CN115290308A - Mechanical state diagnosis system and method based on acoustic fingerprints of circuit breaker - Google Patents
Mechanical state diagnosis system and method based on acoustic fingerprints of circuit breaker Download PDFInfo
- Publication number
- CN115290308A CN115290308A CN202210890929.0A CN202210890929A CN115290308A CN 115290308 A CN115290308 A CN 115290308A CN 202210890929 A CN202210890929 A CN 202210890929A CN 115290308 A CN115290308 A CN 115290308A
- Authority
- CN
- China
- Prior art keywords
- sound wave
- circuit breakers
- acoustic
- circuit breaker
- wave signals
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
-
- 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
- G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
- Arc-Extinguishing Devices That Are Switches (AREA)
Abstract
The invention provides a mechanical state diagnosis system and method based on acoustic fingerprints of circuit breakers. The sound wave signal acquisition modules correspond to the circuit breakers one by one and are used for acquiring sound wave signals of the circuit breakers, wherein each sound wave signal acquisition module comprises two sound wave acquisition devices, and the two sound wave acquisition devices are symmetrically arranged and equal to the distance value corresponding to the centers of the circuit breakers. The processing center is in communication connection with the sound wave signal acquisition modules and is used for receiving the sound wave signals of the circuit breakers acquired by the sound wave signal acquisition modules and diagnosing the mechanical state of the circuit breakers in real time according to the sound wave signals of the circuit breakers. The invention can reduce the influence of other breaker signals on the diagnosis of the mechanical state of the monitored breaker and improve the real-time diagnosis accuracy of the mechanical state of the breaker.
Description
Technical Field
The invention relates to the technical field of circuit breakers, in particular to a mechanical state diagnosis system and method based on acoustic fingerprints of a circuit breaker.
Background
The circuit breaker realizes the opening and closing functions of the contacts by orderly matching of mechanical components in the operating mechanism. During the switching-on and switching-off processes of the circuit breaker, various accompanying signals containing mechanism state information are generated, such as motion tracks of action parts, vibration signals, sound signals, switching-on and switching-off coil currents and the like. The accompanying signals generated after the state of the operating mechanism is changed are different, and various mechanical faults can be diagnosed by using the difference characteristics of the accompanying signals. That is, whether the circuit breaker has a fault can be judged by collecting and analyzing the sound signal generated in the opening and closing action process of the circuit breaker.
The applicant finds some existing technical documents through retrieval, for example, chinese patent application No. 201911261695.8 discloses a sound-based GIS circuit breaker fault online monitoring device, which judges the mechanical state of a circuit breaker through a voiceprint, and the method does not need to be connected with a circuit breaker entity, and has no influence on the operation of a circuit breaker body. Further, for example, the chinese patent application No. 202010252053.8 discloses a method and a system for detecting the state of a circuit breaker of a GIS device, which can detect the mechanical state of the circuit breaker, and overcome the influence of the selection of a detection point on the detection result.
Therefore, for practical problems such as mechanical state or fault which need to be dealt with in practical application of the circuit breaker, a plurality of technical solutions which are not proposed exist.
Disclosure of Invention
Based on the above, in order to realize the real-time diagnosis of the mechanical state of the circuit breaker, the invention provides a mechanical state diagnosis system and method based on the acoustic fingerprint of the circuit breaker, and the specific technical scheme is as follows:
a mechanical state diagnosis system based on acoustic fingerprints of circuit breakers comprises a plurality of circuit breakers; the mechanical state diagnosis system based on the circuit breaker fingerprint further comprises a plurality of sound wave signal acquisition modules and a processing center.
The sound wave signal acquisition modules correspond to the circuit breakers one by one and are used for acquiring sound wave signals of the circuit breakers. Wherein, every sound wave signal acquisition module includes two sound wave collection system, and two sound wave collection system symmetry set up and equal with the distance value that corresponds the circuit breaker center.
The processing center is in communication connection with the sound wave signal acquisition modules and is used for receiving the sound wave signals of the circuit breakers acquired by the sound wave signal acquisition modules and diagnosing the mechanical state of the circuit breakers in real time according to the sound wave signals of the circuit breakers.
For most field environments, such as substation or factory electrical houses, multiple circuit breakers are often installed. Under the condition of a plurality of circuit breakers, the sound wave signal of the circuit breaker which is specified to be monitored is easily influenced by other circuit breaker signals around, so that the diagnosis accuracy of the mechanical state of the circuit breaker is influenced.
In the mechanical state diagnosis system based on the acoustic fingerprints of the circuit breakers, the acoustic signals of the circuit breakers are acquired through the acoustic signal acquisition modules, and the mechanical state of the circuit breakers is diagnosed in real time according to the acoustic signals of the circuit breakers, so that the acoustic signals generated by the monitored circuit breakers and other surrounding circuit breakers are fully considered, the influence of other circuit breaker signals on the mechanical state diagnosis of the monitored circuit breakers can be reduced, and the real-time diagnosis accuracy of the mechanical state of the circuit breakers is improved.
Further, the processing center comprises a preprocessing module and a fault recognition neural network model.
The preprocessing module is used for preprocessing the received sound wave signals of the plurality of circuit breakers.
And the fault recognition neural network model is used for diagnosing the mechanical state of the circuit breaker in real time according to the preprocessed sound wave signals of the plurality of circuit breakers.
Further, the preprocessing module comprises:
and the first filtering unit is used for filtering and denoising and amplifying the received sound wave signals of the plurality of circuit breakers.
Further, the preprocessing module includes:
and the second filtering unit is used for screening the received sound wave signals of the plurality of circuit breakers by comparing the similarity of the sound wave signals of the plurality of circuit breakers acquired by the plurality of sound wave signal acquisition modules.
Further, the second filtering unit includes:
the sampling subunit is used for acquiring a plurality of amplitudes of the sound wave signal of each circuit breaker;
the fitting subunit is used for fitting the acoustic wave signals of the corresponding circuit breakers according to the multiple amplitudes of the acoustic wave signals of the circuit breakers to obtain fitting curves, wherein the acoustic wave signal of one circuit breaker acquired by each acoustic wave signal acquisition module comprises two fitting curves;
and the screening subunit is used for calculating and judging whether the distance value between the two fitting curves corresponding to each sound wave signal acquisition module is smaller than a preset threshold value, if so, screening and rejecting the sound wave signals of the circuit breaker corresponding to the two fitting curves of which the similarity is smaller than the preset threshold value, and if not, diagnosing the mechanical state of the circuit breaker in real time according to the sound wave signals of the circuit breaker corresponding to the two fitting curves of which the similarity is greater than or equal to the preset threshold value.
A mechanical state diagnosis method based on acoustic fingerprints of circuit breakers comprises the following steps:
s1, collecting sound wave signals of a plurality of circuit breakers;
s2, the processing center receives the sound wave signals of the plurality of circuit breakers, which are acquired by the plurality of sound wave signal acquisition modules;
s3, the processing center diagnoses the mechanical state of the circuit breakers in real time according to the sound wave signals of the circuit breakers;
wherein, every sound wave signal acquisition module includes two sound wave collection system, and two sound wave collection system symmetries set up and equal with the distance value that corresponds the circuit breaker center.
Further, in step S3, the specific method for the processing center to diagnose the mechanical state of the circuit breaker in real time according to the acoustic signals of the plurality of circuit breakers includes the following steps:
s30, preprocessing the received sound wave signals of the plurality of circuit breakers;
and S30, diagnosing the mechanical state of the circuit breaker in real time according to the preprocessed sound wave signals of the plurality of circuit breakers.
Further, the specific method for preprocessing the received sound wave signals of the plurality of circuit breakers comprises the following steps: the received sound wave signals of the plurality of circuit breakers are screened by comparing the similarity of the sound wave signals of the plurality of circuit breakers acquired by the plurality of sound wave signal acquisition modules.
Furthermore, the specific method for screening the received sound wave signals of the plurality of circuit breakers by comparing the similarity of the sound wave signals of the plurality of circuit breakers acquired by the plurality of sound wave signal acquisition modules comprises the following steps:
collecting a plurality of amplitudes of the acoustic signal of each circuit breaker;
fitting the acoustic wave signals of the corresponding circuit breakers according to the multiple amplitudes of the acoustic wave signals of the circuit breakers to obtain a fitting curve;
calculating and judging whether the distance value between the two fitting curves corresponding to each acoustic signal acquisition module is smaller than a preset threshold value, if so, screening and rejecting acoustic signals of the circuit breaker corresponding to the two fitting curves of which the similarity is smaller than the preset threshold value, and if not, diagnosing the mechanical state of the circuit breaker in real time according to the acoustic signals of the circuit breaker corresponding to the two fitting curves of which the similarity is greater than or equal to the preset threshold value;
the sound wave signal of a certain circuit breaker collected by each sound wave signal collecting module comprises two fitting curves.
A computer-readable storage medium, storing a computer program which, when executed by a processor, implements the method for diagnosing a mechanical state based on acoustic fingerprints of circuit breakers.
Drawings
The invention will be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Like reference numerals designate corresponding parts throughout the different views.
Fig. 1 is a schematic diagram of the overall structure of a mechanical state diagnosis system based on acoustic fingerprints of a circuit breaker according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the gradual attenuation of the amplitude of an acoustic signal with increasing distance;
FIG. 3 is a schematic overall flowchart of a method for diagnosing a mechanical state based on acoustic fingerprints of a circuit breaker according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a fitting curve corresponding to the acoustic signal of the monitored circuit breaker acquired by the acoustic signal acquisition module according to an embodiment of the present invention.
Description of reference numerals:
1. a circuit breaker; 2. a sound wave collection device; 3. a processing center.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to embodiments thereof. It should be understood that the detailed description and specific examples, while indicating the scope of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not represent the only embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The terms "first" and "second" used herein do not denote any particular order or quantity, but rather are used to distinguish one element from another.
The first embodiment is as follows:
as shown in fig. 1, a mechanical condition diagnosis system based on acoustic fingerprints of circuit breakers in an embodiment of the present invention includes a plurality of circuit breakers 1; the mechanical state diagnosis system based on the circuit breaker fingerprint further comprises a plurality of sound wave signal acquisition modules and a processing center 3.
The sound wave signal acquisition modules correspond to the circuit breakers one by one and are used for acquiring sound wave signals of the circuit breakers. Wherein, every sound wave signal acquisition module includes two sound wave collection system 2, and two sound wave collection system symmetries set up and equal with the distance value that corresponds the circuit breaker center.
The processing center is in communication connection with the sound wave signal acquisition modules and is used for receiving the sound wave signals of the circuit breakers acquired by the sound wave signal acquisition modules and diagnosing the mechanical state of the circuit breakers in real time according to the sound wave signals of the circuit breakers.
For most field environments, such as substation or factory electrical houses, multiple circuit breakers are often installed. Under the condition of a plurality of circuit breakers, the sound wave signal of the circuit breaker which is specified to be monitored is easily influenced by other circuit breaker signals around, so that the diagnosis accuracy of the mechanical state of the circuit breaker is influenced.
In the mechanical state diagnosis system based on the acoustic fingerprints of the circuit breakers, the acoustic signals of the circuit breakers are acquired through the acoustic signal acquisition modules, and the mechanical state of the circuit breakers is diagnosed in real time according to the acoustic signals of the circuit breakers, so that the acoustic signals generated by the monitored circuit breakers and other surrounding circuit breakers are fully considered, the influence of other circuit breaker signals on the mechanical state diagnosis of the monitored circuit breakers can be reduced, and the real-time diagnosis accuracy of the mechanical state of the circuit breakers is improved.
Specifically, the processing center comprises a preprocessing module and a fault recognition neural network model.
The preprocessing module is used for preprocessing the received sound wave signals of the plurality of circuit breakers.
And the fault recognition neural network model is used for diagnosing the mechanical state of the circuit breaker in real time according to the preprocessed sound wave signals of the plurality of circuit breakers.
The fault recognition neural network model is trained by collecting a plurality of acoustic signals of a plurality of circuit breakers. Each circuit breaker corresponds to a plurality of sound wave signals, and the sound wave signals comprise normal operation sound wave signals and fault sound wave signals.
After the fault recognition neural network model is trained through the plurality of sound wave signals, the trained fault recognition neural network model can recognize the sound wave signals of the plurality of circuit breakers, and then the mechanical state of the circuit breakers can be diagnosed in real time.
For the construction of the fault recognition neural network model, the construction is not described herein again because it belongs to the conventional technical means in the field.
Through setting up the neural network model of fault identification, the system can be through the sound wave signal of a plurality of circuit breakers, and the mechanical state of discerning the circuit breaker fast realizes the real-time diagnosis of circuit breaker mechanical state.
Example two:
as shown in fig. 1, in an embodiment of the present invention, a mechanical condition diagnosis system based on acoustic fingerprints of circuit breakers includes a plurality of circuit breakers; the mechanical state diagnosis system based on the circuit breaker fingerprints further comprises a plurality of sound wave signal acquisition modules and a processing center.
The sound wave signal acquisition modules correspond to the circuit breakers one by one and are used for acquiring sound wave signals of the circuit breakers. Wherein, every sound wave signal acquisition module includes two sound wave collection system, and two sound wave collection system symmetry set up and equal with the distance value that corresponds the circuit breaker center.
The processing center is in communication connection with the sound wave signal acquisition modules and is used for receiving the sound wave signals of the circuit breakers acquired by the sound wave signal acquisition modules and diagnosing the mechanical state of the circuit breakers in real time according to the sound wave signals of the circuit breakers.
For most field environments, such as substation or factory electrical houses, multiple circuit breakers are often installed. Under the condition of a plurality of circuit breakers, the sound wave signal of the circuit breaker which is specified to be monitored is easily influenced by other circuit breaker signals around, so that the diagnosis accuracy of the mechanical state of the circuit breaker is influenced.
In the mechanical state diagnosis system based on the acoustic fingerprints of the circuit breakers, the acoustic wave signals of the circuit breakers are acquired through the acoustic wave signal acquisition modules, and the mechanical state of the circuit breakers is diagnosed in real time according to the acoustic wave signals of the circuit breakers, so that the acoustic wave signals generated by the monitored circuit breakers and other circuit breakers around the monitored circuit breakers are fully considered, the influence of other circuit breaker signals on the mechanical state diagnosis of the monitored circuit breakers can be reduced, and the accuracy of the real-time diagnosis of the mechanical state of the circuit breakers is improved.
Specifically, the processing center comprises a preprocessing module and a fault recognition neural network model.
The preprocessing module is used for preprocessing the received sound wave signals of the plurality of circuit breakers.
And the fault recognition neural network model is used for diagnosing the mechanical state of the circuit breaker in real time according to the preprocessed sound wave signals of the circuit breakers.
The fault recognition neural network model is trained by collecting a plurality of acoustic signals of a plurality of circuit breakers. Each circuit breaker corresponds to a plurality of sound wave signals, and the sound wave signals comprise normal operation sound wave signals and fault sound wave signals.
After the fault recognition neural network model is trained through the plurality of sound wave signals, the trained fault recognition neural network model can recognize the sound wave signals of the plurality of circuit breakers, and then the mechanical state of the circuit breakers is diagnosed in real time.
For the construction of the fault recognition neural network model, the construction is not described herein again because it belongs to the conventional technical means in the field.
Through setting up the neural network model of fault identification, the system can be through the sound wave signal of a plurality of circuit breakers, and the mechanical state of discerning the circuit breaker fast realizes the real-time diagnosis of circuit breaker mechanical state.
In this embodiment, the pre-processing module includes a first filtering unit.
The first filtering unit is used for filtering and denoising and amplifying received sound wave signals of the plurality of circuit breakers.
Preferably, the preprocessing module further comprises a second filtering unit.
And the second filtering unit is used for screening the received sound wave signals of the plurality of circuit breakers by comparing the similarity of the sound wave signals of the plurality of circuit breakers acquired by the plurality of sound wave signal acquisition modules.
Specifically, the second filtering unit includes a sampling subunit, a fitting subunit, and a screening subunit.
The sampling subunit is used for acquiring a plurality of amplitudes of the sound wave signal of each breaker. The sampling time points of the plurality of amplitudes of the sampling subunit corresponding to each breaker acoustic wave signal are in one-to-one correspondence, so that the acoustic wave signals are better screened according to the distance value between the two fitting curves. For example, the acoustic wave signal of each circuit breaker samples N amplitudes, the sampling time points corresponding to the ith amplitudes of the circuit breakers are the same and consistent, and i is less than or equal to N.
And the fitting subunit is used for fitting the sound wave signals corresponding to the circuit breakers according to the plurality of amplitude values of the sound wave signals of the circuit breakers to obtain fitting curves, wherein the sound wave signals of one circuit breaker acquired by each sound wave signal acquisition module comprise two fitting curves.
As shown in fig. 1, each acoustic signal collection module includes two acoustic collection devices, including but not limited to an acoustic sensor. When one circuit breaker moves out of service, the sound waves emitted by the circuit breaker are collected by two sound wave collecting devices in each wave signal collecting module.
And the screening subunit is used for calculating and judging whether the distance value between the two fitting curves corresponding to each sound wave signal acquisition module is smaller than a preset threshold value, if so, screening and rejecting the sound wave signals of the circuit breaker corresponding to the two fitting curves with the similarity smaller than the preset threshold value, and if not, diagnosing the mechanical state of the circuit breaker in real time according to the sound wave signals of the circuit breaker corresponding to the two fitting curves with the similarity larger than or equal to the preset threshold value.
The distance value between the two fitting curves corresponding to each sound wave signal acquisition module can be calculated by calculating the average value of the distances between the amplitudes corresponding to the multiple sampling time points.
As shown in fig. 2, the acoustic wave signal generated when the internal driving component of the circuit breaker acts can be regarded as a sinusoidal signal whose amplitude gradually attenuates with the distance. As shown in fig. 4, due to the symmetrical arrangement of the two acoustic wave collection devices corresponding to the monitored circuit breaker and the equal distance value between the two acoustic wave collection devices and the corresponding circuit breaker center, the fitting curves corresponding to the collected acoustic wave signals are not only wholly similar but also wholly and basically coincide. Due to the fact that the distances between the other sound wave acquisition devices and the monitored circuit breaker are different, the corresponding fitting curves of the sound wave signals acquired by the other sound wave acquisition devices are similar on the whole, but the sound wave amplitude values at the same time point are different.
Therefore, by comparing the distance value between the fitting curves corresponding to the circuit breaker sound wave signals acquired by the two sound wave acquisition devices in each sound wave signal acquisition module, whether the circuit breaker sound wave signals acquired by the two sound wave acquisition devices are the sound waves sent by the monitored circuit breaker can be judged. So, can make a plurality of sound wave signal acquisition modules and a plurality of circuit breaker one-to-one that set up, carry out the real-time supervision diagnosis to the mechanical state who is monitored the circuit breaker through corresponding sound wave signal acquisition module, can improve the real-time diagnosis efficiency and the accuracy of a plurality of circuit breaker mechanical states.
Preferably, different circuit breakers correspond to different fault recognition neural network models, and the fault recognition neural network models are trained by a plurality of acoustic signals of the corresponding circuit breakers.
Since in some cases the class models of the multiple circuit breakers in the field may not be the same. Even if a plurality of circuit breakers of the same type and model are used, the service time of the circuit breakers is different. Since the mechanical state of the circuit breaker is affected by the use time, the sound wave signal generated during the action of the circuit breaker is also changed. Therefore, by training different fault recognition neural network models, the mechanical states of different circuit breakers can be diagnosed in real time in a targeted manner, and the accuracy of the real-time diagnosis of the mechanical states of the circuit breakers is improved.
Because the acoustic signal that produces when the inside drive part action of circuit breaker can be regarded as the sinusoidal signal that the amplitude attenuates gradually along with the distance increases this point, because acoustic signal gathers the module apart from corresponding circuit breaker monitored minimum, the amplitude that corresponds that acoustic signal gathers that the module gathered sends acoustic signal by monitoring circuit breaker is greater than the amplitude of gathering the acoustic signal that other circuit breakers sent.
As an optimal technical scheme, the amplitude of the fitting curve corresponding to each acoustic signal acquisition module can be calculated and compared, if the distance value between two fitting curves corresponding to the acoustic signal acquisition modules is greater than or equal to a preset threshold value, whether the amplitude of the fitting curve corresponding to the acoustic signal acquisition module is greater than the amplitudes of the fitting curves corresponding to other acoustic signal acquisition modules is judged, and if yes, the mechanical state of the circuit breaker is diagnosed in real time according to the acoustic signals of the circuit breaker corresponding to the two fitting curves with the similarity greater than or equal to the preset threshold value.
Therefore, the received sound wave signals of the plurality of circuit breakers can be further screened, and the diagnosis accuracy is improved.
Example three:
as shown in fig. 3, the present embodiment provides a method for diagnosing a mechanical state based on an acoustic fingerprint of a circuit breaker, which includes the following steps:
s1, collecting sound wave signals of a plurality of circuit breakers.
And S2, the processing center receives the sound wave signals of the plurality of breakers acquired by the plurality of sound wave signal acquisition modules.
And S3, the processing center diagnoses the mechanical state of the circuit breakers in real time according to the sound wave signals of the circuit breakers.
Wherein, every sound wave signal acquisition module includes two sound wave collection system, and two sound wave collection system symmetry set up and equal with the distance value that corresponds the circuit breaker center.
Specifically, in step S3, the specific method for the processing center to diagnose the mechanical state of the circuit breaker in real time according to the acoustic wave signals of the plurality of circuit breakers includes the following steps:
and S30, preprocessing the received sound wave signals of the plurality of circuit breakers.
And S30, diagnosing the mechanical state of the circuit breaker in real time according to the preprocessed sound wave signals of the plurality of circuit breakers.
The specific method for preprocessing the received sound wave signals of the plurality of circuit breakers comprises the following steps: the received sound wave signals of the plurality of circuit breakers are screened by comparing the similarity of the sound wave signals of the plurality of circuit breakers acquired by the plurality of sound wave signal acquisition modules.
According to the mechanical state diagnosis method based on the acoustic fingerprints of the circuit breakers, the acoustic signals of the circuit breakers are acquired through the acoustic signal acquisition modules, the mechanical state of the circuit breakers is diagnosed in real time according to the acoustic signals of the circuit breakers, the acoustic signals generated by the monitored circuit breakers and other circuit breakers around the monitored circuit breakers are fully considered, the influence of other circuit breaker signals on the mechanical state diagnosis of the monitored circuit breakers can be reduced, and the real-time diagnosis accuracy of the mechanical state of the circuit breakers is improved.
Example four:
it should be understood that this embodiment includes at least all the technical features of the above embodiments, and is further specifically described on the basis of the above embodiments.
In this embodiment, the specific method for screening the received acoustic signals of the plurality of circuit breakers by comparing the similarity of the acoustic signals of the plurality of circuit breakers acquired by the plurality of acoustic signal acquisition modules includes the following steps:
collecting a plurality of amplitudes of the sound wave signal of each circuit breaker;
fitting the acoustic wave signals of the corresponding circuit breakers according to the multiple amplitudes of the acoustic wave signals of the circuit breakers to obtain a fitting curve;
calculating and judging whether the distance value between the two fitting curves corresponding to each sound wave signal acquisition module is smaller than a preset threshold value or not, if so, screening and removing the sound wave signals of the circuit breaker corresponding to the two fitting curves with the similarity smaller than the preset threshold value, and if not, diagnosing the mechanical state of the circuit breaker in real time according to the sound wave signals of the circuit breaker corresponding to the two fitting curves with the similarity larger than or equal to the preset threshold value;
the sound wave signal of a certain circuit breaker collected by each sound wave signal collecting module comprises two fitting curves.
As shown in fig. 2, the sound wave signal generated when the internal driving member of the circuit breaker operates can be regarded as a sinusoidal signal that gradually attenuates. As shown in fig. 4, since the two acoustic wave collection devices corresponding to the monitored circuit breaker are symmetrically arranged and have the same distance value with the corresponding circuit breaker center, the fitting curves corresponding to the collected acoustic wave signals are not only wholly similar but also tend to coincide. Due to the fact that the distances between the other sound wave acquisition devices and the monitored circuit breaker are different, the corresponding fitting curves of the sound wave signals acquired by the other sound wave acquisition devices are similar on the whole, and the sound wave amplitude values at the same time point have certain difference.
Through setting up the adjustment preset threshold value, compare two big or small relations between the distance value that corresponds between the fitting curve and the preset threshold value, can judge whether the sound wave signal that two sound wave collection device in the sound wave signal acquisition module gathered is sent for corresponding by monitoring the circuit breaker, reduce the influence of other circuit breaker signals to the degree of accuracy of monitoring the diagnosis of circuit breaker mechanical state.
Consequently, through the distance value between the fitting curve that two sound wave collection device gather the circuit breaker sound wave signal and correspond in comparing each sound wave signal collection module, can judge whether two sound wave collection device gather the circuit breaker sound wave signal for monitoring the sound wave that the circuit breaker sent. So, can make a plurality of sound wave signal acquisition modules and a plurality of circuit breaker one-to-one that set up, carry out the real-time supervision diagnosis to the mechanical state who is monitored the circuit breaker through corresponding sound wave signal acquisition module, can improve the real-time diagnosis efficiency and the accuracy of a plurality of circuit breaker mechanical states.
The present embodiment also provides a computer-readable storage medium storing a computer program, which when executed by a processor implements the method for diagnosing a mechanical state based on acoustic fingerprints of circuit breakers.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A mechanical state diagnostic system based on acoustic fingerprints of circuit breakers, comprising a plurality of circuit breakers, characterized in that the mechanical state diagnostic system based on acoustic fingerprints of circuit breakers comprises:
the acoustic signal acquisition modules correspond to the circuit breakers one by one and are used for acquiring acoustic signals of the circuit breakers, wherein each acoustic signal acquisition module comprises two acoustic acquisition devices, and the two acoustic acquisition devices are symmetrically arranged and equal to the distance value of the centers of the corresponding circuit breakers;
and the processing center is in communication connection with the plurality of sound wave signal acquisition modules and is used for receiving the sound wave signals of the plurality of circuit breakers acquired by the plurality of sound wave signal acquisition modules and diagnosing the mechanical state of the circuit breakers in real time according to the sound wave signals of the plurality of circuit breakers.
2. The system of claim 1, wherein the processing center comprises:
the preprocessing module is used for preprocessing the received sound wave signals of the plurality of circuit breakers;
and the fault recognition neural network model is used for diagnosing the mechanical state of the circuit breaker in real time according to the preprocessed sound wave signals of the circuit breakers.
3. The system of claim 2, wherein the preprocessing module comprises:
and the first filtering unit is used for filtering and denoising and amplifying the received sound wave signals of the plurality of circuit breakers.
4. The circuit breaker acoustic fingerprint based mechanical condition diagnostic system of claim 2, wherein the preprocessing module further comprises:
and the second filtering unit is used for screening the received sound wave signals of the plurality of circuit breakers by comparing the similarity of the sound wave signals of the plurality of circuit breakers acquired by the plurality of sound wave signal acquisition modules.
5. The system for diagnosing a mechanical state based on acoustic fingerprint of a circuit breaker according to claim 4, wherein the second filtering unit comprises:
the sampling sub-unit is used for acquiring a plurality of amplitudes of the sound wave signal of each circuit breaker;
the fitting subunit is used for fitting the acoustic wave signals of the corresponding circuit breakers according to the multiple amplitudes of the acoustic wave signals of the circuit breakers to obtain fitting curves, wherein the acoustic wave signal of one circuit breaker acquired by each acoustic wave signal acquisition module comprises two fitting curves;
and the screening subunit is used for calculating and judging whether the distance value between the two fitting curves corresponding to each sound wave signal acquisition module is smaller than a preset threshold value, if so, screening and rejecting the sound wave signals of the circuit breaker corresponding to the two fitting curves with the similarity smaller than the preset threshold value, and if not, diagnosing the mechanical state of the circuit breaker in real time according to the sound wave signals of the circuit breaker corresponding to the two fitting curves with the similarity larger than or equal to the preset threshold value.
6. A mechanical state diagnosis method based on acoustic fingerprints of circuit breakers is characterized by comprising the following steps:
s1, collecting sound wave signals of a plurality of circuit breakers;
s2, the processing center receives the sound wave signals of the plurality of circuit breakers, which are acquired by the plurality of sound wave signal acquisition modules;
s3, the processing center diagnoses the mechanical state of the circuit breakers in real time according to the sound wave signals of the circuit breakers;
wherein, every sound wave signal acquisition module includes two sound wave collection system, and two sound wave collection system symmetries set up and equal with the distance value that corresponds the circuit breaker center.
7. The method for diagnosing the mechanical state based on the acoustic fingerprint of the circuit breaker as claimed in claim 6, wherein in the step S3, the specific method for the processing center to diagnose the mechanical state of the circuit breaker in real time according to the acoustic signals of the plurality of circuit breakers comprises the following steps:
s30, preprocessing the received sound wave signals of the plurality of circuit breakers;
and S30, diagnosing the mechanical state of the circuit breaker in real time according to the preprocessed sound wave signals of the plurality of circuit breakers.
8. The method for diagnosing the mechanical state based on the acoustic fingerprint of the circuit breaker according to claim 7, wherein the method for preprocessing the received acoustic signals of the plurality of circuit breakers comprises the following steps: the received sound wave signals of the plurality of circuit breakers are screened by comparing the similarity of the sound wave signals of the plurality of circuit breakers acquired by the plurality of sound wave signal acquisition modules.
9. The method for diagnosing the mechanical state based on the acoustic fingerprint of the circuit breaker according to claim 8, wherein the specific method for screening the received acoustic signals of the plurality of circuit breakers by comparing the similarity of the acoustic signals of the plurality of circuit breakers acquired by the plurality of acoustic signal acquisition modules comprises the following steps:
collecting a plurality of amplitudes of the acoustic signal of each circuit breaker;
fitting the acoustic wave signals of the corresponding circuit breakers according to the multiple amplitudes of the acoustic wave signals of the circuit breakers to obtain a fitting curve;
calculating and judging whether the distance value between the two fitting curves corresponding to each sound wave signal acquisition module is smaller than a preset threshold value or not, if so, screening and removing the sound wave signals of the circuit breaker corresponding to the two fitting curves with the similarity smaller than the preset threshold value, and if not, diagnosing the mechanical state of the circuit breaker in real time according to the sound wave signals of the circuit breaker corresponding to the two fitting curves with the similarity larger than or equal to the preset threshold value;
the sound wave signal of a certain circuit breaker collected by each sound wave signal collecting module comprises two fitting curves.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method for diagnosing a mechanical state based on acoustic fingerprints of circuit breakers according to any one of claims 6 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210890929.0A CN115290308A (en) | 2022-07-27 | 2022-07-27 | Mechanical state diagnosis system and method based on acoustic fingerprints of circuit breaker |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210890929.0A CN115290308A (en) | 2022-07-27 | 2022-07-27 | Mechanical state diagnosis system and method based on acoustic fingerprints of circuit breaker |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115290308A true CN115290308A (en) | 2022-11-04 |
Family
ID=83823530
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210890929.0A Pending CN115290308A (en) | 2022-07-27 | 2022-07-27 | Mechanical state diagnosis system and method based on acoustic fingerprints of circuit breaker |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115290308A (en) |
-
2022
- 2022-07-27 CN CN202210890929.0A patent/CN115290308A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110031088B (en) | Electronic equipment fault detection method, device, equipment and range hood | |
| CN111436944B (en) | Falling detection method based on intelligent mobile terminal | |
| CN110231529A (en) | A kind of control cabinet intelligent Fault Diagnose Systems and method for diagnosing faults | |
| CN102302370A (en) | Method and device for detecting tumbling | |
| CN114004306A (en) | Equipment fault evaluation system and method based on multi-dimensional data of Internet of things | |
| CN115219184A (en) | Acoustic fingerprint-based circuit breaker mechanical state detection system and method | |
| CN109900469B (en) | Stress relaxation fault detection device and method for high-voltage circuit breaker spiral spring | |
| CN110530502A (en) | Motor status monitoring method, device, storage medium and computer equipment | |
| CN107105092A (en) | A kind of human body tumble recognition methods based on dynamic time warping | |
| CN116626544B (en) | Frequency domain trigger data acquisition system and method | |
| CN113075512A (en) | Sound detection-based transformer discharge fault diagnosis method and system | |
| CN115575811A (en) | Method, system, storage medium and equipment for predicting and evaluating electric service life of circuit breaker | |
| CN109934136B (en) | Rolling bearing fault diagnosis method based on Duffing vibrator and eigen mode component | |
| CN115078912A (en) | Method and system for detecting abnormity of roof high-voltage cable connector in real time and train | |
| CN113392874B (en) | Abnormal state diagnosis method and device for rail vehicle and terminal equipment | |
| CN115290308A (en) | Mechanical state diagnosis system and method based on acoustic fingerprints of circuit breaker | |
| CN109211327A (en) | Non-contact vehicle state aware device and method thereof | |
| CN116907029A (en) | Method for detecting abnormality of fan in outdoor unit, control device and air conditioner outdoor unit | |
| CN116699400A (en) | Generator rotor short-circuit fault monitoring system, method and readable storage medium | |
| EP4254261A1 (en) | Blade fault diagnosis method, apparatus and system, and storage medium | |
| CN115825551A (en) | Device and method for detecting output power of isolating switch motor | |
| CN115144172A (en) | GIS breaker fault online monitoring system and method based on sound | |
| CN115790823A (en) | Fault diagnosis method of GIS disconnecting link switch and sound vibration acquisition equipment with multiple monitoring points | |
| CN112345648B (en) | High-voltage circuit breaker cam crack fault detection device and method | |
| CN114118166A (en) | Transformer fault diagnosis system and method based on intelligent frequency spectrum monitoring |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |