KR101491017B1 - System and method for diagnosing sound of power device - Google Patents

Abstract

An apparatus and method for acoustically analyzing an electric power device, which converts sound generated in a power device into an electroacoustic signal and stores the electroacoustic signal, and diagnoses the state of the power device by analyzing the electroacoustic signal. The present invention relates to a power acoustic apparatus diagnosing apparatus comprising: a sound detecting unit for detecting a sound generated in a power device and transmitting the detected sound to a sound signal; A signal processor for converting an acoustic signal from the acoustic detector into an analog signal and then converting the analog signal into a digital signal; And a diagnosis unit for diagnosing and displaying the current state of the power device based on the converted digital signal and transmitting the alert message to at least one of the mobile terminal and the central control server when it is determined that the power device is abnormal.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to an apparatus,

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus and a method for diagnosing an electric power equipment acoustically, The present invention relates to an apparatus and method for an electric power equipment acoustical diagnosis apparatus for diagnosing a state of a power equipment by analyzing a sound generated in the apparatus.

The causes of failure in domestic electrical equipment are natural deterioration, poor repair, and poor manufacturing (58.2%). In order to analyze faults, localization, collectors, and risk assessment of partial discharges that occur when an anomaly occurs in a power device such as a transformer, electromagnetic waves, Sonic sensors and currents.

In recent years, research and development have been conducted in connection with the present invention, and Korean Patent Laid-Open Publication No. 10-2007-0046282 (name: Diagnostic apparatus and method of electric power equipment) and the like are disclosed. The prior art includes a current detector for dividing the current signal into a plurality of channels according to the magnitude of the current signal input from the power device and a signal processor for determining the presence or absence of the power device using the current signal divided into the plurality of channels .

Although the prior art as described above uses a method of confirming whether a power device is faulty by a current signal inputted from a power device, a current signal may be distorted by an abnormal current flowing from the outside, There is a problem that the failure can not be confirmed.

SUMMARY OF THE INVENTION The present invention has been proposed in order to solve the above-mentioned problems of the prior art, and it is an object of the present invention to provide a power device acoustical diagnosis apparatus which converts sound generated in a power device into an electroacoustic signal and stores the electroacoustic signal, And an object of the present invention is to provide an apparatus and a method.

According to an aspect of the present invention, there is provided an apparatus for diagnosing a power device acoustically, comprising: a sound detector for detecting a sound generated in a power device and transmitting the sound signal as an acoustic signal; A signal processor for converting an acoustic signal from the acoustic detector into an analog signal and then converting the analog signal into a digital signal; And a diagnosis unit for diagnosing and displaying the current state of the power device based on the converted digital signal and transmitting the alert message to at least one of the mobile terminal and the central control server when it is determined that the power device is abnormal.

The acoustic detection unit includes: an acoustic sensor for picking up sound generated in the power device; And a magnet disposed around the acoustic sensor.

The acoustic sensor includes: a microphone sensor for detecting an acoustic signal from a sound generated in the power device; And a transformer for detecting an acoustic signal of an electromagnetic wave derived from the acoustic signal detected by the microphone sensor.

The signal processing unit includes a sound collecting module for picking up the sound signal from the sound detecting unit; An amplification module for amplifying the picked up acoustic signal; A band pass filter module for passing a signal of a specific frequency band from the amplified acoustic signal; An encoder module for encrypting the acoustic signal passed by the band-pass filter module and distinguishing the acoustic signal from adjacent acoustic signals; An AD converter module for converting the encrypted acoustic signal provided from the encoder module into a digital acoustic signal; An audio processing module for converting digital sound signals from the AD converter module into digital data and analog sound signals; A decoder module for restoring a digital sound signal from the audio processing module to an original sound signal; And an output module for transmitting the restored sound signal and digital data provided from the decoder module to the diagnosis unit.

The analysis unit may include an analysis module for analyzing the acoustic signal and the digital data from the signal processing unit to determine whether or not an error has occurred in each power device; A storage module for storing the information of the analyzed acoustic signal in the module and providing information of the previously stored acoustic signal to the analysis module in the analysis of the acoustic signal; An alarm module for transmitting an alarm message to at least one of the mobile terminal and the central control server when the analysis module determines that the power device is abnormal; And an image module for outputting the waveform and spectrogram of the acoustic signal from the analysis module.

The analysis module diagnoses abnormality of the power device through time series analysis and frequency series analysis when abnormality data is detected in the acoustic signal and digital data, and sets the diagnostic level for each power device.

The analysis module calculates,

(here,

N is the number of samples in the interval to be analyzed, R (m) is the RZCR in the current sample m, L _th is the experimentally determined constant, w (n) is the window function used for signal processing, (n) calculates an RZCR value using a sampled digital signal of an analog signal input as a signal to obtain a current RZCR).

The analysis module calculates an average value by calculating an RZCR value for the measured sound signals and determines that the average value is within the error range of the RZCR value calculated using the sound signal measured in the steady state, If it is out of the error range of the RZCR value calculated using the sound signal measured in the steady state, it is judged to be abnormal.

The analysis module sets a frequency of 10 Hz to 500 Hz as a low spectral energy, a frequency of 501 Hz to 1000 Hz as a medium spectrum energy, and a frequency of 1 KHz to 20 KHz Set to high spectral energy.

The analysis module may be configured to calculate the spectral energy of the low spectral energy, the medium spectral energy, and the high spectral energy,

To calculate dbML parameters and dbHL parameters.

The analysis module determines that the calculated dbML parameter and dbHL parameter are within the error range of the dbML parameter and the dbHL parameter calculated using the acoustic signal measured in the steady state, and determines that the calculated dbML parameter and the dbHL parameter are in a normal state It is judged abnormal when the error range of the dbML parameter and the dbHL parameter calculated by using the acoustic signal measured in the above step is out of the error range.

According to an aspect of the present invention, there is provided a method for diagnosing a power device acoustically, comprising: detecting an acoustic signal from a sound generated in a power device by an acoustic detector connected to a plurality of power devices; Converting the detected acoustic signal into an analog signal and converting the analog signal into a digital signal by a signal processing unit; Analyzing the converted digital signal by the diagnosis unit to diagnose the current state of the power equipment; Displaying, by the diagnosis unit, the current state of the power device; And transmitting the alert message to at least one of the mobile terminal and the central control server when it is determined by the diagnosis unit that an abnormality has occurred in the power device in the diagnosing step.

Amplifying the detected acoustic signal by a signal processing unit; Encrypting an acoustic signal that has passed through a specific frequency band from the amplified acoustic signal by a signal processing unit; Converting the encrypted acoustic signal into a digital acoustic signal by a signal processing unit; Converting a digital acoustic signal into digital data and an analog acoustic signal by a signal processing unit; Reconstructing the digital acoustic signal into an original acoustic signal by the signal processing unit; And transmitting the restored sound signal and the digital data to the diagnosis unit by the signal processing unit.

The step of diagnosing includes the steps of: receiving, by the analysis unit, information of a previously stored sound signal from a storage module; Analyzing information of the received sound signal by the analyzing unit to determine whether or not an error has occurred in each of the power devices; Transmitting an alarm message to at least one of the mobile terminal and the central control server when it is determined by the analyzing unit that the power device is abnormal in the determining step; And outputting a waveform and a spectrogram of the acoustic signal by the analysis unit.

In the step of determining whether or not an abnormality occurs in the power equipment, if abnormality data is detected in the acoustic signal and the digital data, the analysis module diagnoses abnormality of the power equipment through time series analysis and frequency series analysis, Setting.

In the step of determining whether or not an abnormality has occurred in the power device, in the analysis module,

(here,

N is the number of samples in the interval to be analyzed, R (m) is the RZCR in the current sample m, L _th is the experimentally determined constant, w (n) is the window function used for signal processing, (n) calculates an RZCR value using a sampled digital signal of an analog signal input as a signal to obtain a current RZCR).

The step of determining whether or not an error has occurred in the power device includes the steps of: calculating an RZCR value for the measured sound signals by the analysis module and calculating an average value; Determining that the average value calculated by the analysis module is normal if the calculated average value is within an error range of the RZCR value calculated using the acoustic signal measured in the steady state; And determining, by the analysis module, that the average value is abnormal if the error value is out of the error range of the RZCR value calculated using the acoustic signal measured in the steady state.

The step of determining whether or not the power equipment has an abnormality includes the steps of: setting a frequency of 10 Hz or more and 500 Hz or less as low spectral energy for spectrum analysis spectrogram analysis of a sound signal by the analysis module; Setting a frequency of 501 Hz or more and 1000 Hz or less to a medium spectrum energy by the analysis module; And setting the frequency of above 1 KHz to 20 KHz to a high spectral energy by the analysis module.

The step of determining whether or not an abnormality has occurred in the power device includes the steps of: determining, based on the set low-spectral energy, the medium spectral energy, and the high-

To calculate a dbML parameter and a dbHL parameter.

The step of determining whether or not an error has occurred in the power device is performed when the analysis module determines that the calculated dbML parameter and the dbHL parameter are within the error range of the dbML parameter and the dbHL parameter calculated using the acoustic signal measured in the steady state And the calculated dbML parameter and dbHL parameter are judged to be abnormal if they deviate from the error range of the dbML parameter and the dbHL parameter calculated using the acoustic signal measured in the steady state.

According to the present invention, an apparatus and method for diagnosing an electric power equipment acoustically converts sound generated in an electric power equipment into an acoustic signal, stores and analyzes the converted acoustic signal to diagnose the electric power equipment in real time, There is a possible effect.

In addition, the apparatus and method for power equipment acoustic diagnosis converts sound generated in a power equipment into an acoustic signal, stores and analyzes the converted acoustic signal, diagnoses the power equipment in real time, diagnoses the failure of the power equipment in advance It is possible to improve the performance of the electric power equipment including GIS, EBG and MTR, to restore the reliability, to improve the economical efficiency of maintenance and maintenance, and to change the accident facility at an appropriate time.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a view for explaining a power device acoustic diagnostic apparatus according to an embodiment of the present invention; FIG.
BACKGROUND OF THE INVENTION 1. Field of the Invention [0001]
FIG. 3 is a view for explaining the sound detection unit of FIG. 2;
4 is a view for explaining the signal processing unit of FIG. 2;
5 to 7 are views for explaining the diagnosis unit of Fig. 2; Fig.
FIG. 8 is a flowchart for explaining a power device acoustic diagnostic method according to an embodiment of the present invention; FIG.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings in order to facilitate a person skilled in the art to easily carry out the technical idea of the present invention. . In the drawings, the same reference numerals are used to designate the same or similar components throughout the drawings. In the following description of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a power device acoustic diagnostic apparatus according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. FIG. 1 is a view for explaining a power device acoustic diagnostic apparatus according to an embodiment of the present invention, and FIG. 2 is a diagram for explaining a configuration of an electric power equipment acoustic diagnostic apparatus according to an embodiment of the present invention. 3 is a view for explaining the acoustic sensor of FIG. 3, FIG. 5 is a view for explaining the signal processor 240 of FIG. 2, and FIG. FIG. 8 is a diagram for explaining the diagnosis unit of FIG. 2; FIG.

1, the power device acoustic diagnostic apparatus 200 includes a plurality of power devices 100 such as a gas insulated switchgear 120, a main transformer 140 (MTR), an electromagnetic band gap (EBG) A mobile terminal 300 of an operator responsible for maintenance / management of the power device 100, and a central control server 400. [ The power device acoustic diagnostic apparatus 200 detects an acoustic signal generated in a plurality of power devices 100, converts the detected acoustic signal into a digital acoustic signal, stores and analyzes the converted digital acoustic signal to diagnose the state of the power device 100 do. When it is determined that the power device 100 is abnormal, the power device acoustic diagnostic apparatus 200 transmits a warning message to the mobile terminal 300 and the central control server 400 of the corresponding operator. Of course, the power device acoustic diagnostic apparatus 200 may transmit the state analysis result of the power device 100 to the mobile terminal 300 and the central control server 400 at predetermined intervals.

To this end, as shown in FIG. 2, the power device acoustic diagnostic apparatus 200 includes an acoustic detection unit 220, a signal processing unit 240, and a diagnostic processing unit.

The sound detection unit 220 detects sounds generated in the power device 100 such as the gas insulated switchgear 120 (gas insulated switchgear 120), the main transformer 140, the EBG 160, and the like. 3, the sound detection unit 220 includes an acoustic sensor 224 to which the magnet 222 is inserted and attached to the electric apparatus 100, and is installed in the electric apparatus 100, (100) to the signal processor (240) together with the unique number of the power device (100). Here, although the sound detection unit 220 is shown as a single configuration, the sound detection unit 220 may be composed of a plurality of sound detection units 220 attached to the plurality of power devices 100, respectively.

The acoustic detection unit 220 may include a plurality of acoustic sensors 224 formed in a structure in which a magnet 222 is inserted so that the acoustic sensor 224 can be attached to the power device 100 generating heat. That is, the plurality of acoustic sensors 224 are respectively installed in the power devices 100 to detect sounds generated in the power devices 100. The sound sensor 224 transmits the sensed sound to the sound detection unit 220 together with the unique number (management number) of the power device 100. At this time, the sound detection unit 220 collects the information received from the plurality of sound sensors 224 and transmits the collected information to the signal processing unit 240. 4, the acoustic sensor includes a microphone sensor 225 for detecting a sound signal from a sound generated in the power device, and an acoustic signal of an electromagnetic wave derived from the acoustic signal detected by the microphone sensor 225 And a transformer 226 for detecting the transformer 226.

The signal processing unit 240 amplifies and converts the sound signal from the sound detection unit 220 and transmits the amplified sound signal to the diagnosis unit 260. 5, the signal processing unit 240 includes a sound collecting module 241 for collecting sound signals from the sound detecting unit 220 and providing the sound signals to the amplifying module 242, A band pass filter module 243 for passing a signal of a specific frequency band (i.e., band frequency) from the amplified acoustic signal to the encoder module 244, a band pass filter module 242 An encoder module 244 for encrypting the acoustic signal passed through the encoder module 244 and separating it from other adjacent acoustic signals and providing it to the AD converter module 245, an encoder 244 for converting the encrypted acoustic signal provided from the encoder module 244 into a digital sound signal An AD converter module 245 for providing the audio signal to the audio processing module 246 and an audio processing module 245 for converting the digital sound signal from the AD converter module 245 into digital data and analog sound signals, A decoder module 247 for restoring the digital signal from the audio processing module 246 to the original sound signal and providing the digital data and the recovered sound signal to the output module 248, And an output module for transmitting the provided restored sound signal and digital data to the diagnosis unit 260.

The diagnosis unit 260 analyzes the acoustic signal from the signal processing unit 240 to diagnose the current state of the power device 100. The diagnosis unit 260 displays the current state of the diagnosed power device 100. [ The diagnostic unit 260 transmits an alarm sound, an alarm message, and the like to the mobile terminal 300 and the central control server 400 when the power device 100 is diagnosed as having an error.

The diagnosis unit 260 may include a terminal such as a PC, a notebook, or a tablet in which an embedded program is installed. The diagnosis unit 260 is connected to the signal processing unit 240 via a network and analyzes the digital data received through the network using the embedded program to analyze the current state of the power device 100.

6, the diagnosis unit 260 includes an analysis module 261, a storage module 262, an alarm module 263, and an image module 264.

The analysis module 261 analyzes the digital data related to the acoustic signal received from the signal processing unit 240 (i.e., the output module 248) to collect and classify data such as the power device 100, To analyze whether or not the power device 100 is abnormal. At this time, the analysis module 261 analyzes abnormality data through time series analysis and frequency series analysis when abnormal data corresponding to an abnormality is detected from collected / classified data. The analysis module 261 sets the diagnostic level for each power device based on the analysis result of the abnormality data. The analysis module 261 analyzes whether the power devices 100 are abnormally generated according to time, month, and date, and transmits the acoustic signals to the image module 264 in real time.

7 and 8, the analysis module 261 is formed in a software form and includes a Hanning window algorithm 265, an acoustic signal analysis algorithm 266, , And a visual area / frequency domain display algorithm 267. [ The analysis module 261 puts the Hanning window on the sound signal related data of the power device 100 to limit the size of the data and adjusts the frequency using FFT (Fast Fourier Transform) in the acoustic signal analysis algorithm 266 .

In addition, the analysis module 261 can calculate a crossing value of a signal based on a threshold value set for each frame by setting a threshold value in a relative zero level crossing rate (RZCR) .

here,

N is the number of samples in the interval to be analyzed. In general, the value of N in the signal processing is 256 (or 128).

R (m) represents the RZCR at the current sample m. L _th is an experimentally determined constant. In general, the value used in RZCR is 0, but the values obtained experimentally are used in this device.

w (n) is a window function used in signal processing and is used to exclude the discontinuity of the analysis interval. The window function used uses a Hamming or Hanning function used in signal processing.

x (n) represents the sampled digital signal of the analog signal coming in real time to this unit as the signal to obtain the present RZCR.

The analysis module 261 calculates an RZCR value for the measured sound signals and calculates an average value. The analysis module 261 determines that the average value is within the error range of the RZCR value calculated using the acoustic signal measured in the steady state and determines that the average value of the RZCR value calculated using the acoustic signal measured in the steady state is normal If it is outside the error range, it is judged to be abnormal.

The analyzing module 261 analyzes the data of the power device 100 by setting the frequency band to three levels for the spectrogram analysis of the power device 100, energy. The analysis module 261 sets a middle spectral energy set at a frequency of 501 to 1000 Hz as a medium spectral energy and sets a final spectral energy as a final spectral energy that is set at a frequency of more than 1 KHz and less than 20 KHz.

The analysis module 261 derives the dbML and dbHL parameters from the following Equation (2) using the energy of each of the predetermined three steps.

The analysis module 261 applies the dbML and dbHL parameters derived from Equation (2) in the frequency domain. The analysis module 261 distinguishes between the steady state and the abnormal state of the power device 100 by applying the RZCR value derived from the steady state value of the power device 100 in the time domain.

The analysis module 261 calculates dbML parameters and dbHL parameters from the acoustic signals measured in steady state. The analysis module 261 compares the calculated dbML parameter and dbHL parameter with the normal dbML parameter and the dbHL parameter to determine the abnormal state of the power device 100. At this time, the analysis module 261 determines normal if the dbML parameter and the dbHL parameter calculated within the error range of the normal dbML parameter and the dbHL parameter exist. The analysis module 261 determines that the calculated dbML parameter and dbHL parameter are in an abnormal state of the power equipment when they are out of the error range of the dbML parameter and the dbHL parameter calculated using the acoustic signal measured in the steady state.

The analysis module 261 analyzes the time and frequency domains of the power device 100 including the sensor signal processing technology DSP, the gas insulated switchgear 120, the main transformer 140, the EBG 160, Is an integrated system that measures signals, transmits data through a wired network, and embeds an embedded program to control signal data.

In addition, the analysis module 261 having the embedded program can transmit an abnormal signal extracted from the storage module 262 in real time and can be extended to a remote diagnosis and monitoring system. The analysis module 261 continuously and systematically controls the gas insulated switchgear 120, , The main transformer 140, the EBG 160, and the like can be performed.

The storage module 262 stores the analyzed and classified data in the analysis module 261. That is, the storage module 262 stores the information of the acoustic signal analyzed by the analysis module 261. The storage module 262 provides the analysis module 261 with the information of the acoustic signal stored in the analysis module 261 when analyzing the acoustic signal.

The alarm module 263 transmits an alarm sound or an alarm message to the mobile terminal 300 and the central control server 400 of the corresponding operator when the analysis module 261 analyzes the power device 100 as an abnormal occurrence. That is, the alarm module 263 generates an alarm sound when abnormal data is detected by the analysis module 261, and transmits the location and the failure history of the power device 100 to the mobile terminal 300 of the operator and the central control server 400 send.

The image module 264 outputs the acoustic signal received through the analysis module 261. That is, the image module 264 displays the waveform and spectrogram of the received sound signal. For example, the image module 264 outputs a waveform and a spectrogram of a steady-state acoustic signal received from the gas insulated switchgear 120. The image module 264 displays red when an abnormality occurs in the gas insulated switchgear 120 and displays the date and time when the abnormality occurred in red. The image module 264 displays the contents of the gas insulated switchgear 120 for switching a predetermined number of times to stabilize the power of the gas insulated switchgear 120. In case of an accident, the image module 264 is displayed in red, It is possible to establish a problem and a preventive plan of the gas insulated switchgear 120 through the graph change.

When an accident occurs in the vicinity of the gas-insulated switchgear 120, the image module 264 displays the waveform and the spectrogram in red, and displays the date and the color in red for quick action. At this time, the image module 264 may transmit the corresponding waveform, spectrogram, and year and date to the storage module 262 and store the same.

At this time, when the mobile terminal 300 and the central control server 400 receive the alarm message from the power device acoustic diagnostic apparatus 200, the mobile terminal 300 and the central control server 400 output an alarm sound to notify the operator of the occurrence of the abnormality of the power device 100. That is, the mobile terminal 300 and the central control server 400 transmit a text message (hereinafter referred to as " SMS message ") including the location and the failure history of the power device 100 in response to an error occurrence of the power device 100 from the power device acoustic diagnostic apparatus 200 Or an image, data, etc.).

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a method for diagnosing power equipment acoustics according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. FIG. 9 is a flowchart for explaining a power device acoustic diagnostic method according to an embodiment of the present invention.

The sound detection unit 220 detects the sound signal from the power device 100 (S100). That is, the sound detection unit 220 detects sounds generated in the power device 100 such as the gas insulated switchgear 120, the main transformer 140, the EBG 160, and the like. The sound detection unit 220 transmits the detected sound as a sound signal to the signal processing unit 240.

The signal processing unit 240 converts the analog sound signal received from the sound detection unit 220 into a digital sound signal (S200). That is, the signal processing unit 240 collects and amplifies the sound signal from the sound detection unit 220. The signal processing unit 240 passes a signal of a specific frequency band (that is, a band frequency) out of the amplified sound signal, and then encrypts the sound signal. The signal processing unit 240 converts the encrypted sound signal into a digital sound signal and then converts it into an analog sound signal. The signal processing unit 240 restores the analog sound signal to the original sound signal, and transmits the digital data and the restored sound signal to the diagnosis unit 260.

The diagnosis unit 260 analyzes the converted digital sound signal to diagnose the current state of the power device 100 (S300). At this time, the diagnosis unit 260 analyzes whether the power device 100 is abnormal or not through the time series analysis or the frequency series analysis of the digital sound signal. The diagnosis unit 260 sets the diagnostic level for each power device through the analysis of the digital sound signal.

The diagnosis unit 260 limits the size of the data by covering the sound signal related data with a hanning window for time series analysis of the digital sound signal, and adjusts the frequency through DDT. The diagnostic unit 260 sets a threshold value in the RZCR and calculates a waveform crossing value of the signal based on the threshold value set for each frame through the equation (1). At this time, the diagnosis unit 260 calculates an RZCR value for the measured sound signals and calculates an average value. The analysis module 261 determines that the average value is within the error range of the RZCR value calculated using the acoustic signal measured in the steady state and determines that the average value of the RZCR value calculated using the acoustic signal measured in the steady state is normal If it is outside the error range, it is judged to be abnormal.

The diagnostic unit 260 sets the frequency band to three levels of low spectral energy, medium spectral energy, and high spectral energy for frequency sequence analysis of a digital sound signal. At this time, the diagnosis unit 260 analyzes the data of the power device 100 and sets the fundamental frequency band, which is set at a frequency of 10 to 500 Hz, as Low spectral energy. The diagnostic unit 260 sets a medium spectral energy set at a frequency of 501 to 1000 Hz as a medium spectral energy and sets a final spectral energy as a final spectral energy set at a frequency of 1 KHz to 20 KHz. The diagnostic unit 260 derives the dbML and dbHL parameters through Equation (2). The diagnostic unit 260 calculates the dbML parameter and the dbHL parameter from the acoustic signal measured in the steady state. The diagnostic unit 260 compares the calculated dbML parameter and the dbHL parameter with the normal dbML parameter and the dbHL parameter to determine the abnormal state of the power device 100. At this time, the diagnosis unit 260 determines that the dbML parameter and the dbHL parameter calculated within the error range of the normal dbML parameter and the dbHL parameter are normal. The diagnostic unit 260 determines that the calculated dbML parameter and the dbHL parameter are in an abnormal state of the power equipment if they are out of the error range of the dbML parameter and the dbHL parameter calculated using the acoustic signal measured in the steady state.

The diagnosis unit 260 displays the current status of the diagnosed power equipment 100 (S400). That is, the diagnosis unit 260 displays the waveform and the spectrogram of the acoustic signal received together with the current state of the power device 100. At this time, the diagnosis unit 260 displays the occurrence time (that is, the date and time) through a separate indication when an abnormality occurs in the power device 100, and displays the abnormality occurrence period.

If the abnormality of the power device 100 is diagnosed (S500; Yes), the diagnosis unit 260 transmits an alarm message for alerting the power device 100 to abnormality (S600). That is, the diagnosis unit 260 transmits an alarm message or an alarm sound to the mobile terminal 300 and the central control server 400 of the operator responsible for the power device 100, do. Accordingly, the mobile terminal 300 and the central control server 400 output an alarm message or alarm to alert the power device 100 of the occurrence of an abnormality.

As described above, an apparatus and method for testing an electric power equipment 100 convert sound generated in the electric power apparatus 100 into sound signals, store and analyze the converted sound signals, diagnose the electric power apparatus 100 in real time, It is possible to promptly cope with a failure of the device 100. [

In addition, the apparatus and method for diagnosing a power device 100 convert sound generated in the power device 100 into an acoustic signal, store and analyze the converted acoustic signal to diagnose the power device 100 in real time, ), It is possible to improve the performance of the power device 100 including the gas insulated switchgear 120 and the main transformer 140, improve reliability of the reliability, improve the economical efficiency of maintenance and maintenance, There is an effect that can be done.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but many variations and modifications may be made without departing from the scope of the present invention. It will be understood that the invention may be practiced.

100: Power device 120: Gas insulated switchgear
140: main transformer 160: EBG
200: Acoustic diagnosis device of electric power equipment
220: acoustic detection section 222: magnet
224: Acoustic sensor 240: Signal processor
241: collecting module 242: amplifying module
243: Bandpass filter module 244: Encoder module
245: AD converter module 246: Audio processing module
247: Decoder module 248: Output module
260: Diagnosis module 261: Analysis module
262: Storage module 263: Alarm module
264: video module 265: Hanning window algorithm
266: Sound signal analysis algorithm 267: Visual area / frequency domain display algorithm
300: mobile terminal 400: central control server

Claims (20)

An acoustic detector for detecting a sound generated in the power device and transmitting the sound signal as an acoustic signal;
A signal processor for converting an acoustic signal from the acoustic detector into an analog signal and converting the analog signal into a digital signal; And
Diagnosing and displaying a current state of the power device based on the converted digital signal and transmitting the alert message to at least one of the mobile terminal and the central control server when it is determined that the power device is abnormal,
Wherein the diagnosis unit comprises:
And an abnormality of the power device is diagnosed through a time series analysis and a frequency series analysis when abnormality data is detected from the acoustic signal and the digital data to set a diagnosis level for each power device. The method according to claim 1,
Wherein the sound detection unit comprises:
An acoustic sensor for picking up sound generated by the power device; And
And a magnet disposed around the acoustic sensor. The method of claim 2,
The acoustic sensor comprises:
A microphone sensor for detecting a sound signal from a sound generated in the power device; And
And a transformer for detecting an acoustic signal of an electromagnetic wave derived from the acoustic signal detected by the microphone sensor. The method according to claim 1,
The signal processing unit,
A sound collector module for picking up acoustic signals from the sound detector;
An amplification module for amplifying the collected sound signal;
A band pass filter module for passing a signal of a specific frequency band from the amplified acoustic signal;
An encoder module for encrypting an acoustic signal passed through the band-pass filter module and distinguishing the acoustic signal from other acoustic signals;
An AD converter module for converting an encrypted acoustic signal provided from the encoder module into a digital sound signal;
An audio processing module for converting digital sound signals from the AD converter module into digital data and analog sound signals;
A decoder module for restoring the digital sound signal from the audio processing module into an original sound signal; And
And an output module for transmitting the restored acoustic signal and digital data provided from the decoder module to the diagnosis unit. The method according to claim 1,
Wherein the diagnosis unit comprises:
An analysis module for analyzing the acoustic signal and the digital data from the signal processing unit to determine whether an abnormality has occurred in each power device;
A storage module for storing information of the analyzed acoustic signal in the analysis module and providing information of the previously stored acoustic signal to the analysis module in analyzing the acoustic signal;
An alarm module for transmitting an alarm message to at least one of the mobile terminal and the central control server when the analysis module determines that the power device is abnormal; And
And an image module for outputting a waveform and a spectrogram of an acoustic signal from the analysis module. delete The method according to claim 1,
Wherein the diagnosis unit comprises:
Equation

(here,

N is the number of samples in the interval to be analyzed, R (m) is the RZCR in the current sample m, L _th is the experimentally determined constant, w (n) is the window function used for signal processing, (n) calculates an RZCR value using a sampled digital signal of an analog signal input as a signal to obtain a current RZCR). The method of claim 7,
Wherein the diagnosis unit comprises:
The RZCR value for the measured sound signals is calculated to calculate an average value,
If the average value is within the error range of the RZCR value calculated using the sound signal measured in the steady state, it is determined to be normal. If the average value is out of the error range of the RZCR value calculated using the sound signal measured in the steady state And judges that it is abnormal if it is judged to be abnormal. The method according to claim 1,
Wherein the diagnosis unit comprises:
A spectral energy of not less than 10 Hz and not more than 500 Hz is set as a low spectral energy, a frequency of not less than 501 Hz and not more than 1000 Hz is set as a medium spectral energy, a frequency of not less than 1 KHz and not more than 20 KHz is set as a high- Is set to " 0 ". The method of claim 9,
Wherein the diagnosis unit comprises:
Based on the set low spectral energy, the medium spectral energy, and the high spectral energy,

And calculates a dbML parameter and a dbHL parameter using the parameter. The method of claim 10,
Wherein the diagnosis unit comprises:
If the calculated dbML parameter and the dbHL parameter are within the error range of the dbML parameter and the dbHL parameter calculated using the acoustic signal measured in the steady state,
And determining that the computed dbML parameter and the dbHL parameter are abnormal if the computed dbML parameter and the dbHL parameter are out of the error range of the dbML parameter and the dbHL parameter calculated using the acoustic signal measured in the steady state. Detecting an acoustic signal from a sound generated in a power device by an acoustic detector connected to a plurality of power devices;
Converting the detected acoustic signal into an analog signal and converting the analog signal into a digital signal by a signal processing unit;
Analyzing the converted digital signal by a diagnosis unit to diagnose a current state of the power device;
Displaying, by the diagnosis unit, the current state of the power device; And
And transmitting the alert message to at least one of the mobile terminal and the central control server when it is determined by the diagnosis unit that an abnormality has occurred in the power device in the diagnosing step,
In the step of determining whether or not an abnormality has occurred in the power device,
Wherein when the abnormal data is detected from the acoustic signal and the digital data, the diagnosis unit diagnoses an abnormality of the power device through time series analysis and frequency sequence analysis to set a diagnostic level for each power device Way. The method of claim 12,
Wherein the diagnosing comprises:
Analyzing information of a previously stored sound signal by the diagnosis unit to determine whether or not an abnormality has occurred in each power equipment; And
And transmitting the alert message to at least one of the mobile terminal and the central control server when the diagnosis unit determines that the power device is abnormal in the determining step. 14. The method of claim 13,
Wherein the diagnosing comprises:
And outputting the waveform and the spectrogram of the acoustic signal by the diagnosis unit. delete The method of claim 12,
In the step of determining whether or not an abnormality has occurred in the power device,
By the diagnosis unit,

(here,

N is the number of samples in the interval to be analyzed, R (m) is the RZCR in the current sample m, L _th is the experimentally determined constant, w (n) is the window function used for signal processing, (n) calculates an RZCR value using a sampled digital signal of an analog signal input as a signal to obtain a current RZCR). 18. The method of claim 16,
Wherein the step of determining whether the power device is abnormal includes:
Calculating a RZCR value for the measured sound signals by the diagnosis unit and calculating an average value;
If the calculated average value is within an error range of the RZCR value calculated using the acoustic signal measured in the steady state, determining by the diagnosis unit that the average value is normal; And
And determining that the average value is abnormal if the average value deviates from an error range of the RZCR value calculated using the acoustic signal measured in the steady state. The method of claim 12,
Wherein the step of determining whether the power device is abnormal includes:
Setting a frequency of 10 Hz or more and 500 Hz or less as a low spectral energy for spectral analysis of a frequency sequence analysis of the acoustic signal by the diagnosis unit;
Setting a frequency of 501 Hz or more and 1000 Hz or less to a medium spectrum energy by the diagnosis unit; And
And setting the frequency higher than 1 KHz and lower than 20 KHz to high spectral energy by the diagnosis unit. 19. The method of claim 18,
Wherein the step of determining whether the power device is abnormal includes:
Wherein the diagnostic unit calculates the low spectral energy, the medium spectral energy, and the high spectral energy,

And calculating a dbML parameter and a dbHL parameter using the parameter. The method of claim 19,
Wherein the step of determining whether the power device is abnormal includes:
When the calculated dbML parameter and dbHL parameter are within the error range of the dbML parameter and the dbHL parameter calculated using the acoustic signal measured in the steady state, the diagnostic unit determines that the calculated dbML parameter and dbHL parameter are normal, And the parameter is determined to be abnormal when the parameter is out of the error range of the dbML parameter and the dbHL parameter calculated using the acoustic signal measured in the steady state.

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