CN113053412B - Transformer fault identification method based on sound - Google Patents
Transformer fault identification method based on sound Download PDFInfo
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- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
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- Y04S10/52—Outage or fault management, e.g. fault detection or location
Abstract
The invention discloses a transformer fault identification method based on sound, which mainly comprises the steps of collecting sound signals beside a transformer and surrounding the transformer and preprocessing the sound signals; extracting the amplitude of each harmonic component of the side sound signal of the transformer and the amplitude of each harmonic component of the peripheral sound signal of the transformer; calculating the amplitude of each harmonic component of the sound signal emitted by the transformer based on the extracted amplitude of each harmonic component; the operating state of the transformer is identified based on the amplitude of each harmonic component of the sound signal emitted by the transformer. The invention can discover the faults of the transformer in time through the characteristics and the abrupt change of the on-site sound of the transformer, and ensure the safe and stable operation of the transformer.
Description
Technical Field
The invention relates to a transformer fault identification method based on sound, and belongs to the technical field of transformer detection.
Background
The power transformer always generates uniform sound due to mechanical vibration in the operation process, and the sound under normal operation has certain regularity. When a device fails, the sound emitted by the device changes due to the change of the operation state. The device can be judged whether to be in an abnormal operation state or not through the change of the audio characteristics such as tone quality, volume, frequency, and the like of the sound, and even the type and severity of the fault can be judged.
Disclosure of Invention
The invention aims to provide a transformer fault identification method based on sound, which is used for timely finding out the faults of a transformer by monitoring the characteristics and the mutation quantity of the on-site sound of the transformer on line and ensuring the safe and stable operation of the transformer.
In order to achieve the above purpose, the invention adopts the following technical scheme:
the invention provides a transformer fault identification method based on sound, which comprises the following steps:
collecting noise signals beside and around a transformer and preprocessing the noise signals;
extracting the amplitude of each harmonic component of the side sound signal of the transformer and the amplitude of each harmonic component of the peripheral noise signal of the transformer;
calculating the amplitude of each harmonic component of the sound signal emitted by the transformer based on the extracted amplitude of each harmonic component;
the transformer state is identified based on the amplitude of each harmonic component of the sound signal emitted by the transformer.
Further, the method further comprises the following steps:
2 sound collecting sensors are arranged beside the transformer and used for monitoring sound signals beside the transformer;
and 3 sound collecting sensors are arranged on the periphery of the transformer and used for monitoring noise signals on the periphery of the transformer.
Further, the collecting and preprocessing of the noise signals beside the transformer and around the transformer includes:
sequentially carrying out data filtering, signal unification processing, data amplification and data segmentation processing on the sound signals acquired by the sound acquisition sensor;
the method comprises the steps of,
sound signals above 1500Hz are filtered out.
Further, the extracting the amplitude of each harmonic component of the transformer side sound signal includes:
the average value of the sound signals detected by 2 sound collecting sensors beside the transformer is used as the sound signal beside the transformer, for every N 1 The sound signal beside the transformer corresponding to the power frequency period is subjected to Fourier transformation once, every N 2 The secondary Fourier transform corresponds to a discrimination period, and the sound signal beside the transformer in the ith discrimination period is calculated to pass through N 2 Maximum value Y of corresponding amplitude of kth harmonic after Fourier transform ik_max And a minimum value of Y ik_min ；
According to Y ik_max And Y ik_min Calculating an average value: y is Y ik_ave ＝(Y ik_max +Y ik_min )/2；
Statistics Y ijk Greater than Y ik_ave The number of (C) is m, less than Y ik_ave The number of (2) is n, the number is recorded,
wherein Y is ijk The amplitude corresponding to the kth harmonic after the jth Fourier transform is carried out on the transformer side sound signal in the ith discrimination period, j=1, 2 and ┄ N 2 ，k＝1,2,┄30；
If e is less than or equal to 10%, the corresponding amplitude YY of the kth harmonic of the sound signal beside the transformer in the ith discrimination period is obtained ik ＝Y ik_ave Ending;
if e > 10% and m > n, let Y ik_ave ＝(Y ik_max +Y ik_ave ) Recalculating m and n until e is less than or equal to 10%;
if e > 10% and m < n, let Y ik_ave ＝(Y ik_min +Y ik_ave ) And (2) recalculating m and n until e is less than or equal to 10%.
Further, extracting the amplitude of each harmonic component of the peripheral noise signal of the transformer includes:
taking the average value of sound signals detected by 3 sound collecting sensors at the periphery of the transformer as a peripheral noise signal, and extracting the direct current component of the peripheral noise signal:
wherein YG0 i Represents the direct current component, yg, of the peripheral noise signal of the transformer in the ith discrimination period icba The method comprises the steps of representing a transformer peripheral noise signal corresponding to an a sampling point in a b power frequency period in a c Fourier transformation period in an i discrimination period, and F represents a sampling period;
calculating the difference between the peripheral noise signal and the DC component of the peripheral noise signal to obtain the AC component of the peripheral noise signal;
the amplitudes of the harmonic components of the alternating current component of the peripheral noise signal are extracted by means of Fourier transformation.
Further, the calculating the amplitude of each harmonic component of the sound signal emitted by the transformer based on the extracted amplitude of each harmonic component includes:
amplitude mutation screening is carried out on the amplitude of each harmonic component of the sound signal beside the transformer and the amplitude of each harmonic component of the noise signal around the transformer;
calculating the amplitude of each harmonic component of the sound signal actually emitted by the transformer based on the screened amplitude of each harmonic component:
YS ik ＝YYY ik -YGG ik
wherein YS ik For the (i) th discrimination period, the corresponding amplitude of the (k) th harmonic of the actually emitted sound signal of the transformer is YYY ik The corresponding amplitude of the kth harmonic after the amplitude mutation screening of the ith discrimination period transformer side sound signal is YGG ik For the ith discrimination periodAnd the kth harmonic of the peripheral noise signal of the phase transformer after amplitude mutation screening corresponds to the amplitude.
Further, the method comprises the steps of,
amplitude mutation screening is carried out on the amplitude of each harmonic component of the sound signal beside the transformer, and the method comprises the following steps:
if YY ik The following conditions are satisfied, YYY ik ＝YY ik Otherwise YYY ik ＝YY (i-1)k ，
Wherein E is 1k Representing the maximum allowable error of the amplitude of the kth harmonic corresponding to the side-by-transformer sound signal between two discrimination periods, E 1z Representing the maximum allowable error of the harmonic amplitude corresponding to the side sound signal of the transformer between two judging periods;
amplitude mutation screening is carried out on the amplitude of each harmonic component of the peripheral noise signal of the transformer, and the method comprises the following steps:
if YG ik Meets the following conditions, YGG ik ＝YG ik Otherwise YGG ik ＝YG (i-1)k ，
Wherein YG ik For the corresponding amplitude of the kth harmonic of the peripheral noise signal of the ith discrimination period transformer, E 2k Representing maximum allowable error of the kth harmonic amplitude corresponding to the peripheral noise signal of the transformer between two discrimination periods, E 2z The maximum allowable error of the harmonic amplitude corresponding to the peripheral noise signal of the transformer between two discrimination periods is shown.
Further, the method further comprises the following steps:
under the normal state of the transformer, extracting the amplitude of each harmonic component of the sound signal beside the transformer and the amplitude of each harmonic component of the sound signal around the transformer;
calculating the amplitude of each harmonic component of the sound signal actually emitted by the transformer in a normal state;
and taking the maximum value and the minimum value of the amplitude of each harmonic component of the sound signal actually emitted by the transformer in the calculated distinguishing period, forming the amplitude range of each subharmonic component of the sound signal actually emitted by the transformer in the normal state, and storing the amplitude range in a normal sound library.
Further, the identifying the transformer state based on the amplitude of each harmonic component of the sound signal emitted by the transformer includes:
defining two distinguishing modes of the states of the transformer,
mode 1: judging whether the amplitude of the sound harmonic of the transformer for 30 times is in the range of a normal sound library,
1a) When the ith discrimination period transformer actually emits the 1 st harmonic component amplitude YS of the sound signal i1 Amplitude range [ YS ] of 1 st harmonic component beyond normal sound library signal of transformer min1 ，YS max1 ]When the intermediate discrimination variable s=1;
1b) When the ith discrimination period transformer actually emits the 2 nd harmonic component amplitude YS of the sound signal i2 Amplitude range [ YS ] of 2 nd harmonic component beyond normal sound library signal of transformer min2 ，YS max2 ]When the intermediate discrimination variable s=1;
1c) When the ith discrimination period transformer actually emits the 4 th harmonic component amplitude YS of the sound signal i4 Amplitude range [ YS ] of 4 th harmonic component beyond normal sound library signal of transformer min4 ，YS max4 ]When the intermediate discrimination variable s=1;
1d) When 3 or more than 3 frequencies in 30 harmonic amplitudes of the sound signal actually sent by the transformer in the ith discrimination period exceed the amplitude range of the subharmonic component corresponding to the normal sound library signal of the transformer, the intermediate discrimination variable S=1;
1e) S=0, except for the cases 1 a), 1 b), 1 c) and 1 d);
[YS mink ，YS maxk ]the amplitude range of the kth harmonic component of the sound signal emitted by the transformer in the normal state is represented by k=1, 2, ┄;
mode 2: judging whether the amplitude-frequency progressive parameter is in a normal range,
calculating the amplitude-frequency progressive parameter k of normal sound library signals of the transformer l ：
Calculating amplitude-frequency progressive parameters of sound signals actually emitted by the ith discrimination period transformer
Calculating the amplitude frequency progressive parameter change rate
The conditions for judging the state of the transformer based on the amplitude-frequency progressive parameters are as follows:
2a) The amplitude frequency progressive parameter change rate in the ith discrimination periodMaximum allowable change rate E of progressive parameter greater than 1 st amplitude frequency e1 When t=1;
2b) The amplitude frequency progressive parameter change rate in the ith discrimination periodMaximum allowable change rate E greater than the 2 nd amplitude frequency progressive parameter e2 When t=1;
2c) The amplitude frequency progressive parameter change rate in the ith discrimination periodMaximum allowable change rate E of progressive parameter greater than 3 rd amplitude frequency e3 When t=1;
2d) When the number of the 29 amplitude-frequency progressive parameter change rates of the ith judging period is more than or equal to 3 and the corresponding amplitude-frequency progressive parameter maximum allowable change rate is more than or equal to 3, t=1;
2e) Removing cases 2 a), 2 b), 2 c) and 2 d), t=0;
taking OR operation of the results of the two transformer state discrimination modes as a discrimination result G of the transformer state, namely G=S|T;
when g=1, it indicates that the transformer state is abnormal, i.e. a fault occurs;
when g=0, it indicates that the transformer is in a normal state.
The beneficial effects achieved by the invention are as follows:
the invention provides a transformer fault identification method based on sound, which is used for timely finding out the faults of a transformer by monitoring the characteristics and the mutation quantity of the on-site sound of the transformer on line and ensuring the safe and stable operation of the transformer.
Drawings
FIG. 1 is a flow chart of a transformer fault identification method of the present invention.
Detailed Description
The invention is further described below. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
The embodiment of the invention provides a transformer fault recognition device based on sound, which comprises an external sensor module, a control circuit, a man-machine interaction interface and a communication system.
Specifically, the external sensor module is provided with 5 sound collecting sensors in total, wherein 2 sound collecting sensors are arranged beside the transformer and used for monitoring the sound of the transformer, and 3 sound collecting sensors are respectively arranged at the periphery of the transformer and used for monitoring surrounding interference noise.
The control circuit is used for extracting the sound signals collected by the external sensor module in real time, comparing the sound signals with the signal amplitude of the normal sound library, and realizing the fault identification of the transformer.
The man-machine interaction interface is used for setting state reminding and audible and visual alarm, and can intuitively monitor the running state of the transformer.
The communication system is used for interaction between the transformer fault recognition device and the monitoring system.
In this embodiment, the man-machine interface adopts an anti-interference housing, and is provided with a heat dissipation outlet.
The embodiment of the invention also provides a transformer fault identification method, as shown in fig. 1, which specifically comprises the following steps:
step 1: and preprocessing the collected sound signals.
The sound signal collected by the sound collecting sensor is required to be subjected to four links of data filtering, signal unified processing, data amplifying and data segmentation. Meanwhile, according to the operation of the on-site transformer and the analysis of fault vibration sound, the frequency of vibration and discharge sound of the transformer is extremely low and is more than 1500Hz, so that sound signals higher than 1500Hz are filtered out firstly during pretreatment.
Step 2: the amplitude of the sound signal near the transformer is extracted.
Taking the average value of sound signals detected by 2 sound collecting sensors beside the transformer as a sound signal nearby the transformer;
for every N 1 The sound signal near the transformer corresponding to the power frequency period is subjected to Fourier transformation once, every N 2 The second Fourier transform corresponds to a discrimination period, and the corresponding amplitude of the kth harmonic after the jth Fourier transform of the sound signal near the transformer in the ith discrimination period is set as Y ijk ，j＝1,2,┄N 2 ，k＝1,2,┄30；
Let the corresponding amplitude of the kth harmonic of the processed sound signal near the ith discrimination period transformer be YY ik The calculation method is as follows:
(1) Calculating N of sound signal near the transformer in the ith discrimination period 2 Maximum value Y of corresponding amplitude of kth harmonic after Fourier transform ik_max And a minimum value of Y ik_min ；
(2) According to Y ik_max And Y ik_min Calculating the average value Y ik_ave ＝(Y ik_max +Y ik_min )/2；
(3) Statistics Y ijk Greater than Y ik_ave The number m of (2) is less than Y ik_ave Is recorded as a number n of (c) of,
if e is less than or equal to 10 percent, YY ik ＝Y ik_ave Ending;
if e > 10% and m > n, let Y ik_ave ＝(Y ik_max +Y ik_ave ) Recalculating m and n until e is less than or equal to 10%;
if e > 10% and m < n, let Y ik_ave ＝(Y ik_min +Y ik_ave ) And (2) recalculating m and n until e is less than or equal to 10%.
Step 3: the amplitude of the transformer peripheral noise signal is extracted.
The 3 noise sensors on the periphery of the transformer are utilized to monitor sound interference signals with different frequencies around the transformer, and the sound interference signals mainly comprise wind sound, rain sound, mechanical collision, vehicle noise, animal sound (including people) and nearby equipment sound.
The average value of the signals collected by the 3 noise sensors at the periphery of the transformer is used as a peripheral noise signal, and the DC component of the peripheral noise signal is firstly extracted, and the calculation method is as follows:
in YG0 i Represents the direct current component, yg, of the peripheral noise signal of the transformer in the ith discrimination period icba The method is characterized in that the method comprises the steps of representing a transformer peripheral noise signal corresponding to an a sampling point in a c power frequency period in a c Fourier transformation period in an i discrimination period, and F represents a sampling period, wherein the value of F is greater than or equal to 3000Hz according to a sampling theorem. In this step, the period, N 1 And N 2 The definition of (1) is the same as the above steps.
The difference between the peripheral noise signal and the dc component of the peripheral noise signal is the ac component of the peripheral noise signal;
extracting the amplitude of alternating current component of peripheral noise signal by Fourier transformation, wherein the extraction process is consistent with the extraction process of the amplitude of sound signal nearby the transformer, and the corresponding amplitude of the kth harmonic of the peripheral noise signal of the transformer in the ith discrimination period after extraction processing is YG ik 。
Step 4: the amplitude of the sound signal emitted by the transformer is calculated.
Firstly, introducing an amplitude mutation screening algorithm, and performing Fourier transform amplitude YY on detection signals of two sound acquisition sensors beside a transformer ik Screening again, YY ik The following conditions should be satisfied:
wherein E is 1k Representing the maximum allowable error of the kth harmonic amplitude corresponding to the sound signal near the transformer between two discrimination periods; e (E) 1z The maximum allowable error between two discrimination periods of the harmonic amplitude corresponding to the sound signal near the transformer is indicated.
When YY ik When the conditions are met, introducing an amplitude mutation screening algorithm to determine the corresponding amplitude YYYY of the kth harmonic of the sound signal near the periodic transformer after the ith judgment ik ＝YY ik The method comprises the steps of carrying out a first treatment on the surface of the Otherwise consider YY ik For interference, neglecting the value, introducing an amplitude mutation screening algorithm to judge the corresponding amplitude YYYY of the kth harmonic of the sound signal near the periodic transformer ik ＝YY (i-1)k 。
Fourier transform amplitude YG of detection signals of three sound collecting sensors on the periphery of the transformer based on amplitude mutation screening algorithm ik Screening again, YG ik The following conditions should be satisfied:
wherein E is 2k Representing the maximum allowable error of the kth harmonic amplitude corresponding to the peripheral noise signal of the transformer between two discrimination periods; e (E) 2z The maximum allowable error of the harmonic amplitude corresponding to the peripheral noise signal of the transformer between two discrimination periods is shown.
When YG ik When the conditions are met, the amplitude mutation screening algorithm is introduced to determine the corresponding amplitude YGG of the kth harmonic of the peripheral noise signal of the periodic transformer ik ＝YG ik The method comprises the steps of carrying out a first treatment on the surface of the Otherwise consider YG ik For interference, neglecting the value, introducing amplitude mutation screening algorithm to determine the corresponding amplitude YGG of the kth harmonic of the peripheral noise signal of the periodic transformer ik ＝YG (i-1)k 。
According to YYY ik And YGG ik The corresponding amplitude YS of the kth harmonic of the sound signal actually sent by the ith discrimination period transformer can be obtained ik I.e. YS ik ＝YYY ik -YGG ik 。
Based on the same principle, the amplitude corresponding to the sound signal emitted by the transformer in the normal state can be obtained, namely the normal sound library signal.
Considering that the amplitude corresponding to the sound signal emitted by the transformer in the normal state is not a fixed value and should be changed within a certain range, N is carried out on the sound signal emitted by the transformer in the normal state 3 (N 3 More than or equal to 100) discrimination periods, taking N 3 The maximum amplitude corresponding to the kth harmonic in the distinguishing period is YS maxk ，N 3 The corresponding minimum amplitude value of the kth harmonic in the distinguishing period is YS mink I.e. the corresponding amplitude of the kth harmonic of the sound signal emitted by the transformer in the normal state is in [ YS ] mink ，YS maxk ]And changes between.
Step 5: and judging the running state of the transformer.
Two ways of distinguishing the running states of the transformers are defined.
Mode 1: judging whether the sound harmonic amplitude of the 30 times transformer is in the range of a normal sound library, wherein specific judging conditions are as follows:
1a) When (when)The (i) th discrimination period transformer actually emits the 1 st harmonic component (50 Hz) amplitude YS of the sound signal i1 Amplitude range [ YS ] of 1 st harmonic component beyond normal sound library signal of transformer min1 ，YS max1 ]When the intermediate discrimination variable s=1;
1b) When the ith discrimination period transformer actually emits the amplitude YS of the 2 nd harmonic component (100 Hz) of the sound signal i2 Amplitude range [ YS ] of 2 nd harmonic component beyond normal sound library signal of transformer min2 ，YS max2 ]When the intermediate discrimination variable s=1;
1c) When the ith discrimination period transformer actually emits the amplitude YS of the 4 th harmonic component (200 Hz) of the sound signal i4 Amplitude range [ YS ] of 4 th harmonic component beyond normal sound library signal of transformer min4 ，YS max4 ]When the intermediate discrimination variable s=1;
1d) When the ith discrimination period transformer actually emits 30 th harmonic amplitude YS of sound signal ik More than 3 frequencies are beyond the amplitude range [ YS ] of the subharmonic component corresponding to the normal sound library signal of the transformer mink ，YS maxk ]When the intermediate discrimination variable s=1;
1e) Other cases of 1 a), 1 b), 1 c) and 1 d) are removed, s=0.
Mode 2: judging whether the amplitude-frequency progressive parameter is in a normal range,
setting a signal amplitude-frequency progressive parameter k of a normal sound library of the transformer l Can be expressed as:
amplitude-frequency progressive parameter of sound signal actually sent by ith discrimination period transformerCan be expressed as:
amplitude-frequency progressive parameter change rateCan be expressed as:
the operational state discrimination conditions of the transformer based on amplitude-frequency progressive parameters are as follows:
2a) The amplitude frequency progressive parameter change rate in the ith discrimination periodMaximum allowable change rate E of progressive parameter greater than 1 st amplitude frequency e1 When t=1;
2b) The amplitude frequency progressive parameter change rate in the ith discrimination periodMaximum allowable change rate E greater than the 2 nd amplitude frequency progressive parameter e2 When t=1;
2c) The amplitude frequency progressive parameter change rate in the ith discrimination periodMaximum allowable change rate E of progressive parameter greater than 3 rd amplitude frequency e3 When t=1;
2d) When the number of the 29 amplitude-frequency progressive parameter change rates of the ith judging period is more than or equal to 3 and the corresponding amplitude-frequency progressive parameter maximum allowable change rate is more than or equal to 3, t=1;
2e) Other cases of 2 a), 2 b), 2 c) and 2 d) are removed, t=0.
And taking OR operation of the results of the two transformer running state discrimination modes as a discrimination result G of the transformer running state, namely G=S|T.
When g=1, it indicates that the transformer operating state is abnormal;
when g=0, it indicates that the transformer operating state is normal.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (7)
1. A method for identifying faults of a transformer based on sound, comprising:
collecting noise signals beside and around a transformer and preprocessing the noise signals;
extracting the amplitude of each harmonic component of the side sound signal of the transformer and the amplitude of each harmonic component of the peripheral noise signal of the transformer;
the extracting the amplitude of each harmonic component of the transformer side sound signal comprises the following steps:
the average value of the sound signals detected by 2 sound collecting sensors beside the transformer is used as the sound signal beside the transformer, for every N 1 The sound signal beside the transformer corresponding to the power frequency period is subjected to Fourier transformation once, every N 2 The secondary Fourier transform corresponds to a discrimination period, and the sound signal beside the transformer in the ith discrimination period is calculated to pass through N 2 Maximum value Y of corresponding amplitude of kth harmonic after Fourier transform ik_max And a minimum value of Y ik_min ；
According to Y ik_max And Y ik_min Calculating an average value: y is Y ik_ave ＝(Y ik_max +Y ik_min )/2；
Statistics Y ijk Greater than Y ik_ave The number of (C) is m, less than Y ik_ave The number of (2) is n, the number is recorded,
wherein Y is ijk For the ith period of discriminationThe sound signal beside the transformer is subjected to the jth Fourier transform and then the kth harmonic corresponds to the amplitude value, j=1, 2 and ┄ N 2 ，k＝1,2,┄30；
If e is less than or equal to 10%, the corresponding amplitude YY of the kth harmonic of the sound signal beside the transformer in the ith discrimination period is obtained ik ＝Y ik_ave Ending;
if e > 10% and m > n, let Y ik_ave ＝(Y ik_max +Y ik_ave ) Recalculating m and n until e is less than or equal to 10%;
if e > 10% and m < n, let Y ik_ave ＝(Y ik_min +Y ik_ave ) Recalculating m and n until e is less than or equal to 10%;
extracting the amplitude of each harmonic component of the peripheral noise signal of the transformer, comprising:
taking the average value of sound signals detected by 3 sound collecting sensors at the periphery of the transformer as a peripheral noise signal, and extracting the direct current component of the peripheral noise signal:
wherein YG0 i Represents the direct current component, yg, of the peripheral noise signal of the transformer in the ith discrimination period icba The method comprises the steps of representing a transformer peripheral noise signal corresponding to an a sampling point in a b power frequency period in a c Fourier transformation period in an i discrimination period, and F represents a sampling period;
calculating the difference between the peripheral noise signal and the DC component of the peripheral noise signal to obtain the AC component of the peripheral noise signal;
extracting the amplitude of each harmonic component of the alternating current component of the peripheral noise signal by utilizing Fourier transformation;
calculating the amplitude of each harmonic component of the sound signal emitted by the transformer based on the extracted amplitude of each harmonic component;
the transformer state is identified based on the amplitude of each harmonic component of the sound signal emitted by the transformer.
2. The method for voice-based transformer fault identification of claim 1, further comprising:
2 sound collecting sensors are arranged beside the transformer and used for monitoring sound signals beside the transformer;
and 3 sound collecting sensors are arranged on the periphery of the transformer and used for monitoring noise signals on the periphery of the transformer.
3. The method for identifying a fault in a sound-based transformer according to claim 2, wherein the step of collecting and preprocessing noise signals around the transformer comprises:
sequentially carrying out data filtering, signal unification processing, data amplification and data segmentation processing on the sound signals acquired by the sound acquisition sensor;
the method comprises the steps of,
sound signals above 1500Hz are filtered out.
4. The method of claim 1, wherein calculating the amplitudes of the harmonic components of the sound signal emitted from the transformer based on the extracted amplitudes of the harmonic components comprises:
amplitude mutation screening is carried out on the amplitude of each harmonic component of the sound signal beside the transformer and the amplitude of each harmonic component of the noise signal around the transformer;
calculating the amplitude of each harmonic component of the sound signal actually emitted by the transformer based on the screened amplitude of each harmonic component:
YS ik ＝YYY ik -YGG ik ，
wherein YS ik For the (i) th discrimination period, the corresponding amplitude of the (k) th harmonic of the actually emitted sound signal of the transformer is YYY ik The corresponding amplitude of the kth harmonic after the amplitude mutation screening of the ith discrimination period transformer side sound signal is YGG ik And the corresponding amplitude of the kth harmonic after the amplitude mutation screening of the peripheral noise signal of the ith discrimination period transformer is obtained.
5. A method for voice-based transformer fault identification as claimed in claim 4, wherein,
amplitude mutation screening is carried out on the amplitude of each harmonic component of the sound signal beside the transformer, and the method comprises the following steps:
if YY ik The following conditions are satisfied, YYY ik ＝YY ik Otherwise YYY ik ＝YY (i-1)k ，
Wherein E is 1k Representing the maximum allowable error of the amplitude of the kth harmonic corresponding to the side-by-transformer sound signal between two discrimination periods, E 1z Representing the maximum allowable error of the harmonic amplitude corresponding to the side sound signal of the transformer between two judging periods;
amplitude mutation screening is carried out on the amplitude of each harmonic component of the peripheral noise signal of the transformer, and the method comprises the following steps:
if YG ik Meets the following conditions, YGG ik ＝YG ik Otherwise YGG ik ＝YG (i-1)k ，
Wherein YG ik For the corresponding amplitude of the kth harmonic of the peripheral noise signal of the ith discrimination period transformer, E 2k Representing maximum allowable error of the kth harmonic amplitude corresponding to the peripheral noise signal of the transformer between two discrimination periods, E 2z The maximum allowable error of the harmonic amplitude corresponding to the peripheral noise signal of the transformer between two discrimination periods is shown.
6. The method for voice-based transformer fault identification of claim 4, further comprising:
under the normal state of the transformer, extracting the amplitude of each harmonic component of the sound signal beside the transformer and the amplitude of each harmonic component of the sound signal around the transformer;
calculating the amplitude of each harmonic component of the sound signal actually emitted by the transformer in a normal state;
and taking the maximum value and the minimum value of the amplitude of each harmonic component of the sound signal actually emitted by the transformer in the calculated distinguishing period, forming the amplitude range of each subharmonic component of the sound signal actually emitted by the transformer in the normal state, and storing the amplitude range in a normal sound library.
7. The method for identifying a fault in a sound based transformer of claim 6, wherein the identifying the transformer state based on the magnitude of each harmonic component of the sound signal emitted from the transformer comprises:
defining two distinguishing modes of the states of the transformer,
mode 1: judging whether the amplitude of the sound harmonic of the transformer for 30 times is in the range of a normal sound library,
1a) When the ith discrimination period transformer actually emits the 1 st harmonic component amplitude YS of the sound signal i1 Amplitude range [ YS ] of 1 st harmonic component beyond normal sound library signal of transformer min1 ，YS max1 ]When the intermediate discrimination variable s=1;
1b) When the ith discrimination period transformer actually emits the 2 nd harmonic component amplitude YS of the sound signal i2 Amplitude range [ YS ] of 2 nd harmonic component beyond normal sound library signal of transformer min2 ，YS max2 ]When the intermediate discrimination variable s=1;
1c) When the ith discrimination period transformer actually emits the 4 th harmonic component amplitude YS of the sound signal i4 Amplitude range [ YS ] of 4 th harmonic component beyond normal sound library signal of transformer min4 ，YS max4 ]When the intermediate discrimination variable s=1;
1d) When 3 or more than 3 frequencies in 30 harmonic amplitudes of the sound signal actually sent by the transformer in the ith discrimination period exceed the amplitude range of the subharmonic component corresponding to the normal sound library signal of the transformer, the intermediate discrimination variable S=1;
1e) S=0, except for the cases 1 a), 1 b), 1 c) and 1 d);
[YS mink ，YS maxk ]the amplitude range of the kth harmonic component of the sound signal emitted by the transformer in the normal state is represented by k=1, 2, ┄;
mode 2: judging whether the amplitude-frequency progressive parameter is in a normal range,
calculating the amplitude-frequency progressive parameter k of normal sound library signals of the transformer l ：
Calculating amplitude-frequency progressive parameters of sound signals actually emitted by the ith discrimination period transformer
Calculating the amplitude frequency progressive parameter change rate
The conditions for judging the state of the transformer based on the amplitude-frequency progressive parameters are as follows:
2a) The amplitude frequency progressive parameter change rate in the ith discrimination periodMaximum allowable change rate E of progressive parameter greater than 1 st amplitude frequency e1 When t=1;
2b) The amplitude frequency progressive parameter change rate in the ith discrimination periodMaximum allowable change rate E greater than the 2 nd amplitude frequency progressive parameter e2 When t=1;
2c) The amplitude frequency progressive parameter change rate in the ith discrimination periodMaximum allowable change rate E of progressive parameter greater than 3 rd amplitude frequency e3 When t=1;
2d) When the number of the 29 amplitude-frequency progressive parameter change rates of the ith judging period is more than or equal to 3 and the corresponding amplitude-frequency progressive parameter maximum allowable change rate is more than or equal to 3, t=1;
2e) Removing cases 2 a), 2 b), 2 c) and 2 d), t=0;
taking OR operation of the results of the two transformer state discrimination modes as a discrimination result G of the transformer state, namely G=S|T;
when g=1, it indicates that the transformer state is abnormal, i.e. a fault occurs;
when g=0, it indicates that the transformer is in a normal state.
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