CN111141384A - Transformer state vibration and sound detection signal reconstruction method and system by utilizing Frechet regularization - Google Patents

Transformer state vibration and sound detection signal reconstruction method and system by utilizing Frechet regularization Download PDF

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CN111141384A
CN111141384A CN202010100518.8A CN202010100518A CN111141384A CN 111141384 A CN111141384 A CN 111141384A CN 202010100518 A CN202010100518 A CN 202010100518A CN 111141384 A CN111141384 A CN 111141384A
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matrix
frechet
signal sequence
regularization
operator
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不公告发明人
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Guangdong University of Petrochemical Technology
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    • 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 reconstructing a transformer state vibration and sound detection signal by Frechet regularization, wherein the method comprises the following steps: step 1, inputting an actually measured signal sequence S; step 2, reconstructing the signal sequence S according to Frechet regularization, wherein the reconstructed signal sequence is SNEW. The method specifically comprises the following steps:
Figure DDA0002386743480000011
Figure DDA0002386743480000012
wherein d is an intermediate vector; m is a forward matrix;
Figure DDA0002386743480000013
the operator is Frechet regularized.

Description

Transformer state vibration and sound detection signal reconstruction method and system by utilizing Frechet regularization
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 transformer state vibration and sound detection signal reconstruction method and system by utilizing Frechet regularization. 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 utilizing Frechet regularization comprises the following steps:
step 001 inputting an actually measured signal sequence S;
step 002 reconstructs the signal sequence S according to Frechet regularization, and the reconstructed signal sequence is SNEW. The method specifically comprises the following steps:
Figure BDA0002386743460000011
wherein d is an intermediate vector; m is a forward matrix;
Figure BDA0002386743460000021
the operator is Frechet regularized.
A transformer state vibro-acoustic detection signal reconstruction system with Frechet regularization, comprising:
an acquisition module inputs an actually measured signal sequence S;
the reconstruction module reconstructs the signal sequence S according to Frechet regularization, and the reconstructed signal sequence is SNEW. The method specifically comprises the following steps:
Figure BDA0002386743460000022
wherein d is an intermediate vector; m is a forward matrix;
Figure BDA0002386743460000023
the operator is Frechet regularized.
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 transformer state vibration and sound detection signal reconstruction method and system by utilizing Frechet regularization. The method has better signal reconstruction performance 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 method for reconstructing a transformer state vibration and sound detection signal by Frechet regularization
Fig. 1 is a schematic flow chart of a method for reconstructing a transformer state vibration and sound detection signal by Frechet regularization according to the present invention. As shown in fig. 1, the method for reconstructing a transformer state vibration and sound detection signal by Frechet regularization specifically includes the following steps:
step 001 inputting an actually measured signal sequence S;
step 002 reconstructs the signal sequence S according to Frechet regularization, and the reconstructed signal sequence is SNEW. The method specifically comprises the following steps:
Figure BDA0002386743460000031
wherein d is an intermediate vector; m is a forward matrix;
Figure BDA0002386743460000032
the operator is Frechet regularized.
Prior to the step 002, the method further comprises:
step 003 of solving the forward matrix M and the Frechet regularization operator
Figure BDA0002386743460000033
The step 003 further includes:
step 301, obtaining a cyclic delay signal matrix D, specifically:
Figure BDA0002386743460000034
wherein:
sn: the nth element of the signal sequence S
N: length of the signal sequence S
Step 302, obtaining the forward matrix M specifically includes:
M＝m0U+σ0ΩV
wherein:
m0: mean value of the signal sequence S
σ0: mean square error of the signal sequence S
U: matrix SSTLeft feature matrix of
U: matrix SSTRight feature matrix of
Omega: matrix SSTEigenvalue matrix of
The Frechet regularization operator of step 303
Figure BDA0002386743460000035
The method specifically comprises the following steps:
Figure BDA0002386743460000036
wherein:
Vd: matrix [ d-m ]d][d-md]TLeft feature matrix of
md: mean value of said intermediate vector d
FIG. 2 is a structural intention of a transformer state vibration and sound detection signal reconstruction system utilizing Frechet regularization
Fig. 2 is a schematic structural diagram of a transformer state vibration and sound detection signal reconstruction system using Frechet regularization according to the present invention. As shown in fig. 2, the system for reconstructing a transformer state vibro-acoustic detection signal by Frechet regularization includes the following structures:
the acquisition module 401 inputs an actually measured signal sequence S;
the reconstruction module 402 reconstructs the signal sequence S according to Frechet regularization, where the reconstructed signal sequence is SNEW. The method specifically comprises the following steps:
Figure BDA0002386743460000041
Figure BDA0002386743460000042
wherein d isIs an intermediate vector; m is a forward matrix;
Figure BDA0002386743460000043
the operator is Frechet regularized.
The system further comprises:
calculation module 403 finds the forward matrix M and the Frechet regularization operator
Figure BDA0002386743460000044
The calculation module 403 further includes the following units, which specifically include:
the calculating unit 4031 calculates a cyclic delay signal matrix D, specifically:
Figure BDA0002386743460000045
wherein:
sn: the nth element of the signal sequence S
N: length of the signal sequence S
The calculating unit 4032 calculates the forward matrix M, specifically:
M＝m0U+σ0ΩV
wherein:
m0: mean value of the signal sequence S
σ0: mean square error of the signal sequence S
U: matrix SSTLeft feature matrix of
U: matrix SSTRight feature matrix of
Omega: matrix SSTEigenvalue matrix of
Frechet regularization operator of calculation unit 4033
Figure BDA0002386743460000046
The method specifically comprises the following steps:
Figure BDA0002386743460000047
wherein:
Vd: matrix [ d-m ]d][d-md]TLeft feature matrix of
md: the mean value of the intermediate vector d is provided below as an embodiment to further illustrate the solution of 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:
0 start: inputting measured signal data sequence
S＝[s1,s2,···,sN-1,sN]
Wherein:
s: measured signal sequence of length N
sn: the nth element in the signal sequence S
n: subscript, N ═ 1,2,. cndot., N
1, calculating a cyclic delay signal matrix D, specifically:
Figure BDA0002386743460000051
wherein:
sn: the nth element of the signal sequence S
N: length of the signal sequence S
2, solving the forward matrix M, specifically:
M＝m0U+σ0ΩV
wherein:
m0: mean value of the signal sequence S
σ0: mean square error of the signal sequence S
U: matrix SSTLeft feature matrix of
U: matrix SSTRight feature matrix of
Omega: matrix SSTEigenvalue matrix of
3 the Frechet regularization operator
Figure BDA0002386743460000052
The method specifically comprises the following steps:
Figure BDA0002386743460000053
wherein:
Vd: matrix [ d-m ]d][d-md]TLeft feature matrix of
md: mean value of said intermediate vector d
And 4, finishing: reconstruction
Reconstructing the signal sequence S according to Frechet regularization, wherein the reconstructed signal sequence is SNEW. The method specifically comprises the following steps:
Figure BDA0002386743460000061
wherein d is an intermediate vector; m is a forward matrix;
Figure BDA0002386743460000062
the operator is Frechet regularized.
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 (5)

1. A method for reconstructing a transformer state vibration and sound detection signal by Frechet regularization is characterized by comprising the following steps:
step 001 inputting an actually measured signal sequence S;
step 002 reconstructs the signal sequence S according to Frechet regularization, and the reconstructed signal sequence is SNEW. The method specifically comprises the following steps:
Figure FDA0002386743450000011
wherein d is an intermediate vector; m is a forward matrix;
Figure FDA0002386743450000012
the operator is Frechet regularized.
2. The method of claim 1, wherein prior to step 2, the method further comprises:
step 003 of solving the forward matrix M and the Frechet regularization operator
Figure FDA0002386743450000013
3. The method of claim 2, wherein step 3 comprises:
step 301, obtaining a cyclic delay signal matrix D, specifically:
Figure FDA0002386743450000014
wherein:
sn: the nth element of the signal sequence S
N: length of the signal sequence S
Step 302, obtaining the forward matrix M specifically includes:
M＝m0U+σ0ΩV
wherein:
m0: mean value of the signal sequence S
σ0: mean square error of the signal sequence S
U: matrix SSTLeft feature matrix of
U: matrix SSTRight feature matrix of
Omega: matrix SSTEigenvalue matrix of
The Frechet regularization operator of step 303
Figure FDA0002386743450000015
The method specifically comprises the following steps:
Figure FDA0002386743450000016
wherein:
Vd: matrix [ d-m ]d][d-md]TLeft feature matrix of
md: the mean of the intermediate vector d.
4. A transformer state vibro-acoustic detection signal reconstruction system using Frechet regularization, comprising:
an acquisition module inputs an actually measured signal sequence S;
the reconstruction module reconstructs the signal sequence S according to Frechet regularization, and the reconstructed signal sequence is SNEW. The method specifically comprises the following steps:
Figure FDA0002386743450000021
wherein d is an intermediate vector; m is a forward matrix;
Figure FDA0002386743450000022
the operator is Frechet regularized.
5. The system of claim 4, further comprising:
the calculation module calculates the forward matrix M and the Frechet regularization operator
Figure FDA0002386743450000023
CN202010100518.8A 2020-02-18 2020-02-18 Transformer state vibration and sound detection signal reconstruction method and system by utilizing Frechet regularization Withdrawn CN111141384A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112417994A (en) * 2020-11-03 2021-02-26 华北电力大学 Vibration and sound detection signal filtering method and system using regularization factor

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112417994A (en) * 2020-11-03 2021-02-26 华北电力大学 Vibration and sound detection signal filtering method and system using regularization factor
CN112417994B (en) * 2020-11-03 2021-11-19 华北电力大学 Vibration and sound detection signal filtering method and system using regularization factor

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