CN111473860B - A method for extracting characteristic parameters of vibration signal of high-voltage AC circuit breaker - Google Patents

A method for extracting characteristic parameters of vibration signal of high-voltage AC circuit breaker Download PDF

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CN111473860B
CN111473860B CN202010477132.9A CN202010477132A CN111473860B CN 111473860 B CN111473860 B CN 111473860B CN 202010477132 A CN202010477132 A CN 202010477132A CN 111473860 B CN111473860 B CN 111473860B
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vibration
data
characteristic parameters
vibration signal
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CN111473860A (en
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杨为
朱太云
闫静
朱胜龙
张国宝
赵恒阳
蔡梦怡
陈忠
秦少瑞
赵常威
秦金飞
宋东波
杨海涛
钱宇骋
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Xian Jiaotong University
Electric Power Research Institute of State Grid Anhui Electric Power Co Ltd
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Electric Power Research Institute of State Grid Anhui Electric Power Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
    • G01R31/3271—Testing of circuit interrupters, switches or circuit-breakers of high voltage or medium voltage devices
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Abstract

本发明公开了一种用于高压交流断路器振动信号特征参数提取方法，属于高压断路器状态监测与故障诊断领域。通过对振动信号数据应用三次样条拟合作包络线和prony算法提取特征参数相结合，获得振动信号数据的m个特征参数数组[Imk，fk，ak，tNk]，k＝1,2,…,n。将fk、ak作为模态参量进行振动故障模式识别，将Imk用来评估该模式的振动强度，tNk用来表示该模式振动故障发生的时刻。本发明可以快速、准确地提取振动信号特征参数，对机械故障进行模式识别和状态评估。

Figure 202010477132

The invention discloses a method for extracting characteristic parameters of a vibration signal of a high-voltage AC circuit breaker, and belongs to the field of high-voltage circuit breaker state monitoring and fault diagnosis. By applying the cubic spline fitting to the vibration signal data and combining the envelope curve and the prony algorithm to extract the characteristic parameters, the m characteristic parameter arrays [I mk , f k , a k , t Nk ] of the vibration signal data are obtained, k=1 ,2,…,n. Taking f k and a k as modal parameters to identify the vibration failure mode, I mk is used to evaluate the vibration intensity of the mode, and t Nk is used to represent the moment when the vibration failure occurs in this mode. The invention can quickly and accurately extract the characteristic parameters of the vibration signal, and perform pattern recognition and state evaluation on mechanical faults.

Figure 202010477132

Description

Method for extracting vibration signal characteristic parameters of high-voltage alternating-current circuit breaker
The technical field is as follows:
the invention belongs to the field of state monitoring and fault diagnosis of a high-voltage alternating-current circuit breaker, and particularly relates to a vibration signal characteristic parameter extraction method for the high-voltage alternating-current circuit breaker.
Background art:
the high-voltage alternating-current circuit breaker is an important core device for controlling and protecting a power system, and common faults include mechanical faults, insulation faults and overheating faults. Operational experience has shown that mechanical faults account for about 70% of all faults of a high-voltage ac circuit breaker, mechanical faults are the most dominant faults, and circuit breaker operating mechanism faults account for 37% of major faults. The high-voltage circuit breaker often has the faults of loosening of a base screw, loosening of a soft connection clamping piece at the position of a moving contact, abnormal operation of a lock plunger, jamming of a mechanism and the like. Therefore, the state monitoring and fault diagnosis work of the mechanical fault of the high-voltage alternating-current circuit breaker is actively and effectively carried out, the problems existing in the operation can be found in time, the maintenance or overhaul work is arranged, and the equipment utilization rate and the operation and maintenance management level are improved.
Mechanical failure of a high voltage ac circuit breaker typically results in a plurality of vibration events, and the signal excited by the vibration events may be expressed as a plurality of transient unsteady damped vibration signals, i.e. vibration signals
Figure BDA0002516205630000011
In the formula, AiIs the maximum amplitude of the ith vibration event, aiTo be the attenuation coefficient, fiIs the frequency of vibration, tiε (t) is a step function for the moment of the vibration event. Pass through monitorThe vibration signal of the high-voltage measuring circuit breaker is extracted by applying a proper data analysis algorithm, so that the fault mode can be identified and evaluated, and a reliable basis can be provided for overhaul and maintenance. Therefore, the calculation method for rapidly and accurately acquiring the vibration signal characteristic parameter extraction and the fault mode identification is particularly important, and a reliable basis can be provided for further high-voltage circuit breaker state evaluation.
The invention content is as follows:
the invention aims to provide a method for extracting vibration signal characteristic parameters of a high-voltage alternating-current circuit breaker, which can be used for quickly and accurately extracting the vibration signal characteristic parameters and carrying out mode identification and state evaluation on mechanical faults.
The technical scheme adopted by the invention is as follows:
a vibration signal characteristic parameter extraction method for a high-voltage alternating-current circuit breaker comprises the following steps:
s100, vibration signal data (t) acquired on the time axisi,Ai) Constructing a discrete function, namely:
Ai＝f(ti) i＝1,2,…,N (1)
in the formula, t is time, A is vibration signal amplitude, and N is the number of sampling points;
applying the median filter function g to medfilt (y, n) versus the discrete function Ai＝f(ti) Performing noise elimination processing twice, wherein y is discrete data to be filtered, and n is the size of a neighborhood window;
s200, extracting characteristic parameters by applying cubic spline fitting envelope curve to vibration signal data and prony algorithm to be combined to obtain m characteristic parameter arrays [ I ] of the vibration signal datamk，fk，ak，tNk]，k＝1,2,…,n；
S300, assuming that the calculation is terminated after m operations, obtaining m characteristic parameter arrays, namely: [ I ] ofmk，fk，ak，tNk]K is 1,2, …, m; the characteristic parameter fk、akThe mode of vibration is identified as a mode parameter, assuming a typical vibrationThe standard characteristic parameters of the failure modes are Iref、fref、arefDefining the weighted Euclidean distance lambda as:
Figure BDA0002516205630000021
when lambda is less than or equal to epsilon, the typical vibration fault exists; k is a radical of1、k2Is a weight coefficient, and epsilon is an evaluation deviation;
characteristic parameter ImkAnd IrefRatio of
Figure BDA0002516205630000031
Obtaining two kinds of prompt information of failure and warning as the evaluation index of the vibration signal intensity; characteristic parameter tNkIndicating the time when the vibration fault occurs this time.
The invention further improves the following steps: in step S100, the vibration signal acquisition device is composed of an acceleration sensor, an acquisition card, and an upper computer software system.
The invention further improves the following steps: step S200 specifically includes the following steps:
s201, in the first operation, the discrete function A after noise elimination is carried outi＝f(ti) Intercepting a first section of single-frequency vibration data on a time window, namely:
A1i＝f(ti) i＝N1,2,…,N1end (2)
in the formula, N1To intercept the start position of the sampled data, N1endThe end position of the sample data is intercepted;
applying prony algorithm to single-frequency vibration data A1i＝f(ti) And (3) performing operation, and calculating to obtain the single-frequency data characteristic parameters: initial vibration amplitude Im1Frequency f1Attenuation coefficient a1；
And then obtaining a discrete expression of the single-frequency vibration signal as follows:
Figure BDA0002516205630000032
s202, in the second operation, the discrete data A is collectedi＝f(ti) The first single-frequency vibration signal A 'determined by the first operation is stripped'1i；
And then, intercepting a second section of single-frequency vibration data on a time window, namely:
A2i＝f(ti) i＝N2,2,…,N2end (4)
in the formula, N2To intercept the start position of the sampled data, N2endIntercepting the end position of the sampled data;
applying prony algorithm to single-frequency vibration data A2i＝f(ti) And (3) performing operation, and calculating to obtain the single-frequency data characteristic parameters: initial vibration amplitude Im2Frequency f2Attenuation coefficient a2
And further obtaining an analytic expression of the single-frequency vibration signal as follows:
Figure BDA0002516205630000033
s203, during the k-th operation, the discrete data A is collectedi＝f(ti) K-1 single-frequency vibration signals determined k-1 times before stripping
Figure BDA0002516205630000041
And then intercepting the kth section of single-frequency vibration data on a time window, namely:
Aki＝f(ti) i＝Nk,2,…,Nkend (6)
in the formula, NkTo intercept the start position of the sampled data, NkendIntercepting the end position of the sampled data;
applying prony algorithm to single-frequency vibration data Aki＝f(ti) Performing operation and calculationObtaining the single-frequency data characteristic parameters: initial vibration amplitude ImkFrequency fkAttenuation coefficient ak(ii) a The analytical expression of the single-frequency vibration signal is obtained as follows:
Figure BDA0002516205630000043
setting a threshold value gamma, and setting the initial vibration amplitude I of the k-th operationmk<F, the operation is terminated; otherwise, the calculation process of step S203 is repeated.
The invention further improves the following steps: in S201, N1Is a vibration signal (t)i,Ai) Using cubic spline fitting algorithm to obtain vibration signal Ai＝f(ti) Upper and lower envelope s of the peak1、s2Line of mean value
Figure BDA0002516205630000042
When large fluctuation occurs on the time axis, the sampling point N corresponding to the moment is taken1endTo intercept the end position of the sampled data.
The invention further improves the following steps: in S203, k1、k2The values are respectively 0.9 and 0.1, the value range of epsilon is 0-0.3, or the value is set according to field experience values.
The invention further improves the following steps: in S300, when R is more than or equal to 0.8str<1, sending out a fault signal.
The invention further improves the following steps: when R is more than or equal to 0.2str<A warning signal is sent out when the temperature is 0.5 ℃; when R is more than or equal to 0.5str<At 0.8, a fault or warning signal may be issued based on field experience.
Compared with the prior art, the invention at least has the following technical effects:
the invention relates to a method for extracting the characteristic parameters of a vibration signal of a high-voltage alternating-current circuit breaker, which combines the application of cubic spline fitting envelope curve to the vibration signal data and the extraction of the characteristic parameters by a prony algorithm to obtain m characteristic parameter arrays [ I ] of the vibration signal datamk，fk，ak，tNk]And k is 1,2, …, n. Will f isk、akAs modal parameters, identifying the vibration failure modemkFor evaluating the intensity of vibration of the mode, tNkWhich is used to indicate the moment when the mode vibration fault occurs. The invention can quickly and accurately extract the vibration signal characteristic parameters and carry out mode identification and state evaluation on mechanical faults.
Description of the drawings:
FIG. 1 vibration signal data;
FIG. 2 shows the upper and lower envelope lines and the mean line for the first calculation;
fig. 3 vibration signal vibration mode decomposition results.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
A vibration signal characteristic parameter extraction method for a high-voltage alternating-current circuit breaker comprises the following steps:
1) from vibration signal data (t) acquired on the time axisi,Ai) Constructing a discrete function, namely:
Ai＝f(ti) i＝1,2,…,N (1)
in the formula, t is time, A is vibration signal amplitude, and N is the number of sampling points.
Applying the median filter function g to medfilt (y, n) versus the discrete function Ai＝f(ti) And (5) denoising twice, wherein y is discrete data to be filtered, and n is the size of a neighborhood window.
The device for acquiring the vibration signals comprises an acceleration sensor, an acquisition card and an upper computer software system, wherein the acceleration sensor is front-end measurement equipment of the vibration signals, and the vibration signals measured by the acceleration sensor are input into the data acquisition card and transmitted to the upper computer through the acquisition card to acquire and process data.
2) For the first operation, the discrete function A after noise elimination is performedi＝f(ti) Intercepting a first section of single-frequency vibration data on a time window, namely:
A1i＝f(ti) i＝N1,2,…,N1end (2)
in the formula, N1To intercept the start position of the sampled data, N1endThe end position of the sampled data is truncated.
Applying prony algorithm to single-frequency vibration data A1i＝f(ti) And (3) performing operation, and calculating to obtain the single-frequency data characteristic parameters: initial vibration amplitude Im1Frequency f1Attenuation coefficient a1. Further, the discrete expression of the single-frequency vibration signal can be obtained as follows:
Figure BDA0002516205630000061
preferably, in step 2), N1Is a vibration signal (t)i,Ai) Using cubic spline fitting algorithm to obtain vibration signal Ai＝f(ti) Upper and lower envelope s of the peak1、s2Line of mean value
Figure BDA0002516205630000062
When large fluctuation occurs on the time axis, the sampling point N corresponding to the moment is taken1endTo intercept the end position of the sampled data.
3) From the discrete data A collected during the second operationi＝f(ti) The first single-frequency vibration signal A 'determined by the first operation is stripped'1i. Further, intercepting a second segment of single-frequency vibration data on the time window, namely:
A2i＝f(ti) i＝N2,2,…,N2end (4)
in the formula, N2To intercept the start position of the sampled data, N2endTo intercept the end position of the sampled data.
Applying prony algorithm to single-frequency vibration data A2i＝f(ti) And (3) performing operation, and calculating to obtain the single-frequency data characteristic parameters: initial vibration amplitude Im2Frequency f2Attenuation coefficient a2. Further, the analytic expression of the single-frequency vibration signal can be obtained as follows:
Figure BDA0002516205630000071
4) at the k-th operation, discrete data A is collectedi＝f(ti) K-1 single-frequency vibration signals determined k-1 times before stripping
Figure BDA0002516205630000072
Further, intercepting the kth section of single-frequency vibration data on a time window, namely:
Aki＝f(ti) i＝Nk,2,…,Nkend (6)
in the formula, NkTo intercept the start position of the sampled data, NkendTo intercept the end position of the sampled data.
Applying prony algorithm to single-frequency vibration data Aki＝f(ti) And (3) performing operation, and calculating to obtain the single-frequency data characteristic parameters: initial vibration amplitude ImkFrequency fkAttenuation coefficient ak. Further, the analytic expression of the single-frequency vibration signal can be obtained as follows:
Figure BDA0002516205630000073
setting a threshold value gamma, and setting the initial vibration amplitude I of the k-th operationmk<Γ, the operation terminates. Otherwise, repeating the calculation process of the step.
5) Assuming that the calculation is terminated after m operations, m characteristic parameter arrays can be obtained, namely: [ I ] ofmk，fk，ak，tNk]And k is 1,2, …, m. The characteristic parameter fk、akPerforming vibration fault mode identification as modal parameters, and respectively assuming that standard characteristic parameters of typical vibration fault modes are Iref、fref、arefDefining the weighted Euclidean distance lambda as:
Figure BDA0002516205630000074
when λ ≦ ε, this typical vibration failure is indicated. k is a radical of1、k2Is a weight coefficient, and ε is an evaluation deviation.
Characteristic parameter ImkAnd IrefRatio of
Figure BDA0002516205630000075
And obtaining two kinds of prompt information of failure and warning as the evaluation index of the vibration signal intensity. Characteristic parameter tNkIndicating the time when the vibration fault occurs this time.
As a preferred embodiment, k1、k2The values are respectively 0.9 and 0.1, the value range of epsilon is 0-0.3, or the value is set according to field experience values.
When R is more than or equal to 0.8str<When 1, sending out a fault signal; when R is more than or equal to 0.2str<A warning signal is sent out when the temperature is 0.5 ℃; when R is more than or equal to 0.5str<At 0.8, a fault or warning signal may be issued based on field experience.
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
Examples
With reference to fig. 1 to 3, a method for extracting a vibration signal characteristic parameter of a high-voltage alternating-current circuit breaker includes the following steps:
1) according to the vibration signal (t) shown in FIG. 1i,Ai) Constructing a discrete function, namely:
Ai＝f(ti) i＝1,2,…,N (1)
in the formula, t is time, A is vibration signal amplitude, and N is the number of sampling points.
2) For the first operation, for the discrete function Ai＝f(ti) Intercepting a first section of single-frequency vibration data on a time window, namely:
A1i＝f(ti) i＝N1,2,…,N1end (2)
in the formula, N1To intercept the start position of the sampled data, N1endTo intercept the end position of the sampled data. The vibration signal A is derived by applying spline fitting as shown in FIG. 2i＝f(ti) Upper and lower envelope s of the peak1、s2Line of mean value
Figure BDA0002516205630000081
And when large fluctuation occurs on the time axis, taking the sampling point corresponding to the moment as an end position.
Applying prony algorithm to single-frequency vibration data A1i＝f(ti) And (3) performing operation, and calculating to obtain the single-frequency data characteristic parameters: initial vibration amplitude Im1Frequency f1Attenuation coefficient a1. Further, the discrete expression of the single-frequency vibration signal can be obtained as follows:
Figure BDA0002516205630000082
3) from the discrete data A collected during the second operationi＝f(ti) The first single-frequency vibration signal A 'determined by the first operation is stripped'1i. Further, intercepting a second segment of single-frequency vibration data on the time window, namely:
A2i＝f(ti) i＝N2,2,…,N2end (4)
in the formula, N2To intercept the start position of the sampled data, N2endTo intercept the end position of the sampled data.
Applying prony algorithm to single-frequency vibration data A2i＝f(ti) And (3) performing operation, and calculating to obtain the single-frequency data characteristic parameters: initial vibration amplitude Im2Frequency f2Attenuation coefficient a2. Further, the analytic expression of the single-frequency vibration signal can be obtained as follows:
Figure BDA0002516205630000091
4) after 5 times of calculation, 5 vibration modes are obtained after the calculation is terminated, and the characteristic parameters of each mode are shown in the following table:
vibration mode Amplitude (m/s)2) Frequency (Hz) Coefficient of attenuation Moment of oscillation(s)
1 0.15 1000 64.9 0.15
2 0.30 4000 79.9 0.02
3 1.00 6000 70.0 0.025
4 0.50 8000 54.9 0.04
5 0.20 2600 49.6 0.05
6) The characteristic parameter fk、akPerforming vibration fault mode identification as modal parameters, and respectively assuming that standard characteristic parameters of typical vibration fault modes are Iref、fref、arefDefining the weighted Euclidean distance lambda as:
Figure BDA0002516205630000092
when λ ≦ 0.1, this typical vibration failure is indicated. k is a radical of1、k2The values are respectively 0.9 and 0.1, and epsilon is the evaluation deviation.
7) Characteristic parameter ImkAnd IrefRatio of
Figure BDA0002516205630000093
And obtaining two kinds of prompt information of failure and warning as the evaluation index of the vibration signal intensity. When R is more than or equal to 0.8str<When 1, sending out a fault signal; when R is more than or equal to 0.2str<A warning signal is emitted at 0.8.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only show some embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
It is to be understood that the above description is intended to be illustrative, and not restrictive. Many embodiments and many applications other than the examples provided would be apparent to those of skill in the art upon reading the above description. The scope of the present teachings should, therefore, be determined not with reference to the above description, but should instead be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. The disclosures of all articles and references, including patent applications and publications, are hereby incorporated by reference for all purposes. The omission in the foregoing claims of any aspect of subject matter that is disclosed herein is not intended to forego such subject matter, nor should the applicant consider that such subject matter is not considered part of the disclosed subject matter.

Claims (6)

1.一种用于高压交流断路器振动信号特征参数提取方法，其特征在于，包括以下步骤：1. a method for extracting characteristic parameters of vibration signal of high-voltage AC circuit breaker, is characterized in that, comprises the following steps: S100，根据时间轴上采集得到的振动信号数据(ti,Ai)，构造离散函数，即：S100, according to the vibration signal data (t i , A i ) collected on the time axis, construct a discrete function, namely: Ai＝f(ti) i＝1,2,…,N (1)A i =f(t i ) i=1,2,...,N (1) 式中，t为时间，A为振动信号幅值，N为采样点数；In the formula, t is the time, A is the amplitude of the vibration signal, and N is the number of sampling points; 应用中值滤波函数g＝medfilt(y,n)对离散函数Ai＝f(ti)进行两次消噪处理，y为待滤波离散数据，n为邻域窗口的大小；Apply the median filter function g=medfilt(y,n) to denoise the discrete function A i =f(t i ) twice, y is the discrete data to be filtered, and n is the size of the neighborhood window; S200，通过对振动信号数据应用三次样条拟合作包络线和prony算法提取特征参数相结合，获得振动信号数据的m个特征参数数组[Imk，fk，ak，tNk]，k＝1,2,…,n；S200, by applying the cubic spline fitting envelope to the vibration signal data and combining the characteristic parameters extracted by the prony algorithm to obtain m characteristic parameter arrays [I mk , f k , a k , t Nk ], k of the vibration signal data =1,2,...,n; S300，假定经过m次运算后计算终止，得到m个特征参数数组，即：[Imk，fk，ak，tNk]，k＝1,2,…,m；将特征参数fk、ak作为模态参量进行振动故障模式识别，假定典型振动故障模式标准特征参数分别为Iref、fref、aref，定义加权欧式距离λ为：S300, it is assumed that the calculation is terminated after m operations, and m characteristic parameter arrays are obtained, namely: [I mk , f k , a k , t Nk ], k=1, 2, ..., m; the characteristic parameters f k , A k is used as a modal parameter to identify the vibration failure mode. Assuming that the standard characteristic parameters of the typical vibration failure mode are I ref , f ref , and a ref , the weighted Euclidean distance λ is defined as:
Figure FDA0003212932040000011
Figure FDA0003212932040000011
 当λ≤ε时，则表示存在所述典型振动故障模式；k1、k2为权重系数，ε为评价偏差；When λ≤ε, it means that the typical vibration failure mode exists; k 1 and k 2 are the weight coefficients, and ε is the evaluation deviation; 将特征参数Imk和Iref比值
Figure FDA0003212932040000012
作为本次振动信号强度的评价指标，得出故障和警告两种提示信息；特征参数tNk表示本次振动故障发生的时刻；Ratio of characteristic parameters I mk to I ref
Figure FDA0003212932040000012
As the evaluation index of the current vibration signal strength, two kinds of prompt information, fault and warning, are obtained; the characteristic parameter t Nk represents the moment when the vibration fault occurs; 步骤S200具体包括以下步骤：Step S200 specifically includes the following steps: S201，第一次运算时，对消噪后的离散函数Ai＝f(ti)在时间窗口上截取第一段单频振动数据，即：S201, in the first operation, intercept the first segment of single-frequency vibration data on the time window for the discrete function A i =f(t i ) after denoising, namely: A1i＝f(ti) i＝N1,2,…,N1end (2)A 1i =f(t i ) i=N 1 ,2,...,N 1end (2) 式中，N1为截取采样数据的起始位置，N1end为截取样采样数据的结束位置；In the formula, N 1 is the starting position of the intercepted sampling data, and N 1end is the end position of the intercepted sampling data; 应用prony算法对单频振动数据A1i＝f(ti)进行运算，计算得出第一段单频振动数据的特征参数：起始振动幅值Im1、频率f1、衰减系数a1；The single-frequency vibration data A 1i =f(t i ) is operated by applying the prony algorithm, and the characteristic parameters of the first segment of the single-frequency vibration data are calculated: initial vibration amplitude I m1 , frequency f 1 , attenuation coefficient a 1 ; 进而得出单频振动数据的离散表达式为：Then, the discrete expression of single-frequency vibration data is obtained as:
Figure FDA0003212932040000021
Figure FDA0003212932040000021
 S202，第二次运算时，从采集到的离散数据Ai＝f(ti)中剥离掉第一次运算所确定的第一个单频振动信号A′1i；S202, during the second operation, strip off the first single-frequency vibration signal A′ 1i determined by the first operation from the collected discrete data A i =f(t i ); 进而，在时间窗口上截取第二段单频振动数据，即：Further, intercept the second segment of single-frequency vibration data on the time window, namely: A2i＝f(ti) i＝N2,2,…,N2end (4)A 2i =f(t i ) i=N 2 ,2,...,N 2end (4) 式中，N2为截取采样数据的起始位置，N2end为截取采样数据的结束位置；In the formula, N 2 is the starting position of the intercepted sampling data, and N 2end is the end position of the intercepted sampling data; 应用prony算法对单频振动数据A2i＝f(ti)进行运算，计算得出第二段单频振动数据的特征参数：起始振动幅值Im2、频率f2、衰减系数a2 Apply the prony algorithm to the single-frequency vibration data A 2i =f(t i ), and calculate the characteristic parameters of the second single-frequency vibration data: initial vibration amplitude I m2 , frequency f 2 , attenuation coefficient a 2 进而得出第二段单频振动数据的解析表达式为：Then the analytical expression of the second single-frequency vibration data is obtained as:
Figure FDA0003212932040000022
Figure FDA0003212932040000022
 S203，第k次运算时，从采集到的离散数据Ai＝f(ti)中剥离掉前k-1次所确定的k-1个单频振动信号
Figure FDA0003212932040000023
进而在时间窗口上截取第k段单频振动数据，即：S203, during the k-th operation, strip off the k-1 single-frequency vibration signals determined in the previous k-1 times from the collected discrete data A i =f(t i ).
Figure FDA0003212932040000023
Then, intercept the k-th single-frequency vibration data on the time window, namely: Aki＝f(ti) i＝Nk,2,…,Nkend (6)A ki =f(t i ) i=N k ,2,...,N kend (6) 式中，Nk为截取采样数据的起始位置，Nkend为截取采样数据的结束位置；In the formula, N k is the starting position of the intercepted sampling data, and N kend is the end position of the intercepted sampling data; 应用prony算法对单频振动数据Aki＝f(ti)进行运算，计算得出k-1个单频振动数据的特征参数：起始振动幅值Imk、频率fk、衰减系数ak；得出k-1个单频振动数据的解析表达式为:Apply the prony algorithm to the single-frequency vibration data A ki =f(t i ), and calculate the characteristic parameters of k-1 single-frequency vibration data: initial vibration amplitude I mk , frequency f k , attenuation coefficient a k ; The analytical expression of k-1 single-frequency vibration data is obtained as:
Figure FDA0003212932040000031
Figure FDA0003212932040000031
 设定阈值Γ，当第k次运算的起始振动幅值Imk＜Γ时，运算终止；否则，重复步骤S203的计算过程。The threshold Γ is set, and when the initial vibration amplitude I mk < Γ of the k-th calculation, the calculation is terminated; otherwise, the calculation process of step S203 is repeated. 2.根据权利要求1所述的一种用于高压交流断路器振动信号特征参数提取方法，其特征在于：步骤S100中，振动信号的采集装置由加速度传感、采集卡和上位机软件系统组成。2. A method for extracting characteristic parameters of a vibration signal of a high-voltage AC circuit breaker according to claim 1, characterized in that: in step S100, the acquisition device of the vibration signal is composed of an acceleration sensor, an acquisition card and a host computer software system . 3.根据权利要求1所述的一种用于高压交流断路器振动信号特征参数提取方法，其特征在于：S201中，N1为振动信号(ti,Ai)的起始位置，应用三次样条拟合算法得出振动信号Ai＝f(ti)峰值的上、下包络线s1、s2，当均值线
Figure FDA0003212932040000032
在时间轴上的发生较大波动时，取该时刻对应的采样点N1end为截取采样数据的结束位置。3. a kind of method for extracting characteristic parameters of vibration signal of high-voltage AC circuit breaker according to claim 1, is characterized in that: in S201, N 1 is the starting position of vibration signal (t i , A i ), applied three times The spline fitting algorithm obtains the upper and lower envelopes s 1 and s 2 of the peak value of the vibration signal A i = f(t i ), when the mean line
Figure FDA0003212932040000032
When a large fluctuation occurs on the time axis, the sampling point N 1end corresponding to this moment is taken as the end position of intercepting the sampling data. 4.根据权利要求1所述的一种用于高压交流断路器振动信号特征参数提取方法，其特征在于：S203中，k1、k2分别取值为0.9和0.1，ε的取值范围为0～0.3，或依据现场经验值设定。4. A method for extracting characteristic parameters of a high-voltage AC circuit breaker vibration signal according to claim 1, wherein in S203, k 1 and k 2 are respectively 0.9 and 0.1, and the value range of ε is 0～0.3, or set according to the field experience value. 5.根据权利要求1所述的一种用于高压交流断路器振动信号特征参数提取方法，其特征在于：当0.8≤Rstr＜1时，发出故障信号。5 . The method for extracting characteristic parameters of a vibration signal of a high-voltage AC circuit breaker according to claim 1 , wherein: when 0.8≦ Rstr <1, a fault signal is sent. 6 . 6.根据权利要求5所述的一种用于高压交流断路器振动信号特征参数提取方法，其特征在于：当0.2≤Rstr＜0.5时发出警告信号；当0.5≤Rstr＜0.8时，可依据现场经验决定发出故障或警告信号。6. A method for extracting characteristic parameters of vibration signals of high-voltage AC circuit breakers according to claim 5, characterized in that: when 0.2≤Rstr <0.5, a warning signal is issued; when 0.5≤Rstr <0.8, it can be Issue a fault or warning signal based on field experience.
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