JP6605992B2 - Insulation diagnostic apparatus and insulation diagnostic method for power equipment - Google Patents

Description

  FIELD Embodiments described herein relate generally to an insulation diagnosis apparatus and insulation diagnosis method for a power device that detects partial discharge generated from the power device using an electromagnetic wave sensor.

  Since partial discharge is a factor that accelerates insulation deterioration that occurs in power equipment such as switchgear, insulation deterioration diagnosis by detecting partial discharge is generally performed. In partial discharge detection, there is a method of detecting electromagnetic waves, and in order to distinguish a discharge signal from noise, there is known one that determines whether or not it is synchronized with a commercial frequency voltage (see, for example, Patent Document 1). . Moreover, what measures a several frequency band and classifies a broadcast wave and a discharge signal is known (for example, refer patent document 2).

  However, partial discharge has a weak discharge signal and is easily buried in noise, and there is a limit to improving detection sensitivity. For this reason, even a weak discharge signal is desired to be able to accurately discriminate from noise and detect partial discharge.

JP 2008-45977 A JP-A-9-292433

  The problem to be solved by the present invention is to isolate a weak discharge signal due to partial discharge generated from the inside of a power device from noise propagating from the outside, and to insulate the power device that can reliably perform an insulation diagnosis. The object is to provide a diagnostic device and an insulation diagnostic method.

  In order to solve the above-described problem, an insulation diagnostic apparatus for power equipment according to an embodiment includes a first electromagnetic wave sensor provided inside a box, a second electromagnetic wave sensor provided outside the box, and the first And an insulation diagnostic device to which the second electromagnetic wave sensor is connected. The insulation diagnostic device synthesizes discharge signals for a predetermined cycle into one cycle and overlaps with a predetermined time width. A waveform synthesis and extraction unit that extracts a discharge signal having a high peak value by cutting the discharge signal, a peak value of the discharge signal having a high peak value, and the first electromagnetic wave sensor and the second electromagnetic wave sensor And a peak value detection / comparison unit that compares temporal changes in the peak value detected in step 1 and an insulation determination unit that performs insulation diagnosis from increase / decrease in the temporal change of the peak value. .

The block diagram which shows the structure of the insulation diagnostic apparatus of the electric power equipment which concerns on the Example of this invention. The flowchart explaining the insulation diagnostic method of the electric power equipment which concerns on the Example of this invention. The figure explaining the waveform synthesis and waveform cut which concern on the Example of this invention. The measurement example of the discharge signal by the electromagnetic wave sensor which concerns on the Example of this invention. The example of the output of the discharge signal which concerns on the Example of this invention. The example of the output of the discharge signal which concerns on the Example of this invention. The characteristic view which shows the time change of the peak value of the discharge signal which concerns on the Example of this invention. The characteristic view which shows the time change of the peak value of the discharge signal which concerns on the Example of this invention.

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

  A power equipment insulation diagnosis apparatus according to an embodiment of the present invention will be described with reference to FIGS. FIG. 1 is a configuration diagram showing a configuration of an insulation diagnosis apparatus for a power device according to an embodiment of the present invention, FIG. 2 is a flowchart for explaining an insulation diagnosis method for a power device according to an embodiment of the present invention, and FIG. FIG. 4 is a diagram for explaining waveform synthesis and waveform cut according to an embodiment of the present invention, FIG. 4 is a measurement example of a discharge signal by an electromagnetic wave sensor according to the embodiment of the present invention, and FIGS. 5 and 6 are embodiments of the present invention. FIG. 7 and FIG. 8 are characteristic diagrams showing temporal changes in the peak value of the discharge signal according to the embodiment of the present invention.

  As shown in FIG. 1, a current measuring current transformer 2, a power receiving cable head 3, a voltage measuring transformer 4, a power supply side disconnector 5 that opens and closes the main circuit, and a main circuit are included in the box 1. A circuit breaker 6 to be protected and a bus bar 7 for connecting to an adjacent board are housed. A first electromagnetic wave sensor 8 made of, for example, a loop antenna is provided on the wall surface inside the box 1, and a second wave made of, for example, a loop antenna similar to the first electromagnetic wave sensor 8 is provided on the wall surface outside the box 1. An electromagnetic wave sensor 9 is provided. The outputs of the first electromagnetic wave sensor 8 and the second electromagnetic wave sensor 9 are respectively input to the insulation diagnostic device 10.

  The insulation diagnostic apparatus 10 includes a filter unit 11 having a frequency band of 35 kHz to 180 MHz, an amplifier unit 12, a waveform synthesis extraction unit 13, a peak value detection comparison unit 14, a wavelet conversion unit 15, and an insulation determination unit 16. . The first and second electromagnetic wave sensors 8 and 9 also have a frequency band of 35 kHz to 180 MHz.

  Next, the insulation diagnosis method will be described with reference to FIGS.

  As shown in FIG. 2, first, the first electromagnetic wave sensor 8 and the second electromagnetic wave sensor 9 are simultaneously activated to detect the first and second discharge signals accompanying the partial discharge (st1-1, st1- 2). Both the first electromagnetic wave sensor 8 and the second electromagnetic wave sensor 9 obtain first and second discharge signals for a predetermined commercial frequency cycle, respectively (st2-1, st2-2). The first and second discharge signals obtained for several cycles are synthesized one cycle above by the waveform synthesis / extraction unit 13, and the one with the predetermined time width (phase width) overlapped is cut off the one with the lower peak value. The ones with high peak values are extracted (st3-1, st3-2). FIG. 3 shows an example of synthesis and extraction of the first (second) discharge signal generated three consecutive cycles.

  The reason for cutting the overlapping discharge signals in a predetermined time width is to prevent a change in frequency. In other words, if they are simply combined, those that overlap in a short time have a higher frequency, which is different from the frequency component of the original discharge signal. A typical discharge signal is shown in FIG. 4 and has a frequency of about 35 kHz for vacuum discharge, about 125 MHz for void discharge of an insulator, and about 180 MHz for air discharge.

  5 and 6 show the results when the waveforms are synthesized and extracted so that the frequency at the discharge site does not change. In FIG. 5, there is no discharge signal, FIG. 5 (a) shows the outputs of the electromagnetic wave sensors 8 and 9, and FIG. In FIG. 6, there is a discharge signal, FIG. 6 (a) shows the outputs of the electromagnetic wave sensors 8 and 9, FIG. 6 (b) shows the waveform synthesis, and after extraction, the discharge signal is reliably extracted. . In addition, since the vacuum equipment is housed in the power equipment, the overlapping discharge signals are cut within about 30 μs so that at least about 35 kHz having the lowest frequency is extracted from the representative discharge signals described above. Shall.

  Many noise signals are single-shot signals, and are generated continuously and rarely overlap in phase. Therefore, few signals are cut by waveform synthesis, and signals are accumulated as they are. For this reason, it has a frequency component peculiar to noise.

  Next, the first and second peak values are detected by the peak value detection / comparison unit 14 for the first and second discharge signals that have been combined and extracted (st4-1, st4-2). Then, the change with time of the first and second peak values is compared (st5). For continuous discharge, a short time comparison is sufficient, but when sudden noise is considered, a long time of several seconds is compared. FIG. 7 shows a case where there is no discharge due to insulation deterioration. The circles indicate the characteristics of the first peak value of the first discharge signal, and the triangles indicate the characteristics of the second peak value of the second discharge signal, but change with the same tendency as time elapses. In other words, the first peak value rises at time t1, but the second peak value also rises in the same manner, so it can be considered that this is due to the intrusion of external noise.

  FIG. 8 shows a case where a discharge occurs inside the box 1. The circle marks and triangle marks are the same as those in FIG. 7, and the first peak value increases at time t1, but the second peak value does not increase. That is, it is considered that discharge occurred inside the box 1 and the first peak value increased, but the second peak value was outside the box 1 and was not affected by it. For this reason, insulation diagnosis can be performed by observing temporal changes in the first and second peak values.

  Next, the first and second discharge signals (first and second peak values) are analyzed by a wavelet transform unit 15 that analyzes temporal changes in frequency, using known continuous wavelets, discrete wavelets, mother wavelets, and the like. Then, wavelet transformation is performed (st6-1, st6-2), and insulation deterioration is determined (st7). In the wavelet transform, the discharge signal can be analyzed more reliably, and the discharge site such as vacuum discharge, void discharge, or air discharge can be specified by specifying the frequency.

  Accordingly, the first electromagnetic wave sensor 8 is provided inside the box body 1 and the second electromagnetic wave sensor 9 is provided outside and the discharge signal due to the insulation deterioration is detected. After the waveform synthesis in each predetermined cycle, the one having a high peak value is extracted, the peak value is detected by the peak value detection / comparison unit 14, and the temporal change of the peak value is compared. The noise that enters the inside of the structure such as the box 1 can be physically blocked. Further, it is possible to reliably discriminate between a noise generated randomly with respect to the time axis and a discharge signal accompanying an insulation deterioration generated according to a certain rule from the temporal change of the peak value. Furthermore, the discharge site can be specified by wavelet transforming the discharge signal detected with high sensitivity.

  According to the insulation diagnosis apparatus for power equipment of the above embodiment, the electromagnetic wave sensors 8 and 9 are respectively provided inside and outside the box 1 to detect the discharge signal, and the waveform is synthesized and extracted to obtain the peak value. Since the change over time is detected and the discharge signal is measured, the discharge signal and the noise inside the box 1 can be reliably distinguished, and the insulation deterioration of the power equipment can be prevented beforehand.

  In the above embodiment, the wavelet transform unit 15 and the determination unit 16 are connected to the output of the peak value detection / comparison unit 14 for insulation diagnosis. However, the wavelet transform unit 15 is passed and the peak value detection comparison is performed. The insulation diagnosis can be performed even if the determination unit 16 is directly connected to the output of the unit 14. This is because the peak value detection / comparison unit 14 can efficiently distinguish the discharge signal from the noise.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

DESCRIPTION OF SYMBOLS 1 Box 2 Current transformer 3 Cable head 4 Transformer 5 Disconnector 6 Breaker 7 Busbar 8 1st electromagnetic wave sensor 9 2nd electromagnetic wave sensor 10 Insulation diagnostic apparatus 11 Filter 12 Amplifier 13 Waveform composition extraction part 14 Peak value Detection comparison unit 15 Wavelet transform unit 16 Insulation determination unit

Claims (7)

A first electromagnetic wave sensor provided inside the box;
A second electromagnetic wave sensor provided outside the box;
An insulation diagnostic apparatus to which the first electromagnetic wave sensor and the second electromagnetic wave sensor are connected;
The insulation diagnostic apparatus synthesizes a discharge signal for a predetermined cycle into one cycle, a waveform synthesis extraction unit that extracts a discharge signal having a high peak value by cutting discharge signals that overlap each other with a predetermined time width, and
A peak value detection comparing unit for detecting a peak value of the discharge signal having a high peak value and comparing temporal changes of the peak values detected by the first electromagnetic wave sensor and the second electromagnetic wave sensor; ,
An insulation diagnosis device for a power device, comprising: an insulation determination unit that performs insulation diagnosis based on increase and decrease of the temporal change of the peak value.   The insulation diagnosis apparatus for a power device according to claim 1, wherein the discharge signal detected by the peak value detection / comparison unit is connected to a wavelet transform unit.   The insulation diagnosis apparatus for a power device according to claim 1 or 2, wherein the first electromagnetic wave sensor and the second electromagnetic wave sensor each have a frequency band of 35 kHz to 180 MHz. A first electromagnetic wave sensor is provided inside the box, and a second electromagnetic wave sensor is provided outside the box,
The first electromagnetic wave sensor obtains a first discharge signal, the second electromagnetic wave sensor obtains a second discharge signal,
The first discharge signal and the second discharge signal are combined into one cycle of discharge signals for a predetermined cycle, and the discharge signals overlapping in a predetermined time width are cut to extract a discharge signal having a high peak value. ,
Detecting a first peak value in the first discharge signal and a second peak value in the second discharge signal within a predetermined time;
An insulation diagnosis method for a power device, wherein insulation deterioration is diagnosed from a temporal change between the first peak value and the second peak value.   The insulation diagnosis method for a power device according to claim 4, wherein the first peak value and the second peak value are subjected to wavelet transform to specify a discharge site.   In the temporal change between the first peak value and the second peak value, when the first peak value is significantly higher than the second peak value, the insulation deterioration is determined. The insulation diagnosis method for a power device according to claim 4 or 5, wherein:   7. The discharge signal having a lower peak value is cut when the first discharge signal and the second discharge signal overlap each other within a time of 30 μs. 8. An insulation diagnosis method for power equipment as described in 1.