CN110286287B - Wavelet transform-based method and system for filtering vibration and sound detection signals of running state of transformer - Google Patents

Wavelet transform-based method and system for filtering vibration and sound detection signals of running state of transformer Download PDF

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CN110286287B
CN110286287B CN201910578466.2A CN201910578466A CN110286287B CN 110286287 B CN110286287 B CN 110286287B CN 201910578466 A CN201910578466 A CN 201910578466A CN 110286287 B CN110286287 B CN 110286287B
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vibration
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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
    • 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
    • G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
    • G01R31/62—Testing of transformers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/02—Preprocessing
    • G06F2218/04—Denoising
    • G06F2218/06—Denoising by applying a scale-space analysis, e.g. using wavelet analysis

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Abstract

The embodiment of the invention discloses a method and a system for filtering a vibration and sound detection signal of a transformer in an operating state based on wavelet transformation, wherein the method comprises the following steps: step 1, inputting an actually measured vibration sound signal sequence S; step 2, carrying out noise filtering processing on the vibration sound signal sequence S to generate a data sequence S after noise filteringNEW(ii) a The method specifically comprises the following steps: sNEW＝ΦXOPT(ii) a Wherein phi is a projection matrix formed by continuous wavelet transformation; xOPTIs the best filter vector.

Description

Wavelet transform-based method and system for filtering vibration and sound detection signals of running state of transformer
Technical Field
The invention relates to the field of electric power, in particular to a method and a system for filtering a vibration and sound detection signal of a transformer in an operating 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. 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.
Because the vibration sound detection method utilizes the vibration signal sent by the transformer, the vibration sound detection method is easily influenced by environmental noise, and therefore, how to effectively identify the vibration sound and the noise is the key for success of the method. The existing common method has insufficient attention to the problem, and no effective measure is taken to solve the problem.
Disclosure of Invention
The invention aims to provide a method and a system for filtering a vibration and sound detection signal of a transformer in an operating state based on wavelet transformation. The method has the advantages of good robustness and simple calculation.
In order to achieve the purpose, the invention provides the following scheme:
a method for filtering a vibration and sound detection signal of a transformer in an operation state based on wavelet transformation comprises the following steps:
step 1, inputting an actually measured vibration sound signal sequence S;
step 2, carrying out noise filtering processing on the vibration sound signal sequence S to generate a data sequence S after noise filteringNEW(ii) a The method specifically comprises the following steps: sNEW＝ΦXOPT(ii) a Wherein phi is a projection matrix formed by continuous wavelet transformation; xOPTIs the best filter vector.
A transformer running state vibration and sound detection signal filtering system based on wavelet transformation comprises:
the acquisition module inputs an actually measured vibration sound signal sequence S;
the filtering module is used for carrying out noise filtering processing on the vibration sound signal sequence S to generate a data sequence S after noise filteringNEW(ii) a The method specifically comprises the following steps: sNEW＝ΦXOPT(ii) a Wherein phi is a projection matrix formed by continuous wavelet transformation; xOPTIs the best filter vector.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
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. The invention aims to provide a method and a system for filtering a vibration and sound detection signal of a transformer in an operating state based on wavelet transformation. The method has the advantages of good robustness and simple 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 present invention;
FIG. 2 is a schematic structural view 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 signal filtering method based on wavelet transformation
Fig. 1 is a schematic flow chart of a transformer operation state vibration and sound detection signal filtering method based on wavelet transformation according to the present invention. As shown in fig. 1, the method for filtering the vibration and sound detection signal of the transformer operating state based on the wavelet transform specifically includes the following steps:
step 1, inputting an actually measured vibration sound signal sequence S;
step 2, carrying out noise filtering processing on the vibration sound signal sequence S to generate a data sequence S after noise filteringNEW(ii) a The method specifically comprises the following steps: sNEW＝ΦXOPT(ii) a Wherein phi is a projection matrix formed by continuous wavelet transformation; xOPTIs the best filter vector.
Before the step 2, the method further comprises:
step 3, solving the projection matrix phi and the optimal filtering vector XOPT。
The step 3 comprises the following steps:
step 301, determining the number of columns of the projection matrix, specifically:
L＝[10～20]N
wherein:
l: number of columns of the projection matrix
N: the number of elements in the vibro-acoustic signal sequence S
Step 302, solving the projection matrix, specifically:
Figure BDA0002112629620000041
Figure BDA0002112629620000042
wherein:
ψ [ ]: mohr wavelet with independent variable
ai: scale factor of order i
ai＝2-i,i＝1,2,…,N
Step 303, obtaining the optimal filtering vector, specifically:
the first step is as follows: initializing a filter vector, specifically: x0＝0
The second step is that: the iterative update filtering vector specifically comprises:
Xk＝T[Φ*S]+Xk-1，k＝1,2,…
wherein:
t: threshold operator, operation T [ phi ]*S]Represents phi*Elements in S smaller than the threshold 0.026 are reset to 0
Φ*: pseudo-inverse of the projection matrix phi
Thirdly, continuously repeating the second step until the adjacent two iteration results XKAnd XK-1By less than 0.0001, i.e.
Figure BDA0002112629620000051
And then, stopping iteration to obtain the optimal filtering vector: xOPT＝XK
FIG. 2 is a structural intention of a transformer operation state vibration and sound detection signal filtering system based on wavelet transformation
Fig. 2 is a schematic structural diagram of a transformer operation state vibration and sound detection signal filtering system based on wavelet transformation. As shown in fig. 2, the system for filtering the vibro-acoustic detection signal in the operating state of the transformer based on the wavelet transform comprises the following structures:
the acquisition module 401 inputs an actually measured vibration and sound signal sequence S;
a filtering module 402, configured to perform noise filtering processing on the vibration sound signal sequence S to generate a data sequence S with noise filteredNEW(ii) a The method specifically comprises the following steps: sNEW＝ΦXOPT(ii) a Wherein phi is a projection matrix formed by continuous wavelet transformation; xOPTIs the best filter vector.
The system further comprises:
a calculation module 403 for obtaining the projection matrix Φ and the optimal filtering vector XOPT。
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:
1. inputting measured vibration sound signal sequence
S＝[s1,s2,…,sN-1,sN]
Wherein:
s: real vibration and sound signal data sequence with length N
siI is 1,2, …, N is measured vibration sound signal with serial number i
2. Determining projection matrix column number
L＝[10～20]N
Wherein:
l: number of columns of the projection matrix
N: the number of elements in the vibro-acoustic signal sequence S
3. Determining a projection matrix
Figure BDA0002112629620000061
Figure BDA0002112629620000062
Wherein:
ψ [ ]: mohr wavelet with independent variable
ai: scale factor of order i
ai＝2-i,i＝1,2,…,N
4. Finding the best filter vector
The first step is as follows: initializing a filter vector, specifically: x0＝0
The second step is that: the iterative update filtering vector specifically comprises:
Xk＝T[Φ*S]+Xk-1，k＝1,2,…
wherein:
t: threshold operator, operation T [ phi ]*S]Represents phi*Elements in S smaller than the threshold 0.026 are reset to 0
Φ*: pseudo-inverse of the projection matrix phi
Thirdly, continuously repeating the second step until the adjacent two iteration results XKAnd XK-1By less than 0.0001, i.e.
Figure BDA0002112629620000063
And then, stopping iteration to obtain the optimal filtering vector: xOPT＝XK
5. Filtering
Carrying out noise filtering processing on the vibration sound signal sequence S to generate a data sequence S after noise filteringNEW(ii) a The method specifically comprises the following steps: sNEW＝ΦXOPT(ii) a Wherein phi is a projection matrix formed by continuous wavelet transformation; xOPTIs the best filter vector.
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 (1)

1. A method for filtering a vibration and sound detection signal of a transformer in an operation state based on wavelet transformation is characterized by comprising the following steps:
step 1, inputting an actually measured vibration sound signal sequence S;
step 2, determining the column number of the projection matrix, specifically:
L＝[10～20]N；
wherein:
l: the number of columns of the projection matrix;
n: the number of elements in the vibration and sound signal sequence S;
step 3, solving a projection matrix, specifically:
Figure FDA0003066902600000011
Figure FDA0003066902600000012
wherein:
ψ [ ]: mohr wavelets with argument x;
ai: a scale factor with an order i;
ai＝2-i,i＝1,2,…,N；
step 4, solving an optimal filtering vector, specifically:
the first step is as follows: initializing a filter vector, specifically: x0＝0；
The second step is that: the iterative update filtering vector specifically comprises:
Xk＝T[Φ*S]+Xk-1，k＝1,2,…；
wherein:
t: threshold operator, operation T [ phi ]*S]Represents phi*Elements smaller than a threshold value of 0.026 in S are reset to 0;
Φ*: a pseudo-inverse of the projection matrix Φ;
thirdly, continuously repeating the second step until the adjacent two iteration results XKAnd XK-1By less than 0.0001, i.e.
Figure FDA0003066902600000013
And then, stopping iteration to obtain the optimal filtering vector: xOPT＝XK；
Step 5, carrying out noise filtering processing on the vibration sound signal sequence S to generate a data sequence S after noise filteringNEW(ii) a The method specifically comprises the following steps: sNEW＝ΦXOPT。
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