CN-121995207-A - Intelligent air-break control monitoring method based on lora communication

CN121995207ACN 121995207 ACN121995207 ACN 121995207ACN-121995207-A

Abstract

The invention discloses an intelligent air-break control monitoring method based on lora communication, which relates to the technical field of air-break control monitoring and comprises the following steps of continuously collecting an air-break voltage sampling sequence and a current sampling sequence, generating an amplitude density curve, an inversion interval period value and a waveform pole delay track to form a continuous characteristic sequence so as to judge whether a sampling signal has regular distortion under the influence of electromagnetic interference, extracting a distortion confirmation point set from the continuous characteristic sequence under the condition that the sampling signal has the regular distortion, and calculating a characteristic deviation factor, a trend residual vector and a stability window convergence degree based on each distortion confirmation point to form an abnormal shape mapping group. The invention solves the problem that structural distortion of the sampled data is difficult to identify under electromagnetic interference, realizes distortion perception and state closed-loop regulation and control based on the characteristic sequence, and improves monitoring accuracy and system safety.

Inventors

HUANG SHUAI
MIAO WENJIE
HU QIAN
ZHOU JINYA
LI YUBAO
CHEN JIAMIN

Assignees

杭州市电力设计院有限公司

Dates

Publication Date: 20260508
Application Date: 20260129

Claims (9)

1. The intelligent air-break control monitoring method based on the lora communication is characterized by comprising the following steps of: s1, continuously acquiring an unopened voltage sampling sequence and an unopened current sampling sequence, generating an amplitude-variable density curve, an inversion interval period value and a waveform pole delay track, and forming a continuous characteristic sequence to judge whether a sampling signal has regular distortion under the influence of electromagnetic interference; S2, under the condition that the sampling signal has regular distortion, extracting a distortion confirmation point set from the continuous feature sequence, and calculating a feature deviation factor, a trend residual vector and a stability window convergence degree based on each distortion confirmation point to form an abnormal morphology mapping group; s3, carrying out combination processing on various indexes in the abnormal form mapping group to generate an amplitude response offset rate, a form coupling score and a stability deviation total amount, and calculating a reliability score value of the running state for identifying whether the idle running state is distorted; S4, generating a state classification result based on the relation between the credibility grading value and the dynamic threshold mapping coordinate, and dividing the running state into a data credibility area, a data critical area and a data distortion area; S5, executing dynamic regulation and control operation according to the state classification result, wherein the data trusted region keeps original sampling and communication frequency, the data critical region increases sampling frequency and pauses remote control response, and the data distortion region triggers signal screening and marks current data as an abnormal source and feeds back to a continuous characteristic sequence acquisition process to form a closed loop.
2. The intelligent air-break control monitoring method based on the lora communication according to claim 1, wherein S1 specifically comprises the following steps: s101, continuously collecting the empty voltage sampling sequence and the current sampling sequence according to a unified time reference, so that each voltage sampling value and the current sampling value at the corresponding moment form a time alignment relation, and forming a continuously arranged basic sampling sequence according to the sampling time sequence; S102, calculating amplitude change density in a continuous sampling interval based on an amplitude change relation between adjacent sampling values in a basic sampling sequence to generate an amplitude change density curve, calculating a time interval between adjacent inversion points based on a position where the change direction of the sampling values is inverted to generate an inversion interval period value, and calculating an extreme value time offset based on the position change of an amplitude extreme value point in the sampling sequence relative to a time reference to generate a waveform pole delay track; S103, combining and arranging the amplitude variation density curve, the inversion interval period value and the waveform pole delay track according to a time sequence to form a continuous characteristic sequence, respectively carrying out combined comparison on the period repetition degree of the amplitude variation density curve, the time consistency degree of the inversion interval period value and the offset stability degree of the waveform pole delay track in the continuous characteristic sequence, and judging that the sampling signal has regular distortion under the influence of electromagnetic interference when the amplitude variation density curve shows a fixed period repetition relationship, the inversion interval period value keeps the time consistency relationship and the waveform pole delay track keeps the stable offset relationship.
3. The intelligent air-break control monitoring method based on the lora communication according to claim 2, wherein S102 specifically comprises: In a basic sampling sequence, calculating amplitude difference values aiming at adjacent sampling values, arranging the amplitude difference values according to a sampling time sequence, and forming an amplitude variation density curve reflecting the frequent degree of amplitude variation by counting the distribution density degree of the amplitude difference values in continuous sampling intervals; In the basic sampling sequence, identifying the position of the change direction of the amplitude from ascending to descending or from descending to ascending, determining the position of the change direction inverted as an inversion point, and calculating an inversion interval period value according to the sampling time interval corresponding to the adjacent inversion point; in the basic sampling sequence, the position where the amplitude reaches the local maximum value or the local minimum value is identified as an extreme point, the time offset of each extreme point relative to the time reference is calculated by taking the unified time reference as a reference, and the time offsets of the continuous extreme points are arranged to generate the waveform pole delay track.
4. The intelligent air-break control monitoring method based on the lora communication according to claim 1, wherein S2 specifically comprises the following steps: S201, under the condition that a sampling signal has regular distortion, carrying out point-by-point analysis along the time sequence of a continuous characteristic sequence, when a variable amplitude density curve corresponding to the same time position presents repeated variation rhythms in a plurality of adjacent time intervals, inversion interval period values keep the same time interval distribution in the plurality of adjacent time intervals, and waveform pole delay tracks present continuous and consistent time offset trend in the plurality of adjacent time intervals, determining data of the corresponding time position as distortion confirmation points, and arranging the plurality of distortion confirmation points according to the time sequence to form a distortion confirmation point set; S202, calculating the deviation amplitude of a characteristic value relative to the overall distribution position of a continuous characteristic sequence on the basis of the characteristic value of the continuous characteristic sequence corresponding to the time position for each distortion confirmation point in the distortion confirmation point set to obtain a characteristic deviation factor, simultaneously calculating the difference distribution between the continuous characteristic change trend before and after the time position and the overall change trend of the continuous characteristic sequence to obtain a trend residual vector, and counting the concentration degree of characteristic change in a continuous time window with the distortion confirmation point as a center to obtain a stable window convergence degree; S203, combining and arranging the feature deviation factors, the trend residual vectors and the convergence of the stable window corresponding to each distortion confirmation point according to the time sequence of the distortion confirmation points in the continuous feature sequence to form an abnormal morphology mapping group, wherein the abnormal morphology mapping group is used for describing the abnormal electrical parameter features under the condition that the sampling signal is regularly distorted under the influence of electromagnetic interference.
5. The intelligent air-break control monitoring method based on the lora communication according to claim 4, wherein S202 specifically comprises: extracting a continuous characteristic sequence characteristic value corresponding to the time position aiming at each distortion confirmation point in the distortion confirmation point set, comparing the characteristic value with characteristic value distribution formed by the continuous characteristic sequence in a complete time range, and obtaining a characteristic deviation factor for representing the local characteristic deviation degree by calculating the distance amplitude of the characteristic value relative to the distribution center; Extracting continuous characteristic change tracks in continuous time intervals before and after the time position around the same distortion confirmation point, carrying out trend comparison on the change tracks and the change tracks in the integral time range of the continuous characteristic sequence, and carrying out distribution description on the difference of the two types of change tracks in directivity and change amplitude to obtain a trend residual vector; and taking the time position corresponding to the same distortion confirmation point as a center, selecting a continuous characteristic sequence characteristic value in a continuous time window, counting the concentration degree and the discrete degree of characteristic value change in the time window, taking the counting result as a stable window convergence degree, and describing the aggregation state of characteristic change in the neighborhood of the distortion confirmation point.
6. The intelligent air-break control monitoring method based on the lora communication according to claim 1, wherein S3 specifically comprises the following steps: S301, extracting a characteristic deviation factor, a trend residual vector and a stability window convergence degree corresponding to each distortion confirmation point in the abnormal form mapping group according to a time sequence, and constructing a corresponding index arrangement sequence on the premise of keeping time alignment to serve as a basic characteristic data source of subsequent combination processing; S302, calculating the offset ratio between the maximum value and the average value of the characteristic deviation factors based on the change tracks of different types of indexes in the index arrangement sequence to generate an amplitude response offset rate; And S303, carrying out normalization processing on the amplitude response offset rate, the form coupling score and the stability deviation total amount, carrying out weighted accumulation processing according to a preset multidimensional index fusion weight to generate a reliability score value of the running state, and recognizing that the running state which is open is distorted when the reliability score value is lower than a distortion recognition threshold.
7. The intelligent air-break control monitoring method based on the lora communication according to claim 6, wherein S302 specifically comprises: extracting an index arrangement sequence formed by characteristic deviation factors, calculating the difference ratio between the maximum characteristic deviation factor value and the average characteristic deviation factor value in the index arrangement sequence, and taking the difference ratio as an amplitude response deviation rate for measuring the response intensity difference of the local electric parameter abnormality in the whole sequence; Extracting an index arrangement sequence formed by the trend residual vectors, calculating an included angle between each trend residual vector and the main trend direction of the whole sequence, and carrying out cosine aggregation on all included angles to obtain a morphological coupling score reflecting the consistency of the residual directions, wherein the morphological coupling score is used for describing the consistency degree of multi-point trend deviation; And extracting an index arrangement sequence formed by the convergence of the stability window, respectively calculating the fluctuation amplitude between the convergence values in adjacent time intervals, and constructing the total stability deviation based on the maximum fluctuation amplitude in the statistical range, so as to evaluate the influence intensity of the local stability change on the whole characteristic sequence.
8. The intelligent air-break control monitoring method based on the lora communication according to claim 1, wherein S4 specifically comprises: based on the calibrated running state and the corresponding credibility scoring value in the historical sample, constructing a mapping coordinate between the credibility scoring value and a dynamic threshold value, extracting the corresponding relation between the credibility scoring value and the distortion degree under different working conditions in a plurality of time periods, and generating a plurality of sections of dynamic threshold curves in a sectional fitting mode to form a mapping coordinate system reflecting the relation between the scoring value change and the state dividing boundary; mapping the credibility scoring value of the current running state into a mapping coordinate system which is completed, and determining the relative relation of the credibility scoring value in the mapping coordinate according to the corresponding interval position of the credibility scoring value on the dynamic threshold value curve to obtain a numerical relation foundation between the current credibility scoring value and the dynamic threshold value; And (3) carrying out state classification judgment according to the position relation of the current credibility grading value in the mapping coordinate system, dividing the running state into a data credibility area if the credibility grading value is in a high grading area of the dynamic threshold curve, dividing the running state into a data critical area if the credibility grading value is in a fluctuation transition area of the dynamic threshold curve, and dividing the running state into a data distortion area if the credibility grading value is lower than the lower boundary of the dynamic threshold curve, so as to generate a corresponding state classification result.
9. The intelligent air-break control monitoring method based on the lora communication according to claim 1, wherein S5 specifically comprises: When the state classification result is a data trusted region, the sampling system is controlled to maintain the sampling frequency of the current voltage sampling sequence and the current sampling sequence, and the current LoRa communication frequency is kept unchanged, so that the data continuously enter a continuous characteristic sequence acquisition flow under a stable condition, and the time consistency and the signal integrity in the characteristic generation process are ensured; When the state classification result is a data critical area, adjusting parameters of a sampling control unit, improving the sampling frequency of a voltage sampling sequence and a current sampling sequence to a high-precision sampling level, shielding a response mechanism of a remote control signal, suspending transmission and execution of a remote control instruction, and ensuring that the integrity of the sampling signal is not influenced by controlled intervention so as to enhance the accuracy of anomaly identification; When the state classification result is a data distortion zone, enabling the signal processing unit to perform signal screening on sampling data in the current period, identifying data points with characteristic distribution offset in the continuous characteristic sequence, marking the data as an abnormal source, feeding back the marking result to the continuous characteristic sequence acquisition flow, driving a subsequent sampling period to perform isolation management on the abnormal data, and constructing a dynamic regulation mechanism facing state closed-loop control.

Description

Intelligent air-break control monitoring method based on lora communication Technical Field The invention relates to the technical field of air-break control monitoring, in particular to an intelligent air-break control monitoring method based on lora communication. Background The intelligent air switch control monitoring based on LoRa communication is to upgrade a traditional air switch into intelligent equipment with remote control and state monitoring functions by utilizing LoRa (Long Range) low-power consumption wide area network communication technology, so as to realize intelligent management and fault early warning of a power line. In the prior art, the system generally comprises a plurality of links such as intelligent idle equipment, an embedded LoRa module, a LoRa gateway, a back-end cloud platform, a user terminal and the like. The working flow is generally that a back-end platform or a user terminal sends out control instructions (such as power off and power on), the control instructions are forwarded to a LoRa gateway through a cloud platform, the control instructions are transmitted to a target idle switch through a LoRa wireless channel, the idle switch executes instruction actions, meanwhile, the running states such as current, voltage and temperature are collected in real time and then transmitted to the gateway in a LoRa mode, and the control instructions are reported to the cloud platform by the gateway for storage, analysis and display, so that remote monitoring and control of the running state of equipment are realized. In addition, part of the system also integrates the functions of overload/short circuit identification, automatic power-off protection, alarm pushing, data statistics, strategy control and the like, and forms a closed-loop intelligent control monitoring system covering a plurality of complete links such as instruction issuing, execution response, state acquisition, data feedback, intelligent analysis and the like. The system has the advantages of long communication distance, strong penetrating power and low power consumption, and is particularly suitable for the wide-area deployment, distributed control and low-power-consumption operation of the power equipment. The prior art has the following defects: In the process of realizing intelligent idle opening control monitoring based on LoRa communication, when a high-intensity electromagnetic interference source (such as industrial electric welding equipment) is temporarily accessed in an environment where an idle opening is located, instantaneous interference can be caused to a local electric signal sampling process of the idle opening, so that the phenomenon of 'instantaneous zero return' or 'periodic offset' of the regularity of the operation parameters of the collected voltage, current and the like is caused. Since this interference behavior acts on the data sampling phase rather than the communication link itself and the sampling result is still within the numerical threshold, the data uploaded through the LoRa communication appears as a "surface stable" operating state at the platform end. The existing intelligent air-break control monitoring technology based on LoRa communication generally defaults that a communication link is normal, namely the representative data is real and reliable, and interference factors in the data acquisition process are not effectively identified and checked, and an authenticity judgment mechanism based on data structure characteristics is not established, so that whether the running state of an air-break is distorted or not cannot be identified according to electric parameter abnormal characteristics under the condition that a sampling signal is regularly distorted under the influence of electromagnetic interference, and the platform is in a normal state in the running evaluation. The problem is that the system depends on structural distortion data for a long time to perform state judgment, the accuracy of trend identification and risk assessment is affected, monitoring failure and alarm lag are easy to cause, and finally load faults can not be early-warned in time, so that the intelligent monitoring capability of the system and the safety operation guarantee of electric power are seriously affected. The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art. Disclosure of Invention The invention aims to provide an intelligent air-break control monitoring method based on lora communication, so as to solve the problems in the background technology. In order to achieve the purpose, the invention provides the following technical scheme that the intelligent air-break control monitoring method based on the lora communication specifically comprises the following steps: s1, continuously a