CN112327084B - Method and system for detecting vibration and sound of running state of transformer by utilizing equidistant transformation - Google Patents

Method and system for detecting vibration and sound of running state of transformer by utilizing equidistant transformation Download PDF

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CN112327084B
CN112327084B CN202011206341.6A CN202011206341A CN112327084B CN 112327084 B CN112327084 B CN 112327084B CN 202011206341 A CN202011206341 A CN 202011206341A CN 112327084 B CN112327084 B CN 112327084B
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signal sequence
transformer
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equidistant
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CN112327084A (en
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翟明岳
孙海龙
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North China Electric Power University
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    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
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Abstract

The embodiment of the invention discloses a method and a system for detecting vibration and sound of a running state of a transformer by utilizing equidistant transformation, wherein the method comprises the following steps: step 101, acquiring a signal sequence S acquired according to a time sequence; step 102, calculating a delay length; step 103, obtaining N window signal sequences; 104, solving N central logarithmic transformation vectors; step 105, obtaining N equidistant transformation values; step 106 judges the running state of the transformer.

Description

Method and system for detecting vibration and sound of running state of transformer by utilizing equidistant transformation
Technical Field
The invention relates to the field of electric power, in particular to a method and a system for detecting vibration and sound of a transformer in an operation state.
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.
The basic principle of the transformer operation state detection is to extract each characteristic quantity in the transformer operation, analyze, identify and track the characteristic quantity so as to monitor the abnormal operation state of the transformer. 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.
Although the transformer vibration and sound detection method is widely applied to monitoring the running state of the transformer and the technology is relatively mature, the vibration and sound detection method utilizes the vibration signal sent by the transformer and is easily influenced by the environmental noise, so that the method often cannot obtain satisfactory results when being applied in the actual working environment.
Disclosure of Invention
As mentioned above, the transformer vibration and noise detection method is widely applied to monitoring the operation state of the transformer, and the technology is relatively mature, but because the vibration and noise detection method utilizes the vibration signal emitted by the transformer, the vibration and noise detection method is easily affected by the environmental noise, and therefore, the method often fails to obtain satisfactory results when being applied in the actual working environment.
The invention aims to provide a transformer running state vibration and sound detection method and system by utilizing isometric transformation. The method has better robustness and simpler calculation.
In order to achieve the purpose, the invention provides the following scheme:
a method for detecting vibration and sound of an operation state of a transformer by utilizing equidistant transformation comprises the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102, calculating a delay length, specifically:
the delay length is denoted as M, and the formula used is:
Figure BDA0002757207900000011
wherein:
Figure BDA0002757207900000012
presentation pair
Figure BDA0002757207900000013
The upper part is taken to be the whole,
n is the length of the signal sequence S,
snr is the signal-to-noise ratio of the signal sequence S;
step 103, obtaining N window signal sequences, specifically: the nth window signal sequence is denoted by bnThe ith element of which is
Figure BDA0002757207900000021
The solving formula is as follows:
Figure BDA0002757207900000022
wherein:
n is 1,2, N is a window serial number,
i is 1,2, N is element number,
s|i+(n-1)M|Nis the | i + (n-1) M & lt of the signal sequence SNThe number of the elements is one,
|i+(n-1)M|Nrepresenting that the remainder is taken by i + (N-1) M by taking N as a modulus;
step 104, obtaining N central logarithmic transformation vectors, specifically: the nth center logarithm transformation vector is recorded as ynThe ith element of which is
Figure BDA0002757207900000023
The solving formula is as follows:
Figure BDA0002757207900000024
wherein:
m0is the mean value of the signal sequence S,
l is 1,2, N is summation parameter,
Figure BDA0002757207900000025
for the nth window signal sequence bnThe l element of (1);
step 105, obtaining N equidistant transformation values, specifically: the nth equidistant transformation value is recorded as hnThe formula used is:
hn＝||Uyn||F
wherein:
u is an equidistant transformation matrix, and the ith row and the jth column of the equidistant transformation matrix are marked as UijThe obtaining method comprises the following steps: when i is less than or equal to j, uij1 is ═ 1; when j is i +1, uij-i ═ i; when i is>j +1, uij＝0；||Uyn||FRepresents UynThe Frobenus moustache of (1);
step 106, judging the running state of the transformer, specifically: if the nth equidistant transform value hnIs greater than or equal to
Figure BDA0002757207900000026
The transformer is in an abnormal operation state at the nth point of the signal sequence S; otherwise the transformerIn a normal operation state; wherein the content of the first and second substances,
Figure BDA0002757207900000027
to represent
Figure BDA0002757207900000028
The Frobenus moudle of (1).
A transformer operating condition vibro-acoustic detection system using equidistant transformation, comprising:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 calculates the delay length, specifically:
the delay length is denoted as M, and the formula used is:
Figure BDA0002757207900000031
wherein:
Figure BDA0002757207900000032
presentation pair
Figure BDA0002757207900000033
The upper part is taken to be the whole,
n is the length of the signal sequence S,
snr is the signal-to-noise ratio of the signal sequence S;
the module 203 calculates N window signal sequences, specifically: the nth window signal sequence is denoted by bnThe ith element of which is
Figure BDA0002757207900000034
The solving formula is as follows:
Figure BDA0002757207900000035
wherein:
n is 1,2, N is a window serial number,
i is 1,2, N is element number,
s|i+(n-1)M|Nis the | i + (n-1) M & lt of the signal sequence SNThe number of the elements is one,
|i+(n-1)M|Nrepresenting that the remainder is taken by i + (N-1) M by taking N as a modulus;
the module 204 calculates N central logarithmic transformation vectors, specifically: the nth center logarithm transformation vector is recorded as ynThe ith element of which is
Figure BDA0002757207900000036
The solving formula is as follows:
Figure BDA0002757207900000037
wherein:
m0is the mean value of the signal sequence S,
l is 1,2, N is summation parameter,
Figure BDA0002757207900000038
for the nth window signal sequence bnThe l element of (1);
the module 205 finds N equidistant transformation values, specifically: the nth equidistant transformation value is recorded as hnThe formula used is:
hn＝||Uyn||F
wherein:
u is an equidistant transformation matrix, and the ith row and the jth column of the equidistant transformation matrix are marked as UijThe obtaining method comprises the following steps: when i is less than or equal to j, uij1 is ═ 1; when j is i +1, uij-i ═ i; when i is>j +1, uij＝0；||Uyn||FRepresents UynThe Frobenus moustache of (1);
the module 206 determines the operation status of the transformer, specifically: if the nth equidistant transform value hnIs greater than or equal to
Figure BDA0002757207900000041
The transformer is in an abnormal operation state at the nth point of the signal sequence S; otherwise, the transformer is in a normal operation state; wherein the content of the first and second substances,
Figure BDA0002757207900000042
to represent
Figure BDA0002757207900000043
The Frobenus moudle of (1).
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
as mentioned above, the transformer vibration and noise detection method is widely applied to monitoring the operation state of the transformer, and the technology is relatively mature, but because the vibration and noise detection method utilizes the vibration signal emitted by the transformer, the vibration and noise detection method is easily affected by the environmental noise, and therefore, the method often fails to obtain satisfactory results when being applied in the actual working environment.
The invention aims to provide a transformer running state vibration and sound detection method and system by utilizing isometric transformation. The method has better robustness and simpler calculation.
Drawings
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 transformer operation state vibration and sound detection method using equidistant transformation
Fig. 1 is a schematic flow chart of a method for detecting vibration and sound in a transformer operating state by using equidistant transformation according to the present invention. As shown in fig. 1, the method for detecting the vibration and sound in the operating state of the transformer by using equidistant transformation specifically comprises the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102, calculating a delay length, specifically:
the delay length is denoted as M, and the formula used is:
Figure BDA0002757207900000044
wherein:
Figure BDA0002757207900000051
presentation pair
Figure BDA0002757207900000052
The upper part is taken to be the whole,
n is the length of the signal sequence S,
snr is the signal-to-noise ratio of the signal sequence S;
step 103, obtaining N window signal sequences, specifically: the nth window signal sequence is denoted by bnThe ith element of which is
Figure BDA0002757207900000053
The solving formula is as follows:
Figure BDA0002757207900000054
wherein:
n is 1,2, N is a window serial number,
i is 1,2, N is element number,
Figure BDA00027572079000000511
is the | i + (n-1) M & lt of the signal sequence SNThe number of the elements is one,
|i+(n-1)M|Nrepresenting that the remainder is taken by i + (N-1) M by taking N as a modulus;
step 104, obtaining N central logarithmic transformation vectors, specifically: the nth center logarithm transformation vector is recorded as ynThe ith element of which is
Figure BDA0002757207900000055
The solving formula is as follows:
Figure BDA0002757207900000056
wherein:
m0is the mean value of the signal sequence S,
l is 1,2, N is summation parameter,
Figure BDA0002757207900000057
for the nth window signal sequence bnThe l element of (1);
step 105, obtaining N equidistant transformation values, specifically: the nth equidistant transformation value is recorded as hnThe formula used is:
hn＝||Uyn||F
wherein:
u is an equidistant transformation matrix, and the ith row and the jth column of the equidistant transformation matrix are marked as UijThe obtaining method comprises the following steps: when i is less than or equal to j, uij1 is ═ 1; when j is i +1, uij-i ═ i; when i is>j +1, uij＝0；||Uyn||FRepresents UynThe Frobenus moustache of (1);
step 106, judging the running state of the transformer, specifically: if the nth equidistant transform value hnIs greater than or equal to
Figure BDA0002757207900000058
The transformer is in an abnormal operation state at the nth point of the signal sequence S; otherwise, the transformer is in a normal operation state; wherein the content of the first and second substances,
Figure BDA0002757207900000059
to represent
Figure BDA00027572079000000510
The Frobenus moudle of (1).
FIG. 2 structural intention of a transformer operation state vibration and sound detection system using equidistant transformation
Fig. 2 is a schematic structural diagram of a transformer operation state vibration and sound detection system using equidistant transformation according to the present invention. As shown in fig. 2, the system for detecting the vibration and sound of the operating state of the transformer by using equidistant transformation comprises the following structures:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 calculates the delay length, specifically:
the delay length is denoted as M, and the formula used is:
Figure BDA0002757207900000061
wherein:
Figure BDA0002757207900000062
presentation pair
Figure BDA0002757207900000063
The upper part is taken to be the whole,
n is the length of the signal sequence S,
snr is the signal-to-noise ratio of the signal sequence S;
the module 203 calculates N window signal sequences, specifically: the nth window signal sequence is denoted by bnThe ith element of which is
Figure BDA0002757207900000064
The solving formula is as follows:
Figure BDA0002757207900000065
wherein:
n is 1,2, N is a window serial number,
i is 1,2, N is element number,
Figure BDA0002757207900000069
is the | i + (n-1) M & lt of the signal sequence SNThe number of the elements is one,
|i+(n-1)M|Nrepresenting that the remainder is taken by i + (N-1) M by taking N as a modulus;
the module 204 calculates N central logarithmic transformation vectors, specifically: the nth center logarithm transformation vector is recorded as ynThe ith element of which is
Figure BDA0002757207900000066
The solving formula is as follows:
Figure BDA0002757207900000067
wherein:
m0is the mean value of the signal sequence S,
l is 1,2, N is summation parameter,
Figure BDA0002757207900000068
for the nth window signal sequence bnThe l element of (1);
the module 205 finds N equidistant transformation values, specifically: the nth equidistant transformation value is recorded as hnThe formula used is:
hn＝||Uyn||F
wherein:
u is an equidistant transformation matrix, and the ith row and the jth column of the equidistant transformation matrix are marked as UijThe obtaining method comprises the following steps: when i is less than or equal to j, uij1 is ═ 1; when j is i +1, uij-i ═ i; when i is>j +1, uij＝0；||Uyn||FRepresents UynThe Frobenus moustache of (1);
the module 206 determines the operation status of the transformer, specifically: if the nth equidistant transform value hnIs greater than or equal to
Figure BDA0002757207900000071
The transformer is in an abnormal operation state at the nth point of the signal sequence S; otherwise, the transformer is in a normal operation state; wherein the content of the first and second substances,
Figure BDA0002757207900000072
to represent
Figure BDA0002757207900000073
The Frobenus moudle of (1).
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, calculating a delay length, specifically:
the delay length is denoted as M, and the formula used is:
Figure BDA0002757207900000074
wherein:
Figure BDA0002757207900000075
presentation pair
Figure BDA0002757207900000076
The upper part is taken to be the whole,
n is the length of the signal sequence S,
snr is the signal-to-noise ratio of the signal sequence S;
step 303 finds N window signal sequences, specifically: the nth window signal sequence is denoted by bnThe ith element of which is
Figure BDA0002757207900000077
The solving formula is as follows:
Figure BDA0002757207900000078
wherein:
n is 1,2, N is a window serial number,
i is 1,2, N is element number,
Figure BDA0002757207900000079
is the | i + (n-1) M & lt of the signal sequence SNThe number of the elements is one,
|i+(n-1)M|Nrepresenting that the remainder is taken by i + (N-1) M by taking N as a modulus;
step 304, obtaining N central logarithmic transformation vectors, specifically: the nth center logarithm transformation vector is recorded as ynThe ith element of which is
Figure BDA0002757207900000081
The solving formula is as follows:
Figure BDA0002757207900000082
wherein:
m0is the mean value of the signal sequence S,
l is 1,2, N is summation parameter,
Figure BDA0002757207900000083
for the nth window signal sequence bnThe l element of (1);
step 305 finds N equidistant transformation values, specifically: the nth equidistant transformation value is recorded as hnThe formula used is:
hn＝||Uyn||F
wherein:
u is an equidistant transformation matrix, and the ith row and the jth column of the equidistant transformation matrix are marked as UijThe obtaining method comprises the following steps: when i is less than or equal to j, uij1 is ═ 1; when j is i +1, uij-i ═ i; when i is>j +1, uij＝0；||Uyn||FRepresents UynThe Frobenus moustache of (1);
step 306, judging the running state of the transformer, specifically: if the nth equidistant transform value hnIs greater than or equal to
Figure BDA0002757207900000084
The transformer is in an abnormal operation state at the nth point of the signal sequence S; otherwise, the transformer is in a normal operation state; wherein the content of the first and second substances,
Figure BDA0002757207900000085
to represent
Figure BDA0002757207900000086
The Frobenus moudle of (1).
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. A method for detecting vibration and sound of an operating state of a transformer by utilizing equidistant transformation is characterized by comprising the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102, calculating a delay length, specifically:
the delay length is denoted as M, and the formula used is:
Figure FDA0003353876000000011
wherein:
Figure FDA0003353876000000012
presentation pair
Figure FDA0003353876000000013
The upper part is taken to be the whole,
n is the length of the signal sequence S,
snr is the signal-to-noise ratio of the signal sequence S;
step 103, obtaining N window signal sequences, specifically: the nth window signal sequence is denoted by bnThe ith element of which is
Figure FDA0003353876000000014
The solving formula is as follows:
Figure FDA0003353876000000015
wherein:
n is 1,2, N is a window serial number,
i is 1,2, N is element number,
Figure FDA0003353876000000019
is the | i + (n-1) M & lt of the signal sequence SNAn element, | i + (n-1) M | non-woven phosphorNRepresenting that the remainder is taken by i + (N-1) M by taking N as a modulus;
step 104, obtaining N central logarithmic transformation vectors, specifically: the nth center logarithm transformation vector is recorded as ynThe ith element of which is
Figure FDA0003353876000000016
The solving formula is as follows:
Figure FDA0003353876000000017
wherein:
m0is the mean value of the signal sequence S,
l is 1,2, N is summation parameter,
Figure FDA0003353876000000018
for the nth window signal sequence bnThe l element of (1);
step 105, obtaining N equidistant transformation values, specifically: the nth equidistant transformation value is recorded as hnThe formula used is:
hn＝||Uyn||F
wherein:
u is an equidistant transformation matrix, and the ith row and the jth column of the equidistant transformation matrix are marked as UijThe obtaining method comprises the following steps: when i is less than or equal to j, uij1 is ═ 1; when j is i +1, uij-i ═ i; when in use
i>j +1, uij＝0；
||Uyn||FRepresents UynThe Frobenius mould of (1);
step 106, judging the running state of the transformer, specifically: if the nth equidistant transform value hnIs greater than or equal to
Figure FDA0003353876000000021
The transformer is in an abnormal operation state at the nth point of the signal sequence S; otherwise, the transformer is in a normal operation state; wherein the content of the first and second substances,
Figure FDA0003353876000000022
to represent
Figure FDA0003353876000000023
Frobenius moudle of (1).
2. A transformer operation state vibration and sound detection system using equidistant transformation is characterized by comprising:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 calculates the delay length, specifically:
the delay length is denoted as M, and the formula used is:
Figure FDA0003353876000000024
wherein:
Figure FDA0003353876000000025
presentation pair
Figure FDA0003353876000000026
The upper part is taken to be the whole,
n is the length of the signal sequence S,
snr is the signal-to-noise ratio of the signal sequence S;
the module 203 calculates N window signal sequences, specifically: the nth window signal sequence is denoted by bnThe ith element of which is
Figure FDA0003353876000000027
The solving formula is as follows:
Figure FDA0003353876000000028
wherein:
n is 1,2, N is a window serial number,
i is 1,2, N is element number,
Figure FDA00033538760000000212
is the | i + (n-1) M & lt of the signal sequence SNAn element, | i + (n-1) M | non-woven phosphorNRepresenting that the remainder is taken by i + (N-1) M by taking N as a modulus;
the module 204 calculates N central logarithmic transformation vectors, specifically: the nth center logarithm transformation vector is recorded as ynThe ith element of which is
Figure FDA0003353876000000029
The solving formula is as follows:
Figure FDA00033538760000000210
wherein:
m0is the mean value of the signal sequence S,
l is 1,2, N is summation parameter,
Figure FDA00033538760000000211
for the nth window signal sequence bnThe l element of (1);
the module 205 finds N equidistant transformation values, specifically: the nth equidistant transformation value is recorded as hnThe formula used is:
hn＝||Uyn||F
wherein:
u is an equidistant transformation matrix, and the ith row and the jth column of the equidistant transformation matrix are marked as UijThe obtaining method comprises the following steps: when i is less than or equal to j, uij1 is ═ 1; when j is i +1, uij-i ═ i; when i is>j +1, uij＝0；
||Uyn||FRepresents UynThe Frobenius mould of (1);
the module 206 determines the operation status of the transformer, specifically: if the nth equidistant transform value hnIs greater than or equal to
Figure FDA0003353876000000031
The transformer is in an abnormal operation state at the nth point of the signal sequence S; otherwise, the transformer is in a normal operation state; wherein the content of the first and second substances,
Figure FDA0003353876000000032
to represent
Figure FDA0003353876000000033
Frobenius moudle of (1).
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