KR20130060073A - Noise removal sensor, apparatus and method for diagnosing partial discharge using noise removal sensor - Google Patents

Abstract

PURPOSE: A noise removing sensor, a partial discharge diagnosing device which uses the noise removing sensor, and a method thereof are provided to diagnose a partial discharge precisely by sensing an electromagnetic wave, a sound wave, and a vibration which are generated during the partial discharge at the same time and comparing a mutual connectivity. CONSTITUTION: A noise removing sensor(200) includes an antenna(210) which receives a generated partial discharge signal when generating a partial discharge of electric power equipment; a signal amplification unit(220) which controls the partial discharge signal into a fixed level; a distributer(230) which equally distributes the partial discharge signal which is level-controlled by the signal amplification unit into three signals; a dispersion signal processor(240) which processes a dispersion signal in a high, medium, and low speed about each signal which is distributed by the distributer; a differential signal processor(250) which calculates a difference value of a dispersion signal processing result per each speed of the dispersion signal processor and removes a noise which is included in the partial discharge signal; a linkup unit(270) which is inputted with a control signal in order to remove a noise about the partial discharge signal by using a second communication method and outputs the partial discharge signal in which the noise is removed to connected external equipment by using a second communication method; and a processor(260) which controls the signal amplification unit and the dispersion signal processor and processes the result value of the differential signal processor and the signal which is inputted and outputted through the linkup unit. [Reference numerals] (210) Antenna; (241) High-speed logarithmic amplifier; (243) Variable middle-speed logarithmic amplifier; (245) Variable low-speed logarithmic amplifier; (250) Differential signal processor; (260) Processor; (270) Linkup unit

Description

Noise removal sensor, apparatus and method for diagnosing partial discharge using noise canceling sensor {{Noise removal sensor, apparatus and method for diagnosing partial discharge using noise removal sensor}

The present invention relates to a noise canceling sensor, and a partial discharge diagnostic apparatus and method using the noise canceling sensor. More particularly, the present invention relates to a partial discharge diagnosis by detecting the electromagnetic waves and the sound waves / vibrations generated at the same time, and comparing the correlations. The present invention relates to a noise canceling sensor for diagnosing discharge, and a partial discharge diagnostic device using the noise canceling sensor and a method thereof.

The conventional partial discharge diagnosis apparatus includes an ultrasonic microphone sensor and a detection sensor to detect a partial discharge by detecting an ultrasonic wave and a pulse voltage generated when a partial discharge occurs in a power facility.

At this time, the electromagnetic wave generated when the partial discharge occurs through a certain outlet (gasket, spacer), which appears as a pulse waveform having a few mV amplitude and several ns rise time at the ground potential of the metal enclosure of the power equipment. Diagnose partial discharge.

In this case, if there is an electromagnetic wave source outside the 1GHZ band, for example, a mobile phone, an RF transmitter, etc. in the DC stage, the result value is affected, which lowers the diagnostic reliability.

In addition, the conventional partial discharge diagnostic device detects the ultrasonic wave transmitted through the air when the partial discharge occurs, and diagnoses the partial discharge, the center band of the ultrasonic measurement microphone is 40kHz.

In this case, there should be an air passage through which ultrasonic waves can flow out, but the structure made of steel enclosure is not suitable because of the absence of the ultrasonic passage passage. In addition, when the ambient 40kHz noise is excessive, the diagnosis conditions are inadequate and diagnosis is impossible, and the ultrasonic sensor may malfunction even when the ambient electrical noise is strong.

An object of the present invention, by detecting the electromagnetic waves, sound waves and vibrations generated during partial discharge at the same time to compare the correlation, the partial discharge diagnostic device using a noise removal sensor, and noise removal sensor to diagnose the partial discharge more precisely and To provide a method.

The noise removing sensor according to the present invention for achieving the above object, the antenna for receiving the partial discharge signal generated when the partial discharge of the power device, a signal amplifier for adjusting the partial discharge signal to a predetermined level, the signal A distribution unit for equally distributing the partial discharge signal level-adjusted by the amplifier into three signals, a distributed signal processing unit for performing distributed signal processing at high speed, medium speed, and low speed on each signal distributed by the distribution unit, and the distributed signal A differential signal processor for removing noise included in the partial discharge signal by calculating a difference value of the distributed signal processing result for each speed of the processor; and a control signal for removing the noise for the partial discharge signal using a first communication method A device receiving an input and outputting the partial discharge signal from which the noise is removed to a connected external device using a second communication method , And characterized in that it comprises a processor for controlling the signal amplifier and the distributed signal processor, it processes the signal to be input and output through the result value and the device connection of the differential signal processing.

The first communication method may be any one of CAN, LIN, RS-485, and RS-422.

The second communication method may be any one of optical Ethernet, Sonet / SDH, and T1 / E1.

The distributed signal processor may include a fixed speed fast log amp, a variable speed medium speed log amp, and a variable speed low speed log amp.

The differential signal processor may remove noise of the partial discharge signal based on a difference value of an output signal due to a difference in reaction speed between the high speed log amplifier and the low speed log amplifier.

The differential signal processing unit may remove noise of the partial discharge signal by using a subtractor.

When the signal similar to the partial discharge signal is repeated in the same time period, the differential signal processor may generate noise of the partial discharge signal based on a difference value of an output signal due to a difference in response speed between the fast log amplifier and the variable intermediate speed log amplifier. It characterized in that to remove.

In the partial discharge diagnosis apparatus according to the present invention for achieving the above object, when generating a partial discharge signal, the noise to remove the noise of the partial discharge signal by using the difference in the response speed of the signal, and outputs a signal from which the noise is removed A removal sensor, a laser module for outputting a laser to a surface of a power device when the partial discharge signal is generated, and extracting sound waves and vibration data from the reflected signal of the laser, and the partial discharge signal from which the noise is input through the sensor connection part And a correlation analysis unit for comparing the sound waves and vibration data extracted by the laser module and analyzing the correlation, and as a result of the correlation analysis of the correlation analysis unit, the partial discharge signal from which the noise is removed and the sound wave and vibration data For a signal in which at least one of the generation period, time, and phase of Minutes, characterized in that it comprises discharge diagnosing partial discharge diagnosing section for.

The correlation analysis unit extracts change data of magnitude with respect to time from the sound wave and vibration data, and extracts a signal related to 60 Hz by performing Fast Fourier Transform (FFT) analysis on the sound wave and vibration data. It is done.

The correlation analysis unit may calculate data of a magnitude component corresponding to each phase of each speed of the partial discharge signal from which the low noise component is removed through the noise removing sensor.

The correlation analysis unit may analyze the correlation by comparing the vibration frequency of the sound wave and vibration data with at least one of a generation period, time, and phase of the partial discharge signal from which the noise is removed.

The correlation analysis unit may compare the correlation between the sound wave and vibration data generated at the same time and the partial discharge signal from which the noise is removed.

The partial discharge diagnosis unit may calculate a weight according to a correlation between the sound wave and vibration data and the partial discharge signal from which the noise is removed.

On the other hand, in the partial discharge diagnostic method according to the present invention for achieving the above object, when the partial discharge signal is generated, by removing the noise of the partial discharge signal by using the difference in the response speed of the signal through the noise removal sensor, the noise is Outputting the removed signal; outputting a laser to a surface of a power device through a laser module when the partial discharge signal is generated; extracting sound waves and vibration data from the reflected signal of the laser; receiving from the noise removing sensor Analyzing the correlation by comparing the partial discharge signal from which the noise has been removed and the sound wave and vibration data extracted through the laser module, and analyzing the correlation; At least one of the generation cycle, time, and phase of the partial discharge signal and the sound wave and vibration data And diagnosing the partial discharge with respect to the signal corresponding to I.

The analyzing of the correlation may include extracting change data of magnitude with respect to time from the sound wave and vibration data, and extracting a signal corresponding to a set frequency by performing fast Fourier transform analysis on the sound wave and vibration data. It is characterized by including.

The analyzing of the correlation may include calculating data of a magnitude component corresponding to each phase of each speed of the partial discharge signal from which the low noise component is removed through the noise removing sensor.

The analyzing of the correlation may include comparing the vibration frequency of the sound wave and vibration data with at least one of a generation period, a time, and a phase of the noise-free partial discharge signal.

The analyzing of the correlation may include comparing correlations between the sound wave and vibration data generated at the same time and the partial discharge signal from which the noise is removed.

The diagnosing of the partial discharge may include calculating a weight according to a correlation between the sound wave and vibration data and the partial discharge signal from which the noise is removed.

The noise of the partial discharge signal from which the noise is removed is based on the difference value of the output signal due to the difference in response speed of the high speed log amplifier, the variable intermediate speed log amplifier, and the variable low speed log amplifier of the noise removing sensor. Characterized in that removed.

According to the present invention, the partial discharge signal (electromagnetic waves) from which the noise is removed by the active sensor and the acoustic wave and vibration data of the laser module are compared with each other to detect a correlated signal, thereby diagnosing the partial discharge. There is an advantage in that the accuracy of the error of the single sensor method or the ultrasonic method is improved, and the partial discharge detection and the partial discharge generation position are increased.

In addition, the present invention by using the excellent straightness of the laser beam to be able to measure at a certain distance or more, to ensure the separation distance between the main body of the power device and the sensor, thereby to check the equipment of the place that was not accessible or easy. There is an advantage to this.

In addition, the present invention has the advantage that it is possible to implement a noise canceling sensor simple and economic structure by removing the noise in real time using a subtractor.

1 is a view showing the configuration of a partial discharge diagnostic apparatus according to the present invention.
2 is a block diagram referred to for explaining the configuration of the partial discharge diagnostic apparatus according to the present invention.
3 is a block diagram referred to to explain the configuration of the noise canceling sensor according to the present invention.
4 is an exemplary diagram referred to for describing a configuration of the device connection unit of FIG. 3.
5 to 7 are exemplary views referred to for describing the operation of the partial discharge diagnostic apparatus according to the present invention.
8 is a flowchart illustrating an operation flow of the laser module of the partial discharge diagnostic apparatus according to the present invention.
9 is a flowchart illustrating an operation flow of a noise removing sensor according to the present invention.
10 is a flowchart illustrating an operation flow of the partial discharge diagnostic method according to the present invention.

The types of energy generated during partial discharge include electromagnetic waves, sound waves, light, and heat. In this case, the partial discharge diagnosis apparatus according to the present invention detects electromagnetic waves, sound waves, and vibrations of energy generated at the time of partial discharge at the same time and compares and analyzes the correlations, thereby diagnosing the partial discharge more precisely.

In addition, in the present invention, in the method of diagnosing partial discharge, a SRPDA (Speed Related Partial Discharge Analysis) method for diagnosing pure partial discharge by removing noise based on a difference in response speed of a signal is applied. For a detailed technical description thereof, please refer to the following description.

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings.

1 is a view showing the configuration of a partial discharge diagnostic apparatus according to the present invention.

As shown in FIG. 1, the partial discharge diagnosis apparatus 100 according to the present invention is largely divided into a partial discharge diagnosis apparatus main body, a noise removing sensor 200, and a laser module 140.

At this time, the noise removing sensor 200 is provided separately on the outside of the partial discharge diagnosis apparatus main body, the laser module 140 is preferably provided integrally with the partial discharge diagnosis apparatus main body on the inner or outer surface of the partial discharge diagnosis apparatus main body. Do.

However, the laser transceiver of the laser module 140 is to be arranged outside the main body of the partial discharge diagnostic device. In addition, the noise removing sensor 200 is fixed through a support, and is disposed in a position where a person cannot access. Of course, it is not limited thereto.

The laser module 140 outputs laser light to the surface of the power device to be diagnosed through the laser transceiver, and the output laser light is received through the laser transceiver as reflected light having a sound wave component. The laser transmitter / receiver may be formed separately from the laser transmitter 143 and the laser receiver, or may be integrally formed.

In this case, the laser module 140 amplifies a frequency included in the received reflected light to acquire a vibration frequency, and then outputs the vibration frequency to a control unit (not shown) of the partial discharge diagnosis apparatus 100.

The noise removing sensor 200 is assumed to be an active sensor. Of course, it is not limited thereto.

The noise removing sensor 200 applies a noise removing method according to a response speed difference, removes noise of the partial discharge signal detected under the control of the control unit of the partial discharge diagnosis apparatus 100, and then removes the partial discharge from the noise. The signal is output to the control unit of the partial discharge diagnosis apparatus 100.

In this case, the main body of the partial discharge diagnosis apparatus 100 and the noise removing sensor 200 are connected to the photo-composite medium method using the optical Ethernet method and the CAN method as a communication protocol. Specifically, the control signal and the power source, which are downstream signals, use a CAN protocol and a copper wire as a communication medium. On the other hand, the upstream response signal uses an optical Ethernet communication protocol and POF (Plastic Optical Fiber) as a communication medium. As one example, an optical fiber, glass optical fiber, or the like may be used.

Here, the control signal has the following characteristics.

-Signal synchronized to external 60 Hz

-Control signal of variable medium speed log amplifier and variable low speed log amplifier

Variable Gain Amplifier (VGA) Control Signal

On the other hand, the response signal has the following characteristics.

-60Hz synchronous waveform digital conversion signal of noise-reduced time division variable medium speed log amplifier and variable low speed log amplifier

-Simple diagnosis result (alarm output): Provide self-diagnosis result through high speed algorithm algorithm built in DSP

2 is a block diagram referred to for explaining the configuration of the partial discharge diagnostic apparatus according to the present invention.

As shown in FIG. 2, the partial discharge diagnosis apparatus 100 according to the present invention includes an input unit 110, a display unit 120, a control unit 130, a laser module 140, a sensor connection unit 150, and noise removal. The sensor 200, the correlation analysis unit 160, and the partial discharge diagnosis unit 170 are included. In this case, the controller 130 controls the operation of each part of the partial discharge diagnosis apparatus 100.

The input unit 110 may be disposed in the form of a key button on the outside of the partial discharge diagnosis apparatus 100 and may be disposed in the form of a soft key implemented on a touch screen. At this time, the input unit 110 outputs a corresponding signal to the control unit 130 according to the key operation.

The display unit 120 may be disposed outside the partial discharge diagnosis apparatus 100 in the form of a monitor or a touch screen. In this case, the display unit 120 outputs an operation state and a result of the partial discharge diagnosis apparatus 100.

The laser module 140 includes a laser output controller 141, a laser transmitter 143, a signal processor 145, and a laser receiver 147. Here, the laser transmitter 143 and the laser receiver 147 may be formed separately or may be integrally formed.

The laser output controller 141 transmits the laser output signal to the laser transmitter 143 according to the control signal from the controller 130.

The laser transmitter 143 includes a laser light output means therein, and drives the laser light output means according to the laser output signal from the laser output controller 141 to direct the laser light to the surface of the power device to diagnose partial discharge. Output

The laser receiver 147 receives a reflected signal in the form of light in which the laser light output by the laser transmitter 143 is reflected from the surface of the power device. In this case, the received reflected light includes sound waves and vibration components due to vibration generated on the surface of the power device.

The signal processor 145 processes the reflected signal received by the laser receiver 147. In detail, the signal processor 145 amplifies the reflected signal received by the laser receiver 147 to extract sound waves and vibration data, and outputs the extracted sound waves and vibration data to the controller 130. Here, the sound wave and vibration data includes vibration frequency information of the reflected signal.

Since the noise removing sensor 200 is separately provided outside the main body of the partial discharge diagnosis apparatus, the noise removing sensor 200 is connected to the main body of the partial discharge diagnosis apparatus 100 through the sensor connection unit 150.

The noise elimination sensor 200 detects noise of the partial discharge signal based on the difference value of the output signal due to the difference in the response speed of the high speed log amplifier 233, the variable medium speed log amplifier 235, and the variable low speed log amplifier 237. Remove That is, since the sum of the rise time, the duration time, and the fall time differs between the partial discharge signal and the noise signal, noise is removed from the partial discharge signal by using the difference. At this time, the partial discharge signal from which the noise is removed is output to the controller 130 through the sensor connection unit 150.

Detailed configuration of the noise removing sensor 200 will be described with reference to the embodiments of FIGS. 3 and 4.

The correlation analysis unit 160 analyzes the correlation of each signal by comparing the partial discharge signal from which the noise output from the noise removal sensor 200 is removed with the sound wave and vibration data extracted through the laser module 140.

At this time, the correlation analysis unit 160 extracts the change data of the magnitude of time from the sound wave and vibration data, analyzes the sound wave and vibration data by Fast Fourier Transform (FFT), and compares it with the commercial power frequency (60 Hz). Extract the relevant signal.

In addition, the correlation analysis unit 160 calculates data of the magnitude component corresponding to each phase for each reaction rate of the partial discharge signal from which the noise is removed through the noise removing sensor 200.

The correlation analysis unit 160 analyzes the correlation by comparing the partial discharge signal from which noise generated at the same time is removed with at least one of a generation period, time, and phase of sound wave and vibration data.

As a result of the correlation analysis of the correlation analysis unit 160, the partial discharge diagnosis unit 170 may detect a partial discharge signal from which noise is removed, and a signal in which at least one of a generation cycle, time, and phase of sound wave and vibration data coincide with each other. Diagnose partial discharge.

In this case, the partial discharge diagnosis unit 170 calculates a weight according to the correlation between the sound wave and vibration data and the partial discharge signal from which the noise is removed, and applies the same to diagnose the partial discharge.

3 is a block diagram referred to to explain the configuration of the noise canceling sensor according to the present invention.

The most important technique in diagnosing partial discharge using electromagnetic waves is a denoise technique that distinguishes a partial discharge signal from ambient noise in a received electromagnetic signal. In this case, most of the noise is power noise such as a corona signal generated from a wireless electromagnetic wave for electromagnetic communication or a peripheral power device.

Unlike other signals, the partial discharge signal has a very rapid and very short rise, duration and fall time of several ns. Therefore, in the noise removing sensor 200 according to the present invention, a method of removing noise from an initially generated partial discharge signal using a difference in response characteristics to the partial discharge signal and the noise signal is applied.

As shown in FIG. 3, the noise removing sensor 200 according to the present invention includes an antenna 210, a signal amplifier 220, a distributor 230, a distributed signal processor 240, and a differential signal processor 250. , A processor unit 260, and a device connection unit 270.

The antenna 210 receives the partial discharge signal generated when the partial discharge of the power device occurs.

That is, when the partial discharge signal is generated in the power device, the generated partial discharge signal is input to the noise removing sensor 200 through the antenna 210. In this case, the partial discharge signal input through the antenna 210 is a signal in which a noise signal is mixed. As an example, the antenna 210 may be implemented in the form of a chip antenna, and a passive sensor may be used.

The signal amplifier 220 includes a low noise amplifier (hereinafter referred to as "LNA") 221 and a variable gain amplifier (hereinafter referred to as "VGA") 225. At this time, the signal amplifier 220 adjusts the partial discharge signal to a predetermined level using the LNA 221 and the VGA 225.

The distribution unit 230 evenly distributes the partial discharge signal adjusted by the signal amplifier 220 to two or more signals. 3 shows an example of equal distribution of three signals. The three signals equally distributed by the distribution unit 230 are input to the distributed signal processing unit 240.

The distributed signal processor 240 performs distributed signal processing on each signal distributed by the distribution unit 230 at high speed, medium speed, and low speed.

Here, the distributed signal processor 240 may include a fixed speed high speed log amplifier 241, a variable speed medium speed log amplifier 243, a variable speed low speed log amplifier 245, and an output signal of each log amplifier from an analog signal to a digital signal. Analog to digital converters (hereinafter referred to as " ADC ") 242, 244, and 246.

Therefore, each signal distributed by the distribution unit 230 is input to the high speed log amplifier 241, the variable intermediate speed log amplifier 243, and the variable low speed log amplifier 245. In this case, the signals input to the high speed log amplifier 241, the variable intermediate speed log amplifier 243, and the variable low speed log amplifier 245 are signals of the same time and in the same condition.

On the other hand, in the embodiment of the present invention, it is assumed that the same signal is input to the high speed log amplifier 241, the variable intermediate speed log amplifier 243, and the variable low speed log amplifier 245, respectively, at the same time and under the same conditions. If the input signals to the high speed log amplifier 241, the variable intermediate speed log amplifier 243, and the variable low speed log amplifier 245 are not the same due to the characteristic difference of the circuit implemented according to the present invention, zero adjustment means for the input signal ( Not shown) may be provided separately.

Here, the zero point adjusting means may generate an electromagnetic wave signal from the outside for calibration purposes and be input to the partial discharge sensor, or by placing a test input point in front of the distribution unit 230 and inputting an electrical high frequency signal from the outside to zero point. You can also adjust.

In addition, the high speed log amplifier 241 and the variable medium speed log amplifier 243 may be used to prevent a characteristic change between the high speed log amplifier 241, the variable medium speed log amplifier 243, and the variable low speed log amplifier 245. And correction means (not shown) for correcting the deviation of the low speed log amplifier 245 may be separately provided.

Here, the correction means corrects the characteristic value of the internal circuit in order to correct the signal characteristics of the high speed log amplifier 241, the variable intermediate speed log amplifier 243, and the variable low speed log amplifier 245, or the result value is software-adjusted. You can correct it.

On the other hand, since the fast log amplifier 241 of the distributed signal processor 240 has a high response speed, the high speed log amplifier 241 detects signals having high speed, medium speed, and low operating speed, and converts the first voltage signal proportional to the signal strength into an ADC. Output to (242).

At this time, the ADC 242 converts the analog voltage first voltage signal into a digital signal and outputs it to the differential signal processor 250.

Since the variable medium speed log amplifier 243 has a reaction speed of medium speed, it does not detect a signal having a high operating speed, that is, a partial discharge signal, and detects signals having a medium speed and a low operating speed, A proportional second voltage signal is output to the ADC 244.

At this time, the ADC 244 converts the second voltage signal of the analog form into a digital signal and outputs it to the differential signal processor 250.

Since the variable low speed log amplifier 245 has a low response speed, the variable low speed log amplifier 245 does not detect a signal having a high speed and a medium speed but detects only a signal having a low speed. The low speed log amplifier 245 outputs a third voltage signal proportional to the detected signal strength to the ADC 246.

At this time, the ADC 246 converts the third voltage signal of the analog form into a digital signal and outputs it to the differential signal processor 250.

Here, the high speed log amplifier 241, the variable medium speed log amplifier 243, and the variable low speed log amplifier 245 simultaneously process input signals and operate at the same reference voltage and sampling frequency.

In addition, the variable intermediate speed log amplifier 243 may be controlled by the control logic of the processor 260 in a variable speed type. In some cases, the variable speed of the variable intermediate speed log amplifier 243 may be manually controlled by a control signal input from the outside.

The differential signal processor 250 removes noise included in the partial discharge signal by calculating a difference value of the distributed signal processing result for each speed of the distributed signal processor 240.

Here, the differential signal processor 250 removes noise of the partial discharge signal based on the difference value of the output signal due to the difference in the response speed of the high speed log amplifier and the variable low speed log amplifier.

In an embodiment, the differential signal processor 250 may include a first voltage signal, a second voltage signal, and a first voltage signal output from the high speed log amplifier 241, the variable intermediate speed log amplifier 243, and the variable low speed log amplifier 245. When the three voltage signals are input, the voltage strengths of the first voltage signal, the second voltage signal, and the third voltage signal are measured to be proportional to the voltage strengths of the first voltage signal, the second voltage signal, and the third voltage signal. The first electromagnetic wave signal dBm, the second electromagnetic wave signal dBm, and the third electromagnetic wave signal dBm are output.

At this time, the signal processing unit 239 compares the peak values of the first electromagnetic wave signal, the second electromagnetic wave signal, and the third electromagnetic wave signal, and subtracts the peak value of the second electromagnetic wave signal / third electromagnetic wave signal from the peak value of the first electromagnetic wave signal. The noise of the input partial discharge signal is removed.

More specifically, the partial discharge signal is a high speed signal having a very short time of rise time, duration, and fall time, whereas the noise signal is a low speed signal having a slow rise time of the rise time, duration, and fall time. to be. Therefore, the signal passing through the high speed log amplifier 241 becomes a partial discharge signal + a noise signal, and the signal passing through the variable low speed log amplifier 245 becomes a noise signal. Accordingly, the signal obtained by subtracting the signal passing through the variable low speed log amplifier 245 from the signal passing through the high speed log amplifier 241 is a partial discharge signal from which noise is removed.

Meanwhile, the differential signal processor 250 may include a subtractor therein and may remove noise of the partial discharge signal by subtracting the third voltage signal from the first voltage signal using the subtractor. Of course, when the differential signal processor 250 removes noise of the partial discharge signal using a subtractor, the ADCs 242, 244, and 246 of the distributed signal processor 240 may be omitted.

In addition, the differential signal processing unit 250 may be caused by a difference in response speed between the high speed log amplifier 241 and the variable intermediate speed log amplifier 243 / variable low speed log amplifier 245 when a signal similar to the partial discharge signal is duplicated at the same time period. The noise of the partial discharge signal can be removed more precisely based on the difference value of the output signal.

The device connection unit 270 is a connection means for connecting the noise removing sensor and an external device, for example, a partial discharge measuring device. The device connection unit 270 may correspond to a connector for connecting the noise removing sensor and the external device.

The device connection unit 270 receives a control signal for removing the noise of the partial discharge signal using the first communication method and outputs the partial discharge signal from which the noise is removed using the second communication method to the connected external device.

Detailed configuration description of the device connection unit 270 will be described with reference to FIG. 4.

The processor 260 controls the signal amplifier 220 and the distributed signal processor 240, and processes the result values of the differential signal processor 250 and the signals input and output through the device connection unit 270. Meanwhile, the processor unit 260 may include an embedded system having a memory function to enable secular change, history management, and failure notification.

4 is an exemplary view referred to to explain the detailed configuration of the device connection unit according to the present invention. As shown in FIG. 4, the device connection unit 270 is divided into a communication line for inputting a signal from an external device and a communication line for outputting a signal to the external device.

First, in the device connection unit 270, a communication line that receives a signal from an external device, that is, LINE_1 may be implemented as a copper wire. At this time, LINE_1 receives a control signal for removing noise with respect to the partial discharge signal using the first communication method. In this case, the control signal is downstream, and the data capacity is small, but the communication method with excellent noise immunity is applied. As an example, the first communication scheme may be any one of CAN, LIN, RS-485, and RS-422.

On the other hand, the communication line, that is, the signal input line from the external device in the device connection unit 270, that is, LINE_2 can be implemented as an optical cable, that is, an optical cable such as glass optical fiber, plastic optical fiber and the like. At this time, LINE_2 outputs the data signal of the noise removing sensor, that is, the partial discharge signal from which the noise is removed, to the external device using the second communication method.

Here, the data signal is upstream upstream, the data capacity is large, and a high noise immunity communication method is applied. As an example, the second communication method may be any one of optical Ethernet, 155 Mbps Sonet / SDH, and 1.544 Mbps / 2.048 Mbps T1 / E1.

Therefore, the noise removing sensor 200 outputs the partial discharge signal from which the noise is finally removed through the optical cable connected to the partial discharge diagnosis apparatus main body.

5 to 7 are exemplary views referred to for describing the operation of the partial discharge diagnostic apparatus according to the present invention.

First, FIG. 5 illustrates size change data over time with respect to sound waves and vibration data obtained through a laser module. 6 illustrates an example of fast Fourier transforming sound wave and vibration data acquired through a laser module to a set frequency. In FIG. 6, it can be seen that a frequency component of 60 Hz is detected.

Meanwhile, FIG. 7 illustrates magnitude component data corresponding to each phase for each speed with respect to the partial discharge signal from which noise is removed through the noise removing sensor 200.

5 to 7, the correlation analysis unit 160 compares the frequency according to the phase for each speed of the partial discharge signal with a frequency component of 60 Hz, which is a commercial power frequency of sound waves and vibration data, and generates a period and a time. Determine if there is a signal that matches at least one of,, and phase. In this case, the correlation analysis unit 160 determines that there is a correlation between signals in which at least one of a generation period, a time, and a phase matches.

Therefore, the partial discharge diagnosis unit 170, as a result of the analysis of the correlation analysis unit 160, the magnitude of the signal according to the phase, according to the phase of each frequency of 60Hz frequency components of the sound wave and vibration data and the partial discharge signal The partial discharge diagnosis is performed on a signal in which at least one of the generation period, time, and phase matches.

8 is a flowchart illustrating an operation flow of the laser module of the partial discharge diagnostic apparatus according to the present invention.

As shown in FIG. 8, when the laser module 140 is driven by the control unit 130 of the partial discharge diagnosis apparatus 100 (S100), the laser module 140 may determine the power device to be diagnosed through the laser transceiver. The laser signal is output to the surface (S110).

Thereafter, the laser signal output in step S110 is reflected on the surface of the power device, and the laser receiver 147 receives a reflected signal including sound waves and vibration components caused by the vibration of the surface of the power device (S120).

Accordingly, the signal processor 145 of the laser module 140 obtains sound wave and vibration data from the reflected signal received in step S120 (S130).

9 is a flowchart illustrating an operation flow of a noise removing sensor according to the present invention.

As shown in FIG. 9, when the noise removing sensor 200 is driven by the control unit 130 of the partial discharge diagnosis apparatus 100 (S200), the noise removing sensor 200 is a high speed circuit, a medium speed circuit, and a low speed. The speed and cycle of the circuit are set (S210).

In this case, since the high speed circuit has a high speed, the medium speed circuit has a medium speed, and the low speed circuit has a low operating speed, and the middle speed circuit and the low speed circuit include a variable log amplifier, the speed can be changed later according to the operation of the processor unit.

Thereafter, the noise removing sensor 200 performs a partial discharge detection operation (S220), and detects the partial discharge signal when the partial discharge occurs in the power device. In this case, the detected partial discharge signal is a signal including a noise component.

Therefore, when the partial discharge signal is input (S230), the noise removing sensor 200 removes noise included in the partial discharge signal from the output value of the circuit for each speed (S270). Here, each speed circuit refers to a high speed circuit, a medium speed circuit, and a low speed circuit.

More specifically, when the partial discharge signal is detected, the partial discharge signal is divided into three signals having the same condition by the divider 232, wherein the three signals are divided into the high speed log amplifier 241 and the high speed circuit, respectively. To the variable intermediate speed log amplifier 243 of the medium speed circuit and the variable low speed log amplifier 245 of the low speed circuit. The high speed log amplifier 241, the variable medium speed log amplifier 243, and the variable low speed log amplifier 245 detect and output an input signal according to a set operating speed.

In this case, the differential signal processing unit of the noise removing sensor 200 compares the difference between the output values of the signals output from the high speed log amplifier 241, the variable intermediate speed log amplifier 243, and the variable low speed log amplifier 245, The noise included in the partial discharge signal is removed by subtracting the output value of the variable low speed log amplifier 245 from the output value of the log amplifier 241.

If a signal similar to the partial discharge signal is repeated in the same time period, the differential signal processing unit of the noise removing sensor 200 compares the output value of the high speed log amplifier 241 with the output value of the variable intermediate speed log amplifier 243 and the partial discharge signal. Noise can be removed finely.

In addition, when the partial discharge signal is input in the 'S230' process, the noise removing sensor 200 measures the repetition characteristic of the partial discharge signal (S240) and compares it with the reference value. The reference value can be set to the default value or can be changed during operation. If the repetition characteristic of the partial discharge signal does not exceed the reference value (S250), the process returns to the step S240 and then compares the repetition characteristic of the partial discharge signal with the reference value.

On the other hand, if the repetition characteristic of the partial discharge signal exceeds the reference value (S250), after varying the speed of the predetermined variable medium speed log amplifier 243 and variable low speed log amplifier 245 (S255), finely adjusted high speed The signal distribution data for each speed is generated for the signals of the medium speed and the low speed (S260), and the noise of the partial discharge signal is removed by comparing the speed difference of each signal (S270).

Here, the signal distribution data for each speed are used to diagnose the partial discharge signal in the partial discharge diagnosis apparatus, and more specifically, to generate the graph of FIG. 7, and can be used in the 'S330' process of FIG. have.

Therefore, the noise removing sensor 200 outputs the partial discharge signal from which the noise is removed in the 'S270' process to the partial discharge diagnosis apparatus main body (S280). In this case, the noise removing sensor 200 may output the signal distribution data for each speed generated in the 'S260' process in addition to the partial discharge signal to the partial discharge diagnosis apparatus main body. Of course, the signal distribution data for each speed generated in the 'S260' process may respond to a control signal of an external device such as an alarm signal from the processor unit or a partial discharge diagnosis device immediately after being generated, regardless of the noise removing operation of the partial discharge signal. The ACK signal may be output directly to an external partial discharge diagnosis apparatus.

10 is a flowchart illustrating an operation flow of the partial discharge diagnostic method according to the present invention.

As shown in FIG. 10, the partial discharge diagnosis apparatus 100 according to the present invention drives the laser module 140 and the noise removing sensor 200 to diagnose partial discharge occurring in the power device (S300).

Subsequently, when a partial discharge occurs in the power device, sound wave and vibration data are obtained from the laser module 140 through the processes of FIG. 8 (S310), and noise from the noise removing sensor 200 through the processes of FIG. 9. Obtain the removed partial discharge signal (S320).

In this case, the partial discharge diagnosis apparatus 100 compares the sound wave vibration frequency of the sound wave and vibration data acquired in step S310 with the repetition rate of the partial discharge signal from which the noise obtained in step S320 is removed (S330).

In other words, in the 'S330' process, at least one of a generation period, a time, and a phase of the sound wave vibration frequency and the noise portion-free partial discharge signal is compared. Therefore, the partial discharge diagnosis apparatus 100 analyzes the correlation between the sound wave and vibration data and the partial discharge signal from which the noise is removed from the comparison result of the 'S330' process (S340).

If, as a result of the analysis of the 'S340' process, it is confirmed that there is a correlation between the sound wave and vibration data and the partial discharge signal from which the noise is removed, the partial discharge diagnosis apparatus 100 diagnoses the partial discharge (S350), and the result of the partial discharge diagnosis. Outputs (S360).

As described above, the noise canceling sensor according to the present invention, and the partial discharge diagnosis apparatus using the noise canceling sensor and the method thereof have been described with reference to the illustrated drawings, but the present invention is not limited to the embodiments and drawings disclosed herein. However, it can be applied within the scope of protection of technical ideas.

100: partial discharge diagnostic device 110: input unit
120: display unit 130: control unit
140: laser module 141: laser output control unit
143: laser transmitter 145: signal processor
147: laser receiver 150: sensor connection
160: correlation analysis unit 170: partial discharge diagnosis unit
200: noise reduction sensor 210: antenna
220: signal amplification unit 230: distribution unit
240: distributed signal processor 241: high-speed log amplifier
243 variable variable speed log amplifier 245 low speed log amplifier
242, 244, 246: analog-to-digital converters (ADCs)
250: differential signal processing unit 260: processor unit
270 device connection

Claims (20)

An antenna for receiving the generated partial discharge signal when the partial discharge of the power device occurs;
A signal amplifier for adjusting the partial discharge signal to a predetermined level;
A distribution unit equally distributing the partial discharge signals adjusted by the signal amplifier to three signals;
A distributed signal processing unit configured to perform distributed signal processing on each of the signals distributed by the distribution unit at high speed, medium speed, and low speed;
A differential signal processor configured to remove a noise included in the partial discharge signal by calculating a difference value of the distributed signal processing result for each speed of the distributed signal processor;
A device connection unit receiving a control signal for removing noise of the partial discharge signal using a first communication method and outputting the partial discharge signal from which the noise is removed using a second communication method to a connected external device; And
And a processor configured to control the signal amplifier and the distributed signal processor, and to process a result value of the differential signal processor and a signal input and output through the device connection unit. The method according to claim 1,
The first communication method,
Noise canceling sensor, characterized in that the communication method of any one of CAN, LIN, RS-485, and RS-422. The method according to claim 1,
The second communication method,
Noise canceling sensor, characterized in that the communication method of any one of optical Ethernet, Sonet / SDH, and T1 / E1. The method according to claim 1,
The distributed signal processing unit,
Noise canceling sensor comprising a fixed speed high speed log amplifier, a variable speed medium speed log amplifier, and a variable speed low speed log amplifier The method of claim 4,
The differential signal processing unit,
And removing the noise of the partial discharge signal based on a difference value of an output signal due to a difference in response speed between the high speed log amplifier and the low speed log amplifier. The method according to claim 5,
The differential signal processing unit,
Noise canceling sensor, characterized in that for removing the noise of the partial discharge signal using a subtractor. The method according to claim 5,
The differential signal processing unit,
When the signal similar to the partial discharge signal is repeated in the same time period, the noise of the partial discharge signal is removed based on the difference value of the output signal due to the response speed difference between the fast log amplifier and the variable intermediate speed log amplifier. Noise reduction sensor. A noise removing sensor which removes noise of the partial discharge signal by using a difference in response speed of the signal when the partial discharge signal is generated, and outputs a signal from which the noise is removed;
A laser module that outputs a laser to a surface of a power device when the partial discharge signal is generated, and extracts sound waves and vibration data based on a reflection signal reflected from the surface of the power device by the laser;
A correlation analysis unit analyzing the correlation between the signals by comparing the partial discharge signal from which the noise is removed from the noise removing sensor and the sound wave and vibration data extracted through the laser module; And
And a partial discharge diagnosis unit configured to perform partial discharge diagnosis on the partial discharge signal from which the noise is removed and a signal in which at least one of the generation period, time, and phase of the sound wave and vibration data coincide with each other as a result of the correlation analysis of the correlation analysis unit; Partial discharge diagnostic device, characterized in that. The method according to claim 8,
The correlation analysis unit,
Partial discharge diagnostic apparatus, characterized in that for extracting the change data of the magnitude with respect to time from the sound wave and vibration data, and extracting a signal corresponding to a set frequency by fast Fourier transform analysis of the sound wave and vibration data. The method according to claim 8,
The correlation analysis unit,
Partial discharge diagnostic apparatus, characterized in that for calculating the data of the magnitude component corresponding to each phase of the speed of the partial discharge signal from which the noise is removed by the noise removal sensor. The method according to claim 8,
The correlation analysis unit,
And analyzing at least one of a vibration frequency of the sound wave and vibration data and at least one of a generation period, a time, and a phase of the partial discharge signal from which the noise is removed. The method according to claim 8,
The correlation analysis unit,
And comparing the correlation between the sound wave and vibration data generated at the same time and the partial discharge signal from which the noise is removed. The method according to claim 8,
The partial discharge diagnosis unit,
Partial discharge diagnostic apparatus, characterized in that the weight is calculated according to the correlation between the sound wave and vibration data and the partial discharge signal from which the noise is removed. When the partial discharge signal is generated, removing the noise of the partial discharge signal by using the response speed difference of the signal through the noise removal sensor, and outputting the signal from which the noise is removed;
Outputting a laser to a surface of a power device through a laser module when the partial discharge signal is generated, and extracting sound wave and vibration data based on a reflected signal reflected from the surface of the power device by the laser;
Analyzing the correlation by comparing the partial discharge signal from which the noise is removed from the noise removing sensor and sound waves and vibration data extracted through the laser module; And
As a result of the correlation analysis in analyzing the correlation, performing a partial discharge diagnosis on a signal in which the noise of the partial discharge signal from which the noise is removed and the occurrence period, time, and phase of the sound wave and vibration data coincide with each other; Partial discharge diagnostic method comprising a. The method according to claim 14,
Analyzing the correlation,
Extracting change data of magnitude with respect to time from the sound wave and vibration data; And
And performing a fast Fourier transform analysis on the sound wave and vibration data to extract a signal corresponding to a set frequency. The method according to claim 14,
Analyzing the correlation,
And calculating data of a magnitude component corresponding to each phase of each speed of the partial discharge signal from which the noise is removed through the noise removing sensor. The method according to claim 14,
Analyzing the correlation,
And comparing at least one of a generation frequency, a time, and a phase of a vibration signal of the sound wave and vibration data with the noise-free partial discharge signal. The method according to claim 14,
Analyzing the correlation,
And comparing the correlation between the sound wave and vibration data generated at the same time and the partial discharge signal from which the noise is removed. The method according to claim 14,
Diagnosing the partial discharge,
And calculating a weight value according to the correlation between the sound wave and vibration data and the partial discharge signal from which the noise has been removed. The method according to claim 14,
The partial discharge signal from which the noise is removed,
Partial discharge diagnostic method characterized in that the noise of the partial discharge signal is removed based on the difference value of the output signal due to the response speed difference of the high speed log amplifier, the variable intermediate speed log amplifier and the variable low speed log amplifier of the noise removing sensor .

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