CN110632477A - Transformer running state vibration and sound detection method and system by using Hilbert space factor - Google Patents

Transformer running state vibration and sound detection method and system by using Hilbert space factor Download PDF

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CN110632477A
CN110632477A CN201911062087.4A CN201911062087A CN110632477A CN 110632477 A CN110632477 A CN 110632477A CN 201911062087 A CN201911062087 A CN 201911062087A CN 110632477 A CN110632477 A CN 110632477A
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transformer
hilbert space
state
space factor
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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
    • G01R31/12—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

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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 using Hilbert space factors, wherein the method comprises the following steps: step 1, inputting an actually measured signal sequence S; and 2, judging the running state of the transformer according to the properties of the Hilbert space factor. The method specifically comprises the following steps: if the Kth window Hilbert space factor HKSatisfies the judgment condition | HK|≥e0If so, at the Kth point of the signal sequence S, the transformer is in an abnormal operation state; otherwise, the transformer is in a normal operation state. Wherein e is0A threshold is determined for the state.

Description

Transformer running state vibration and sound detection method and system by using Hilbert space factor
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
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 transformer operation state vibration and sound detection method and system by using Hilbert space factors. The method has better robustness and simpler calculation.
In order to achieve the purpose, the invention provides the following scheme:
a transformer operation state vibration and sound detection method utilizing Hilbert space factors comprises the following steps:
step 001 inputting an actually measured signal sequence S;
and step 002, judging the running state of the transformer according to the properties of the Hilbert space factor. The method specifically comprises the following steps: if the Kth window Hilbert space factor HKSatisfies the judgment condition | HK|≥e0If so, at the Kth point of the signal sequence S, the transformer is in an abnormal operation state; otherwise, the transformer is in a normal operation state. Wherein e is0A threshold is determined for the state.
A transformer operating state vibration and sound detection system utilizing Hilbert space factors comprises:
an acquisition module inputs an actually measured signal sequence S;
and the judging module judges the running state of the transformer according to the properties of the Hilbert space factors. The method specifically comprises the following steps: if the Kth window Hilbert space factor HKSatisfies the judgment condition | HK|≥e0If so, at the Kth point of the signal sequence S, the transformer is in an abnormal operation state; otherwise, the transformer is in a normal operation state. Wherein e is0A threshold is determined for the state.
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 transformer operation state vibration and sound detection method and system by using Hilbert space factors. 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 Hilbert space factors
Fig. 1 is a schematic flow chart of a transformer operation state vibration and sound detection method using Hilbert space factors 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 the Hilbert space factor specifically includes the following steps:
step 001 inputting an actually measured signal sequence S;
and step 002, judging the running state of the transformer according to the properties of the Hilbert space factor. The method specifically comprises the following steps: if the Kth window Hilbert space factor HKSatisfies the judgment condition | HK|≥e0If so, at the Kth point of the signal sequence S, the transformer is in an abnormal operation state; otherwise, the transformer is in a normal operation state. Wherein e is0A threshold is determined for the state.
Prior to the step 002, the method further comprises:
step 003 of solving the Hilbert space factor HKAnd the state judgment threshold e0。
The step 003 further includes:
step 301 generates an nth signal first-order difference sequence, specifically:
Figure BDA0002258203410000031
wherein:
Figure BDA0002258203410000032
the nth signal first order difference sequence
sn: the nth element, N, of the signal sequence S is 1,2, N
N: length of the signal sequence S
n: subscripts of the elements, if n>N, element s corresponding ton＝0
Step 302 generates an nth signal second order difference sequence, specifically:
Figure BDA0002258203410000033
wherein:
Figure BDA0002258203410000034
the nth signal second order difference sequence
n: subscripts of the elements, if n>N, element s corresponding ton＝0
Step 303 finds the nth expected difference sequence
Figure BDA0002258203410000035
The method specifically comprises the following steps:
Figure BDA0002258203410000036
wherein:
Wn: nth desired weight matrix
λ: correlation matrix
Figure BDA0002258203410000038
Maximum eigenvalue of
Figure BDA00022582034100000312
The correlation matrix
Figure BDA0002258203410000039
The jth feature vector of
j: subscripts, j ═ 1,2, ·, N
ρ: the correlation matrix
Figure BDA00022582034100000310
Trace of
Step 304, calculating the Hilbert space factor of the kth window, specifically:
Figure BDA00022582034100000311
wherein:
σ: mean square error of the signal sequence S
Step 305 of obtaining the state determination threshold e0The method specifically comprises the following steps:
wherein:
κj: matrix array
Figure BDA0002258203410000042
The jth characteristic value of
j: subscripts, j ═ 1,2, ·, N
FIG. 2 is a structural intention of a transformer operation state vibration and sound detection system using Hilbert space factors
Fig. 2 is a schematic structural diagram of a vibration and sound detection system for an operating state of a transformer using Hilbert space factors according to the present invention. As shown in fig. 2, the transformer operating state vibration and sound detection system using the Hilbert space factor includes the following structures:
the acquisition module 401 inputs an actually measured signal sequence S;
the judging module 402 judges the operation state of the transformer according to the properties of the Hilbert space factor. The method specifically comprises the following steps: if the Kth window Hilbert space factor HKSatisfies the judgment condition | HK|≥e0If so, at the Kth point of the signal sequence S, the transformer is in an abnormal operation state; otherwise, the transformer is in a normal operation state. Wherein e is0A threshold is determined for the state.
The system further comprises:
calculation module 403 finds the Hilbert space factor HKAnd the state judgment threshold e0。
The calculation module 403 further includes the following units, which specifically include:
the calculating unit 4031 generates an nth signal first-order difference sequence, specifically:
Figure BDA0002258203410000043
wherein:
Figure BDA0002258203410000044
the nth signal first order difference sequence
sn: the nth element, N, of the signal sequence S is 1,2, N
N: length of the signal sequence S
n: subscripts of the elements, if n>N, element s corresponding ton＝0
The calculating unit 4032 generates an nth signal second-order difference sequence, specifically:
wherein:
the nth signal second order difference sequence
n: subscripts of elementsIf n is>N, element s corresponding ton＝0
Calculation unit 4033 finds the nth expected difference sequence
Figure BDA0002258203410000051
The method specifically comprises the following steps:
wherein:
Wn: nth desired weight matrix
Figure BDA0002258203410000053
λ: correlation matrix
Figure BDA0002258203410000054
Maximum eigenvalue of
The correlation matrixThe jth feature vector of
j: subscripts, j ═ 1,2, ·, N
ρ: the correlation matrix
Figure BDA0002258203410000057
Trace of
The calculation unit 4034 calculates the Hilbert space factor of the kth window, specifically:
Figure BDA0002258203410000058
wherein:
σ: mean square error of the signal sequence S
Calculating unit 4035 obtains state determination threshold e0, specifically:
Figure BDA0002258203410000059
wherein:
Figure BDA00022582034100000510
the jth characteristic value of
j: subscripts, j ═ 1,2, ·, N
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:
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, generating an nth signal first-order difference sequence, specifically:
Figure BDA00022582034100000511
wherein:
Figure BDA0002258203410000061
the nth signal first order difference sequence
sn: the nth element, N, of the signal sequence S is 1,2, N
N: length of the signal sequence S
n: subscripts of the elements, if n>N, element s corresponding ton＝0
2, generating an nth signal second-order difference sequence, specifically:
Figure BDA0002258203410000062
wherein:
Figure BDA0002258203410000063
the nth signal second order difference sequence
n: subscripts of the elements, if n>N, element s corresponding ton＝0
3 obtaining the nth expected difference sequenceThe method specifically comprises the following steps:
Figure BDA0002258203410000065
wherein:
Wn: nth desired weight matrix
Figure BDA0002258203410000066
λ: correlation matrix
Figure BDA0002258203410000067
Maximum eigenvalue of
Figure BDA0002258203410000068
The correlation matrix
Figure BDA0002258203410000069
The jth feature vector of
j: subscripts, j ═ 1,2, ·, N
ρ: the correlation matrix
Figure BDA00022582034100000610
Trace of
4, solving the Hilbert space factor of the Kth window, specifically:
Figure BDA00022582034100000611
wherein:
σ: mean square error of the signal sequence S
5 obtaining the state judgment threshold e0The method specifically comprises the following steps:
Figure BDA00022582034100000612
wherein:
κj: matrix array
Figure BDA00022582034100000613
The jth characteristic value of
j: subscripts, j ═ 1,2, ·, N
And 6, finishing: determining an event
And judging the running state of the transformer according to the properties of the Hilbert space factor. The method specifically comprises the following steps: if the Kth window Hilbert space factor HKSatisfies the judgment condition | HK|≥e0If so, at the Kth point of the signal sequence S, the transformer is in an abnormal operation state; otherwise, the transformer is in a normal operation state. Wherein e is0A threshold is determined for the state.
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 transformer operation state vibration and sound detection method utilizing Hilbert space factors is characterized by comprising the following steps:
step 001 inputting an actually measured signal sequence S;
and step 002, judging the running state of the transformer according to the properties of the Hilbert space factor. The method specifically comprises the following steps: if the Kth window Hilbert space factor HKSatisfies the judgment condition | HK|≥e0If so, at the Kth point of the signal sequence S, the transformer is in an abnormal operation state; otherwise, the transformer is in a normal operation state. Wherein e is0A threshold is determined for the state.
2. The method of claim 1, wherein prior to step 2, the method further comprises:
step 003 of solving the Hilbert space factor HKAnd the state judgment threshold e0。
3. The method of claim 2, wherein step 3 comprises:
step 301 generates an nth signal first-order difference sequence, specifically:
Figure FDA0002258203400000011
wherein:
Figure FDA0002258203400000012
the nth signal first order difference sequence
sn: the nth element, N ═ 1,2, …, N, of the signal sequence S
N: length of the signal sequence S
n: subscripts of the elements, if n>N, element s corresponding ton＝0
Step 302 generates an nth signal second order difference sequence, specifically:
Figure FDA0002258203400000013
wherein:
Figure FDA0002258203400000014
the nth signal second order difference sequence
n: subscripts of the elements, if n>N, element s corresponding ton＝0
Step 303 finds the nth expected difference sequence
Figure FDA0002258203400000015
The method specifically comprises the following steps:
Figure FDA0002258203400000016
wherein:
Wn: nth desired weight matrix
Figure FDA0002258203400000017
λ: correlation matrix
Figure FDA0002258203400000018
Maximum eigenvalue of
Figure FDA00022582034000000111
The correlation matrixThe jth feature vector of
j: subscript, j ═ 1,2, …, N
ρ: the correlation matrixTrace of
Step 304, calculating the Hilbert space factor of the kth window, specifically:
Figure FDA0002258203400000021
wherein:
σ: mean square error of the signal sequence S
Step 305 of obtaining the state determination threshold e0The method specifically comprises the following steps:
Figure FDA0002258203400000022
wherein:
κj: matrix array
Figure FDA0002258203400000023
The jth characteristic value of
j: subscript, j ═ 1,2, …, N.
4. A transformer running state vibration and sound detection system utilizing Hilbert space factors is characterized by comprising the following components:
an acquisition module inputs an actually measured signal sequence S;
and the judging module judges the running state of the transformer according to the properties of the Hilbert space factors. The method specifically comprises the following steps: if the Kth window Hilbert space factor HKSatisfies the judgment condition | HK|≥e0If so, at the Kth point of the signal sequence S, the transformer is in an abnormal operation state; otherwise, the transformer is in a normal operation state. Wherein e is0A threshold is determined for the state.
5. The system of claim 4, further comprising:
calculating the Hilbert space factor H by a calculation moduleKAnd the state judgment threshold e0。
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CN112254808B (en) * 2020-11-03 2021-12-31 华北电力大学 Method and system for detecting vibration and sound of running state of transformer by utilizing gradient change

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