CN111579059A - Transformer state vibration and sound detection signal reconstruction method and system by utilizing quadratic approximation - Google Patents

Transformer state vibration and sound detection signal reconstruction method and system by utilizing quadratic approximation Download PDF

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CN111579059A
CN111579059A CN202010480862.4A CN202010480862A CN111579059A CN 111579059 A CN111579059 A CN 111579059A CN 202010480862 A CN202010480862 A CN 202010480862A CN 111579059 A CN111579059 A CN 111579059A
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翟明岳
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Guangdong University of Petrochemical Technology
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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
    • G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
    • G01R31/1209—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing using acoustic measurements
    • 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
    • G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
    • G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials

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Abstract

The embodiment of the invention discloses a method and a system for reconstructing a transformer state vibration and sound detection signal by utilizing quadratic approximation, wherein the method comprises the following steps: step 101, acquiring a signal sequence S acquired according to a time sequence; step 102, solving a correction factor lambda; step 103, calculating an initial value x of an error reconstruction sequence0(ii) a 104, assigning an iteration control parameter k as 1; step 105 finds the k-th step x of the error reconstruction sequencek(ii) a Step 106, solving an iteration error e; step 107, determining whether the iteration error e is greater than or equal to a preset threshold0And obtaining a first judgment result. If the first judgment result shows that the iteration error e is greater than or equal to the preset threshold value0Then the value of the iterative control parameter k is increased by 1 and returns to the step 104, the step 105, the step 106 and the stepStep 107, until the first judgment result shows that the iteration error e is smaller than the preset threshold value0. Wherein the preset threshold is00.001; step 108 of obtaining the reconstructed signal sequence SNEW(ii) a In particular SNEW＝S‑xk。

Description

Transformer state vibration and sound detection signal reconstruction method and system by utilizing quadratic approximation
Technical Field
The invention relates to the field of electric power, in particular to a reconstruction method and a reconstruction system of a vibration sound signal of a transformer.
Background
With the high-speed development of the smart grid, the safe and stable operation of the power equipment is particularly important. At present, the detection of the operating state of the power equipment with ultrahigh voltage and above voltage grades, especially the detection of the abnormal state, is increasingly important and urgent. As an important component of an electric power system, a power transformer is one of the most important electrical devices in a substation, and its reliable operation is related to the safety of a power grid. Generally, the abnormal state of the transformer can be divided into core abnormality and winding abnormality. The core abnormality is mainly represented by core saturation, and the winding abnormality generally includes winding deformation, winding looseness and the like.
The basic principle of the transformer abnormal state detection is to extract each characteristic quantity in the operation of the transformer, analyze, identify and track the characteristic quantity so as to monitor the abnormal operation state of the transformer. The detection method can be divided into invasive detection and non-invasive detection according to the contact degree; the detection can be divided into live detection and power failure detection according to whether the shutdown detection is needed or not; the method can be classified into an electrical quantity method, a non-electrical quantity method, and the like according to the type of the detected quantity. In comparison, the non-invasive detection has strong transportability and is more convenient to install; the live detection does not affect the operation of the transformer; the non-electric quantity method is not electrically connected with the power system, so that the method is safer. The current common detection methods for the operation state of the transformer include a pulse current method and an ultrasonic detection method for detecting partial discharge, a frequency response method for detecting winding deformation, a vibration detection method for detecting mechanical and electrical faults, and the like. The detection methods mainly detect the insulation condition and the mechanical structure condition of the transformer, wherein the detection of the vibration signal (vibration sound) of the transformer is the most comprehensive, and the fault and the abnormal state of most transformers can be reflected.
In the running process of the transformer, the magnetostriction of the iron core silicon steel sheets and the vibration caused by the winding electrodynamic force can radiate vibration sound signals with different amplitudes and frequencies to the periphery. When the transformer normally operates, uniform low-frequency noise is emitted outwards; if the sound is not uniform, it is not normal. The transformer can make distinctive sounds in different running states, and the running state of the transformer can be mastered by detecting the sounds made by the transformer. It is worth noting that the detection of the sound emitted by the transformer in different operating states not only can detect a plurality of serious faults causing the change of the electrical quantity, but also can detect a plurality of abnormal states which do not endanger the insulation and do not cause the change of the electrical quantity, such as the loosening of internal and external parts of the transformer, and the like.
Disclosure of Invention
As mentioned above, the vibration and sound detection method utilizes the vibration signal emitted by the transformer, which is easily affected by the working environment, resulting in interruption of signal transmission and severe degradation of signal quality, so that the received partial vibration and sound signal cannot be used, and therefore how to effectively reconstruct the vibration and sound signal of the transformer is an important constraint factor for successful application of the method. The existing common method has insufficient attention to the problem, and no effective measure is taken to solve the problem.
The invention aims to provide a method and a system for reconstructing a transformer state vibration and sound detection signal by utilizing quadratic approximation. The method has better signal reconstruction performance and simpler calculation.
In order to achieve the purpose, the invention provides the following scheme:
a transformer state vibration and sound detection signal reconstruction method using quadratic approximation comprises the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102 finds a correction factor λ, specifically
Figure BDA0002517310650000021
Wherein m is0Is the mean of the signal sequence S; Δ T is the sampling interval of the signal sequence S; max S is the maximum value of the signal sequence S; min S is the minimum value of the signal sequence S;
step 103, calculating an initial value x of an error reconstruction sequence0Specifically, the error reconstruction sequence initial value x0A zero vector of length N; n is the length of the signal sequence S;
104, assigning an iteration control parameter k as 1;
step 105 finds the k-th step x of the error reconstruction sequencekThe method specifically comprises the following steps:
Figure BDA0002517310650000022
Figure BDA0002517310650000023
wherein x isk-1Reconstructing the k-1 step value of the sequence for the error;
Figure BDA0002517310650000024
is a first order difference with the value of the 1 st element being 0 and the value of the ith element being
Figure BDA0002517310650000025
siIs the i-th element, S, of the signal sequence Si-1The element is the i-1 th element of the signal sequence S, i is the first serial number of the element, and the value range of i is 2,3, ·, N;
Figure BDA0002517310650000026
is a second order difference with the value of the 1 st and 2 nd elements being 0 and the value of the jth element being
Figure BDA0002517310650000027
sjIs the jth element, S, of the signal sequence Sj-2J is the j-2 th element of the signal sequence S, and is the second serial number of the element, and the value range of j is 3,4, ·, N;
step 106 finds an iteration error e, specifically e ═ xk-xk-1|；
Step 107, determining whether the iteration error e is greater than or equal to a preset threshold0And obtaining a first judgment result. If the first judgment result shows that the iteration error e is greater than or equal to the preset threshold value0Adding 1 to the value of the iteration control parameter k and returning to the step 104, the step 105, the step 106 and the step 107 until the first judgment result shows that the iteration error e is smaller than the preset threshold value0. Wherein the preset threshold is0＝0.001；
Step 108 of obtaining the reconstructed signal sequence SNEW(ii) a In particular SNEW＝S-xk。
A transformer state vibro-acoustic detection signal reconstruction system using quadratic approximation, comprising:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 finds a correction factor λ, in particular
Figure BDA0002517310650000028
Wherein m is0Is the mean of the signal sequence S; Δ T is the sampling interval of the signal sequence S; max S is the maximum value of the signal sequence S; min S is the minimum value of the signal sequence S;
module 203 finds the initial value x of the error reconstruction sequence0Specifically, the error reconstruction sequence initial value x0A zero vector of length N; n is the length of the signal sequence S;
the module 204 iterates the assignment of the control parameter k to 1;
the module 205 finds the k-th step x of the error reconstruction sequencekThe method specifically comprises the following steps:
Figure BDA0002517310650000029
Figure BDA00025173106500000210
wherein x isk-1Reconstructing the k-1 step value of the sequence for the error;
Figure BDA00025173106500000211
is a first order difference with the value of the 1 st element being 0 and the value of the ith element being
Figure BDA00025173106500000212
siIs the i-th element, S, of the signal sequence Si-1The element is the i-1 th element of the signal sequence S, i is the first serial number of the element, and the value range of i is 2,3, ·, N;
Figure BDA00025173106500000213
is a second order difference with the value of the 1 st and 2 nd elements being 0 and the value of the jth element being
Figure BDA0002517310650000031
sjIs the jth element, S, of the signal sequence Sj-2Being said signal sequence SJ is the second serial number of the element, and the value range of j is 3,4, and N;
the module 206 finds the iteration error e, specifically e ═ xk-xk-1|；
The module 207 determines whether the iteration error e is greater than or equal to a preset threshold0And obtaining a first judgment result. If the first judgment result shows that the iteration error e is greater than or equal to the preset threshold value0If so, the value of the iteration control parameter k is added by 1 and returned to the module 204, the module 205, the module 206, and the module 207 until the first judgment result shows that the iteration error e is smaller than the preset threshold value0. Wherein the preset threshold is0＝0.001；
Module 208 finds the reconstructed signal sequence SNEW(ii) a In particular SNEW＝S-xk。
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
as mentioned above, the vibration and sound detection method utilizes the vibration signal emitted by the transformer, which is easily affected by the working environment, resulting in interruption of signal transmission and severe degradation of signal quality, so that the received partial vibration and sound signal cannot be used, and therefore how to effectively reconstruct the vibration and sound signal of the transformer is an important constraint factor for successful application of the method. The existing common method has insufficient attention to the problem, and no effective measure is taken to solve the problem.
The invention aims to provide a method and a system for reconstructing a transformer state vibration and sound detection signal by utilizing quadratic approximation. The method has better signal reconstruction performance and simpler calculation.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic flow chart of the system of the present invention;
FIG. 3 is a flow chart illustrating an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
FIG. 1 is a schematic flow chart of a method for reconstructing a transformer state vibration and sound detection signal by utilizing quadratic approximation
Fig. 1 is a schematic flow chart of a method for reconstructing a transformer state vibration and sound detection signal by using quadratic approximation according to the present invention. As shown in fig. 1, the method for reconstructing a transformer state vibration and sound detection signal by using quadratic approximation specifically includes the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102 finds a correction factor λ, specifically
Figure BDA0002517310650000041
Wherein m is0Is the mean of the signal sequence S; Δ T is the sampling interval of the signal sequence S; max S is the maximum value of the signal sequence S; min S is the minimum value of the signal sequence S;
step 103, calculating an initial value x of an error reconstruction sequence0In particularReconstructing an initial value x of the sequence for said error0A zero vector of length N; n is the length of the signal sequence S;
104, assigning an iteration control parameter k as 1;
step 105 finds the k-th step x of the error reconstruction sequencekThe method specifically comprises the following steps:
Figure BDA0002517310650000042
Figure BDA0002517310650000043
wherein x isk-1Reconstructing the k-1 step value of the sequence for the error;
Figure BDA0002517310650000044
is a first order difference with the value of the 1 st element being 0 and the value of the ith element being
Figure BDA0002517310650000045
siIs the i-th element, S, of the signal sequence Si-1The element is the i-1 th element of the signal sequence S, i is the first serial number of the element, and the value range of i is 2,3, ·, N;
Figure BDA0002517310650000046
is a second order difference with the value of the 1 st and 2 nd elements being 0 and the value of the jth element being
Figure BDA0002517310650000047
sjIs the jth element, S, of the signal sequence Sj-2J is the j-2 th element of the signal sequence S, and is the second serial number of the element, and the value range of j is 3,4, ·, N;
step 106 finds an iteration error e, specifically e ═ xk-xk-1|；
Step 107, determining whether the iteration error e is greater than or equal to a preset threshold0And obtaining a first judgment result. If the first judgment result shows that the iteration error e is greater than or equal to the preset threshold value0Then the value of the iterative control parameter k is added by 1 and the step is returned to104. The step 105, the step 106 and the step 107 are performed until the first judgment result shows that the iteration error e is smaller than the preset threshold value0. Wherein the preset threshold is0＝0.001；
Step 108 of obtaining the reconstructed signal sequence SNEW(ii) a In particular SNEW＝S-xk。
FIG. 2 is a structural intention of a transformer state vibration and sound detection signal reconstruction system using quadratic approximation
Fig. 2 is a schematic structural diagram of a transformer state vibro-acoustic detection signal reconstruction system using quadratic approximation according to the present invention. As shown in fig. 2, the system for reconstructing a transformer state vibro-acoustic detection signal by using quadratic approximation includes the following structures:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 finds a correction factor λ, in particular
Figure BDA0002517310650000048
Wherein m is0Is the mean of the signal sequence S; Δ T is the sampling interval of the signal sequence S; max S is the maximum value of the signal sequence S; min S is the minimum value of the signal sequence S;
module 203 finds the initial value x of the error reconstruction sequence0Specifically, the error reconstruction sequence initial value x0A zero vector of length N; n is the length of the signal sequence S;
the module 204 iterates the assignment of the control parameter k to 1;
the module 205 finds the k-th step x of the error reconstruction sequencekThe method specifically comprises the following steps:
Figure BDA0002517310650000051
Figure BDA0002517310650000052
wherein x isk-1Reconstructing the k-1 step value of the sequence for the error;
Figure BDA0002517310650000053
is a first order difference with the value of the 1 st element being 0 and the value of the ith element being
Figure BDA0002517310650000054
siIs the i-th element, S, of the signal sequence Si-1The element is the i-1 th element of the signal sequence S, i is the first serial number of the element, and the value range of i is 2,3, ·, N;
Figure BDA0002517310650000055
is a second order difference with the value of the 1 st and 2 nd elements being 0 and the value of the jth element being
Figure BDA0002517310650000056
sjIs the jth element, S, of the signal sequence Sj-2J is the j-2 th element of the signal sequence S, and is the second serial number of the element, and the value range of j is 3,4, ·, N;
the module 206 finds the iteration error e, specifically e ═ xk-xk-1|；
The module 207 determines whether the iteration error e is greater than or equal to a preset threshold0And obtaining a first judgment result. If the first judgment result shows that the iteration error e is greater than or equal to the preset threshold value0If so, the value of the iteration control parameter k is added by 1 and returned to the module 204, the module 205, the module 206, and the module 207 until the first judgment result shows that the iteration error e is smaller than the preset threshold value0. Wherein the preset threshold is0＝0.001；
Module 208 finds the reconstructed signal sequence SNEW(ii) a In particular SNEW＝S-xk。
The following provides an embodiment for further illustrating the invention
FIG. 3 is a flow chart illustrating an embodiment of the present invention. As shown in fig. 3, the method specifically includes the following steps:
step 301, acquiring a signal sequence S acquired according to a time sequence;
step 302 calculates a correction factor λIs concretely provided with
Figure BDA0002517310650000057
Wherein m is0Is the mean of the signal sequence S; Δ T is the sampling interval of the signal sequence S; max S is the maximum value of the signal sequence S; min S is the minimum value of the signal sequence S;
step 303 finds an initial value x of an error reconstruction sequence0Specifically, the error reconstruction sequence initial value x0A zero vector of length N; n is the length of the signal sequence S;
step 304, the iteration control parameter k is assigned to 1;
step 305 finds the k-th step x of the error reconstruction sequencekThe method specifically comprises the following steps:
Figure BDA0002517310650000058
Figure BDA0002517310650000059
wherein x isk-1Reconstructing the k-1 step value of the sequence for the error;
Figure BDA00025173106500000510
is a first order difference with the value of the 1 st element being 0 and the value of the ith element being
Figure BDA00025173106500000511
siIs the i-th element, S, of the signal sequence Si-1The element is the i-1 th element of the signal sequence S, i is the first serial number of the element, and the value range of i is 2,3, ·, N;
Figure BDA00025173106500000512
is a second order difference with the value of the 1 st and 2 nd elements being 0 and the value of the jth element being
Figure BDA00025173106500000513
sjIs the jth element, S, of the signal sequence Sj-2J is the j-2 th element of the signal sequence S, and the value range of j is 3,4 · · and the second sequence number of the element,N；
Step 306 calculates an iteration error e, specifically, e ═ xk-xk-1|；
Step 307 determines whether the iteration error e is greater than or equal to a predetermined threshold0And obtaining a first judgment result. If the first judgment result shows that the iteration error e is greater than or equal to the preset threshold value0Adding 1 to the value of the iteration control parameter k and returning to the step 304, the step 305, the step 306 and the step 307 until the first judgment result shows that the iteration error e is smaller than the preset threshold value0. Wherein the preset threshold is0＝0.001；
Step 308 finds the reconstructed signal sequence SNEW(ii) a In particular SNEW＝S-xk。
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is simple because the system corresponds to the method disclosed by the embodiment, and the relevant part can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (2)

1. The method for reconstructing the transformer state vibration and sound detection signal by utilizing quadratic approximation is characterized by comprising the following steps of:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102 finds a correction factor λ, specifically
Figure FDA0002517310640000011
Wherein m is0Is the mean of the signal sequence S; Δ T is the sampling interval of the signal sequence S; max S is the maximum value of the signal sequence S; min S is the minimum value of the signal sequence S;
step 103, calculating an initial value x of an error reconstruction sequence0Specifically, the error reconstruction sequence initial value x0A zero vector of length N; n is the length of the signal sequence S;
104, assigning an iteration control parameter k as 1;
step 105 finds the k-th step x of the error reconstruction sequencekThe method specifically comprises the following steps:
Figure FDA0002517310640000012
Figure FDA0002517310640000013
wherein x isk-1Reconstructing the k-1 step value of the sequence for the error;
Figure FDA0002517310640000014
is a first order difference with the value of the 1 st element being 0 and the value of the ith element being
Figure FDA0002517310640000015
siIs the i-th element, S, of the signal sequence Si-1The element is the i-1 th element of the signal sequence S, i is the first serial number of the element, and the value range of i is 2,3, ·, N;
Figure FDA0002517310640000016
is a second order difference with the value of the 1 st and 2 nd elements being 0 and the value of the jth element being
Figure FDA0002517310640000017
sjIs the jth element, S, of the signal sequence Sj-2J is the j-2 th element of the signal sequence S, and is the second serial number of the element, and the value range of j is 3,4, ·, N;
step 106 finds an iteration error e, specifically e ═ xk-xk-1|；
Step 107, determining whether the iteration error e is greater than or equal to a preset threshold0And obtaining a first judgment result. If the first judgment result shows that the iteration error e is greater than or equal to the preset threshold value0Adding 1 to the value of the iteration control parameter k and returning to the step 104, the step 105, the step 106 and the step 107 until the first judgment result shows that the iteration error e is smaller than the preset threshold value0. Wherein the preset threshold is0＝0.001；
Step 108 of obtaining the reconstructed signal sequence SNEW(ii) a In particular SNEW＝S-xk。
2. The system for reconstructing the transformer state vibration and sound detection signal by utilizing quadratic approximation is characterized by comprising the following steps of:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 finds a correction factor λ, in particular
Figure FDA0002517310640000018
Wherein m is0Is the mean of the signal sequence S; Δ T is the sampling interval of the signal sequence S; maxS is the maximum value of the signal sequence S; min S is the minimum value of the signal sequence S;
module 203 finds the initial value x of the error reconstruction sequence0Specifically, the error reconstruction sequence initial value x0A zero vector of length N; n is the length of the signal sequence S;
the module 204 iterates the assignment of the control parameter k to 1;
the block 205 finds the k-th step x of the error reconstruction sequencekThe method specifically comprises the following steps:
Figure FDA0002517310640000021
Figure FDA0002517310640000022
wherein x isk-1Reconstructing the k-1 step value of the sequence for the error;
Figure FDA0002517310640000023
is a first order difference with the value of the 1 st element being 0 and the value of the ith element being
Figure FDA0002517310640000024
siIs the i-th element, S, of the signal sequence Si-1The element is the i-1 th element of the signal sequence S, i is the first serial number of the element, and the value range of i is 2,3, ·, N;
Figure FDA0002517310640000025
is a second order difference with the value of the 1 st and 2 nd elements being 0 and the value of the jth element being
Figure FDA0002517310640000026
sjIs the jth element, S, of the signal sequence Sj-2J is the j-2 th element of the signal sequence S, and is the second serial number of the element, and the value range of j is 3,4, ·, N;
the module 206 finds the iteration error e, specifically e ═ xk-xk-1|；
The module 207 determines whether the iteration error e is greater than or equal to a preset threshold0And obtaining a first judgment result. If the first judgment result shows that the iteration error e is greater than or equal to the preset threshold value0If so, the value of the iteration control parameter k is added by 1 and returned to the module 204, the module 205, the module 206, and the module 207 until the first judgment result shows that the iteration error e is smaller than the preset threshold value0. Wherein the preset threshold is0＝0.001；
Module 208 finds the reconstructed signal sequence SNEW(ii) a In particular SNEW＝S-xk。
CN202010480862.4A 2020-05-30 2020-05-30 Transformer state vibration and sound detection signal reconstruction method and system by utilizing quadratic approximation Withdrawn CN111579059A (en)

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