A multi-band discharge signal screening and identifying system for a metal-enclosed apparatus

Abstract

The present application relates to the technical fields of electrical equipment insulation performance detection and partial discharge detection, and discloses a kind of metal-enclosed equipment multi-band discharge signal screening identification system.The system obtains the multi-band discharge signal of metal-enclosed distribution switchgear under operating condition, based on power supply synchronous reference attached frequency phase label, separate generation power frequency phase period pulse signal and high frequency burst characteristic signal;According to phase shift, generate target phase window and extract target partial discharge pulse, count hit frequency, unit time pulse density and phase concentration to generate partial discharge density level;When meeting active deterioration condition, switch conventional trigger threshold to sensitive trigger threshold, attenuate compensation, delay calibration and complete time sequence interception are carried out to high frequency burst signal, and fault evolution record is generated based on timestamp alignment.The present application can improve the accuracy of metal-enclosed distribution switchgear partial discharge signal screening identification and the continuity of discharge evolution record.

Description

Technical Field

[0001] This invention relates to the field of electrical equipment insulation performance testing and partial discharge detection technology, and in particular to a multi-frequency discharge signal screening and identification system for metal-enclosed equipment. Background Technology

[0002] Metal-enclosed switchgear is widely used in power distribution systems, and its internal insulation condition directly affects power supply safety. After long-term operation, the insulation components may experience partial discharge due to electric field stress, moisture, localized contamination, or mechanical defects, which can generate stronger high-frequency burst discharge signals as deterioration deepens. Because the equipment uses a metal-enclosed structure, the discharge signal is easily affected by shielding attenuation, reflection, and phase shift during propagation.

[0003] Existing partial discharge detection methods typically employ transient ground voltage, ultra-high frequency (UHF), and high-frequency current detection. These methods collect transient ground voltage signals from the outer surface of the cabinet, UHF electromagnetic wave signals, and high-frequency pulse current signals from the grounding loop, respectively, and combine these with power synchronization signals to generate phase spectra or pulse statistics. Some detection systems can also determine the type and severity of discharge in switchgear through threshold extraction, spectra display, data storage, and offline analysis.

[0004] However, existing methods mostly focus on single-band detection results or fixed threshold triggering, making it difficult to unify the phase correlation between the power frequency phase periodic pulse signal and the high-frequency burst characteristics when the metal enclosure structure causes signal attenuation and phase shift. When the local discharge activity evolves from weak pulses to high-frequency burst discharge, it is easy to encounter problems such as early pulse missed detection, high-frequency burst signal missed capture or false triggering, and the inability to continuously track the discharge evolution process.

[0005] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] This invention provides a multi-band discharge signal screening and identification system for metal-enclosed equipment, which solves the problems of existing partial discharge detection methods in the insulation status detection of metal-enclosed power distribution switchgear, which are difficult to perform unified phase correlation on multi-band discharge signals affected by shielding attenuation and phase shift, and are difficult to capture high-frequency burst discharges and continuously track the discharge evolution process based on the degree of partial discharge activity.

[0007] The technical solution of this invention is as follows: a multi-band discharge signal screening and identification system for metal-enclosed equipment, applied to the insulation status detection of metal-enclosed power distribution switchgear in intelligent power distribution systems, comprising the following modules: a multi-band partial discharge acquisition module, used to acquire multi-band discharge signals generated by the metal-enclosed power distribution switchgear during operation, add power frequency phase markers to the multi-band discharge signals based on power synchronization reference, and separate and generate power frequency phase periodic pulse signals and high-frequency burst characteristic signals according to the detection frequency band; a phase window pulse extraction module, used to generate a target phase window based on the phase offset corresponding to the power frequency phase periodic pulse signal, and extract target partial discharge pulses characterizing insulation defect activity within the target phase window; and a partial discharge density evaluation module, used to statistically analyze the target partial discharge pulses within the target phase window. The system generates a partial discharge density level based on the number of hits, pulse density per unit time, and phase concentration. A high-frequency trigger sensitization module switches the conventional trigger threshold for the high-frequency burst characteristic signal to a sensitive trigger threshold when the partial discharge density level meets a preset active degradation condition, and generates a high-frequency discharge capture state when the high-frequency burst characteristic signal meets the target trigger condition. A high-frequency calibration and interception module performs attenuation compensation and delay calibration on the high-frequency burst characteristic signal in the high-frequency discharge capture state to obtain a calibrated high-frequency burst signal and intercepts a complete time series containing transition signals. A homogeneous evolution identification module performs time-series alignment based on the first timestamp of the target partial discharge pulse and the second timestamp of the complete time series, and generates a fault evolution record based on the aligned time-series discharge sequence.

[0008] Preferably, the multi-band partial discharge acquisition module is further configured to: connect to the transient ground voltage detection unit, the ultra-high frequency detection unit, the high frequency current detection unit, and the power synchronization unit respectively; acquire the transient ground voltage signal on the outer surface of the metal-enclosed power distribution switchgear cabinet, the ultra-high frequency electromagnetic wave signal generated by partial discharge, and the high frequency pulse current signal in the grounding circuit; and, based on the power frequency phase reference provided by the power synchronization unit, enable the discharge signals of different detection frequency bands to have comparable phase marks.

[0009] Preferably, the multi-band partial discharge acquisition module is further configured to: perform bandpass separation on the multi-band discharge signal according to the transient ground voltage detection channel, the ultra-high frequency detection channel, and the high frequency current detection channel; filter out non-target frequency band interference and respectively form a power frequency phase periodic pulse signal, a high frequency electromagnetic burst signal, and a high frequency current burst signal; output the power frequency phase periodic pulse signal to the phase window pulse extraction module, and output the high frequency electromagnetic burst signal and the high frequency current burst signal as the high frequency burst characteristic signal to the high frequency trigger sensitization module.

[0010] Preferably, the phase window pulse extraction module is further configured to: acquire the enclosed cavity structure layer data and shielding layer material data of the metal-enclosed power distribution switchgear; determine the high-frequency attenuation value and phase offset based on the enclosed cavity structure layer data, the shielding layer material data, and field calibration data; compensate the phase offset to obtain a target offset when the high-frequency attenuation value meets a preset compensation condition; set the start and end times of the target phase window based on the target offset, and extract candidate partial discharge pulses through the target phase window.

[0011] Preferably, the phase window pulse extraction module and the partial discharge density evaluation module are further configured to: classify and identify the candidate partial discharge pulses according to their pulse amplitude, phase position, and recurrence status to obtain the target partial discharge pulse; encapsulate the target partial discharge pulse into a pulse object, the pulse object including at least a pulse identifier, amplitude, phase position, hit time, detection frequency band identifier, and confidence level; statistically analyze the hit count, the pulse density per unit time, and the phase concentration based on the pulse object, and generate the partial discharge density level when the hit count and the phase concentration meet the set conditions.

[0012] Preferably, the high-frequency trigger sensitization module is further configured to: extract the amplitude change, phase feature, and detection band identifier of the high-frequency burst characteristic signal; generate a transient mapping value based on the amplitude change, the phase feature, the detection band identifier, and the partial discharge density level; determine the sensitive trigger threshold as the target trigger threshold when the partial discharge density level meets the preset active degradation condition; and generate a high-frequency burst discharge capture state when the transient mapping value is greater than the target trigger threshold, and use the high-frequency burst discharge capture state as the high-frequency discharge capture state.

[0013] Preferably, the high-frequency trigger sensitization module is further configured to: normalize the amplitude mutation amount, the phase feature, the detection frequency band identifier, and the partial discharge density level; record the normalized amplitude mutation amount as the amplitude mutation normalization value, record the normalized phase feature as the phase matching normalization value, convert the detection frequency band identifier into a detection frequency band weight value, and convert the partial discharge density level into a partial discharge density level value; perform a weighted summation of the amplitude mutation normalization value, the phase matching normalization value, the detection frequency band weight value, and the partial discharge density level value according to a preset weight, and limit the weighted summation result to 0 to 1 to generate the transient mapping value; when the partial discharge density level does not meet the preset active degradation condition, maintain the conventional trigger threshold and prevent the high-frequency burst feature signal from directly entering the sensitive trigger state.

[0014] Preferably, the high-frequency calibration and interception module is further configured to: perform frequency domain transformation on the high-frequency burst characteristic signal under the high-frequency discharge capture state, extract frequency band values, amplitude sequences and phase angles to form a target burst matrix; calculate the attenuation error vector and phase offset gradient based on the target burst matrix; construct joint calibration parameters based on the attenuation error vector and the phase offset gradient; and perform inverse compensation on the target burst matrix based on the joint calibration parameters to obtain the calibrated high-frequency burst signal.

[0015] Preferably, the high-frequency calibration interception module is further configured to: calculate the attenuation error vector and the phase offset gradient using a state observation filtering model; the state observation filtering model is a Kalman filter model; the joint calibration parameters include a compensation value corresponding to the signal transmission attenuation within the enclosed cavity of the metal-enclosed power distribution switchgear and a delay amount corresponding to the propagation delay; when the calibrated high-frequency burst signal meets the preset amplitude change amount and duration conditions, intercept the historical signal before triggering, the signal at the triggering time, and the continued attenuation signal after triggering to generate the complete time series.

[0016] Preferably, the homogeneous evolution identification module is further configured to: calculate the initial time offset between the first timestamp and the second timestamp; translate the target partial discharge pulse according to the initial time offset to obtain a candidate matching pulse; convert the candidate matching pulse and the complete time series into normalized feature sequences with the same fields, and calculate the sequence distance value between the two normalized feature sequences using a dynamic time warping algorithm; when the sequence distance value is less than a preset distance threshold, determine the candidate matching pulse and the complete time series as homogeneous discharge evolution events; perform clustering on the time-series discharge sequences corresponding to the homogeneous discharge evolution events, and extract boundary data when the distance between the cluster centers meets a preset boundary extraction condition to generate the fault evolution record; associate and save the fault evolution record with distribution station information, distribution switch equipment number, measurement point information, trigger time, detection frequency band identifier, partial discharge density level, and high-frequency discharge capture status for use in the intelligent distribution system for distribution switch equipment status inspection and insulation status assessment.

[0017] The beneficial effects of this invention are as follows: This invention integrates the transient ground voltage detection unit, ultra-high frequency detection unit, high frequency current detection unit, and power synchronization unit into the same discharge signal processing chain through a multi-band partial discharge acquisition module, enabling discharge signals from different detection frequency bands to have comparable phase markers; the phase window pulse extraction module determines the target phase window based on the closed cavity structure layer data and shielding layer material data, allowing candidate partial discharge pulses to be screened under the condition of phase offset compensation; the partial discharge density evaluation module generates partial discharge density levels, providing a basis for high-frequency trigger sensitization based on the degree of insulation defect activity; the high-frequency trigger sensitization module switches the sensitive trigger threshold when the preset active degradation condition is met, and the high-frequency calibration interception module and the homogeneous evolution identification module complete attenuation compensation, delay calibration, timing alignment, and fault evolution record saving, thereby improving the problems of existing detection methods that are difficult to correlate multi-band signals and capture degradation transition processes. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall module and processing link of a multi-band discharge signal screening and identification system for metal-enclosed equipment provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of multi-band discharge signal acquisition, frequency band separation, and power frequency phase marking provided in one embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the generation of a target phase window, extraction of a target partial discharge pulse, and evaluation of partial discharge density provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of high-frequency triggering sensitization, attenuation compensation, delay calibration, and complete time series extraction provided in one embodiment of the present invention; Figure 5 This is a schematic diagram of homogeneous evolution identification and fault evolution record generation provided in one embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention; that is, the described embodiments are merely some embodiments of the invention, and not all embodiments. The components of the embodiments of the invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0021] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0022] In existing technologies, partial discharge detection typically employs transient ground voltage, ultra-high frequency (UHF), and high-frequency current detection methods. These methods collect transient ground voltage signals from the outer surface of the cabinet, UHF electromagnetic wave signals, and high-frequency pulse current signals from the grounding loop, respectively, and combine these with power synchronization signals to generate phase spectra or pulse statistics. Some detection systems can also determine the discharge type and severity of switchgear through threshold interception, spectra display, data storage, and offline analysis. However, existing methods often focus on single-frequency band detection results or fixed threshold triggering, making it difficult to establish a unified phase correlation between the power frequency phase periodic pulse signal and high-frequency burst characteristics, especially when the metal enclosure structure causes signal attenuation and phase shift. Furthermore, when partial discharge activity evolves from weak pulses to high-frequency burst discharges, problems such as missed early pulse detection, missed or false triggering of high-frequency burst signals, and the inability to continuously track the discharge evolution process can easily occur.

[0023] To address this, the present invention provides a multi-band discharge signal screening and identification system for metal-enclosed equipment, thereby solving the aforementioned technical problems.

[0024] Example 1:

[0025] like Figure 1As shown, this embodiment of the invention provides a multi-band discharge signal screening and identification system for metal-enclosed equipment, which can operate in a metal-enclosed power distribution switchgear insulation status detection terminal, a station-end partial discharge detection data processing environment, or a field partial discharge detection service environment. The system receives detection objects as metal-enclosed power distribution switchgear, which can be switch cabinets, ring main units, circuit breaker cabinets, and other power distribution switch control equipment with metal-enclosed cavities.

[0026] This invention provides a multi-band discharge signal screening and identification system for metal-enclosed equipment, which is applied to the insulation status detection of metal-enclosed power distribution switchgear in intelligent power distribution systems. The system includes the following modules: a multi-band partial discharge acquisition module, a phase window pulse extraction module, a partial discharge density evaluation module, a high-frequency trigger sensitization module, a high-frequency calibration interception module, and a homogeneous evolution identification module.

[0027] The multi-band partial discharge acquisition module is used to acquire the multi-band discharge signals generated by the metal-enclosed power distribution switchgear in operation, add power frequency phase markers to the multi-band discharge signals based on the power synchronization reference, and separate and generate power frequency phase periodic pulse signals and high-frequency burst characteristic signals according to the detection frequency band.

[0028] like Figure 2 As shown, specifically, the multi-band partial discharge acquisition module can be connected to a transient ground voltage detection unit, an ultra-high frequency (UHF) detection unit, a high-frequency current detection unit, and a power synchronization unit. The transient ground voltage detection unit acquires transient ground voltage signals from the outer surface of the metal-enclosed power distribution switchgear cabinet; the UHF detection unit acquires UHF electromagnetic wave signals generated by partial discharge; the high-frequency current detection unit acquires high-frequency pulse current signals in the grounding loop; and the power synchronization unit provides a unified power frequency phase reference for the discharge signals of the different detection frequency bands. The power synchronization reference can originate from the field power synchronization signal or the internal synchronization signal. The field power frequency period can be measured in real time by the power synchronization unit (for example, a field power frequency period of 20ms corresponds to a 50Hz power frequency, derived from the power synchronization unit's detection of the field power grid frequency; the power synchronization adaptation frequency can be from 20Hz to 300Hz, derived from the power synchronizer configuration range).

[0029] The phase window pulse extraction module is used to generate a target phase window based on the phase offset corresponding to the power frequency phase periodic pulse signal, and extract the target partial discharge pulse that characterizes the activity of insulation defects within the target phase window.

[0030] like Figure 3As shown, the phase window pulse extraction module determines the high-frequency attenuation value and phase offset based on the enclosed cavity structure layer data, shielding layer material data, and field calibration data. It then generates a target phase window based on the target offset to extract the target partial discharge pulse and provide it to the partial discharge density evaluation module for density evaluation. Specifically, after receiving the power frequency phase periodic pulse signal, the phase window pulse extraction module determines the high-frequency attenuation value and phase offset based on the enclosed cavity structure layer data, shielding layer material data, and field calibration data of the metal-enclosed switchgear. The high-frequency attenuation value can be statistically determined by the difference between the input amplitude and received amplitude of the calibration pulse during field trial operation of the same type of metal-enclosed switchgear (e.g., a high-frequency attenuation value of 8dB). The phase offset is then used to correct the start and end times of the target phase window. The target phase window is used to define the phase range requiring focused screening within one power frequency cycle (e.g., the target phase window width is 40°, derived from historical PRPD / PRPS spectrum statistics and field trial operation results of the same type of metal-enclosed switchgear). The power frequency phase periodic pulse signal that is within the target phase window and meets the basic pulse interception conditions is used as a candidate partial discharge pulse, and is further determined as the target partial discharge pulse based on the pulse amplitude, phase position and recurrence state.

[0031] The partial discharge density evaluation module is used to count the number of hits, pulse density per unit time, and phase concentration of the target partial discharge pulse within the target phase window, and generate a partial discharge density level.

[0032] Specifically, after receiving the target partial discharge pulses, the partial discharge density evaluation module encapsulates each target partial discharge pulse into a pulse object and counts the number of hits, pulse density per unit time, and phase concentration within a set observation period. The number of hits represents the cumulative number of actual partial discharge pulses appearing within the target phase window, the pulse density per unit time represents the frequency of occurrence of target partial discharge pulses per unit time, and the phase concentration represents whether target partial discharge pulses are concentrated in the same phase region. The partial discharge density level can be low-density, medium-density, and high-density, where the level boundaries can be derived from historical inspection records of the same model of equipment, on-site background noise test results, and manually verified sample statistics (for example, a medium-density level corresponds to a target partial discharge pulse hit count of no less than 30 times, a pulse density of no less than 0.50 times / s, and a phase concentration of no less than 0.70 times / s within a 60-second observation period).

[0033] The high-frequency trigger sensitization module is used to switch the conventional trigger threshold for the high-frequency burst characteristic signal to a sensitive trigger threshold when the partial discharge density level meets the preset active degradation condition, and to generate a high-frequency discharge capture state when the high-frequency burst characteristic signal meets the target trigger condition.

[0034] like Figure 4 As shown, the high-frequency triggering sensitization module generates a transient mapping value based on the high-frequency burst characteristic signal and the partial discharge density level, and determines the target trigger threshold when a preset active degradation condition is met. After generating the high-frequency discharge capture state, the high-frequency calibration and interception module performs attenuation compensation and delay calibration on the high-frequency burst characteristic signal and intercepts the complete time series. Specifically, after receiving the high-frequency burst characteristic signal and the partial discharge density level, the high-frequency triggering sensitization module extracts the amplitude change, phase characteristics, and detection frequency band identifier of the high-frequency burst characteristic signal, and generates a transient mapping value in combination with the partial discharge density level. The target trigger threshold is the current trigger threshold determined from the conventional trigger threshold and the sensitive trigger threshold based on the partial discharge density level, and is not configured as a fixed threshold alone. When the preset active degradation condition is met, the high-frequency trigger sensitization module uses the sensitive trigger threshold as the target trigger threshold (for example, the normal trigger threshold is 0.75 and the sensitive trigger threshold is 0.55, both dimensionless, derived from historical high-frequency discharge samples, on-site false trigger records, and manual verification results); when the preset active degradation condition is not met, the high-frequency trigger sensitization module uses the normal trigger threshold as the target trigger threshold. When the transient mapping value is greater than the target trigger threshold, a high-frequency discharge capture state is generated, and the corresponding high-frequency burst characteristic signal is sent to the high-frequency calibration interception module.

[0035] The high-frequency calibration and interception module is used to perform attenuation compensation and delay calibration on the high-frequency burst characteristic signal under the high-frequency discharge capture state to obtain the calibrated high-frequency burst signal, and to intercept the complete time series containing the transition signal, which includes the historical signal before triggering, the triggering time signal, and the continued attenuation signal after triggering.

[0036] Specifically, after receiving the high-frequency burst characteristic signal under high-frequency discharge capture state, the high-frequency calibration interception module transforms the high-frequency burst characteristic signal into a target burst matrix containing frequency band values, amplitude sequences, and phase angles, and determines joint calibration parameters based on signal propagation attenuation and propagation delay within the enclosed cavity. The joint calibration parameters include compensation values ​​and delay amounts, which can be jointly determined by enclosed cavity structure layer data, shielding layer material data, the current target burst matrix, and calibration data of the same model of equipment (for example, the joint calibration parameters include an 8dB compensation value and a 20ns delay amount, derived from the amplitude difference and arrival time difference of the calibration pulse in the current detection frequency band). The compensation value is used to inversely compensate for the amplitude attenuation caused by the metal enclosed cavity and shielding layer, and the delay amount is used to calibrate the phase delay caused by propagation path differences. When the high-frequency burst signal meets the preset amplitude mutation and duration conditions after calibration, the high-frequency calibration interception module intercepts the historical signal before triggering, the trigger time signal, and the continued attenuation signal after triggering, generating a complete time series. The preset amplitude mutation amount and duration conditions can be derived from historical high-frequency discharge samples, detection channel noise levels, and on-site trial operation records (for example, the amplitude mutation amount is not less than 10dB within 5μs and the duration is not less than 20μs).

[0037] The homogeneous evolution identification module is used to perform time-series alignment based on the first timestamp of the target partial discharge pulse and the second timestamp of the complete time sequence, and to generate a fault evolution record based on the aligned time-series discharge sequence.

[0038] like Figure 5 As shown, the homogeneous evolution identification module calculates an initial time offset based on the first timestamp of the target partial discharge pulse and the second timestamp of the complete time series. It then converts the candidate matching pulse and the complete time series into normalized feature sequences with the same fields to perform homogeneous evolution identification and generate a fault evolution record. Specifically, after receiving the target partial discharge pulse and the complete time series, the homogeneous evolution identification module calculates the initial time offset between the first and second timestamps and shifts the target partial discharge pulse according to the initial time offset to obtain the candidate matching pulse. Before entering the dynamic time warping algorithm, the complete time series and the candidate matching pulse are respectively converted into normalized feature sequences with the same fields. The normalized feature sequence includes at least a time step, an amplitude normalization value, and a phase normalization value. The homogeneous evolution identification module uses the dynamic time warping algorithm to calculate the sequence distance value between the two normalized feature sequences. When the sequence distance value is less than a preset distance threshold, the candidate matching pulse and the complete time series are identified as homogeneous discharge evolution events.

[0039] The fault evolution record is used to preserve the evolution process from the target partial discharge pulse to a high-frequency burst characteristic signal. The fault evolution record can be associated with and saved in conjunction with substation information, substation switchgear number, measurement point information, trigger time, detection frequency band identifier, partial discharge density level, and high-frequency discharge capture status. The associated and saved fault evolution record can be used for traceability, verification, and status assessment of the insulation status detection results of metal-enclosed substation switchgear.

[0040] Based on the above system, the present invention can first identify target partial discharge pulses with phase concentration and recurring characteristics in the multi-band discharge signals of metal-enclosed power distribution switchgear, then adjust the acquisition conditions of high-frequency burst characteristic signals based on the partial discharge density level, and generate fault evolution records through attenuation compensation, delay calibration and timing alignment, so that the discharge signal screening and identification results can reflect the activity level and evolution process of insulation defects in metal-enclosed equipment.

[0041] Example 2:

[0042] To provide a clearer and more complete explanation of the above embodiments, the present invention also provides Embodiment Two. In Embodiment Two, the specific processing methods of each module are further explained.

[0043] Preferably, the multi-band partial discharge acquisition module is further used for:

[0044] They are respectively connected to the transient ground voltage detection unit, the ultra-high frequency detection unit, the high frequency current detection unit, and the power supply synchronization unit;

[0045] Acquire the transient ground voltage signal, the ultra-high frequency electromagnetic wave signal generated by partial discharge, and the high frequency pulse current signal in the grounding circuit on the outer surface of the metal-enclosed power distribution switchgear cabinet;

[0046] Based on the power frequency phase reference provided by the power synchronization unit, discharge signals of different detection frequency bands are made to have comparable phase marks.

[0047] The transient ground voltage signal can be acquired by a transient ground voltage detection unit installed on the outer surface of the metal-enclosed power distribution switchgear cabinet. This unit senses the transient voltage changes formed on the outer surface of the metal cabinet by electromagnetic waves excited by partial discharge. The ultra-high frequency electromagnetic wave signal can be acquired by an ultra-high frequency detection unit, which receives the ultra-high frequency electromagnetic waves generated by partial discharge. The high-frequency pulse current signal can be acquired by a high-frequency current detection unit, which detects the high-frequency pulse current formed by the propagation of partial discharge along the grounding loop.

[0048] Specifically, the multi-band partial discharge acquisition module can communicate with each detection unit via a smart terminal or data processing terminal. The acquired transient ground voltage signal, ultra-high frequency electromagnetic wave signal, and high frequency pulse current signal are all written into the detection time, detection frequency band identifier, and measurement point information. The smart terminal or data processing terminal can display partial discharge amplitude spectrum, phase spectrum, waveform spectrum, and PRPD / PRPS spectrum, and can save, view, and replay the detection data. This display and saving function is used to support on-site detection data management without changing the core processing chain of this invention, which is based on phase window extraction, partial discharge density evaluation, high frequency trigger sensitization, calibration interception, and homogeneous evolution identification.

[0049] Specifically, the power frequency phase marker can be determined by the following formula:

[0050]

[0051] in, This represents the phase position of the discharge pulse within the current power frequency cycle, in degrees. The sampling time for the discharge pulse is in milliseconds (ms). The most recent power frequency synchronization reference time, in milliseconds; This represents the power frequency period at the site, measured in milliseconds (ms). If... If the calculation exceeds one power frequency cycle, then the remainder within one power frequency cycle is used for calculation. The calculated result... The data is written into the corresponding discharge signal data field for subsequent target phase window extraction, phase concentration statistics, and phase feature extraction of high-frequency burst characteristic signals.

[0052] More preferably, the multi-band partial discharge acquisition module is further used for:

[0053] The multi-band discharge signal is bandpass separated according to the transient ground voltage detection channel, the ultra-high frequency detection channel, and the high frequency current detection channel.

[0054] Non-target frequency band interference is filtered out, and power frequency phase periodic pulse signals, high-frequency electromagnetic burst signals, and high-frequency current burst signals are generated respectively;

[0055] The power frequency phase periodic pulse signal is output to the phase window pulse extraction module, and the high-frequency electromagnetic burst signal and the high-frequency current burst signal are output as the high-frequency burst feature signal to the high-frequency trigger sensitization module.

[0056] The transient ground voltage detection channel can be configured according to the transient ground voltage detection frequency band (e.g., 3MHz to 100MHz, derived from the detection bandwidth configuration of the transient ground voltage detection unit) to generate a power frequency phase periodic pulse signal with power frequency phase distribution characteristics. The ultra-high frequency detection channel can be configured according to the ultra-high frequency detection frequency band (e.g., 300MHz to 1.5GHz, derived from the detection bandwidth configuration of the ultra-high frequency detection unit) to generate a high-frequency electromagnetic burst signal. The high-frequency current detection channel can be configured according to the high-frequency current detection frequency band (e.g., 0.5MHz to 50MHz, derived from the detection bandwidth configuration of the high-frequency current detection unit) to generate a high-frequency current burst signal. Filtering non-target frequency band interference means retaining signals in each detection channel that match the detection channel frequency band and meet the basic pulse width condition, while suppressing power frequency harmonics, wireless communication interference, occasional mechanical vibration pulses, and background noise that does not match the current detection frequency band.

[0057] Preferably, the phase window pulse extraction module is further used for:

[0058] Obtain the enclosed cavity structure layer data and shielding layer material data of the metal-enclosed power distribution switchgear;

[0059] Based on the data of the enclosed cavity structure layer, the material data of the shielding layer, and the on-site calibration data, the high-frequency attenuation value and phase offset are determined.

[0060] When the high-frequency attenuation value meets the preset compensation condition, the phase offset is compensated to obtain the target offset.

[0061] The start and end times of the target phase window are set according to the target offset, and candidate partial discharge pulses are intercepted through the target phase window.

[0062] The enclosed cavity structure layer data may include the cabinet compartment structure, shielding layer levels, observation window position, detection hole position, grounding path, and detection point layout data of the metal-enclosed power distribution switchgear. The shielding layer material data may include the shielding layer material type, thickness, grounding continuity, and calibration attenuation data for the corresponding frequency band. The high-frequency attenuation value can be determined by calibration pulses or historical samples of the same model of equipment (for example, a high-frequency attenuation value of 8dB is derived from the statistical analysis of the difference between the input amplitude and the received amplitude of the calibration pulse during field trial operation of the same model of metal-enclosed power distribution switchgear). The phase offset can be determined by the difference between the reference phase and the detection phase of the calibration pulse (for example, a phase offset of 12° is derived from the phase comparison results of the calibration pulse under the power synchronization reference).

[0063] The preset compensation condition is used to determine whether the phase offset needs to be corrected. The preset compensation condition can be derived from equipment calibration data, enclosed cavity structure parameters, and field trial operation records (e.g., the preset compensation condition is met when the high-frequency attenuation value is greater than 6dB). When the high-frequency attenuation value meets the preset compensation condition, the phase window pulse extraction module calls the compensation table corresponding to the shielding layer material data to correct the phase offset and obtain the target offset; when the high-frequency attenuation value does not meet the preset compensation condition, the phase window pulse extraction module retains the phase offset as the target offset. Specifically, the compensation table can store different enclosed cavity structure layer data, shielding layer material data, and compensation angles corresponding to the detection frequency band. The target offset is the result of the superposition of the phase offset and the compensation angle. The compensation angle can be derived from the phase comparison results of calibration pulses of the same model of equipment (e.g., the compensation angle is 3°, and the target offset is 15°).

[0064] Furthermore, the phase window pulse extraction module uses the phase after the target offset correction from the reference phase center as the target phase window center, and extends the target phase window width by half on both sides of the target phase window center to determine the start and end times of the target phase window. For example, when the reference phase center is 90°, the target offset is 15°, and the target phase window width is 40°, the target phase window center is 105°, the target phase window start position is 85°, and the target phase window end position is 125°. Corresponding to a 50Hz power frequency cycle, the start and end times of the target phase window are calculated from the phase position according to a 20ms power frequency cycle. In this way, the target phase window can intercept candidate partial discharge pulses under the condition of considering the phase offset of the metal sealed cavity.

[0065] More preferably, the phase window pulse extraction module and the partial discharge density evaluation module are further used for:

[0066] The target partial discharge pulse is obtained by classifying and identifying the candidate partial discharge pulses based on their pulse amplitude, phase position, and recurrence status.

[0067] The target partial discharge pulse is encapsulated as a pulse object, which includes at least a pulse identifier, amplitude, phase position, hit time, detection frequency band identifier, and confidence level.

[0068] Based on the pulse object, the number of hits, the pulse density per unit time, and the phase concentration are statistically analyzed, and the partial discharge density level is generated when the number of hits and the phase concentration meet the set conditions.

[0069] The candidate partial discharge pulse's amplitude is used to determine if it exceeds the ambient background noise level. Its phase position is used to determine if it falls within the target phase window. The repetition rate is used to determine if it repeats within the same phase range across multiple consecutive power frequency cycles. The basic threshold for pulse amplitude extraction can be derived from the detection channel range, ambient background noise testing, and historical inspection records (e.g., the basic threshold for pulse amplitude extraction for the transient ground voltage detection channel is 15 dBm, derived from ambient noise statistics and manually verified samples within the 0 dBm to 80 dBm detection range). When the candidate partial discharge pulse's amplitude exceeds the basic threshold, its phase position falls within the target phase window, and its repetition frequency across consecutive power frequency cycles meets the repetition condition, the phase window pulse extraction module identifies it as the target partial discharge pulse.

[0070] The confidence level is used to represent the degree of certainty that a target partial discharge pulse is identified as a genuine partial discharge pulse. The confidence level can be determined jointly by pulse amplitude stability, phase position stability, and recurrence status. The confidence level input conditions can be derived from historical manually reviewed samples, detection channel noise statistics, and field trial operation records (e.g., a confidence level input condition of 0.70, dimensionless). Pulse objects with a confidence level lower than the confidence level input condition are not included in the partial discharge density level generation but are saved as pulses to be reviewed.

[0071] Specifically, the pulse density per unit time can be expressed by the following formula:

[0072]

[0073] in, This refers to the pulse density per unit time, measured in pulses per second. The number of times the target partial discharge pulse hits within the observation period, expressed in times; The observation time is in seconds. The calculated... Used for comparison with the pulse density threshold per unit time and involved in the generation of partial discharge density levels.

[0074] Specifically, the phase concentration can be expressed by the following formula, where the phase position recorded in degrees is first converted to radians and then substituted into the formula:

[0075]

[0076] in, Let be the phase concentration, dimensionless, and ; The number of times the target partial discharge pulse hits within the observation period, expressed in times; For the first The phase position of a target partial discharge pulse within the current power frequency cycle is represented in radians, in rad. The calculated... The closer the value is to 1, the more concentrated the target partial discharge pulse is on the phase axis; the calculated value... The closer it is to 0, the more dispersed the target partial discharge pulse is on the phase axis. When At this time, the phase concentration is recorded as 0, and no medium-density or high-density levels are generated. The phase concentration is used for comparison with the phase concentration threshold and participates in the generation of partial discharge density levels.

[0077] Specifically, when the number of hits is not less than 30 times / 60 seconds, the pulse density per unit time is not less than 0.50 times / second, and the phase concentration is not less than 0.70, the partial discharge density evaluation module can generate a medium density level; when the number of hits is not less than 60 times / 60 seconds, the pulse density per unit time is not less than 1.00 times / second, and the phase concentration is not less than 0.75, the partial discharge density evaluation module can generate a high density level. The above example thresholds are derived from historical inspection records of the same model of equipment, on-site background noise test results, and manually reviewed sample statistics, and are not intended to be the only limitation.

[0078] Preferably, the high-frequency triggering sensitization module is further used for:

[0079] Extract the amplitude abrupt change, phase characteristics, and detection frequency band identifier of the high-frequency burst characteristic signal;

[0080] A transient mapping value is generated based on the amplitude abrupt change, the phase characteristics, the detection frequency band identifier, and the partial discharge density level;

[0081] When the partial discharge density level meets the preset active degradation condition, the sensitive trigger threshold is determined as the target trigger threshold;

[0082] When the transient mapping value is greater than the target trigger threshold, a high-frequency burst discharge capture state is generated, and the high-frequency burst discharge capture state is used as the high-frequency discharge capture state.

[0083] The amplitude abrupt change is used to characterize the degree of amplitude jump of the high-frequency burst characteristic signal within a short period of time. The phase feature is used to characterize the position of the high-frequency burst characteristic signal relative to the power frequency cycle. The detection frequency band identifier is used to distinguish between the ultra-high frequency detection channel and the high-frequency current detection channel. The partial discharge density level is used to indicate whether the current insulation defect activity has entered an active degradation state. The amplitude abrupt change can be derived from the difference between the peak amplitude within the trigger window and the average background amplitude before triggering (for example, an amplitude abrupt change of 10dB is derived from the difference between the peak amplitude within the 5μs trigger window and the average background amplitude within the 20μs background window before triggering).

[0084] More preferably, the high-frequency triggering sensitization module is further used for:

[0085] The amplitude abrupt change, the phase characteristic, the detection frequency band identifier, and the partial discharge density level are normalized.

[0086] The normalized amplitude mutation is recorded as the amplitude mutation normalized value, the normalized phase feature is recorded as the phase matching normalized value, the detection frequency band identifier is converted into the detection frequency band weight value, and the partial discharge density level is converted into the partial discharge density level value; the amplitude mutation normalized value, the phase matching normalized value, the detection frequency band weight value, and the partial discharge density level value are weighted and summed according to preset weights, and the weighted summation result is limited to 0 to 1 to generate the transient mapping value;

[0087] When the partial discharge density level does not meet the preset active degradation condition, the normal trigger threshold is maintained, and the high-frequency burst characteristic signal is prevented from directly entering the sensitive trigger state.

[0088] Specifically, the transient mapping value can be generated according to a preset mapping relationship. The input items of the preset mapping relationship include the normalized amplitude change amount, the normalized phase feature, the detection frequency band weight value converted from the detection frequency band identifier, and the partial discharge density level value converted from the partial discharge density level. The output item is the transient mapping value with a value range of 0 to 1.

[0089] The normalized amplitude abrupt change is used to characterize the amplitude jump of the high-frequency burst characteristic signal; the normalized phase feature is used to characterize the matching degree between the phase position of the high-frequency burst characteristic signal and the target phase window; the detection frequency band weight value is used to distinguish the contribution of the ultra-high frequency detection channel and the high-frequency current detection channel to the high-frequency burst discharge capture; and the partial discharge density level value is used to characterize the activity level of the current target partial discharge pulse.

[0090] The transient mapping value can be obtained by weighted summing of the normalized amplitude abrupt change, the normalized phase characteristic, the detection frequency band weight value, and the partial discharge density level value, and then limiting the weighted summation result to 0 to 1. The preset weights can be pre-calibrated based on historical high-frequency discharge samples, on-site false trigger records, and manual verification results. The larger the transient mapping value, the closer the current high-frequency burst characteristic signal is to the high-frequency discharge capture state. The calculated transient mapping value is used for comparison with the conventional trigger threshold or the sensitive trigger threshold.

[0091] Specifically, when the discharge density level reaches a medium-density level or above, and the phase concentration is not less than 0.70 within three consecutive observation windows, the high-frequency trigger sensitization module determines the sensitive trigger threshold as the target trigger threshold; when the discharge density level is low-density or the phase concentration does not continuously meet the conditions, the high-frequency trigger sensitization module maintains the conventional trigger threshold. Preventing the high-frequency burst characteristic signal from directly entering the sensitive trigger state means that the system does not use the sensitive trigger threshold as the current target trigger threshold; even if the transient mapping value of the high-frequency burst characteristic signal is higher than the sensitive trigger threshold but lower than the conventional trigger threshold, a high-frequency discharge capture state is not generated.

[0092] Preferably, the high-frequency calibration interception module is further used for:

[0093] The high-frequency burst characteristic signal under the high-frequency discharge capture state is transformed in the frequency domain to extract the frequency band value, amplitude sequence and phase angle, and form the target burst matrix.

[0094] Calculate the attenuation error vector and phase offset gradient based on the target burst matrix;

[0095] Construct joint calibration parameters based on the attenuation error vector and the phase offset gradient;

[0096] The target burst matrix is ​​inversely compensated based on the joint calibration parameters to obtain the calibrated high-frequency burst signal.

[0097] The target burst matrix is ​​used to record the frequency band values, amplitude sequences, and phase angles of the high-frequency burst characteristic signal at different frequency components. The attenuation error vector represents the amplitude loss of different frequency components, and the phase offset gradient represents the propagation delay variation trend of different frequency components. The attenuation error vector and phase offset gradient can be jointly determined based on the closed cavity structure layer data, shielding layer material data, calibration data of the same type of equipment, and the current target burst matrix.

[0098] More preferably, the high-frequency calibration interception module is further used for:

[0099] The attenuation error vector and the phase offset gradient are calculated using a state observation filtering model;

[0100] The state observation filtering model is a Kalman filter model;

[0101] The joint calibration parameters include a compensation value corresponding to the signal transmission attenuation within the enclosed cavity of the metal-enclosed power distribution switchgear and a delay amount corresponding to the propagation delay.

[0102] When the calibrated high-frequency burst signal meets the preset amplitude change amount and duration conditions, the historical signal before the trigger, the trigger time signal, and the continued attenuation signal after the trigger are extracted to generate the complete time series.

[0103] In this model, the state variables can be the attenuation error vector and the phase offset gradient, while the observation variables can be the amplitude sequence and phase angle in the target burst matrix. The initial state of the Kalman filter model is determined by the estimated attenuation error and phase offset of the first effective detection cycle of the calibration pulse. The process noise parameters and observation noise parameters can be derived from equipment calibration data, historical detection data of the same model of equipment, and on-site noise statistics (e.g., the observation noise variance is 2 dB², and the process noise variance is 0.5 dB², both derived from repeated measurement statistics of the calibration pulse during on-site trial operation). The compensation value can be recorded in dB form (e.g., the compensation value is 8 dB, derived from the high-frequency attenuation value of the current detection frequency band), and the delay can be recorded in ns form (e.g., the delay is 20 ns, derived from the difference between the reference arrival time of the calibration pulse and the detection arrival time).

[0104] The attenuation error vector is generated based on the difference between the amplitude sequence of each frequency band in the target burst matrix and the corresponding calibrated amplitude sequence of the frequency band; the phase offset gradient is generated based on the difference between the phase angle change of adjacent frequency bands and the corresponding calibrated phase change; the compensation value is determined based on the statistical value of the attenuation error vector; and the delay is determined based on the propagation delay difference corresponding to the phase offset gradient.

[0105] Specifically, the high-frequency calibration and extraction module corrects the amplitude sequence in the target burst matrix by applying compensation values ​​and calibrates the phase angle by a delay, obtaining calibrated frequency domain data. This calibrated frequency domain data is then converted into a calibrated high-frequency burst signal. If the amplitude change in the calibrated high-frequency burst signal within 5 μs is not less than 10 dB and the duration is not less than 20 μs, the high-frequency calibration and extraction module extracts the complete time series centered on the trigger moment. The length of the historical signal window before triggering can be derived from the statistics of high-frequency discharge precursor samples and the buffer length configuration (e.g., the length of the historical signal window before triggering is 20 μs); the length of the continued attenuation signal window after triggering can be derived from the statistics of high-frequency discharge attenuation samples and the storage window configuration (e.g., the length of the continued attenuation signal window after triggering is 80 μs).

[0106] Preferably, the homology recognition module is further used for:

[0107] Calculate the initial time offset between the first timestamp and the second timestamp;

[0108] The target partial discharge pulse is translated according to the initial time offset to obtain a candidate matching pulse;

[0109] The candidate matching pulses and the complete time series are respectively converted into normalized feature sequences with the same fields, and the sequence distance between the two normalized feature sequences is calculated using a dynamic time warping algorithm.

[0110] When the sequence distance value is less than a preset distance threshold, the candidate matching pulse and the complete time series are determined to be homogeneous discharge evolution events;

[0111] The time-series discharge sequences corresponding to the homogeneous discharge evolution events are clustered and divided, and boundary data is extracted when the distance between the cluster centers meets the preset boundary extraction conditions to generate the fault evolution record;

[0112] The fault evolution record is associated with and saved with power distribution site information, power distribution switch equipment number, measurement point information, trigger time, detection frequency band identifier, partial discharge density level, and high-frequency discharge capture status, so as to be called upon for power distribution switch equipment status inspection and insulation status assessment of the intelligent power distribution system.

[0113] Wherein, the first timestamp is the hit time of the target partial discharge pulse, which can be in milliseconds (ms); the second timestamp is the trigger time of the complete time series, which can also be in milliseconds. Both the first and second timestamps are recorded based on the same system clock and power frequency phase reference. The initial time offset is used to shift the target partial discharge pulse to a time reference that is comparable to the complete time series.

[0114] Specifically, the initial time offset can be expressed by the following formula:

[0115]

[0116] in, This is the initial time offset, in milliseconds (ms). The first timestamp of the target partial discharge pulse, in milliseconds; This is the second timestamp of the complete time series, in milliseconds. Calculated... Used to translate the target partial discharge pulse and form candidate matching pulses.

[0117] Specifically, before entering the dynamic time warping algorithm, the homogeneous evolution identification module first converts the complete time series and the candidate matching pulses into normalized feature sequences with the same fields. For the complete time series, the pre-trigger historical signal, the trigger time signal, and the post-trigger continuous decay signal are arranged in chronological order to form an amplitude-time series, and each sampling point in the amplitude-time series is mapped to a unified time step. For the candidate matching pulses, the target partial discharge pulse is shifted according to the initial time offset, and the pulse hit time, pulse amplitude, and phase position after shifting are mapped to the same unified time step as the complete time series.

[0118] The normalized feature sequence includes at least a time step, an amplitude normalized value, and a phase normalized value. The amplitude normalized value represents the pulse amplitude or high-frequency burst signal amplitude at the corresponding time step, and the phase normalized value represents the power frequency phase position at the corresponding time step. The dynamic time warping algorithm searches for alignment paths with smaller cumulative distances based on the differences in amplitude and phase normalized values ​​at corresponding time steps in the two normalized feature sequences to obtain the sequence distance value. The smaller the sequence distance value, the closer the candidate matching pulse is to the complete time sequence in terms of temporal morphology, amplitude variation, and phase correlation. The clustering can be based on the amplitude level, phase position, pulse density per unit time, detection frequency band identifier, and high-frequency discharge capture state in the time-series discharge sequence. The cluster center distance represents the feature differences between different discharge stages. The preset boundary extraction conditions can be derived from historical fault evolution records and manual review results (e.g., a cluster center distance threshold of 0.25, dimensionless). When the distance between the centers of adjacent clusters reaches 0.25, the homogeneous evolution identification module extracts the boundary data of the corresponding transition position and writes the boundary data into the fault evolution record. The boundary data may include typical amplitude, phase position, pulse density per unit time, detection frequency band identifier, and high-frequency discharge capture status before and after the transition.

[0119] Furthermore, the fault evolution record is associated with and stored in conjunction with distribution site information, distribution switchgear number, measurement point information, trigger time, detection frequency band identifier, partial discharge density level, and high-frequency discharge capture status. The distribution site information is used to determine the site corresponding to the detection record; the distribution switchgear number is used to determine the metal-enclosed distribution switchgear corresponding to the detection record; the measurement point information is used to determine the detection locations of the transient ground voltage detection unit, the ultra-high frequency detection unit, and the high-frequency current detection unit; the trigger time is used to determine the moment the high-frequency discharge capture status occurs; the detection frequency band identifier is used to determine the corresponding signal source; the partial discharge density level is used to indicate the activity level of the insulation defect; and the high-frequency discharge capture status is used to indicate whether the system has captured a high-frequency burst characteristic signal that meets the target triggering conditions.

[0120] For example, during the inspection of a metal-enclosed power distribution switchgear, the on-site power synchronization unit detected a power frequency period of 20ms, the transient ground voltage detection unit collected a transient ground voltage signal on the outer surface of the cabinet, the ultra-high frequency detection unit collected an ultra-high frequency electromagnetic wave signal near the observation window, and the high-frequency current detection unit collected a high-frequency pulse current signal in the grounding loop. The multi-band partial discharge acquisition module writes the detection time, detection frequency band identifier, measurement point information, and power frequency phase mark for the three types of detection signals, and forms a power frequency phase periodic pulse signal, a high-frequency electromagnetic burst signal, and a high-frequency current burst signal through bandpass separation.

[0121] During the inspection, the phase window pulse extraction module reads the enclosed cavity structure layer data and shielding layer material data of the metal-enclosed power distribution switchgear. Based on the calibration pulse comparison, it obtains a high-frequency attenuation value of 8dB and a phase offset of 12°. Since the high-frequency attenuation value is greater than 6dB, the phase window pulse extraction module calls the compensation table to obtain a compensation angle of 3°, and then superimposes the phase offset with the compensation angle to obtain a target offset of 15°. If the reference phase center is 90° and the target phase window width is 40°, then the target phase window center is 105°, the target phase window start position is 85°, and the target phase window end position is 125°. The phase window pulse extraction module intercepts candidate partial discharge pulses within this phase range and determines the candidate partial discharge pulses that meet the conditions as the target partial discharge pulses based on the pulse amplitude, phase position, and recurrence status.

[0122] Subsequently, the partial discharge density evaluation module encapsulates the target partial discharge pulse as a pulse object. If, within a 60-second observation period, the number of target partial discharge pulse hits within the target phase window is 38, the pulse density per unit time is 0.63 pulses / s, and the phase concentration is 0.74, then the detection result meets the medium density level condition. Based on this, the high-frequency trigger sensitization module determines that the partial discharge density level meets the preset active degradation condition and switches the target trigger threshold from the conventional trigger threshold of 0.75 to the sensitive trigger threshold of 0.55. Subsequently, if the UHF detection channel acquires a high-frequency burst characteristic signal with an amplitude mutation of 12dB and a phase feature located in the vicinity of the target phase window, according to a preset mapping relationship, the normalized amplitude mutation is used as the amplitude mutation normalization value, the normalized phase feature is used as the phase matching normalization value, the detection frequency band identifier is converted into the detection frequency band weight value, and the partial discharge density level is converted into the partial discharge density level value; then, the amplitude mutation normalization value, the phase matching normalization value, the detection frequency band weight value, and the partial discharge density level value are weighted and summed according to preset weights, and the weighted summation result is limited to 0 to 1 to generate a transient mapping value greater than the sensitive trigger threshold. The high-frequency trigger sensitization module generates a high-frequency burst discharge capture state and uses the high-frequency burst discharge capture state as the high-frequency discharge capture state.

[0123] Upon receiving the high-frequency discharge capture status, the high-frequency calibration interception module performs frequency domain transformation on the corresponding high-frequency burst characteristic signal to form a target burst matrix containing frequency band values, amplitude sequences, and phase angles. It then uses a Kalman filter model to estimate the attenuation error vector and phase shift gradient. If the joint calibration parameters include an 8dB compensation value and a 20ns delay, the high-frequency calibration interception module performs inverse compensation on the target burst matrix to obtain the calibrated high-frequency burst signal. When the amplitude change of the calibrated high-frequency burst signal within 5μs is not less than 10dB and the duration is not less than 20μs, the high-frequency calibration interception module intercepts the historical signal 20μs before triggering, the trigger time signal, and the continued attenuation signal 80μs after triggering, forming a complete time series.

[0124] The homogeneous evolution identification module compares the first timestamp of the target partial discharge pulse with the second timestamp of the complete time series, calculates the initial time offset, and shifts the target partial discharge pulse to obtain candidate matching pulses. The homogeneous evolution identification module then converts the complete time series and candidate matching pulses into normalized feature sequences with the same fields. These normalized feature sequences include at least the time step, amplitude normalization value, and phase normalization value. A dynamic time warping algorithm is used to calculate the sequence distance between the two normalized feature sequences. If the sequence distance is 0.12 and less than a preset distance threshold of 0.18, the homogeneous evolution identification module determines the candidate matching pulse and the complete time series as homogeneous discharge evolution events. Subsequently, the time-series discharge sequences corresponding to the homogeneous discharge evolution events are clustered. When the distance between the centers of adjacent clusters reaches 0.25, boundary data at the transition position is extracted, and a fault evolution record is generated. The fault evolution record is associated with and stored in conjunction with the power distribution site information, power distribution switch equipment number, measurement point information, trigger time, detection frequency band identifier, partial discharge density level, and high-frequency discharge capture status, and is used for the traceability and verification of the insulation status detection results of metal-enclosed power distribution switch equipment.

[0125] Furthermore, when the same power distribution switchgear continuously exhibits increased partial discharge density, frequent activation of sensitive trigger states, persistently lower than a preset distance threshold, and cluster center distances meeting preset boundary extraction conditions across multiple inspection cycles, the homogeneous evolution identification module can save this information as a continuous fault evolution record for the same device. This continuous fault evolution record represents the process from the activation of the target partial discharge pulse to the capture of high-frequency burst characteristic signals, and finally to the extraction of the fault evolution boundary, supporting the insulation status assessment of metal-enclosed power distribution switchgear.

[0126] Accordingly, this invention integrates the transient ground voltage detection unit, ultra-high frequency detection unit, high frequency current detection unit, and power synchronization unit into the same discharge signal processing chain through a multi-band partial discharge acquisition module, enabling discharge signals from different detection frequency bands to have comparable phase markers; the phase window pulse extraction module determines the target phase window based on the closed cavity structure layer data and shielding layer material data, allowing candidate partial discharge pulses to be screened under the condition that phase offset is compensated; the partial discharge density evaluation module encapsulates the target partial discharge pulse into a pulse object and generates a partial discharge density level, ensuring that subsequent high-frequency triggering sensitization has insulation. The activity level of defects is determined by the following: a high-frequency trigger sensitization module switches the sensitive trigger threshold when the preset active degradation conditions are met, and generates a high-frequency discharge capture state when the transient mapping value meets the target trigger threshold; a high-frequency calibration and interception module performs attenuation compensation, delay calibration, and complete time series interception on the high-frequency burst characteristic signal; and a homogeneous evolution identification module performs time sequence alignment, homogeneity determination, and boundary data extraction on the target partial discharge pulse and the complete time series, thereby forming a closed-loop processing process from multi-band acquisition, target pulse screening, density evaluation, high-frequency capture, calibration and interception to fault evolution record storage.

[0127] The above description is merely a preferred embodiment of the technical solution of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A multi-band discharge signal screening and identification system for metal-enclosed equipment, characterized in that, Insulation condition detection for metal-enclosed switchgear in intelligent power distribution systems includes the following modules: The multi-band partial discharge acquisition module is used to acquire the multi-band discharge signals generated by the metal-enclosed power distribution switchgear in operation, add power frequency phase markers to the multi-band discharge signals based on the power synchronization reference, and separate and generate power frequency phase periodic pulse signals and high-frequency burst characteristic signals according to the detection frequency band. The phase window pulse extraction module is used to generate a target phase window based on the phase offset corresponding to the power frequency phase periodic pulse signal, and extract the target partial discharge pulse that characterizes the activity of insulation defects within the target phase window; The partial discharge density evaluation module is used to count the number of hits, pulse density per unit time, and phase concentration of the target partial discharge pulse within the target phase window, and generate a partial discharge density level. The high-frequency trigger sensitization module is used to switch the conventional trigger threshold for the high-frequency burst characteristic signal to a sensitive trigger threshold when the partial discharge density level meets the preset active degradation condition, and to generate a high-frequency discharge capture state when the high-frequency burst characteristic signal meets the target trigger condition. The high-frequency calibration and interception module is used to perform attenuation compensation and delay calibration on the high-frequency burst characteristic signal under the high-frequency discharge capture state, to obtain the calibrated high-frequency burst signal, and to intercept the complete time series containing the transition signal. The homogeneous evolution identification module is used to perform time-series alignment based on the first timestamp of the target partial discharge pulse and the second timestamp of the complete time sequence, and to generate a fault evolution record based on the aligned time-series discharge sequence.

2. The system according to claim 1, characterized in that, The multi-band partial discharge acquisition module is further used for: They are respectively connected to the transient ground voltage detection unit, the ultra-high frequency detection unit, the high frequency current detection unit, and the power supply synchronization unit; Acquire the transient ground voltage signal, the ultra-high frequency electromagnetic wave signal generated by partial discharge, and the high frequency pulse current signal in the grounding circuit on the outer surface of the metal-enclosed power distribution switchgear cabinet; Based on the power frequency phase reference provided by the power synchronization unit, discharge signals of different detection frequency bands are made to have comparable phase marks.

3. The system according to claim 2, characterized in that, The multi-band partial discharge acquisition module is further used for: The multi-band discharge signal is bandpass separated according to the transient ground voltage detection channel, the ultra-high frequency detection channel, and the high frequency current detection channel. Non-target frequency band interference is filtered out, and power frequency phase periodic pulse signals, high-frequency electromagnetic burst signals, and high-frequency current burst signals are generated respectively; The power frequency phase periodic pulse signal is output to the phase window pulse extraction module, and the high-frequency electromagnetic burst signal and the high-frequency current burst signal are output as the high-frequency burst feature signal to the high-frequency trigger sensitization module.

4. The system according to claim 1, characterized in that, The phase window pulse extraction module is further used for: Obtain the enclosed cavity structure layer data and shielding layer material data of the metal-enclosed power distribution switchgear; Based on the data of the enclosed cavity structure layer, the material data of the shielding layer, and the on-site calibration data, the high-frequency attenuation value and phase offset are determined. When the high-frequency attenuation value meets the preset compensation condition, the phase offset is compensated to obtain the target offset. The start and end times of the target phase window are set according to the target offset, and candidate partial discharge pulses are intercepted through the target phase window.

5. The system according to claim 4, characterized in that, The phase window pulse extraction module and the partial discharge density evaluation module are further used for: The target partial discharge pulse is obtained by classifying and identifying the candidate partial discharge pulses based on their pulse amplitude, phase position, and recurrence status. The target partial discharge pulse is encapsulated as a pulse object, which includes at least a pulse identifier, amplitude, phase position, hit time, detection frequency band identifier, and confidence level. Based on the pulse object, the number of hits, the pulse density per unit time, and the phase concentration are statistically analyzed, and the partial discharge density level is generated when the number of hits and the phase concentration meet the set conditions.

6. The system according to claim 1, characterized in that, The high-frequency triggering sensitization module is further used for: Extract the amplitude abrupt change, phase characteristics, and detection frequency band identifier of the high-frequency burst characteristic signal; A transient mapping value is generated based on the amplitude abrupt change, the phase characteristics, the detection frequency band identifier, and the partial discharge density level; When the partial discharge density level meets the preset active degradation condition, the sensitive trigger threshold is determined as the target trigger threshold; When the transient mapping value is greater than the target trigger threshold, a high-frequency burst discharge capture state is generated, and the high-frequency burst discharge capture state is used as the high-frequency discharge capture state.

7. The system according to claim 6, characterized in that, The high-frequency triggering sensitization module is further used for: The amplitude abrupt change, the phase characteristic, the detection frequency band identifier, and the partial discharge density level are normalized. The normalized amplitude mutation is recorded as the amplitude mutation normalized value, the normalized phase feature is recorded as the phase matching normalized value, the detection frequency band identifier is converted into the detection frequency band weight value, and the partial discharge density level is converted into the partial discharge density level value; the amplitude mutation normalized value, the phase matching normalized value, the detection frequency band weight value, and the partial discharge density level value are weighted and summed according to preset weights, and the weighted summation result is limited to 0 to 1 to generate the transient mapping value; When the partial discharge density level does not meet the preset active degradation condition, the normal trigger threshold is maintained, and the high-frequency burst characteristic signal is prevented from directly entering the sensitive trigger state.

8. The system according to claim 1, characterized in that, The high-frequency calibration interception module is further used for: The high-frequency burst characteristic signal under the high-frequency discharge capture state is transformed in the frequency domain to extract the frequency band value, amplitude sequence and phase angle, and form the target burst matrix. Calculate the attenuation error vector and phase offset gradient based on the target burst matrix; Construct joint calibration parameters based on the attenuation error vector and the phase offset gradient; The target burst matrix is ​​inversely compensated based on the joint calibration parameters to obtain the calibrated high-frequency burst signal.

9. The system according to claim 8, characterized in that, The high-frequency calibration interception module is further used for: The attenuation error vector and the phase offset gradient are calculated using a state observation filtering model; The state observation filtering model is a Kalman filter model; The joint calibration parameters include a compensation value corresponding to the signal transmission attenuation within the enclosed cavity of the metal-enclosed power distribution switchgear and a delay amount corresponding to the propagation delay. When the calibrated high-frequency burst signal meets the preset amplitude change amount and duration conditions, the historical signal before the trigger, the trigger time signal, and the continued attenuation signal after the trigger are extracted to generate the complete time series.

10. The system according to claim 1, characterized in that, The homology evolution identification module is further used for: Calculate the initial time offset between the first timestamp and the second timestamp; The target partial discharge pulse is translated according to the initial time offset to obtain a candidate matching pulse; The candidate matching pulses and the complete time series are respectively converted into normalized feature sequences with the same fields, and the sequence distance between the two normalized feature sequences is calculated using a dynamic time warping algorithm. When the sequence distance value is less than a preset distance threshold, the candidate matching pulse and the complete time series are determined to be homogeneous discharge evolution events; Cluster the time-series discharge sequences corresponding to the homogeneous discharge evolution events, and extract boundary data when the distance between the cluster centers meets the preset boundary extraction conditions to generate the fault evolution record; The fault evolution record is associated with and saved with the power distribution site information, power distribution switch equipment number, measurement point information, trigger time, detection frequency band identifier, partial discharge density level, and high-frequency discharge capture status, so as to be called upon for the power distribution switch equipment status inspection and insulation status assessment of the intelligent power distribution system.

Images