JP2008045977A - Insulation diagnostic device and insulation diagnosis method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an insulation diagnosis device capable of solving the problems, wherein a commercial synchronized high frequency is wrongly decided as partial discharge, or much time is required for determining a wideband external noise or the like. <P>SOLUTION: This insulation diagnosis device has a configuration, equipped with a receiving part connected to a partial discharge detection sensor for detecting a partial discharge, for receiving a detection signal from the partial discharge detection sensor; and an insulation diagnosis part for sampling the signal level in each of a plurality of object of diagnosis frequencies from received signals by the receiving part, and comparing a signal level determined as being at a commercial voltage peak time, with the signal level determined as being an asynchronous commercial voltage in each diagnosis object frequency, and partial discharge is decided. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an insulation diagnosis apparatus and insulation diagnosis method for monitoring the insulation state of power electrical equipment such as gas insulation equipment and power transformers, or power cables, and in particular, detects electromagnetic waves caused by partial discharges generated inside the electrical equipment. The present invention relates to an insulation diagnosis apparatus and an insulation diagnosis method that perform insulation diagnosis by doing so.

  In electric power equipment such as gas insulation equipment and power transformers, partial discharge occurs when insulation is abnormal, and electromagnetic waves are generated secondarily by this partial discharge. In order to prevent serious accidents due to dielectric breakdown of electrical equipment, an insulation diagnosis device that diagnoses whether or not insulation abnormality has occurred inside the electrical equipment in operation by detecting electromagnetic waves at the stage of partial discharge. Proposed.

  In such an insulation diagnostic apparatus, electromagnetic waves generated by partial discharge are detected by a partial discharge detection antenna. In addition, since the partial discharge detection antenna picks up not only electromagnetic waves from the inside of the electrical equipment but also other electromagnetic waves as external noise, it is necessary to eliminate erroneous determination due to this external noise.

  In order to eliminate this misjudgment due to external noise, it has a partial discharge detection antenna and a noise antenna that detects only external noise in order to detect partial discharge by separating electromagnetic waves due to partial discharge and external noise, By calculating the signals from the two antennas in a differential manner, the external noise is removed, and the periodic peak point and the 1/4 cycle point of the commercial voltage cycle are calculated and compared from the differentially calculated data. Insulation diagnostic devices that detect partial discharge are disclosed (Patent Document 1 and Patent Document 2).

  Further, there is disclosed a partial discharge detection antenna and an insulation diagnostic apparatus that detects a partial discharge by tracking a temporal change in the spectrum of an external noise detection signal to determine noise. In this device and this method, the time change of the spectrum is tracked in the entire band to be diagnosed, and when a frequency exceeding the specified value indicating the external noise level is detected, the frequency is shifted by a certain frequency width. By repeating the tracking until the value falls below the value, sudden electromagnetic waves are determined (Patent Document 3 and Patent Document 4).

JP 2001-249156 A JP 2001-249157 A JP 7-333288 A Japanese Patent No. 3707161

  However, in the method of calculating and comparing the periodic peak point and the 1/4 cycle point of the commercial voltage cycle from the differentially calculated data, partial discharge is caused by the commercial synchronism of the signal obtained by collectively detecting the in-band frequency after filtering. Since the determination is made, it is determined that partial discharge occurs even at a single frequency (high frequency) modulated at a commercial frequency or n times the frequency.

  In addition, in the method of tracking the time change of the spectrum of the external noise detection signal, when a frequency exceeding the specified value indicating the external noise level is detected, the tracking is repeated until the frequency is shifted to a specified value or less by shifting a certain frequency width. Even for electromagnetic waves generated over a long period of time, such as noise, discharge noise, spike noise, etc. caused by internal combustion engines such as engines, partial discharge is judged to be partial discharge and spectrum analysis is performed over the wide band of the electromagnetic wave. It takes time to complete.

  Furthermore, each of the above-described methods has a noise sensor for detecting external noise and a partial discharge sensor for partial discharge. Therefore, the difference in reception band sensitivity depends on the structure and installation location of both sensors, and There is a problem of reliability such as difficulty in maintaining the synchronization of the sampling period.

  In addition, when two sensors are required, two sensor input circuits are required, and as a countermeasure for the lack of reliability, it is necessary to further duplicate the circuit. As a result, the insulation diagnosis apparatus is large and costly. There is also a problem.

  An insulation diagnostic apparatus according to the present invention is connected to a partial discharge detection sensor for detecting partial discharge, receives a detection signal from the partial discharge detection sensor, and receives a plurality of diagnostic target frequencies from the reception signal of the reception unit. Sampling the signal level every time, and comparing the signal level determined to be at the commercial voltage peak and the signal level determined to be commercial voltage asynchronous for each diagnosis target frequency, and the insulation diagnostic unit to determine partial discharge, An insulation diagnostic device is provided.

  The signal level that is asynchronous with the commercial voltage may be a signal level that is shifted by ¼ cycle from the peak of the commercial voltage. The insulation diagnostic unit may exclude the frequency to be diagnosed from the comparison target frequency when the signal level of the commercial voltage asynchronous is a relatively high signal level.

  The partial discharge determination of the insulation diagnosis unit may be determined by subtracting the signal level asynchronous with the commercial voltage from the signal level at the commercial voltage peak.

  An insulation diagnosis method according to the present invention is provided in an insulation diagnosis apparatus having a reception unit connected to a partial discharge detection sensor for detecting partial discharge and receiving a detection signal from the partial discharge detection sensor, and an insulation diagnosis unit An insulation diagnosis method, wherein the insulation diagnosis unit samples a signal level for each of a plurality of diagnosis target frequencies from a reception signal of the reception unit, determines a signal level determined to be during a commercial voltage peak, and determines that the commercial voltage is asynchronous. And comparing the signal level for each frequency to be diagnosed to determine partial discharge.

  According to the insulation diagnostic apparatus of the present invention, a diagnosis unit is connected to a partial discharge detection sensor for detecting partial discharge, and receives a detection signal from the partial discharge detection sensor. Insulation diagnostic unit that determines partial discharge by sampling the signal level for each target frequency and comparing the signal level determined to be at the commercial voltage peak and the signal level determined to be commercial voltage asynchronous for each frequency to be diagnosed Therefore, by selecting the frequency to be diagnosed from a frequency other than the commercial frequency or n times the frequency, it is possible to classify the commercial voltage-synchronized high frequency.

  Further, since the signal level determined to be commercial voltage asynchronous can be set to the signal level when the signal level is determined to be 1/4 cycle from the time of sampling of the signal level determined to be commercial voltage peak, the signal level at the commercial voltage peak is Since the insulation diagnosis can be performed by discriminating and comparing the signal level with the signal level before 1/4 cycle, the partial discharge determination time is extremely short.

  Furthermore, according to the insulation diagnostic apparatus of the present invention, one detection sensor is connected, and by having a plurality of sensors, the difference in reception band sensitivity depending on the structure of the sensor, the installation location, and the synchronization of the sampling period There is no problem of reliability such as difficulty in maintaining reliability, and the sensor input circuit does not need to be duplicated.

  Embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 shows a functional configuration diagram of an insulation diagnostic apparatus according to an embodiment of the present invention. The insulation diagnostic device 10 includes an input amplifier circuit 20, an A / D converter 12, and a CPU 14, and is connected to the partial discharge sensor 1. Each function will be described below.

  The partial discharge sensor 1 is a sensor for detecting a physical phenomenon generated by partial discharge, and an electromagnetic wave sensor, a vibration sensor, a current sensor, an ultrasonic sensor, or the like can be used. When the electromagnetic wave sensor is applied as the partial discharge sensor 1, during insulation diagnosis, electromagnetic waves generated by partial discharge generated inside the sealed container constituting the electric device are radiated, such as a bushing portion and an insulating spacer of the electric device. It is installed in an easy place.

  The input amplifier circuit 20 receives the detection signal from the partial discharge sensor 1, and the detection signal has a specific frequency according to the control signal from the CPU 14 and is suitable for the A / D converter 12. This circuit converts the signal level (voltage) into an analog signal and outputs the analog signal. The input amplifier circuit 20 includes a BPF (band pass filter) 21, a preamplifier 22, a PLL (phase synchronization circuit) synthesizer 23, a transmitter 24, a mixer 25, an intermediate frequency filter 26, and a log amplifier 27.

  The BPF 21 is a filter circuit that passes a specific frequency band from a signal detected by partial discharge. In the present embodiment, 300 MHz to 800 MHz is set as a pass band as a band in which partial discharge is easily confirmed by experiments. However, it is not limited to this band, and the pass band is preferably set to a band where partial discharge can be easily confirmed according to the installation conditions of the partial discharge sensor 1 and the like.

  The preamplifier 22 is an amplifier that amplifies the signal that has passed through the BPF 21 to an appropriate voltage as an input signal to the mixer 25. The PLL synthesizer 23 is a circuit that varies the frequency from the transmitter 24 according to a control signal received from the CPU 14 and outputs a frequency signal fA. The mixer 25 is a circuit that receives the signal of the frequency fx from the preamplifier 22 and the signal of the frequency fA from the PLL synthesizer 23, synthesizes them and outputs them as one signal so that impedance matching is not disturbed. The intermediate frequency filter 26 is a filter circuit that extracts a signal component of the intermediate frequency fB from the input signal from the mixer 25. The log amplifier 27 is an amplifier that outputs the voltage of the input signal from the intermediate frequency filter 26 to an appropriate voltage to the A / D converter 12. For example, the log amplifier 27 has a voltage corresponding to the voltage of the output signal from the preamplifier 22. Output analog signals.

  In this way, the input amplifier circuit 20 receives the detection signal from the partial discharge sensor 1, has a specific frequency fB according to the control signal from the CPU 14 based on the detection signal, and the A / D converter 12 The analog signal of the voltage for output is output.

  Therefore, the insulation diagnostic apparatus 10 according to the present invention excludes the single frequency (high frequency) modulated at the commercial frequency or n times the frequency from the specific frequency fB from the partial discharge determination, thereby increasing the frequency n times the commercial frequency. The partial discharge is not judged by the nature.

  The A / D converter 12 is a circuit that converts the analog signal received from the log amplifier 27 into a digital signal. In order to obtain the signal level of the measurement target frequency fB at a specific sampling timing from the A / D converter 12, the CPU 14 outputs a control signal indicating the frequency fB to the PLL synthesizer 23 at the sampling timing. When the CPU 14 acquires the signal level of the frequency fB at the sampling timing described above from the A / D converter 12, the CPU 14 caches the signal level for each frequency fB and sampling time, or an insulation diagnosis device (not shown). 10 is stored in the memory.

  A partial discharge signal of an electric device is generated due to insulation deterioration or contamination, and is generated for each cycle or intermittently near the peak of the commercial voltage phase. Therefore, if data is acquired for each cycle for each set frequency of the insulation diagnosis target frequency band, each data when the set frequency is used as a parameter even if the data sampling start time does not coincide with the zero cross of the commercial frequency Becomes the same position (same phase) with respect to the commercial voltage phase every cycle. Therefore, the sampling timing is obtained by acquiring data for one cycle for each set frequency (for example, in the case of 50 Hz, data sampling is performed at an interval of 100 points = 200 μs per cycle). obtain. That is, data is acquired continuously for one cycle (for example, 100 points) for one set frequency in the diagnosis target frequency band, and then the set frequency is changed by the control signal of the CPU 14 within the data sampling time. Acquire data continuously for one cycle. At this time, if the frequency setting is not in time within the sampling time, the frequency may be set during one commercial cycle and data may be acquired in the next one cycle.

  The CPU 14 sets the received data group (the received data array corresponding to the data sampling points with respect to the set frequency) as a parameter to the received data group (the same phase with respect to the commercial voltage). (Receiving level with respect to frequency at sampling point). Next, if a signal of a certain level or higher is constantly present in the vicinity of the same frequency with respect to an array of frequency data using all or a plurality of data sampling timings as parameters, it is determined as external noise such as communication that is not synchronized with commercial use. In the partial discharge determination, this frequency is excluded. Further, it is determined that a frequency at which a signal of a certain level or higher is present at random is a sudden commercial asynchronous asynchronous noise, and this frequency is also excluded in the partial discharge determination.

  Next, in the frequency data array using the data sampling points as parameters, if all or a certain number of data at frequencies other than the frequency determined as external noise as described above are above a certain level, this data array Is determined to be synchronized with the commercial voltage frequency, and it is determined that partial discharge is suspected. A value obtained by subtracting background noise (hereinafter referred to as “BGN”) from the average of data of a certain level or more used for determining the commercial voltage synchronization in the data array determined to be synchronized with the commercial voltage frequency. Is determined to be partial discharge.

  As described above, it is determined that the data array is determined to be synchronized with commercial use, and the data array determined to be partial discharge is assumed to be generated near the peak of the commercial voltage phase, and is determined to be synchronized with the commercial voltage frequency. It is considered that a data array shifted by ¼ cycle with respect to the generated array occurred near the zero cross point of the commercial voltage phase. Therefore, BGN is calculated from a data array shifted by 1/4 cycle with respect to the array determined to be synchronized with the commercial voltage frequency. Specifically, in the data array shifted by ¼ cycle, the average value, minimum value, and maximum value of data at frequencies other than the frequency determined as external noise are defined as BGN.

  Note that it may be determined whether the determination result is valid with reference to the value of the BGN level calculated at this time. For example, if the BGN level is greater than a certain value, it may be determined that “the determination result is a reference value due to excessive noise”.

  Thereby, it is possible to discriminate the partial discharge without being affected by external noise generated at the same frequency as the partial discharge. Therefore, in the prior art, the external noise sensor and the partial discharge noise sensor were provided, but the insulation diagnostic apparatus 10 according to the present invention can determine partial discharge by one partial discharge sensor. It solves the problems of reliability due to the two-sensor method, the duplication of the amplifier circuit, and the complexity of the device.

  As described above, when frequency data having a signal level above a certain level is detected, it can be determined that the data is not an external noise but a partial discharge at a commercial voltage peak. In the case of (5), it can be estimated that the time before zero crossing is 5 ms). Therefore, synchronization with the commercial voltage waveform is possible by determining that the frequency data having a signal level of a certain level or more is detected as the peak time, and obtaining the detected data around 1/4 cycle after the peak time is determined. Thus, it is possible to execute the partial discharge determination described above. Therefore, the insulation diagnosis apparatus 10 according to the present invention can start the partial discharge determination process immediately after sampling data of a predetermined set frequency.

  Therefore, in the prior art, electromagnetic waves having a wide band and a long generation time such as an internal combustion engine such as an engine are repeatedly detected by shifting the frequency, and accordingly, a long detection time is required. The diagnostic device 10 can make a partial discharge determination by comparing data detected for each predetermined set frequency with data before and after a quarter cycle, so the partial discharge determination time is extremely short.

  The CPU 14 described above can use a DSP (Digital Signal Processor). The DSP is a microprocessor specialized for processing of voice, images, etc., has a lower cost than a general CPU, and has a function of efficiently performing complicated digital processing. Is suitable. The CPU 14 can also be a high-speed CPU such as a RISC microcomputer.

  The time change of the sampling data detected for every diagnosis object frequency is demonstrated using FIG. The data sampling process is performed over the diagnostic frequency band set by the BPF 21. For example, the diagnosis target frequency band is 300 MHz to 800 MHz. At this time, the diagnosis target frequency fx is defined as f1 = 300 MHz and fm = 800 MHz, where m is the frequency division number. At this time, since the noise synchronized with the commercial frequency is not determined to be partial discharge, the frequency n times the commercial frequency is removed from the diagnosis target frequency fx.

  2A is a commercial voltage waveform, FIG. 2B is a detected waveform at a frequency fa indicating a large signal level in the peak period in synchronization with the commercial voltage waveform, and FIG. 2C is asynchronous with the commercial voltage waveform. (D) is a detection waveform at a frequency fc indicating a small signal level that is asynchronous with the commercial voltage waveform. The diagnosis target frequencies fa, fb, and fc are all included in the diagnosis target frequency fx.

  The commercial voltage waveform shown in (A) is a frequency waveform of 50 Hz, and one cycle is 20 ms. In FIG. 2, for the purpose of illustration, 20 ms is divided by time t1 to t80, peak section 1 is shown by time t18 to t22, zero cross section is shown by t38 to t42, and peak section 2 is shown by t58 to t62. It is.

  The detected waveform at the frequency fa shown in FIG. 2B shows a large signal level in the peak section 1 and the peak section 2, but does not show a large signal level in the zero-cross section, so it is determined that the partial discharge is synchronized with the commercial frequency. Is possible.

  Further, the detection waveform at the frequency fb shown in FIG. 2C shows the same high signal level in the peak sections 1 and 2 and the zero-cross section, but can be determined as external noise indicating a high signal level because it is asynchronous with the commercial frequency. It is.

  Further, the detection waveform at the frequency fc shown in FIG. 2D shows the same low signal level in the peak sections 1 and 2 and the zero cross section, and is asynchronous with the commercial frequency, so that it can be determined as external noise indicating a low signal level. is there.

  Further, since the signal level of the detected data is detected for each sampling time and frequency, it may be stored in the cache memory in the CPU 14 as a data array. For example, the address of the data array of the cache memory can be defined as a data array D in which m is the frequency division number of the diagnosis target frequency band and n is the total sampling time. For example, the address of the data array in which the detection data of the sampling times t1 to tn of the frequency f1 is stored is defined as D11 to D1n, and the data array in which the detection data of the sampling times t1 to tn of the frequency fm is stored. Addresses can be defined as Dm1 to Dmn. In addition, as shown in FIG. 2, this signal level is made reliable by a statistical method such as an average value of sample data detected in a peak interval or a zero-cross interval or an average value of sample data within a certain standard deviation. An increased signal level can also be achieved.

  Since the detection data has a signal level corresponding to the commercial voltage phase, the old data may be deleted and the new data may be recorded in the data array D for each cycle of the commercial voltage.

  The signal level for each diagnosis target frequency detected by the insulation diagnosis apparatus according to the present invention will be described with reference to FIG. FIG. 3 (A) shows the signal level and frequency at a certain time point (same commercial phase point) in one cycle section, and (B) shows the signal level at a different time point from the certain time point shown in (A) of one cycle section. (C) shows a signal level and a frequency at a certain point in one cycle section. In addition, although the number of diagnosis object frequencies is small for illustration in this figure, in fact, it is good also considering the frequency of 30 or more as a diagnosis object.

  In FIG. 3A, the diagnosis target frequency fb indicates a signal level higher than the signal level L1 that is a threshold for determining the ineffective frequency. Here, the signal level L1 is a threshold value set in order to invalidate the set frequency of the low signal level that is asynchronous with the commercial voltage and does not correspond to the partial discharge in the partial discharge determination. This signal level L1 can determine a frequency that is not subject to partial discharge determination. Thereby, the insulation diagnostic apparatus according to the present invention does not erroneously determine partial discharge due to the high signal level frequency of the asynchronous signal.

  In FIG. 3B, the diagnosis target frequency fe is sudden noise with a high signal level. The diagnosis target frequency fe is external noise that occurs suddenly because it is not detected in (A). Since such external noise also exhibits a high signal level equal to or higher than L1, it can be set to a frequency that is not subject to partial discharge determination. On the other hand, since the frequency fb is a standing wave, it is detected also in (B).

  As shown in FIG. 3C, when partial discharge occurs, frequencies other than frequency fb and frequency fe also show high signal levels. A signal level L2, which is a threshold value for determining a commercial frequency synchronization frequency for determining partial discharge, is set, and partial discharge is determined based on the number of frequency signals exceeding L2. Therefore, since the frequency fe appears in FIG. 3B and is sudden, it is excluded from the partial discharge frequency. Since the frequency fb constantly appears in FIGS. 3A, 3B, and 3C, it is regarded as a standing wave, excluded from the partial discharge determination target frequency, and other frequencies are shown in FIG. Since the signal level L2 is exceeded only in FIG. 2, it is regarded as an electromagnetic wave synchronized with the commercial frequency and becomes the frequency of the partial discharge determination target. The signal level L2 is a signal level for selecting a commercial frequency synchronization signal level that is not stationary or sudden external noise from frequency data exceeding the signal level L1. Therefore, L2 needs to be set to at least L1 or at least the same as L1 (in this case, only the signal level of either L1 or L2 is required).

  FIG. 4 is a flowchart of the invalid frequency determination process of the insulation diagnostic apparatus according to the present invention. This invalid frequency determination process is for determining a frequency that is not a determination target when performing partial discharge determination. Therefore, it is basically performed during the partial discharge determination process or as a pre-process thereof, and may be performed at a time deviated by ¼ cycle from the time when the partial discharge is determined.

  In step S101, the procedure starts from the lowest frequency to be diagnosed, and then proceeds to step S102.

  In step S102, the D data array in one cycle section is searched for the specific diagnosis target frequency fx, the signal level for each time of the frequency fx is acquired, and the process proceeds to step S103.

  In step S103, it is determined whether the signal level of the frequency fx is equal to or higher than a threshold L1 for determining the invalid frequency. If it is greater than or equal to L1, the process proceeds to step S104. If it is less than L1, the process proceeds to step S105.

  In step S104, the frequency fx determined in step S103 is set as invalid frequency data in the partial discharge determination, and the process proceeds to step S106.

  In step S105, the frequency fx determined in step S103 is used as effective frequency data in the partial discharge determination, and the process proceeds to step S106.

  In step S106, it is determined whether or not the frequency fx is the maximum frequency fm among the diagnosis target frequencies. If the frequency fx is the maximum frequency fm, the process ends. If the frequency fx is not the maximum frequency fm, the process returns to step S102.

  In this way, the frequency determined as the ineffective frequency in the ineffective frequency determination process exists as a standing wave or a sudden electromagnetic wave asynchronously with the commercial voltage. Therefore, the ineffective frequency is determined in the partial discharge determination described below. Excluded from.

  FIG. 5 is a flowchart of the partial discharge determination process of the insulation diagnostic apparatus according to the present invention. This process may be performed constantly, or may be performed once every hour, or intermittently, such as during an insulation diagnosis by a human.

  In step S201, it is determined by searching the data array D whether or not there is frequency data that is equal to or higher than the signal level L2 that is a threshold value for partial discharge determination within a certain time interval corresponding to one cycle interval, and the number Count. In this determination process, in order not to misdetermine external noise as partial discharge, the frequency determined to be invalid in the invalid frequency determination process described in FIG. 4 is not counted as frequency data of L2 or more. If the number of data equal to or greater than L2 is equal to or greater than a threshold value within one cycle interval, the process proceeds to step S202. If the number of data is equal to or less than the threshold value, the process returns to step S201 and the same process is repeated.

  In step S202, the data before 1/4 cycle is acquired from the detection time of the frequency data of L2 or more searched in step S201, and the corresponding frequency before 1/4 cycle is obtained from the signal level of the frequency data of L2 or more. The signal level of data is subtracted as background noise (BGN). The signal level of the background noise may be data obtained by adding an average value, a minimum value, a maximum value, or other statistical processing of the frequency data.

  In step S203, if the average frequency after subtraction exceeds a certain threshold, it is determined that partial discharge has occurred, and the process proceeds to step S204. If not, the process returns to step S201.

  In step S204, since occurrence of partial discharge is determined, a necessary abnormality warning is output or abnormality processing is performed, and the partial discharge determination processing is terminated. In this abnormal process, if the above background noise is larger than a certain value, it is displayed on a display means (not shown) connected to the insulation diagnostic device, such as “the judgment result is a reference value due to excessive noise”. Also good.

  In addition, as a method for confirming the soundness of the insulation diagnostic apparatus 10 according to the present invention, for example, a frequency of a television, radio, or the like that is preset in advance may be received and the reception intensity thereof may be confirmed. This broadcast wave frequency may be an analog broadcast wave or a digital broadcast wave.

  Further, the CPU 14 can alternatively execute the band-pass filter processing of the input amplifier circuit 20 of the insulation diagnostic device 10 according to the present invention, the filter processing of the diagnosis target frequency fB, and the like. For example, in this case, the insulation diagnostic apparatus 10 according to the present invention amplifies the detection signal from the sensor 1 with the preamplifier 22, digitizes the analog signal with the A / D converter 12, and transmits it to the CPU 14. Thus, it is possible to perform bandpass filter processing and filter processing of the diagnosis target frequency fB.

  As described above, according to the present invention, it is possible to classify commercial-synchronized electromagnetic waves by selecting the frequency to be diagnosed, and to detect the signal level for each frequency to be diagnosed. By comparing partial discharge and determining partial discharge, it is possible to determine partial discharge by excluding external noise, and it is possible to execute partial discharge determination processing in real time.

  In this way, if a device that provides high partial discharge determination performance and improved determination speed as in the present invention is applied to a device that is widely applied to electrical equipment such as an insulation diagnosis device, it will be greatly increased in the electric power industry. Will bring about profits.

It is a functional block diagram of the insulation diagnostic apparatus by one Embodiment of this invention. It is a figure which shows the time change of the sampling data detected with the insulation diagnostic apparatus by this invention. It is a figure which shows the signal level for every diagnosis object frequency detected with the insulation diagnostic apparatus by this invention. It is a flowchart of the invalid frequency judgment process of the insulation diagnostic apparatus by this invention. It is a flowchart of the partial discharge judgment process of the insulation diagnostic apparatus by this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Sensor 10 Insulation diagnostic apparatus 12 A / D converter 14 CPU
20 Input amplifier circuit 21 BPF
22 Preamplifier 23 PLL Synthesizer 24 Transmitter 25 Mixer 26 Intermediate Frequency Filter 27 Log Amplifier

Claims (7)

A receiving unit connected to a partial discharge detection sensor for detecting the partial discharge and receiving a detection signal from the partial discharge detection sensor;
The signal level is sampled for each of a plurality of diagnosis target frequencies from the reception signal of the reception unit, and the signal level determined to be a commercial voltage peak and the signal level determined to be a commercial voltage asynchronous are determined for each diagnosis target frequency. Insulation diagnostic unit that determines partial discharge by comparing to
An insulation diagnostic apparatus characterized by comprising:   The comparison of the insulation diagnosis unit is determined to be asynchronous with the commercial voltage, and when the signal level relatively higher than the other signal levels is steady or sudden in a plurality of sampling times, The insulation diagnosis apparatus according to claim 1, wherein the diagnosis target frequency at a signal level is not set as the diagnosis target frequency.   The determination that the signal level is at the peak of the commercial voltage is a signal level that is relatively higher than the other signal levels and that is present a predetermined number of times at a plurality of sampling times as a signal level at the peak of the commercial voltage. The insulation diagnostic apparatus according to claim 1 or 2, wherein the determination is made.   The said comparison of the said insulation diagnostic part is performed based on the value which subtracted the said signal level judged to be the commercial voltage asynchronous from the said signal level judged that the commercial voltage peak time. Insulation diagnostic equipment.   5. The signal level determined when the commercial voltage is asynchronous is a signal level when the signal level is determined to be at the peak of the commercial voltage and is shifted by ¼ cycle from the sampling time of the signal level. The insulation diagnostic apparatus as described. An insulation diagnosis method in an insulation diagnosis apparatus having a reception unit connected to a partial discharge detection sensor for detecting partial discharge and receiving a detection signal from the partial discharge detection sensor, and an insulation diagnosis unit,
The insulation diagnosis unit samples a signal level for each of a plurality of diagnosis target frequencies from the reception signal of the reception unit;
The insulation diagnosis unit determines the partial discharge by comparing the signal level determined to be a commercial voltage peak and the signal level determined to be a commercial voltage asynchronous for each diagnosis target frequency;
An insulation diagnostic method characterized by comprising: An insulation diagnostic program executed by a computer connected to a partial discharge detection sensor for detecting partial discharge,
Sampling a signal level for each of a plurality of diagnosis target frequencies from a detection signal of the partial discharge detection sensor;
A step of determining partial discharge by comparing the signal level determined at the commercial voltage peak and the signal level determined as commercial voltage asynchronous for each frequency to be diagnosed;
For causing the computer to execute the program.

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