CN-122017605-A - Communication base station energy storage battery nondestructive testing method based on charge-discharge curve characteristics

CN122017605ACN 122017605 ACN122017605 ACN 122017605ACN-122017605-A

Abstract

The invention discloses a non-destructive testing method of an energy storage battery of a communication base station based on characteristics of charge and discharge curves, which relates to the technical field of energy storage battery testing and comprises the following steps of collecting lossy samples and non-destructive samples of charge and discharge curves of energy storage batteries of different communication base stations; the method comprises the steps of extracting curve characteristics of a lossy sample and a lossless sample, respectively named as the lossy characteristic and the lossless characteristic, learning the lossy characteristic and the lossless characteristic, analyzing characteristic divergence between the lossy characteristic and the lossless characteristic, analyzing a charging and discharging curve of an energy storage battery of a communication base station based on characteristic analysis, and monitoring whether the energy storage battery of the communication base station is abnormal or not.

Inventors

ZHENG YING
ZHENG YI

Assignees

重庆桦秀科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260410

Claims (6)

1. The nondestructive testing method for the energy storage battery of the communication base station based on the characteristics of the charge-discharge curve is characterized by comprising the following steps: collecting lossy samples and lossless samples of charge-discharge curves of energy storage batteries of different communication base stations; The method comprises the following substeps of connecting a left end point and a right end point of a characteristic curve through a straight line, naming the connected straight line as a characteristic auxiliary line, naming an intersection point of the characteristic curve and the characteristic auxiliary line as a characteristic auxiliary point, numbering the characteristic auxiliary points according to a left-to-right sequence, and representing the characteristic auxiliary point by a symbol CAP n , wherein n is a nonzero natural number and n is a sequence number of the CAP, marking the characteristic curve between the CAP n and the CAP n+1 as CL n , obtaining a coordinate point farthest from the characteristic auxiliary line in the CL n and marked as CHL n , carrying out linear regression on the CL n , obtaining a slope of a regression function, marking the slope as CK n , simultaneously obtaining the maximum value of a residual error of the regression function, marking the slope as CC n , and jointly forming the characteristic of the characteristic curve by the CAP n 、CK n and the CC n ; Extracting curve features in the lossy sample and the lossless sample through a feature extraction model to obtain lossy features and lossless features; The method comprises the following substeps of counting all CAP n in the lossless feature, analyzing any value of n, circling CAP n with the same value of n through a minimum circle to obtain a distribution circle, obtaining the circle center of CR n through the representation of a symbol CR n , marking the circle center of CR n as R n , simultaneously marking the radius of CR n as RR n , counting the range of CK n in the lossless feature and the range of CC n , analyzing each value of n independently, marking the statistical result as KT n and CT n respectively, analyzing each lossy feature, judging whether CAP n in the lossy feature is in CR n , outputting a point feature to be determined signal if not, judging whether CK n in the lossy feature is in KT n , outputting a slope feature to be determined signal if not, judging whether CK n in the lossy feature is in the lossy feature, outputting a residual feature if the lossy feature is in the lossy feature, outputting a residual error signal if the residual feature is not The slope characteristic lossy signal and the residual characteristic lossy signal are collectively called as lossy characteristic signals, if any lossy characteristic signal is output in one lossy characteristic, CAP n 、CK n or CC n corresponding to the lossy characteristic signal in the lossy characteristic is marked as an actual lossy parameter, the CR n 、KT n and CT n are the lossless comprehensive characteristics, and the actual lossy parameter is the lossy comprehensive characteristics; Analyzing characteristic divergence between the lossy comprehensive characteristics and the lossless comprehensive characteristics; and analyzing a charge-discharge curve of the energy storage battery of the communication base station based on the feature analysis, and monitoring whether the energy storage battery of the communication base station is abnormal.
2. The method for non-destructive testing of energy storage batteries of communication base stations based on characteristics of charge and discharge curves according to claim 1, wherein collecting the lossy samples and the lossless samples of the charge and discharge curves of the energy storage batteries of different communication base stations comprises the following sub-steps: The communication base station energy storage battery is provided with a charging and discharging scheme, the charging and discharging scheme is that the communication base station energy storage battery is charged, the charging is stopped after the battery electric quantity is full, and the communication base station energy storage battery is charged again when the battery electric quantity of the communication base station energy storage battery is monitored to be reduced to an electric quantity threshold value, so that the battery electric quantity of the communication base station energy storage battery is always kept to be more than the electric quantity threshold value when the communication base station energy storage battery does not work; the time between the battery power from the power threshold value to the full charge is named as a charging period, and the time between the battery power from the full charge to the power threshold value is named as a discharging period; Recording the change curves of the battery voltage and the battery current in the energy storage battery of the charging period communication base station and time to obtain a charging curve, and recording the change curves of the battery voltage and the battery current in the energy storage battery of the discharging period communication base station and time to obtain a discharging curve; the method comprises the steps of respectively naming a charging curve and a discharging curve of a communication base station energy storage battery in a history record as a charging normal curve and a discharging normal curve when the communication base station energy storage battery does not have faults, forming a nondestructive sample together by the charging normal curve and the discharging normal curve, respectively naming the charging curve and the discharging curve of the communication base station energy storage battery in the history record as a charging abnormal curve and a discharging abnormal curve when the communication base station energy storage battery has faults, and forming a destructive sample together by the charging abnormal curve and the discharging abnormal curve.
3. The method for non-destructive testing of an energy storage battery of a communication base station based on charge-discharge curve characteristics according to claim 2, wherein the steps of extracting the characteristics of the curve in the lossy sample and the lossless sample by the characteristic extraction model to obtain the lossy characteristic and the lossless characteristic comprise the following sub-steps: The method comprises the steps of (1) naming a curve formed by battery voltage and time in a charging curve as a charging voltage curve, naming a curve formed by battery current and time as a charging current curve, naming a curve formed by battery voltage and time in a discharging curve as a discharging voltage curve, and naming a curve formed by battery current and time as a discharging current curve; Analyzing curve characteristics of a charging voltage curve, a charging current curve, a discharging voltage curve and a discharging current curve in a lossy sample, which are named as lossy charging voltage characteristics, lossy charging current characteristics, lossy discharging voltage characteristics and lossy discharging current characteristics respectively, wherein the lossy charging voltage characteristics, the lossy charging current characteristics, the lossy discharging voltage characteristics and the lossy discharging current characteristics form lossy characteristics together; And analyzing curve characteristics of a charging voltage curve, a charging current curve, a discharging voltage curve and a discharging current curve in the lossless sample, which are respectively named as a lossless charging voltage characteristic, a lossless charging current characteristic, a lossless discharging voltage characteristic and a lossless discharging current characteristic, wherein the lossless charging voltage characteristic, the lossless charging current characteristic, the lossless discharging voltage characteristic and the lossless discharging current characteristic jointly form a lossless characteristic.
4. A method for non-destructive testing of a communication base station energy storage battery based on characteristics of a charge-discharge curve according to claim 3, wherein analyzing the lossy integrated characteristic and the characteristic divergence between the lossless integrated characteristic comprises the sub-steps of: CAP n 、CK n and CC n in the lossy synthesis feature are labeled FP n 、FK n and FC n , respectively; Calculating the distance between FP n and R n , marking as FL n , searching the minimum value in FL n , marking as FR n , and calculating the median between FR n and RR n to obtain point characteristic divergence; Counting the range of FK n , respectively counting FK n smaller than KT n and larger than KT n , marking the range smaller than KT n as DKA n , marking the range larger than KT n as DKB n , calculating the median of the maximum value in DKA n and the minimum value in KT n , marking QKA n , calculating the median of the minimum value in DKB n and the maximum value in KT n , marking QKB n , and naming QKA n and QKB n as slope characteristics divergence; Counting the ranges of FC n , respectively counting FC n smaller than CT n and larger than CT n , marking the ranges smaller than CT n as DCA n , marking the ranges larger than CT n as DCB n , calculating the median of the maximum value in DCA n and the minimum value in CT n , marking QCA n , calculating the median of the minimum value in DCB n and the maximum value in CT n , marking QCB n , and naming QCA n and QCB n as residual characteristic divergence; The point characteristic divergence, the slope characteristic divergence and the residual characteristic divergence form the characteristic divergence together, and each value of n in the charging voltage curve, the charging current curve, the discharging voltage curve and the discharging current curve has one characteristic divergence.
5. The non-destructive testing method for the energy storage battery of the communication base station based on the characteristics of the charge and discharge curves of the energy storage battery of the communication base station according to claim 4, wherein the analyzing the charge and discharge curves of the energy storage battery of the communication base station based on the characteristic analysis, and the monitoring whether the energy storage battery of the communication base station is abnormal comprises the following sub-steps: when the charging and discharging scheme is executed by the energy storage battery of the monitoring communication base station, a charging voltage curve, a charging current curve, a discharging voltage curve and a discharging current curve are monitored in real time; After the monitoring communication base station energy storage battery completes a primary charging and discharging scheme, extracting the monitored curve characteristics of a charging voltage curve, a charging current curve, a discharging voltage curve and a discharging current curve, which are respectively named as a charging voltage real-time characteristic, a charging current real-time characteristic, a discharging voltage real-time characteristic and a discharging current real-time characteristic; and carrying out anomaly analysis on the real-time characteristics of the charging voltage, the real-time characteristics of the charging current, the real-time characteristics of the discharging voltage and the real-time characteristics of the discharging current based on characteristic divergence.
6. The non-destructive testing method for the energy storage battery of the communication base station based on the characteristics of the charge-discharge curve according to claim 5, wherein the anomaly analysis of the real-time characteristics of the charge voltage, the real-time characteristics of the charge current, the real-time characteristics of the discharge voltage and the real-time characteristics of the discharge current based on the characteristic divergence comprises the following sub-steps: Comparing each charging voltage real-time characteristic, charging current real-time characteristic, discharging voltage real-time characteristic and discharging current real-time characteristic with corresponding characteristic divergence; If any one of the charge voltage real-time feature, the charge current real-time feature, the discharge voltage real-time feature and the discharge current real-time feature, which are greater than or equal to CAP n , CK n which is less than or equal to QKA n , CK n which is greater than or equal to QKB n , CC n which is less than or equal to QCA n or CC n which is greater than or equal to QCB n , is met, outputting a battery abnormal signal, otherwise outputting a battery normal signal.

Description

Communication base station energy storage battery nondestructive testing method based on charge-discharge curve characteristics Technical Field The invention relates to the technical field of energy storage battery detection, in particular to a nondestructive detection method for an energy storage battery of a communication base station based on charge-discharge curve characteristics. Background The detection technology of the energy storage battery refers to a whole set of methodology for acquiring, analyzing, diagnosing and predicting the state parameters of the battery by means of physics, chemistry, electrochemistry, data analysis and the like under the condition of not damaging the battery structure or not affecting the normal operation of the system or under specific test working conditions in order to ensure the safety, reliability and economy of the energy storage system. The existing energy storage battery detection technology generally needs to carry out deep charge and discharge on the energy storage battery to carry out health analysis on the energy storage battery, and the communication base station energy storage battery ensures that the communication base station energy storage battery has sufficient electric energy at required time due to the specificity of the energy storage battery, so that deep charge data cannot be obtained, the use times of the communication base station energy storage battery are less, deep discharge data cannot be obtained, and therefore the existing energy storage battery detection technology is not suitable for the communication base station energy storage battery, and the existing energy storage battery detection technology also has the problem that the communication base station energy storage battery cannot be subjected to deep charge and discharge when the communication base station energy storage battery is detected, so that a detection result of the communication base station energy storage battery has larger error. Disclosure of Invention The invention aims to solve at least one of the technical problems in the prior art to a certain extent, by collecting lossy samples and lossless samples of charge and discharge curves of energy storage batteries of different communication base stations, then constructing a feature extraction model, extracting curve features through the feature extraction model, extracting the curve features in the lossy samples and the lossless samples through the feature extraction model to obtain lossy features and lossless features, learning the lossy features and the lossless features to obtain lossy comprehensive characteristics and lossless comprehensive characteristics, analyzing feature divergence between the lossy comprehensive characteristics and the lossless comprehensive characteristics, analyzing the charge and discharge curves of the energy storage batteries of the communication base stations based on feature analysis, and monitoring whether the energy storage batteries of the communication base stations are abnormal, so as to solve the problem that the detection result of the energy storage batteries of the communication base stations has larger error because the conventional energy storage battery detection technology cannot deeply charge and discharge the energy storage batteries of the communication base stations when detecting the energy storage batteries of the communication base stations. In order to achieve the above purpose, the application provides a nondestructive testing method for an energy storage battery of a communication base station based on charge-discharge curve characteristics, which comprises the following steps: collecting lossy samples and lossless samples of charge-discharge curves of energy storage batteries of different communication base stations; The method comprises the following substeps of connecting a left end point and a right end point of a characteristic curve through a straight line, naming the connected straight line as a characteristic auxiliary line, naming an intersection point of the characteristic curve and the characteristic auxiliary line as a characteristic auxiliary point, numbering the characteristic auxiliary points according to a left-to-right sequence, and representing the characteristic auxiliary point by a symbol CAP n, wherein n is a nonzero natural number and n is a sequence number of the CAP, marking the characteristic curve between the CAP n and the CAP n+1 as CL n, obtaining a coordinate point farthest from the characteristic auxiliary line in the CL n and marked as CHL n, carrying out linear regression on the CL n, obtaining a slope of a regression function, marking the slope as CK n, simultaneously obtaining the maximum value of a residual error of the regression function, marking the slope as CC n, and jointly forming the characteristic of the characteristic curve by the CAP n、CKn and the CC n; Extracting curve features in the lossy sample and the lossless sample thr