference, can capture weak nonlinear impedance distortion characteristics caused by mechanical contact deterioration, and improves the identification sensitivity and accuracy of early latent faults of the ring network cabinet.

Description

Technical Field

[0001] This invention relates to a method for monitoring electrical variables in the operation of ring main units, belonging to the field of power distribution network automation technology. Background Technology

[0002] In current power distribution networks, ring main units (RMS) undertake the tasks of power distribution and control. The reliability of their contact connections affects the stable operation of the power supply system. To monitor the operating status of RMS units, current transformers are used to collect voltage and current signals from the circuit. Based on the root mean square value, amplitude, or phase changes of the signals, it is used to determine whether there are overcurrent, overvoltage, or short-circuit faults in the equipment. This is a commonly used technical method in current power distribution automation systems. This monitoring method based on steady-state threshold comparison has high accuracy in identifying faults such as metallic short circuits or open circuits. Existing monitoring technologies focus on discretized logic judgment of the external physical state of the equipment. For example, Chinese invention patent CN110514961B... The patent discloses a ring main unit fault monitoring and control device, which constructs a monitoring network for SF6 gas pressure and equipment fault signals through a low-pressure sensor, relay contacts, and hard-wired logic circuits. Although such solutions improve the hardware circuit and enhance the equipment's ability to sense changes in switching quantities, they are essentially post-fault response measures for faults or obvious physical anomalies. The monitoring logic relies on the physical closure of hardware nodes or hard triggering of predetermined thresholds. For the early stage of contact connection deterioration, i.e., when the electrical connection is not broken but the contact interface has already generated a weak nonlinear impedance distortion latent stage, it lacks the microscopic analysis dimension based on the waveform characteristics of electrical variables, and it is difficult to see the health of the internal conductive circuit through the surface logic on / off state.

[0003] However, in monitoring early contact defects in ring main units, existing technologies face limitations at the physical mechanism level. As power distribution equipment becomes more compact, the three-phase busbars inside the ring main unit are arranged closely, and the insulation distance between phases is reduced. When the circuit current fluctuates significantly due to load adjustments, the alternating magnetic field generated by adjacent phase conductors induces a voltage component on the current phase conductor through mutual inductance. Existing monitoring algorithms are usually based on single-phase independent models and do not include decoupling mechanisms for such three-phase electromagnetic coupling. They are prone to misjudging the linear mutual inductance voltage originating from adjacent phase load fluctuations as nonlinear distortion signals caused by abnormal contact impedance. At the same time, early contact connection deterioration is mainly manifested as weak nonlinear characteristics such as micro-arcs or tunneling effects near the current zero-crossing point. Conventional analysis methods based on full-cycle effective value calculation or Fourier transform focus on the statistics of energy throughout the time period, causing the transient characteristic signals located in the zero-crossing dead zone to be masked by the fundamental signal in the high-current segment.

[0004] Therefore, the technical problem to be solved by this invention is how to utilize existing electrical variable acquisition channels, construct signal processing logic that conforms to the laws of electromagnetic physics, accurately extract nonlinear features representing the contact state under strong power frequency background and electromagnetic coupling interference, and thus achieve accurate identification of early latent faults in ring main units. Summary of the Invention

[0005] To address the problems mentioned in the background art, the technical solution of the present invention is as follows: A method for monitoring electrical variables during the operation of a ring main unit, comprising the following steps:

[0006] When the load current change rate of the power distribution circuit exceeds the preset micro-motion excitation threshold, the instantaneous current data sequence and instantaneous voltage data sequence of the three-phase conductors are acquired simultaneously.

[0007] Based on the preset three-phase equivalent circuit parameters, the reference voltage value of each phase under ideal linear contact state is calculated using the circuit state equation containing interphase mutual inductance coupling terms.

[0008] Calculate the voltage deviation vector between the instantaneous voltage data sequence and the reference voltage value, and construct a rotating coordinate system with the instantaneous current data sequence as the reference axis;

[0009] In the rotating coordinate system, the voltage deviation vector is decomposed to separate the resistive temperature drift voltage component parallel to the reference axis, and the nonlinear impedance voltage component perpendicular to the reference axis or with phase deviation.

[0010] The nonlinear impedance voltage component is defined as a monitoring parameter characterizing the nonlinear impedance characteristics of the contact interface, and the contact state of the conductive circuit of the ring main unit is determined based on the dynamic response characteristics of the nonlinear impedance voltage component during load current changes.

[0011] The step of separating the resistive temperature drift voltage component parallel to the reference axis aims to decouple the resistive voltage drop change caused by the Joule heating effect of the conductor from the voltage deviation vector, so as to eliminate the baseline interference of linear temperature rise on contact fault determination.

[0012] Preferably, the step of calculating the reference voltage value of each phase under ideal linear contact state using the circuit state equations containing interphase mutual inductance coupling terms specifically includes: calculating the reference voltage value of phase A using the following differential relationship based on Kirchhoff's voltage law. : ,in, For phase A The reference voltage value at that moment; , and These are sampled values ​​from the instantaneous current data sequences of phases A, B, and C, respectively. The equivalent DC resistance parameter of phase A circuit; Let be the self-inductance coefficient of phase A circuit; Let be the mutual inductance coefficient between phase B and phase A; d is the mutual inductance coefficient between phase C and phase A; d / dt represents the first-order differential operation with respect to time.

[0013] Preferably, the steps for determining the equivalent circuit parameters of the three-phase circuit include: during the initial stable operation phase after the ring main unit is put into operation, collecting three-phase current data and three-phase voltage data for a preset duration; using the least squares method to solve for the parameters in the differential equation with the objective function of minimizing the magnitude of the voltage deviation vector; and converting the converged solution into a single data set. , , as well as The inherent impedance fingerprint parameters of the ring main unit are stored and used for the generation of reference voltage during subsequent online monitoring.

[0014] Preferably, the step of separating the resistive temperature drift voltage component parallel to the reference axis and the nonlinear impedance voltage component perpendicular to the reference axis or having a phase deviation includes: extracting the power frequency fundamental component of the instantaneous current data sequence and establishing the phasor direction of the power frequency fundamental component as the real axis direction; mapping the voltage deviation vector to the real axis direction to obtain the resistive temperature drift voltage component, which characterizes the linear resistance voltage drop increment caused by the conductor temperature change; and defining the remaining vector after subtracting the resistive temperature drift voltage component from the voltage deviation vector as the nonlinear impedance voltage component, which characterizes the nonlinear distortion of the contact resistance generated at the contact interface under the action of electrodynamic force.

[0015] Preferably, the steps for setting the micro-motion excitation threshold include: obtaining the rated contact pressure value and the friction coefficient of the contact surface material at the contact point of the conductive circuit of the ring main unit; calculating the minimum electrodynamic force value that can overcome the static friction of the contact surface and induce physical displacement of the wiring terminal; calculating the current change rate required to generate the minimum electrodynamic force value according to the Ampere force formula, and setting the current change rate as the micro-motion excitation threshold; the monitoring method only initiates the extraction and analysis of the nonlinear impedance voltage component when the load current change rate is greater than or equal to the micro-motion excitation threshold.

[0016] Preferably, the step of determining the contact state of the conductive circuit of the ring main unit based on the dynamic response characteristics of the nonlinear impedance voltage component includes: performing time-domain envelope analysis on the nonlinear impedance voltage component and extracting its damped oscillation characteristics; if the nonlinear impedance voltage component exhibits a damped oscillation waveform with a frequency in the range of 100Hz to 500Hz, it is determined that there is a loose mechanical connection in the conductive circuit; if the nonlinear impedance voltage component exhibits a non-sinusoidal distorted waveform that monotonically increases with the amplitude of the load current, it is determined that there is oxidation corrosion on the contact surface of the conductive circuit.

[0017] Preferably, the method further includes a parameter correction step based on the resistive temperature drift voltage component: calculating the ratio of the resistive temperature drift voltage component to the instantaneous current data sequence to obtain the temperature rise change of the loop resistance; using the temperature rise change to update the equivalent DC resistance parameter in the circuit state equation in real time, so as to eliminate the interference of linear resistance change caused by ambient temperature or load heating on the extraction of nonlinear impedance voltage component.

[0018] Preferably, after determining the contact status of the conductive circuit of the ring main unit, the method further includes: performing time integration on the effective value of the nonlinear impedance voltage component to calculate the cumulative value of contact loss energy; comparing the cumulative value of contact loss energy with a preset contact ring wear model; and generating an operation and maintenance instruction containing a suggested tightening torque value when the cumulative value of contact loss energy exceeds a preset safety threshold.

[0019] Preferably, the steps of simultaneously acquiring the instantaneous current data sequence and instantaneous voltage data sequence of the three-phase conductors include: using an electronic instrument transformer installed at the high-voltage bushing of the ring main unit to synchronously acquire the three-phase analog signals at a sampling frequency of not less than 4kHz; performing anti-aliasing filtering on the acquired analog signals and converting them from analog to digital sequences; wherein, the differential operation in the differential relationship is discretized using a five-point differential format to suppress high-frequency quantization noise.

[0020] Preferably, the method is applied to an intelligent ring main unit containing a local control unit, which is configured to: perform circuit state equation calculations and vector decomposition in real time in a local processor; and upload waveform data of the nonlinear impedance voltage component to the distribution automation master station via a communication interface only when the amplitude of the nonlinear impedance voltage component exceeds a preset alarm limit.

[0021] Compared with the prior art, the beneficial effects of the present invention are:

[0022] 1. In the monitoring of electrical variables during the operation of ring main units, a common-mode interference immunity mechanism based on spatial topology constraints is constructed to fundamentally solve the problem of false alarms caused by external power grid disturbances in compact equipment. This invention utilizes the inherent spatial topology correlation of the three-phase circuits of the ring main unit. Based on the extraction of single-phase contact residuals, instantaneous lateral comparison logic of the three-phase signals is introduced simultaneously. By calculating the common-mode components of the three-phase residual sequences in the same time sequence, it is possible to identify and remove external global interference signals originating from upstream power grid switching, lightning strikes, or systemic harmonic injections in real time. This specific purification process based on spatial coherence enables the monitoring system to respond only to real contact degradation with independent single-phase characteristics occurring within the circuit without the need to add additional shielding hardware or dedicated filters. This establishes an exclusive detection capability for intrinsic faults in the complex electromagnetic environment of the power grid.

[0023] 2. Establish a phase-gated micro-statistical system for the current zero-crossing dead zone, breaking through the masking effect of traditional full-cycle integration algorithms on early weak defects. Addressing the nonlinear characteristics of early contact degradation, which is physically manifested as micro-arc or tunneling failure near the zero-crossing point, this invention abandons the traditional method of averaging the full-cycle signal and instead constructs a local observation window that locks the current zero-crossing phase. By statistically analyzing the dispersion change of the residual signal under this specific sensitive situation, this invention constructs a micro-amplification mechanism for transient instability during the low-current setup stage. This allows the microsecond-level random jitter signal, hidden in the background of a high-current fundamental wave and characterizing micro-cracks in the insulation layer or oxide film breakdown, to be captured in a targeted manner, providing an early warning capability for identifying the degradation of the contact interface's microstructure.

[0024] 3. This invention enables electromechanical fault demodulation based on electrodynamic impact response, resolving the attribution dilemma of static resistance monitoring being unable to distinguish between mechanical loosening and chemical corrosion. It utilizes naturally occurring load steps or short-circuit impacts during power grid operation as active excitation sources. By analyzing the time-domain attenuation characteristics of the nonlinear residual envelope under strong electrodynamic forces, a logical mapping between electrical signals and mechanical structural stability is established. When fasteners in the circuit are loose, the conductor micro-motion induced by electrodynamic forces modulates the contact impedance, thereby generating a specific damped oscillation waveform in the residual signal. By identifying this dynamic response characteristic across physical fields, the system can effectively demodulate the mechanical structural state information behind the contact point even when only electrical variables are collected, providing maintenance personnel with a clear physical indication for fault attribute identification. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating the principle of vector decomposition and fault determination in the monitoring method of the present invention.

[0026] Figure 2 This is a diagram illustrating the interaction between on-site pre-calibration and online operation of the system of this invention. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0028] A method for monitoring electrical variables during the operation of a ring main unit includes the following steps:

[0029] When the load current change rate of the power distribution circuit exceeds the preset micro-motion excitation threshold, the instantaneous current data sequence and instantaneous voltage data sequence of the three-phase conductors are acquired simultaneously.

[0030] Based on the preset three-phase equivalent circuit parameters, the reference voltage value of each phase under ideal linear contact state is calculated using the circuit state equation containing interphase mutual inductance coupling terms.

[0031] Calculate the voltage deviation vector between the instantaneous voltage data sequence and the reference voltage value, and construct a rotating coordinate system with the instantaneous current data sequence as the reference axis;

[0032] In the rotating coordinate system, the voltage deviation vector is decomposed to separate the resistive temperature drift voltage component parallel to the reference axis, and the nonlinear impedance voltage component perpendicular to the reference axis or with phase deviation.

[0033] The nonlinear impedance voltage component is defined as a monitoring parameter characterizing the nonlinear impedance characteristics of the contact interface, and the contact state of the conductive circuit of the ring main unit is determined based on the dynamic response characteristics of the nonlinear impedance voltage component during load current changes.

[0034] The step of separating the resistive temperature drift voltage component parallel to the reference axis aims to decouple the resistive voltage drop change caused by the Joule heating effect of the conductor from the voltage deviation vector, so as to eliminate the baseline interference of linear temperature rise on contact fault determination.

[0035] Preferably, the step of calculating the reference voltage value of each phase under ideal linear contact state using the circuit state equation containing interphase mutual inductance coupling terms specifically includes: calculating the reference voltage value of phase A using the following differential relationship based on Kirchhoff's voltage law. : ,in, For phase A The reference voltage value at that moment; , and These are sampled values ​​from the instantaneous current data sequences of phases A, B, and C, respectively. The equivalent DC resistance parameter of phase A circuit; Let be the self-inductance coefficient of phase A circuit; Let be the mutual inductance coefficient between phase B and phase A; d is the mutual inductance coefficient between phase C and phase A; d / dt represents the first-order differential operation with respect to time.

[0036] Preferably, the steps for determining the equivalent circuit parameters of the three-phase circuit include: during the initial stable operation phase after the ring main unit is put into operation, collecting three-phase current data and three-phase voltage data for a preset duration; using the least squares method to solve for the parameters in the differential equation with the objective function of minimizing the magnitude of the voltage deviation vector; and converting the converged solution into a single data set. , , as well as The inherent impedance fingerprint parameters of the ring main unit are stored and used for the generation of reference voltage during subsequent online monitoring.

[0037] Preferably, the step of separating the resistive temperature drift voltage component parallel to the reference axis and the nonlinear impedance voltage component perpendicular to the reference axis or having a phase deviation includes: extracting the power frequency fundamental component of the instantaneous current data sequence and establishing the phasor direction of the power frequency fundamental component as the real axis direction; mapping the voltage deviation vector to the real axis direction to obtain the resistive temperature drift voltage component, which characterizes the linear resistance voltage drop increment caused by the conductor temperature change; and defining the remaining vector after subtracting the resistive temperature drift voltage component from the voltage deviation vector as the nonlinear impedance voltage component, which characterizes the nonlinear distortion of the contact resistance generated at the contact interface under the action of electrodynamic force.

[0038] Preferably, the steps for setting the micro-motion excitation threshold include: obtaining the rated contact pressure value and the friction coefficient of the contact surface material at the contact point of the conductive circuit of the ring main unit; calculating the minimum electrodynamic force value that can overcome the static friction of the contact surface and induce physical displacement of the wiring terminal; calculating the current change rate required to generate the minimum electrodynamic force value according to the Ampere force formula, and setting the current change rate as the micro-motion excitation threshold; the monitoring method only initiates the extraction and analysis of the nonlinear impedance voltage component when the load current change rate is greater than or equal to the micro-motion excitation threshold.

[0039] Preferably, the step of determining the contact state of the conductive circuit of the ring main unit based on the dynamic response characteristics of the nonlinear impedance voltage component includes: performing time-domain envelope analysis on the nonlinear impedance voltage component and extracting its damped oscillation characteristics; if the nonlinear impedance voltage component exhibits a damped oscillation waveform with a frequency in the range of 100Hz to 500Hz, it is determined that there is a loose mechanical connection in the conductive circuit; if the nonlinear impedance voltage component exhibits a non-sinusoidal distorted waveform that monotonically increases with the amplitude of the load current, it is determined that there is oxidation corrosion on the contact surface of the conductive circuit.

[0040] Preferably, the method further includes a parameter correction step based on the resistive temperature drift voltage component: calculating the ratio of the resistive temperature drift voltage component to the instantaneous current data sequence to obtain the temperature rise change of the loop resistance; using the temperature rise change to update the equivalent DC resistance parameter in the circuit state equation in real time, so as to eliminate the interference of linear resistance change caused by ambient temperature or load heating on the extraction of nonlinear impedance voltage component.

[0041] Preferably, after determining the contact status of the conductive circuit of the ring main unit, the method further includes: performing time integration on the effective value of the nonlinear impedance voltage component to calculate the cumulative value of contact loss energy; comparing the cumulative value of contact loss energy with a preset contact ring wear model; and generating an operation and maintenance instruction containing a suggested tightening torque value when the cumulative value of contact loss energy exceeds a preset safety threshold.

[0042] Preferably, the steps of simultaneously acquiring the instantaneous current data sequence and instantaneous voltage data sequence of the three-phase conductors include: using an electronic instrument transformer installed at the high-voltage bushing of the ring main unit to synchronously acquire the three-phase analog signals at a sampling frequency of not less than 4kHz; performing anti-aliasing filtering on the acquired analog signals and converting them from analog to digital sequences; wherein, the differential operation in the differential relationship is discretized using a five-point differential format to suppress high-frequency quantization noise.

[0043] Preferably, the method is applied to an intelligent ring main unit containing a local control unit, which is configured to: perform circuit state equation calculations and vector decomposition in real time in a local processor; and upload waveform data of the nonlinear impedance voltage component to the distribution automation master station via a communication interface only when the amplitude of the nonlinear impedance voltage component exceeds a preset alarm limit.

[0044] Example 1: In the operation scenario of a compact 10kV ring main unit supplying power to heavy industrial loads, the physical spacing of the three-phase busbar conductors inside the cabinet is close to the limit distance of phase-to-phase insulation. The distribution circuit needs to frequently withstand transient load current impacts caused by the starting or switching of downstream high-power motors. Under this condition, the monitoring system monitors the load current change rate of the distribution circuit in real time. When it exceeds the fretting excitation threshold determined based on the rated contact pressure and material friction coefficient of the contact point, the system starts the data acquisition process, simultaneously acquiring the instantaneous current data sequence and instantaneous voltage data sequence of the three-phase conductors. In response to the strong magnetic coupling interference between the high-density conductors, the system calculates the ideal linear reference voltage value of phase A at the current moment based on the preset circuit state equation. The calculation logic follows the differential relation: ,in, , and The three-phase instantaneous current values ​​are collected synchronously. , , and To obtain the inherent impedance fingerprint parameters, including the mutual inductance coefficient, through least squares regression during the initial stable operation phase of the equipment, this step involves calculating and subtracting... and This eliminates the linear mutual inductance voltage component generated on the A-phase conductor by the drastic fluctuations in adjacent-phase current.

[0045] The system calculates the voltage deviation vector between the instantaneous voltage data sequence and the reference voltage value, and constructs a rotating coordinate system with the instantaneous current data sequence as the reference axis. Vector orthogonal decomposition is performed on this voltage deviation vector. The vector decomposition digital signal processing flow is as follows: The system applies a Hanning window to the synchronously sampled instantaneous current data sequence and the calculated voltage deviation time-domain sequence to suppress spectral leakage. The processor uses a discrete Fourier transform algorithm to extract the amplitude and phase angle of the fundamental components of both to construct a rotating phasor space. The specific construction logic is as follows: The processor internally allocates a ring buffer with a length of 80 sampling points to store the instantaneous current data in real time at a sampling frequency of 4kHz; it reads the current sample value at the current time t as the α-axis component, and reads back 20 sampling points (i.e., 5ms) from the buffer. Historical data from a quarter-cycle of the 50Hz power frequency is used as a virtual β-axis orthogonal component. These two components are used to synthesize the current rotating current vector. The real-time angle of the fundamental phasor of this instantaneous current is used as the real axis direction d-axis of the rotating coordinate system. The fundamental phasor of the voltage deviation is projected onto the coordinate system. The projected d-axis component is directly read as the resistive temperature drift voltage component. The projected imaginary q-axis component and the high-order harmonic residuals are used to synthesize the nonlinear impedance voltage component. The extraction of the fundamental component uses a sliding window Discrete Fourier Transform (SDFT) algorithm, with the calculation window length locked at 40ms (i.e., 2 power frequency cycles), and each sliding step size is 5ms. Simultaneously, the differential operation in the aforementioned state equation uses a five-point central difference scheme. The specific discretization calculation formula is configured as follows: Here, h is set to 0.25ms (corresponding to a 4kHz sampling interval). This differential coefficient configuration effectively maintains a linear phase response within the passband and attenuates high-frequency quantization noise above 2kHz. This logic ensures that the coordinate system remains locked to the fundamental current phasor under minor fluctuations in the grid frequency, achieving precise separation of the temperature drift component. During the decomposition process, the system separates a resistive temperature drift voltage component parallel to the reference axis. This component reflects the linear resistance drift caused by Joule heating of the conductor due to large current surges. This component is used to correct the state equation in real time. The system maintains the zero-point stability of the reference model by extracting the nonlinear impedance voltage component perpendicular to the reference axis. After eliminating mutual inductance crosstalk and resistance temperature drift, it exhibits a damped oscillation waveform with a frequency range of 100Hz to 500Hz. Based on the oscillation characteristics of this specific frequency band, the system determines that the contact point of the conductive circuit has undergone mechanical displacement under the action of electrodynamic force and outputs a status monitoring signal characterizing the loosening of the mechanical connection. This enables the qualitative identification of early mechanical contact faults in a complex environment of strong electromagnetic coupling and thermal effects.

[0046] Example 2: In a high-voltage electrical laboratory environment equipped with a programmable high-current generator and a three-phase busbar simulation bench, a controlled test platform was constructed to verify the effectiveness of the ring main unit electrical variable monitoring method. A copper busbar with a cross-sectional area of ​​10 cm² was used to construct the three-phase conductive circuit. A loose contact point with insufficient torque was pre-set at the connection of the A-phase conductor to simulate early contact degradation faults. To reproduce the complexity of the electromagnetic environment in a real industrial setting, Gaussian white noise with a signal-to-noise ratio of 20 dB was actively injected into the three-phase current signal during the experiment, and 3rd and 5th order background noise with a total harmonic distortion (THD) of 5% was superimposed. Harmonics were used to construct a realistic noise interference scenario for engineering purposes. The data acquisition unit was configured as an industrial-grade data acquisition card with 16-bit resolution and a synchronous sampling rate of 20kHz. The sampling rate parameter was set according to the Nyquist sampling theorem to ensure that the nonlinear impedance oscillation characteristics with a frequency upper limit of 500Hz could be captured without distortion, while reserving sufficient oversampling gain space for subsequent digital filtering algorithms. Before the test started, the system parameter identification procedure was executed. Under steady-state current conditions, the circuit state equation containing mutual inductance coupling terms was solved using the least squares regression method to calibrate the inherent impedance fingerprint parameters of the test bench. It is determined to be 0.0012 ohms. The value was determined to be 0.0054 millihenries. and The parameters were determined to be 0.0021 millihenries and 0.0018 millihenries, respectively. The certainty of this calibration process lies in the fact that, through the accumulation of steady-state data for no less than 5 power frequency cycles, the parameter convergence error is controlled within 0.1%, thus establishing a precise linear reference for subsequent dynamic monitoring. The load impact of controlling the output of the high current source to jump from 200A to 600A is simulated. This process simulates the transient impact when a high-power motor starts. At this time, the monitoring system detects that the load current change rate reaches 15A / ms, which exceeds the preset micro-motion excitation threshold of 10A / ms, thereby triggering the high-frequency synchronous acquisition and analysis process.

[0047] As a control group, the existing steady-state effective value monitoring method was used. The system simultaneously calculated the change in the effective voltage (RMS) across the contact point of phase A and the temperature rise data of the contact point. The test data showed that within 100ms after the current step, due to thermal inertia, the temperature rise of the contact point was only 0.2℃, which could not trigger an over-temperature alarm. At the same time, the relative change in the effective voltage of phase A was only 0.8%, which was completely submerged in the background fluctuation of the grid voltage of 2.0% and the harmonic interference of 5%, causing the existing technology to be unable to identify the contact fault at this time, and the judgment result was normal. The sample group of this invention started the nonlinear feature extraction process based on vector orthogonal decomposition. The system based on the real-time acquisition , , And the preset fingerprint parameters, substituted into the formula: The system calculates a linear reference voltage, then calculates the deviation vector between the actual observed voltage and this reference voltage, and performs vector decomposition in a rotating coordinate system with the current vector as the reference axis. In the first scene's data presentation, the separated resistive temperature drift voltage component parallel to the reference axis exhibits a monotonically increasing linear trend, with its amplitude slowly climbing from an initial 0mV to 5.2mV. This data characteristic highly matches the physical law of the linear increase in conductor resistivity caused by the Joule heating effect. Based on this, the system... The parameters were dynamically corrected, effectively avoiding baseline drift caused by temperature drift. In the core performance of the second act, the isolated nonlinear impedance voltage component perpendicular to the reference axis revealed hidden fault characteristics. Data showed that after removing linear mutual inductance and resistance voltage drop, this component exhibited a damped oscillation waveform with a frequency concentrated in the 120Hz to 350Hz range, with a peak amplitude of 185mV, higher than the background noise floor of 15mV. The emergence of this key intermediate data confirmed that under the action of electrodynamic repulsion, the loose contact point underwent micrometer-level mechanical displacement and nonlinear jump in contact resistance. In the value loop of the third act, the system calculated the energy integral value of this nonlinear impedance voltage component, and the results... The system detected that the fault exceeded the preset fault judgment threshold and then output a fault warning signal for loose mechanical connection. Further gradient pressure test showed that when the pre-tightening torque of the contact point was gradually increased until it returned to the normal standard value, the peak amplitude of the above nonlinear impedance voltage component showed a nonlinear decreasing trend from 185mV to 12mV (close to the noise level). Moreover, this decreasing trend showed a performance inflection point when the pre-tightening torque reached 80% of the rated value. This proved that the nonlinear impedance voltage component, as a fault characteristic parameter, has high sensitivity and specificity for mechanical contact state. It solved the industry problem that existing technology cannot effectively identify early micro-motion contact faults under strong interference and thermal effect masking.

[0048] Example 3: In the long-term stability assessment scenario of a ring main unit online monitoring system, this example constructs a closed-loop adaptive parameter calibration procedure to address the parameter drift problem. Through a dynamic benchmark update mechanism based on statistical principles, it solves the problem of model accuracy degradation caused by aging or environmental changes after long-term operation. In the initial state definition procedure, the system defines the electrical characteristics of the ring main unit in a healthy operating state. These characteristics are a statistical set obtained through continuous monitoring under specific operating conditions, conforming to a normal distribution. The system sets a benchmark sliding window of 24 hours. Within this time window, the system continuously collects and calculates the linear impedance parameters of the three-phase conductors, i.e., resistance. , , and self-awareness , , .

[0049] During the execution phase of the process judgment quantification procedure, the system introduces drift significance testing logic. For each newly acquired impedance sample data, the system calculates its deviation from the current benchmark mean, i.e., calculates its Z-Score. If the absolute value of this score is less than the preset statistical threshold of 3.0 (corresponding to a 99.7% confidence interval), the sample is determined to be a normal random fluctuation and is included in the benchmark sliding window update queue. The benchmark mean is fine-tuned using an exponentially weighted moving average (EWMA) algorithm. This algorithm, based on the higher weight of recent data, enables the benchmark model to smoothly track the natural aging trend of equipment parameters, achieving parameter adaptation. Conversely, if the absolute value of the Z-Score of a new sample exceeds the above threshold five times consecutively, and the direction is consistent, the system determines that unnatural drift has occurred, i.e., there may be sudden physical damage. In the event of severe contact degradation, the system freezes the baseline update mechanism to prevent fault data from contaminating the baseline model and triggers the abnormal state verification process. By calling the nonlinear feature extraction algorithm, the current current and voltage signals are analyzed in depth. If the nonlinear impedance component also shows an anomaly, it is confirmed as a fault, and an alarm signal is output. If the nonlinear component is normal, it is determined to be a parameter jump caused by a sudden change in the environment. After confirming that the environmental parameters have stabilized, the system will restart the baseline initialization process. Through the implementation of the above adaptive parameter calibration procedure, this embodiment constructs a monitoring system with self-evolution capabilities. It not only eliminates the risk of inaccuracy of the static parameter model in long-term operation, but also achieves accurate differentiation between natural aging and sudden faults through the deep coupling of statistical testing and physical feature analysis, providing engineering assurance for the reliability of the system throughout its entire life cycle.

[0050] Example 4: To address the initial measurement errors that may be introduced into the actual industrial deployment of the monitoring system due to installation process deviations, sensor batch differences, or grounding impedance fluctuations, this example supplements a pre-deployment calibration procedure to ensure the measurement consistency and stability of the monitoring system under different application scenarios. Before the system is officially put into operation, standardized injection testing and bias correction steps are used to eliminate the interference of non-ideal hardware characteristics on subsequent weak nonlinear feature extraction. In the initial state definition procedure, the ring main unit is required to be under power outage maintenance or unloaded, and the three-phase busbars are ensured to be reliably grounded. At this time, the current and voltage sensors of the monitoring system are connected to the primary circuit according to the predetermined wiring scheme, and the connection tightness and insulation status of the secondary side of the sensors are checked. The system enters the zero-point drift calibration mode. Under the condition of no primary current excitation, the channel noise floor data is continuously collected for no less than 1 minute, the DC bias component and random noise variance of each channel are calculated, and the DC bias value is stored as the inherent zero-point offset of the system in non-volatile memory for real-time subtraction of subsequent data.

[0051] During the execution phase of the process judgment quantification procedure, an injection-type gain consistency verification is implemented. Using a portable current injector and voltage generator, a standard sine wave signal with precise amplitude and a frequency of 50Hz is injected into the secondary side of the current transformer and the input terminal of the voltage sensor of the monitoring system, respectively. The system synchronously acquires the standard signal and calculates the gain error and phase delay between the measured value and the injected true value. If the gain error of the channel exceeds ±0.5% or the phase error exceeds ±0.2 degrees, the system automatically adjusts the digital gain coefficient and phase compensation parameters of the channel until the error converges to the allowable range. This step not only calibrates the measurement accuracy of the sensor itself, but also eliminates the phase mismatch between channels caused by the difference in the length of the signal transmission cable, ensuring the orthogonality of the three-phase data in the vector space. After completing the above calibration, the system generates an electronic verification report containing a comparison of the errors before and after calibration and the final correction parameters, which serves as proof that the system has passed the pre-calibration and is ready for online operation.

[0052] Example 5: In the scenario of in-depth optimization and engineering solidification of the nonlinear impedance characteristic analysis algorithm for ring main units, this example constructs an adaptive calibration procedure for the fretting excitation threshold and nonlinear criterion. This solves the problem that the fretting excitation threshold and fault judgment threshold may deviate from the optimal operating point due to differences in contact material characteristics, contact surface roughness, or assembly tolerance fluctuations from different manufacturers. This ensures that the monitoring system can maintain a balance between high sensitivity and low false alarm rate in diverse equipment batches. In the initial state definition procedure, the key physical parameters of the current monitored object are obtained, including the elastic modulus E and Poisson's ratio ν of the contact material, and the root mean square value of the micro-roughness of the contact surface. By consulting the equipment's technical manual or conducting offline material testing, the data is obtained and imported into the system's calibration module as initial input. Based on the Hertzian contact model and micro-convexity contact theory in contact mechanics, the system calculates the theoretical critical force for fretting initiation. This critical force characterizes the minimum electrodynamic force required to overcome static friction and induce tangential slippage of micro-contact spots under a specific contact pressure.

[0053] During the execution phase of the process judgment quantification procedure, the system initiates a threshold optimization gradient test. A series of low-frequency pulse currents with increasing amplitude are injected into the circuit under test using a programmable current source. For example, a frequency of 5Hz is set to simulate the quasi-static process of mechanical micro-motion and avoid interference from power frequency thermal effects. At each current amplitude point, the system synchronously collects the weak voltage drop across the contact point and calculates the nonlinearity index of the dynamic impedance, defining it as the second derivative norm of the voltage-current characteristic curve near zero. When the electrodynamic force generated by the injected current gradually approaches and exceeds the actual micro-motion critical value, the microstructure of the contact interface undergoes slip reconstruction, causing a step change in the nonlinearity index. The system captures the current change rate corresponding to this change point and corrects it to the actual micro-motion excitation threshold of the current equipment. Simultaneously, the amplitude of the nonlinear impedance voltage component in this state is recorded, and its statistical distribution upper limit of three times the standard deviation is set as the fault judgment benchmark threshold for online monitoring. The 100Hz to 500Hz damped oscillation characteristic frequency band of the nonlinear impedance voltage component is measured by the field mechanical impedance. The scanning procedure determines that during the initial commissioning of the monitoring device, frequency sweep excitation or impact vibration generated by circuit breaker switching is performed to collect the mechanical response spectrum of the conductive circuit. The distribution range of the inherent mechanical resonance peak of the ring main unit bus structure is identified through spectrum analysis. The upper and lower limits of the range, such as the -3dB bandwidth covering the main resonance peak, are written into the bandpass filter parameter register of the monitoring algorithm as the frequency band for judging loose mechanical connections. The calibration eliminates the influence of inherent frequency shift caused by differences in cabinet material and bus installation length on fault identification. The micro-motion excitation threshold is set based on the material properties of the contact point and the assembly process parameters to establish a lookup table. The static friction coefficient of the contact surface and the standard normal pressure value corresponding to the bolt tightening torque are read from the pre-stored non-volatile memory. The critical value of the current change rate to overcome the maximum static friction force is calculated in reverse according to the Ampere force formula. During system operation, this threshold is dynamically corrected according to the most recent contact point temperature rise history. When the monitoring contact point temperature baseline rises, the correction coefficient table is read to reduce the material yield strength parameter and the micro-motion excitation threshold is lowered to adapt to the decreased contact stability characteristics of metal softening at high temperatures.

[0054] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for monitoring electrical variables during the operation of a ring main unit, characterized in that, Includes the following steps: When the load current change rate of the power distribution circuit exceeds the preset micro-motion excitation threshold, the instantaneous current data sequence and instantaneous voltage data sequence of the three-phase conductors are acquired simultaneously. Based on the preset three-phase equivalent circuit parameters, the reference voltage value of each phase under ideal linear contact state is calculated using the circuit state equation containing interphase mutual inductance coupling terms. Calculate the voltage deviation vector between the instantaneous voltage data sequence and the reference voltage value, and construct a rotating coordinate system with the instantaneous current data sequence as the reference axis; In the rotating coordinate system, the voltage deviation vector is decomposed to separate the resistive temperature drift voltage component parallel to the reference axis, and the nonlinear impedance voltage component perpendicular to the reference axis or with phase deviation. The nonlinear impedance voltage component is defined as a monitoring parameter characterizing the nonlinear impedance characteristics of the contact interface, and the contact state of the conductive circuit of the ring main unit is determined based on the dynamic response characteristics of the nonlinear impedance voltage component during load current changes. The step of separating the resistive temperature drift voltage component parallel to the reference axis aims to decouple the resistive voltage drop change caused by the Joule heating effect of the conductor from the voltage deviation vector. The steps for calculating the reference voltage values ​​of each phase under ideal linear contact conditions using circuit state equations that include interphase mutual inductance coupling terms specifically include: calculating the reference voltage value of phase A using the following differential relationship based on Kirchhoff's voltage law. : ,in, For phase A The reference voltage value at that moment; , and These are sampled values ​​from the instantaneous current data sequences of phases A, B, and C, respectively. The equivalent DC resistance parameter of phase A circuit; Let be the self-inductance coefficient of phase A circuit; Let be the mutual inductance coefficient between phase B and phase A; d is the mutual inductance coefficient between phase C and phase A; d / dt represents the first-order differential operation with respect to time. The steps for determining the contact status of the conductive circuit of a ring main unit based on the dynamic response characteristics of the nonlinear impedance voltage component include: performing time-domain envelope analysis on the nonlinear impedance voltage component and extracting its damped oscillation characteristics; if the nonlinear impedance voltage component exhibits a damped oscillation waveform with a frequency range of 100Hz to 500Hz, it is determined that there is a loose mechanical connection in the conductive circuit; if the nonlinear impedance voltage component exhibits a non-sinusoidal distorted waveform that monotonically increases with the amplitude of the load current, it is determined that there is oxidation corrosion on the contact surface of the conductive circuit.

2. The method for monitoring electrical variables in the operation of a ring main unit according to claim 1, characterized in that, The steps for determining the equivalent circuit parameters of the three-phase circuit include: during the initial stable operation phase after the ring main unit is put into operation, collecting three-phase current and three-phase voltage data for a preset duration; using the least squares method to solve for the parameters in the differential equation with the objective function of minimizing the magnitude of the voltage deviation vector; and converting the converged solution into a single data set. , , as well as The inherent impedance fingerprint parameters of the ring main unit are stored and used for the generation of reference voltage during subsequent online monitoring.

3. The method for monitoring electrical variables in the operation of a ring main unit according to claim 1, characterized in that, The steps of separating the resistive temperature drift voltage component parallel to the reference axis and the nonlinear impedance voltage component perpendicular to the reference axis or having a phase deviation include: extracting the power frequency fundamental component of the instantaneous current data sequence and establishing the phasor direction of the power frequency fundamental component as the real axis direction; mapping the voltage deviation vector to this real axis direction to obtain the resistive temperature drift voltage component, which characterizes the linear resistance voltage drop increment caused by the conductor temperature change; and defining the remaining vector after subtracting the resistive temperature drift voltage component from the voltage deviation vector as the nonlinear impedance voltage component, which characterizes the nonlinear distortion of the contact resistance generated at the contact interface under the action of electrodynamics.

4. The method for monitoring electrical variables in the operation of a ring main unit according to claim 1, characterized in that, The steps for setting the fretting excitation threshold include: obtaining the rated contact pressure value and the friction coefficient of the contact surface material at the contact point of the conductive circuit of the ring main unit; calculating the minimum electrodynamic force value that can overcome the static friction of the contact surface and induce physical displacement of the wiring terminal; calculating the current change rate required to generate the minimum electrodynamic force value according to the Ampere force formula, and setting this current change rate as the fretting excitation threshold; the monitoring method only initiates the extraction and analysis of the nonlinear impedance voltage component when the load current change rate is greater than or equal to the fretting excitation threshold.

5. The method for monitoring electrical variables in the operation of a ring main unit according to claim 1, characterized in that, The method also includes a parameter correction step based on the resistive temperature drift voltage component: calculating the ratio of the resistive temperature drift voltage component to the instantaneous current data sequence to obtain the temperature rise change of the loop resistance; using the temperature rise change to update the equivalent DC resistance parameter in the circuit state equation in real time to eliminate the interference of linear resistance changes caused by ambient temperature or load heating on the extraction of nonlinear impedance voltage components.

6. The method for monitoring electrical variables in the operation of a ring main unit according to claim 1, characterized in that, After determining the contact status of the conductive circuit of the ring main unit, the process also includes: integrating the effective value of the nonlinear impedance voltage component over time to calculate the cumulative value of contact loss energy; comparing the cumulative value of contact loss energy with a preset contact ring wear model; and generating a maintenance instruction containing a suggested tightening torque value when the cumulative value of contact loss energy exceeds a preset safety threshold.

7. The method for monitoring electrical variables in the operation of a ring main unit according to claim 1, characterized in that, The steps for synchronously acquiring the instantaneous current data sequence and instantaneous voltage data sequence of three-phase conductors include: using an electronic instrument transformer installed at the high-voltage bushing of the ring main unit to synchronously acquire three-phase analog signals at a sampling frequency of not less than 4kHz; performing anti-aliasing filtering on the acquired analog signals and converting them from analog to digital sequences; wherein, the differential operation in the differential relationship is discretized using a five-point differential format.

8. The method for monitoring electrical variables in the operation of a ring main unit according to claim 1, characterized in that, The method is applied to intelligent ring main units containing local control units, which are configured to: perform circuit state equation calculations and vector decomposition in real time in a local processor; and upload waveform data of the nonlinear impedance voltage component to the distribution automation master station via a communication interface only when the amplitude of the nonlinear impedance voltage component exceeds a preset alarm limit.

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