Discharge detection unit

Abstract

To detect a discharge event occurring even in a situation in which the event is hardly detected before.SOLUTION: There is provided a discharge detection unit 1 which is electrically connected to a cable run where a load is connected to detect noise superposed on a voltage or current of the cable run to which the load is connected, and the discharge detection unit comprises: a filter part 11 which cuts noise of predetermined frequency or lower superposed on the voltage or current of the cable run to output waveforms of noise of a high-frequency range passed while disallowing noise of commercial frequency and a low frequency range to pass; a count part 12 which can calculate the number of times of detection of the waveforms in a predetermined time from the waveforms passed through the filter part; and an arithmetic processing part 13 which uses the number of times of detection calculated by the count part to determine whether there is noise due to a discharge of the cable run.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an electric discharge detection unit. [Background technology]

[0002] As described in Patent Document 1, a discharge detection device is known that can extract high-frequency discharge noise superimposed on a commercial frequency by using a current sensor or a voltage sensor. In the technology disclosed in Patent Document 1, the fact that noise is always superimposed when using a specific electric drill or hand mixer is utilized to determine discharge detection. Specifically, the technology disclosed in Patent Document 1 distinguishes between a peak time region including the region before and after the peak in the commercial frequency and a zero value time region before and after the output in the commercial frequency becomes zero, and compares the output at the timing of the peak time region with the output at the timing of the zero value time region to determine discharge noise. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2022-89758

[0004] The technology disclosed in Patent Document 1 is to determine whether the noise output exceeds a threshold. Therefore, in order to distinguish between equipment noise and discharge noise, the discharge event must be large to a certain extent. In addition, the noise attenuates as you move away from the point where the discharge noise occurs, making it difficult to detect discharge noise that occurs far away. Summary of the Invention [Problem to be solved by the invention]

[0005] The inventors of the present invention have made extensive research into this issue and have attempted to solve the problem. The problem that the present invention aims to solve is to make it possible to detect the occurrence of a discharge event even in situations where it has been difficult to detect in the past. [Means for solving the problem]

[0006] In order to solve the above problems, the present invention provides a discharge detection unit that is electrically connected to an electric circuit to which a load is connected, and is capable of detecting noise superimposed on the voltage or current of the electric circuit to which the load is connected, the discharge detection unit comprising: a filter section that cuts out noise below a predetermined frequency that is superimposed on the voltage or current of the electric circuit, thereby preventing commercial frequency and low-frequency band noise from passing, and enabling the output of a waveform of the high-frequency band noise that has been passed; a counting section that is capable of calculating the number of times the waveform has been detected in a predetermined period of time from the waveform that has passed the filter section; and an arithmetic processing section that is capable of determining the presence or absence of noise due to discharge in the electric circuit, using the number of detections calculated by the counting section.

[0007] In addition, when either equipment noise caused by the load or discharge noise in the electrical circuit is occurring, it is preferable to have a configuration that can determine which is occurring by using the number of detections obtained by the counting unit.

[0008] It is also preferable to provide a setting section that allows the time for which the counting section calculates the number of times the waveform is detected to be set.

[0009] In addition, it is preferable that the number of detections is judged multiple times, and if it is confirmed that the number of detections is greater than a set number of times consecutively, it is possible to determine that noise due to a discharge event is occurring.

[0010] It is also preferable to have a configuration that can identify the cause of a discharge event using both the regularity of noise occurrence over a long period of time that is one cycle or more, or the regularity of output over a long period of time that is one cycle or more, and the number of detections by the counting unit over a short period that is shorter than the long period.

[0011] It is also preferable that an upper limit is set for the number of detections by the counting section, and that if a detection count exceeding the upper limit is detected, it can be determined that the noise is caused by electromagnetic waves.

[0012] In addition, it is preferable that the number of detections measured by the counting unit can be obtained for each cycle of the voltage or current on which noise is superimposed, and the calculation processing unit can determine the presence or absence of noise caused by discharge in the electric circuit using at least one of the increase in the number of detections per cycle and the variation in the increase in the number of detections per cycle.

[0013] In addition, it is preferable that the counting unit is provided with at least one threshold value for the number of detections measured by the counting unit, and at least one threshold value for the measurement time of the counts measured by the counting unit, and that the calculation processing unit is configured to be able to determine the presence or absence of noise due to discharge in the electrical circuit using the threshold value for the number of detections and the threshold value for the measurement time of the counts.

[0014] Furthermore, it is preferable that the power distribution system is one in which the discharge detection unit is electrically connected to a plurality of branch breakers, the relationship between the number of detections and the location where the discharge event occurred is stored so as to correspond to the number of branch breakers, and the power distribution system is equipped with a switch input unit that inputs information regarding the number of branch breakers or a switch estimation unit that estimates the number of branch breakers, and an occurrence location estimation unit that is capable of estimating the location where the discharge event occurred using the input or estimated number of branch breakers and the number of detections measured by the counting unit.

[0015] It is also preferable that the configuration include a frequency estimation section that stores the relationship between the number of detections and the frequency and is capable of identifying the frequency of the discharge event using the number of detections counted by the counting section.

[0016] In addition, it is preferable that the relationship between the distance between the discharge detection unit and the location where the discharge event occurs and the attenuation rate is stored for each frequency, and that the configuration is provided with an occurrence location estimation unit and an attenuation rate determination unit that can determine the attenuation rate of the discharge noise from the occurrence distance estimated by the frequency estimation unit and the frequency estimation unit. Effect of the Invention

[0017] The present invention makes it possible to detect the occurrence of a discharge event even in situations where detection was previously difficult. [Brief description of the drawings]

[0018] [Figure 1] FIG. 1 illustrates an example of a discharge event detection system including a discharge detection unit. [Diagram 2] FIG. 13 is a diagram showing an example in which a discharge detection unit is attached to a distribution board. [Diagram 3] FIG. 4 is a schematic diagram showing a configuration example of a discharge detection unit. [Figure 4] FIG. 13 is a diagram showing that equipment noise is superimposed on a voltage waveform, and that a waveform of a specific frequency is extracted using a high-pass filter or the like, and also showing an enlarged portion of the extracted waveform. [Diagram 5] FIG. 13 is a diagram showing that discharge noise is superimposed on a voltage waveform, and that a waveform of a specific frequency is extracted using a high-pass filter or the like, and also showing an enlarged portion of the extracted waveform. [Figure 6] FIG. 13 is a diagram showing extracted equipment noise and extracted discharge noise side by side. [Figure 7] FIG. 13 shows an example of a table of confirmed voltage outputs. [Figure 8] FIG. 13 is a diagram showing an example in which the output value of discharge noise is small. [Figure 9] FIG. 13 is a diagram showing an example in which both discharge noise and equipment noise occur. [Figure 10] FIG. 13 is a diagram showing an example in which a quarter cycle of a commercial frequency is set as a time for count integration. [Figure 11] 1 is a diagram showing an example in which the count is accumulated only around the peak of the commercial frequency, where the count is accumulated over a quarter cycle of the commercial frequency. [Figure 12] FIG. 13 is a diagram showing an example in which the count is accumulated over two periods of a commercial frequency. [Figure 13] FIG. 1 is a diagram showing an example in which it is determined that discharge noise is occurring when it is confirmed that the integrated value of the count exceeds a predetermined value consecutively. Note that the time for which the count is integrated is set to one period of the commercial frequency. [Figure 14] This figure shows that noise caused by a partial break (or break) is superimposed on the voltage waveform, and that a waveform of a specific frequency is extracted using a high-pass filter or the like, and also shows an enlarged portion of the extracted waveform. [Figure 15] This is a diagram showing the differences in output waveforms, etc. between "equipment noise", "discharge noise caused by a short circuit between electrodes", and "discharge noise caused by a partial break". [Figure 16] 11 is a diagram showing an example in which threshold value A for distinguishing between equipment noise and discharge noise, and threshold value B for distinguishing between discharge noise and electromagnetic wave noise, etc., are set. FIG. [Figure 17] 17 is a diagram illustrating an example of a determination logic when thresholds A and B shown in FIG. 16 are set. FIG. [Figure 18] 18 is a diagram showing an example of a determination logic different from that shown in FIG. 17 when thresholds A and B shown in FIG. 16 are set. [Figure 19] 13 is a diagram showing an example of the change over time in the integrated value of the number of detections measured by the counting unit when equipment noise occurs, with the data for five times showing the same change over time. [Figure 20] 1 is a diagram showing an example of a change over time in the integrated value of the number of detections measured by a counting unit when AC discharge noise occurs, where five samples are shown. [Figure 21] 20 with arrows indicating the tendency of change over time. [Figure 22] 13 is a diagram showing an example of the change over time in the integrated value of the number of detections measured by the counting unit when AC discharge noise occurs, with the data for five times showing the same change over time. [Figure 23] FIG. 13 is a diagram illustrating an example in which a threshold value regarding the number of detections is set. [Figure 24]1 is a diagram showing an example of the relationship between the type of noise, the number of detections, and the noise measurement time, where (a) shows a case where equipment noise is occurring, (b) shows a case where AC discharge noise is occurring, and (c) shows a case where DC discharge noise is occurring. [Diagram 25] FIG. 13 is an image showing how noise is dispersed due to the presence of a branch circuit. [Figure 26] 11A and 11B are diagrams illustrating an example of information used when estimating a noise occurrence location. [Figure 27] FIG. 27 is a diagram showing an example of deriving an estimated distance from the number of detections using the information shown in FIG. 26. [Figure 28] 1 is a diagram showing the distribution of the number of detections at each time during the time period in which the number of detections is accumulated, where five samples are shown. [Figure 29] FIG. 13 is a diagram illustrating an example of the relationship between the number of detections and frequency. [Diagram 30] FIG. 30 is a diagram showing an example in which the data shown in FIG. 28 is rewritten using the information shown in FIG. 29. [Diagram 31] 11 is a diagram showing an example of the relationship between the distance from the generation point to the detection point and the attenuation rate for each frequency. FIG. [Diagram 32] FIG. 32 is a diagram showing an example in which an attenuation rate is derived from the distance from the occurrence point to the detection point using the information shown in FIG. 31. [Diagram 33] 4 is a schematic diagram showing an example of the configuration of the discharge detection unit, where a second arithmetic processing unit is added to the configuration shown in FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] The following describes an embodiment of the invention. As can be understood from FIGS. 1 to 4, the discharge detection unit 1 of this embodiment is electrically connected to the electric circuit 6 to which the load 8 is connected, and is thereby capable of detecting noise superimposed on the voltage or current of the electric circuit 6 to which the load 8 is connected. The discharge detection unit 1 includes a filter section 11 that cuts out noise below a predetermined frequency superimposed on the voltage or current of the electric circuit 6, thereby preventing commercial frequency and low-frequency band noise from passing and outputting the waveform of the high-frequency band noise that has been passed, a count section 12 that can calculate the number of detections of the waveform in a predetermined time from the waveform that has passed the filter section 11, and a calculation processing section 13 that can determine the presence or absence of noise caused by discharge in the electric circuit 6 using the number of detections calculated by the count section 12. This makes it possible to detect the occurrence of a discharge event even in a situation where it was difficult to detect in the past. For example, since the cause can be determined by the number of detections calculated by the count section 12, smaller noise can be used for the determination. This makes it possible to suppress the effects of the magnitude and distance of the discharge (the effect of attenuation). This makes it possible to determine whether or not discharge noise has occurred at an early stage of discharge. Furthermore, even if discharge noise occurs at a position somewhat distant from the discharge detection unit 1, it is possible to determine whether or not the noise has occurred.

[0020] Here, we will explain a discharge event detection system 100 that includes the discharge detection unit 1. The discharge event detection system 100 detects the output of noise superimposed on the voltage or current of an electric circuit 6 to which a load 8 is connected. For this reason, the discharge detection unit 1 is connected to the electric circuit 6 that is interposed between a commercial power source 7 and the load 8 (see FIG. 1).

[0021] The discharge detection unit 1 is electrically connected to an electric circuit 6 that carries electricity between a commercial power source 7 and a load 8, and is attached, for example, inside a house. This discharge detection unit 1 may be disposed inside a distribution board 50 (see FIG. 2). This makes it possible to detect the presence or absence of a discharge event in the electric circuit 6 of the house that is connected to the distribution board 50. For example, it is preferable to connect the discharge detection unit 1 to the electric circuit 6 that connects a main breaker 51 and a branch breaker 52. However, the discharge detection unit 1 may also be electrically connected to the primary side of the main breaker 51 or the secondary side of the branch breaker 52.

[0022] Here, the discharge detection unit 1 of the embodiment will be described. The discharge detection unit 1 of the embodiment includes a filter section 11 so as to cut noise below a predetermined frequency that is superimposed on the voltage or current of the electric circuit 6. This filter section 11 does not pass commercial frequencies and low-frequency band noise, but allows high-frequency band noise to pass. The discharge detection unit 1 also includes a waveform generating section 15 that generates a high-frequency band noise waveform that has passed through the filter section 11.

[0023] The discharge detection unit 1 also includes a counting section 12 that counts the number of waves generated by the waveform generating section 15. The discharge detection unit 1 also includes a memory section 16 that stores the number of times the waves are detected measured by the counting section 12. The discharge detection unit 1 of the example shown in FIG. 3 also includes a reset section 17 that can reset the count of the counting section 12 and can reset the information in the memory section 16. Note that the reset section 17 may only reset the count of the counting section 12 or reset the information in the memory section 16. The discharge detection unit 1 may omit the waveform generating section 15. The discharge detection unit 1 may be configured so that the counting section 12 counts the output based on the output extracted by the filter section 11.

[0024] The discharge detection unit 1 also includes a setting section 14 that can set the judgment conditions used when judging whether or not discharge noise is occurring from the number of detections. The setting section 14 of the embodiment can be operated to change and reset the judgment conditions. By providing the discharge detection unit 1 with such a setting section 14, for example, if the measurement time is set to be short, the measurement can be completed quickly. Also, if the measurement time is set to be long, the accuracy of the judgment of whether or not noise is occurring can be improved.

[0025] As can be seen from these descriptions, it is preferable that the discharge detection unit 1 is configured to include a setting section 14 that enables the counting section 12 to set the time for calculating the number of times the waveform is detected.

[0026] The discharge detection unit 1 also includes a calculation processing unit 13 capable of performing calculations to determine whether or not discharge noise is occurring based on the number of detections and information on the determination conditions. The calculation processing unit 13 in the embodiment is a processor, but may be something else as long as it is capable of performing the above-mentioned calculations.

[0027] Moreover, the discharge detection unit 1 shown in FIG. 3 includes an output section 18 used to notify the outside of the discharge detection unit 1 after the result of the arithmetic processing section 13 is obtained. The output section 18 may be configured to be able to notify visually. In this case, the output section 18 may be configured using an LED. The output section 18 may be configured to be able to notify auditorily. In this case, the output section 18 may be configured using a buzzer. The output section 18 may also output a signal. For example, it may be a signal output section that outputs the detection result to an external measuring device or monitoring device. The output section 18 may also be a signal output section that is able to output a cutoff signal to the main breaker 51 or the branch breaker 52.

[0028] The filter unit 11 can extract equipment noise caused by equipment and discharge noise caused by a discharge event. Here, the difference in the tendency of noise passing through the filter unit 11 between discharge noise and equipment noise will be described.

[0029] First, a case where equipment noise is extracted by filter unit 11 will be described (see FIG. 4). Note that since the handling of a current waveform superimposed with noise and the handling of a voltage waveform superimposed with noise are similar, the explanation will be given here by taking an example of a voltage waveform superimposed with noise.

[0030] When no noise is superimposed, the voltage waveform repeats a constant waveform in accordance with the frequency of the commercial power source 7. When equipment noise is superimposed, as can be seen from Fig. 4, the noise is superimposed regardless of the position of the waveform of the commercial power source 7. For this reason, in the example shown in Fig. 4, small waves caused by equipment noise are always superimposed on large waves represented by the voltage waveform caused by the commercial power source 7.

[0031] When equipment noise is extracted using filter unit 11 and waveform generation unit 15, the influence of the waveform of commercial power supply 7 disappears, and a waveform caused by equipment noise is generated. In other words, a waveform containing only noise output is generated by cutting the commercial frequency output from the voltage waveform using filter unit 11. The number of waveform outputs containing only noise output is counted by count unit 12.

[0032] Here, we will explain a specific example using numerical values. For example, equipment noise caused by equipment operation is mainly noise generated by switching ON / OFF operations. The noise generated by this switching is from several kilohertz to several tens of kilohertz. Note that frequency indicates the number of times a wave repeats per second, so switching noise generated at 10 kHz is output at intervals of 1 / 10000s = 0.1 ms. Also, when the commercial frequency is 60 Hz, one cycle lasts for 16.7 ms, so 167 waves (= 16.7 ms / 0.1 ms) are output during this one cycle due to switching.

[0033] Next, discharge noise will be explained. Discharge noise caused by inter-pole short circuits such as tracking occurring between poles is detected in a frequency band that is an order of magnitude different from the switching noise frequency (for example, kilohertz level) (for example, megahertz or gigahertz level).

[0034] To explain with a concrete example, if the noise in the target discharge event occurs in the 1MHz frequency band, and the commercial frequency is 60Hz, waves can be generated due to the discharge event at a pace such that they are output 16,700 times (=16.7ms / 0.001ms) in one cycle. However, with regard to discharge noise, detection is not performed near the zero crossing point (see Figure 5). In other words, this value is not detected continuously during one cycle, so the only value that can be detected is a smaller value than this.

[0035] As mentioned above, noise in discharge events is detected only near the peak region of the commercial frequency, and is not detected near zero-crossing points such as the 0-value time region, but even with discharge noise output of half a cycle, thousands to tens of thousands of waves are superimposed. In contrast, equipment noise is a noise output in which hundreds of waves are superimposed in one cycle. In other words, the number of detections obtained per unit time for noise in discharge events and equipment noise is quite different, making it possible to distinguish whether the noise is discharge noise or equipment noise (switching noise) (see Figure 6).

[0036] Specifically, when equipment noise occurs, the number of waves detected in one period is, for example, 167, and when discharge noise occurs, the number of waves detected in one period is, for example, half of 16700, or 8350. Taking note of this difference, in this embodiment, a threshold value for the number of detections of waves measured by the counting unit is set by setting unit 14, and the set threshold value is used to determine whether the noise is equipment noise or discharge noise by calculation processing unit 13.

[0037] In the above example, the switching noise occurs at several tens of kHz, and the discharge noise occurs at several MHz, but the frequency bands that can be determined are not limited to these.

[0038] Furthermore, in the embodiment, if there is noise, the counting unit 12 counts the number of detections per cycle regardless of the magnitude (large or small) of the noise, and stores the result in the memory unit 16. The number of detections stored in the memory unit 16 is compared with the threshold value of the number of detections set in the setting unit 14, and it is determined whether equipment noise or discharge noise is occurring using the calculation processing unit 13. In this way, by checking the number of waves, it is possible to determine whether the noise is due to a discharge event or due to the equipment.

[0039] As can be understood from these descriptions, it is preferable that the discharge detection unit 1 is configured to be able to determine which of the two is occurring, equipment noise caused by the load 8 or discharge noise in the electrical circuit 6, using the number of detections obtained by the counting unit 12 when either one is occurring.

[0040] The counting method performed by the counting unit 12 may be any method, but for example, the presence or absence of voltage output for each time is confirmed in a matrix (see FIG. 7). In the example shown in FIG. 7, the number of detections is increased by one each time an output equal to or greater than a specific value is confirmed.

[0041] Here, an example of detecting discharge noise in a short circuit between poles will be described. Regarding discharge noise in a short circuit between poles, when the measurement position is far from the occurrence point or in the early stages of discharge, the output value of the discharge noise tends to be detected as small (see FIG. 8). However, even if the detected noise value is small, the number of occurrences can be confirmed. Therefore, in judging noise, the influence of the distance between the occurrence point and the measurement position, the smallness of the generated noise, etc. can be suppressed. In other words, it is possible to judge discharge noise even when the distance between the discharge detection unit 1 and the occurrence point of the discharge event is long or when the noise is in the early stages.

[0042] It is also possible that discharge noise and equipment noise coexist (see Figure 9). In this case, it is difficult to distinguish between equipment noise and discharge noise, but it is possible to determine the presence or absence of discharge noise from the magnitude of the count. In other words, even when discharge noise and equipment noise coexist, it is possible to determine whether or not discharge noise is occurring using the number of detections. Since it is not so important whether or not equipment noise is occurring, but rather whether or not discharge noise is occurring, the most necessary information can be obtained without distinguishing between equipment noise and discharge noise.

[0043] In this example, the count value is handled based on one period. For example, if no noise is detected in one period, or if a predetermined number of noises or more are not detected, the count of the counting unit 12 is reset by the reset unit 17, and the counting is restarted from the beginning.

[0044] Up to this point, the number of waves per one cycle time (approximately 16.7 ms for 60 Hz) has been detected, but the time for measuring the number of waves does not need to be limited to one cycle. For example, the number of waves per quarter cycle time (approximately 4.2 ms for 60 Hz) may be measured instead of one cycle time (see FIG. 10). Also, since discharge noise is detected largely around the peaks of the commercial frequency of current and voltage, it is possible to measure only around the peak time of the commercial frequency waveform (see FIG. 11). Also, in order to improve the accuracy of distinguishing between equipment noise and discharge noise, the number of waves per two cycles time (approximately 33.4 ms for 60 Hz) may be measured (see FIG. 12). Of course, it is not necessary to limit the time to these cycles.

[0045] It should be noted that the number of detections may increase due to momentary trouble. Therefore, when determining whether or not a discharge event occurs based on the number of detections per cycle, it is determined that a discharge event occurs even if such a thing occurs. For this reason, it is possible to determine whether or not the number of detections exceeds a predetermined number every predetermined time (e.g., one cycle). In this case, if the state in which the "number of detections exceeds the predetermined number" occurs multiple times (multiple hours) in succession, it may be determined that the discharge noise exists (see FIG. 13). In this way, it is possible to reduce the possibility of erroneous detection due to momentary trouble. In other words, it is possible to more accurately determine whether or not the discharge noise exists. When determining whether or not the state in which the "number of detections exceeds the predetermined number" occurs multiple times in succession, even if the number of detections does not exceed the predetermined number for a predetermined time (e.g., one cycle), if the state in which the "count exceeds the predetermined number" occurs again in the measurement time of the next cycle, it may be determined that the state continues.

[0046] For example, if it is determined that noise has occurred when the "detection count exceeds a predetermined number" state has occurred four consecutive times, and the "detection count exceeds a predetermined number" state has occurred three consecutive times, but the "detection count exceeds a predetermined number" state does not occur at the next timing, but the "detection count exceeds a predetermined number" state occurs at the timing after that, then it is determined that noise has occurred because the "count exceeds a predetermined number" state has occurred four consecutive times.

[0047] As can be understood from these descriptions, it is preferable that the discharge detection unit 1 is configured to determine the number of detections multiple times and determine that noise caused by a discharge event is occurring when it is confirmed that the number of detections is greater than a set number of times consecutively, because this allows for more accurate determination of the occurrence of a discharge.

[0048] Next, discharge noise caused by partial breaks will be explained. In addition to discharges caused by pole-to-pole short circuits, discharges can also occur due to partial breaks (or breaks) at the same pole. In the case of partial breaks (or breaks), the wires repeatedly connect and disconnect, leading to sparks and irregular output (see Figure 14). However, discharge noise caused by partial breaks (or breaks) occurs in the same frequency band as discharge noise caused by pole-to-pole short circuits. Also, like pole-to-pole short circuits, the detection count is different in magnitude from equipment noise. Therefore, by using the detection count, it is possible to determine whether or not there is a suspicion of discharge noise caused by partial breaks (or breaks) occurring, regardless of whether equipment noise is occurring or not.

[0049] Here, we will summarize the differences in output waveforms etc. between "equipment noise", "discharge noise caused by a short circuit between electrodes", and "discharge noise caused by a partial break". Equipment noise and discharge noise (caused by a short circuit between electrodes or a partial break) behave as shown in Fig. 15, for example. Therefore, it is possible to distinguish between equipment noise and discharge noise by using the number of times noise is detected per unit time.

[0050] In addition, by using the regularity of the noise output waveform over a long period of time (1 to 2 cycles), the type of discharge noise can also be determined.

[0051] For example, if it is confirmed that the output waveform is continuously output for one or two cycles, it can be determined that equipment noise is occurring. Note that it is also possible to extract a portion of one cycle and determine that there is equipment noise if it is confirmed that the number of detections is relatively low, but it may also be determined that there is equipment noise if both the continuity of the noise output and the number of detections satisfy the conditions. For example, it may be determined that there is equipment noise if it is confirmed that there is continuous noise output for more than half a cycle and that the number of detections is relatively low.

[0052] On the other hand, for example, when checking the output waveform for one or more cycles and finding that noise is continuously output in the peak time region but no noise is output near the zero crossing point, it may be determined that discharge noise caused by a short circuit between electrodes is occurring. Of course, it may also be determined that discharge noise caused by a short circuit between electrodes is occurring after also checking that the number of detections is relatively high.

[0053] Also, if noise is output without regularity, it may be determined that discharge noise is occurring due to a partial disconnection (or disconnection). Of course, it may also be determined that discharge noise is occurring due to a partial disconnection (or disconnection) after also checking that the number of detections is relatively high.

[0054] In other words, the type of noise may be determined by using not only the noise appearance of the output waveform over a long period (e.g., 1 to 2 periods of the commercial frequency) and the output waveform over a short period (e.g., 1 ms), but also the detection results of both. Note that the long period is preferably one period or more, and the short period is preferably less than one period. The long period and the short period are not limited to the above, but are different periods.

[0055] As can be understood from these descriptions, it is preferable that the discharge detection unit 1 is configured to be able to identify the cause of a discharge event using both the regularity of noise occurrence over a long period of one cycle or more, or the regularity of output over a long period of one cycle or more, and the number of detections by the counting unit 12 in a short cycle that is shorter than the long period.

[0056] If the number of detections exceeds a predetermined value set in the setting unit 14, it may be determined that noise due to a discharge event is occurring, but electromagnetic waves and the like have a frequency band that is even larger than the frequency band corresponding to discharge noise, and noise in such a frequency band may occur depending on the installation location. In this case, for example, if the number of detections is equal to or greater than a predetermined value (for example, a count of one million times in one period), an output that is not discharge noise is detected.

[0057] For this reason, it is preferable to set a lower limit (A threshold) and an upper limit (B threshold) for the threshold of the number of detections as well (see Fig. 16). In this case, for example, if the number of detections is below the lower limit (below A threshold), it is determined to be equipment noise, if the number of detections is equal to or greater than the upper limit (B threshold), it is determined to be radio noise or electromagnetic noise (EMC noise), and if the number of detections is equal to or greater than the lower limit but less than the upper limit, it is determined to be discharge noise (see Fig. 17).

[0058] However, even if a lower limit (threshold A) and an upper limit (threshold B) are set, there may be cases where equipment noise occurs that falls between threshold A and threshold B. Taking this into consideration, it may be advisable to incorporate another step.

[0059] For example, equipment noise is mainly switching noise, and there is a pattern to the duration and output magnitude of the noise. On the other hand, discharge noise is not uniform, with output magnitude varying. Therefore, it may be a good idea to incorporate a step to check the pattern (see Figure 18). Note that if the equipment is used in an environment where there is no noise in a frequency band that is an order of magnitude larger than the frequency band corresponding to discharge noise, the upper limit range is not necessarily required.

[0060] As can be understood from these descriptions, it is preferable that the discharge detection unit 1 is configured to set an upper limit on the number of detections by the counting section 12, and if a detection count exceeding the upper limit is detected, it can be determined that the noise is caused by electromagnetic waves.

[0061] Incidentally, the majority of equipment noise is switching noise, which is output at regular intervals. Furthermore, because switching noise does not change with voltage or current, when the number of detections is accumulated, the relationship between time and the accumulated number of detections is proportional. This tendency is basically the same for every cycle (see Figure 19). In contrast, in the case of discharge noise, the size of the discharge event (magnitude of current and voltage) and the presence or absence of a discharge event are not constant, so the tendency for the number of detections to increase varies from cycle to cycle (see Figure 20).

[0062] In other words, by obtaining multiple integrated values ​​of the number of detections over a certain period of time and comparing them, it is possible to estimate whether the noise is equipment noise caused by the operation of the equipment or discharge noise caused by discharge. For example, by obtaining multiple integrated values ​​of the number of detections in one cycle of a voltage or current on which noise is superimposed, if the variation therebetween is small, it can be estimated that the noise is equipment noise, and if the variation therebetween is large, it can be estimated that the noise is discharge noise.

[0063] As can be seen from Figs. 19 and 20, in the case of equipment noise, the integrated value of the number of detections and the time are in a roughly proportional relationship, but in the case of discharge noise, this is not the case. More specifically, in the case of discharge noise, when the integrated value of the number of detections in one cycle of the voltage or current on which the noise is superimposed is examined, it can be seen that there are time periods during which the integrated value increases rapidly and time periods during which the integrated value stagnates (see Fig. 21). It can also be seen that there are two time periods during one cycle in which the integrated value increases rapidly. This is because discharge noise is detected near the peak region of the commercial frequency, but is difficult to detect in the zero value time region. Although this cannot be read from Fig. 21, the time during which noise occurs near the peak region usually changes depending on the magnitude of the discharge.

[0064] As can be understood from these descriptions, equipment noise and discharge noise have different increasing trends in the integrated value of the number of times the noise is detected over a certain period of time for the voltage or current on which the noise is superimposed. Therefore, by checking the increasing trend of the integrated value of the number of times the noise is detected, it is possible to estimate whether it is equipment noise or discharge noise. For example, by checking the growth of the integrated value of the number of times the noise is detected over one cycle of the voltage or current on which the noise is superimposed, if the integrated value is proportional to time, it is estimated to be equipment noise, and if the integrated value is not proportional to time, it is estimated to be discharge noise. The difference in the increasing trend can be confirmed by simply checking a half cycle of the voltage or current on which the noise is superimposed.

[0065] As can be understood from these descriptions, it is possible to check only either "the variation in the integrated count value" or "the tendency of the increase in the integrated count value" and use it to estimate the equipment noise and the discharge noise, but it is also possible to check both and use it to estimate the equipment noise and the discharge noise. In order to make this possible, it is preferable that the number of detections measured by the counting unit can be obtained for each cycle of the voltage or current on which noise is superimposed, and the calculation processing unit can determine the presence or absence of noise caused by discharge in the electric circuit using at least one of the increase in the number of detections for each cycle and the variation in the increase in the number of detections for each cycle.

[0066] So far, we have given examples of detecting discharge events in AC systems, but discharge events also occur in DC systems. In a DC system, when noise is superimposed on the voltage output or current output of the wiring circuit, the integrated value of the number of detections is approximately proportional to the time (see Figure 22). However, the number of detections is much greater than when equipment noise is occurring, and the integrated value is also larger. This is because noise is constantly being output, and is a high-frequency output. As a result, the number of detections for discharge noise when a discharge event occurs in a DC system is greater than the number of detections for discharge noise in an AC system.

[0067] As can be understood from these descriptions, by using the number of detections obtained by the counting unit, it is possible not only to distinguish between equipment noise and discharge noise, but also to distinguish whether the discharge noise is AC discharge noise or DC discharge noise.

[0068] For example, A and B thresholds are set for the number of detections, and a range below the A threshold is set as the AA range, a range between the A threshold and the B threshold is set as the BB range, and a range above the B threshold is set as the CC range. In this case, if the number of detections is in the AA range, it may be determined that it is equipment noise, if it is in the BB range, it is AC discharge noise, and if it is in the CC range, it is other noise (such as DC discharge noise) (see FIG. 23). Note that the determination using the number of detections may be made using the total number of detections or the average number of detections per specific time period (for example, one cycle), etc.

[0069] Even if the detection count is in the BB region, if there is no variation from period to period and the increase in the detection count is proportional and linear, it can be determined to be equipment noise or DC discharge noise. In this case, too, whether it is equipment noise or DC discharge noise can be determined based on the magnitude of the detection count. For example, if it is in the BB region close to the AA region, but there is no variation from period to period and the increase in the detection count is proportional and linear, it can be determined to be equipment noise. Also, if it is in the BB region close to the CC region, but there is no variation from period to period and the increase in the detection count is proportional and linear, it can be determined to be DC discharge noise.

[0070] Even if the detection count is in the AA region, the variation from period to period and the increase in the detection count may be further examined to determine whether it is equipment noise or AC discharge noise.

[0071] Similarly, even if the number of detections is in the CC region, it may be possible to further check the variation for each period and the increase in the number of detections to determine whether it is AC discharge noise or DC discharge noise.

[0072] As can be understood from these descriptions, the accuracy of the judgment result can be improved by using not only the number of detections but also other information provided by the number of detections. Also, the accuracy of the judgment result can be improved by using information that is not provided by the number of detections but is incidentally obtained when the counting unit counts.

[0073] An example of information that can be obtained incidentally when the counting unit counts is the measurement time when noise is detected. The measurement time when noise is detected here refers to the time when the integrated count value tends to increase.

[0074] In the case of equipment noise, noise may occur only when the equipment is first put into operation, or noise may occur continuously. In contrast, in the case of AC discharge noise, there are regular intervals between periods when noise due to discharge can be detected and periods when it is not detected. In the case of DC discharge noise, there are no regular intervals between periods when noise due to discharge is not detected. For this reason, the noise measurement time is affected by the type of noise. It is therefore preferable to be able to set a threshold value for the noise measurement time.

[0075] Here, an example of the relationship between the type of noise, the number of detections, and the noise measurement time will be described. Fig. 24 shows an example of the relationship between the number of detections and the noise measurement time for equipment noise, AC discharge noise, and DC discharge noise. In this example, the noise measurement period is set as the time during which the noise is measured during five cycles (five cycles for the voltage or current on which the noise is superimposed), and the number of detections counted within the noise measurement time is plotted. Of course, the reference period does not have to be five cycles.

[0076] In this example, multiple pieces of data on the noise measurement time and the number of detections under the above conditions are obtained (see FIG. 24). The multiple pieces of data obtained can be used to determine the type of noise. It is not necessary to use all of the obtained data to determine the type of noise. However, using multiple pieces of data can improve the accuracy of the noise type determination. For example, it is preferable to set it so that if the obtained data satisfies the conditions a predetermined number of times in succession, it is determined that the corresponding type of noise is occurring.

[0077] The example shown in Fig. 24(a) shows data obtained due to the occurrence of equipment noise. In this example, the obtained detection counts are all smaller than the set threshold A. Also, the obtained noise measurement times are all smaller than the set threshold X.

[0078] It is preferable to determine whether or not it is equipment noise by checking whether or not "the obtained detection count is smaller than threshold A and the obtained noise measurement time is smaller than threshold X" occurs a predetermined number of times in succession. However, it is also possible to set other conditions, such as determining whether or not it is equipment noise by checking whether or not either "the obtained detection count is smaller than threshold A" or "the obtained noise measurement time is smaller than threshold X" occurs multiple times.

[0079] The example shown in (b) of Fig. 24 shows data obtained when AC discharge noise occurs. In this example, all of the obtained detection counts are greater than the set threshold A and smaller than the set threshold B. Also, all of the obtained noise measurement times are greater than the set threshold X and smaller than the set threshold Y.

[0080] It is preferable to determine whether or not it is AC discharge noise by checking whether or not the following occurs consecutively a predetermined number of times: "the obtained detection count is equal to or greater than threshold A and less than threshold B, and the obtained noise measurement time is equal to or greater than threshold X and less than threshold Y." However, it is also possible to set other conditions, such as "the obtained detection count is equal to or greater than threshold A, and the obtained noise measurement time is equal to or greater than threshold X and less than threshold Y," or "the obtained detection count is equal to or greater than threshold A and less than threshold B, and the obtained noise measurement time is equal to or greater than threshold X."

[0081] 24(c) shows data obtained by the occurrence of DC discharge noise. In this example, all of the obtained detection counts are greater than the set threshold value B. Also, all of the obtained noise measurement times are greater than the set threshold value Y.

[0082] It is preferable to determine whether or not it is DC discharge noise by checking whether or not "the obtained detection count is equal to or greater than threshold B and the obtained noise measurement time is equal to or greater than threshold Y" occurs a predetermined number of times in succession. However, it is also possible to set other conditions, such as determining whether or not it is DC discharge noise by checking whether or not either "the obtained detection count is equal to or greater than threshold B" or "the obtained noise measurement time is equal to or greater than threshold Y" occurs multiple times.

[0083] If it is only necessary to determine whether or not discharge noise occurs, the condition for the determination can be "the obtained detection count is equal to or greater than threshold A, and the obtained noise measurement time is equal to or greater than threshold X." Of course, the condition for the determination can also be "either the obtained detection count is equal to or greater than threshold A, or the obtained noise measurement time is equal to or greater than threshold X, occurring a predetermined number of times in succession."

[0084] As can be understood from these descriptions, it is preferable to have at least one or more thresholds for the number of detections measured by the counting unit, and at least one or more thresholds for the measurement time of the counts measured by the counting unit, and the calculation processing unit is configured to be able to determine the presence or absence of noise due to discharge in the electrical circuit using the thresholds for the number of detections and the thresholds for the measurement time of the counts.

[0085] When multiple pieces of data are used to determine the type of discharge, the determination may be made using an average or median value, which can reduce the influence of irregular measurement results.

[0086] The discharge detection unit detects high-frequency noise generated by spark discharge. However, high-frequency noise has the characteristic that it attenuates the longer the wiring length of the electric circuit. If the detection judgment takes such attenuation into account, the actual magnitude of the discharge can be estimated even if the discharge occurs at a distance. Furthermore, the discharge detection unit of the present invention can be electrically connected to a distribution board equipped with multiple branch breakers 52. By configuring the power distribution system 3 in this way, it becomes possible to monitor the power distribution system of the entire building.

[0087] While studying this issue, it was found that the noise detected by the discharge detection unit tends to depend on the number of branch breakers 52. This is thought to be because the noise is dispersed, and the noise detected by the discharge detection unit is also dispersed (see FIG. 25). If the discharge noise is dispersed, it affects the number of detections obtained by the counting unit. In other words, it was found that the number of branch breakers 52 (number of circuits) affects the number of detections measured by the counting unit.

[0088] The discharge noise itself attenuates not only with the number of circuits but also with distance, but it was found that there is a relationship between the number of branch breakers 52, the number of detections, and the estimated distance (see Fig. 26). In this way, if the relationship between the number of branch breakers 52, the number of detections, and the estimated distance can be derived from empirical values, etc., then it is possible to use that relationship to estimate the location where the discharge noise occurs and the distance at which the discharge was detected (see Fig. 27).

[0089] 27 shows an example in which the number of detections by the counting unit is 600, and the number of branch breakers 52 is 25. It can be seen that the number of branch breakers 52 can be compared with the information represented by the dashed and dotted line, and it can be seen that the portion in the information represented by the dashed and dotted line where the number of detections is 600 is the portion where the estimated distance can be estimated to be 30 m. In this way, it can be estimated that the distance between the discharge detection unit and the location where the discharge event occurred is 30 m.

[0090] Since this is possible, it is preferable to have a configuration including an occurrence location estimation unit that estimates the location where a discharge event occurred based on the number of branch breakers 52 and the number of detections by the counting unit.

[0091] Furthermore, in order for such an occurrence location estimation unit to function, information on the number of branch breakers 52 is required. The number of branch breakers 52 may be directly input by a user or may be derived from some other information. In the former case, a switch input unit capable of inputting information on the number of branch breakers 52 may be provided. In the latter case, a switch estimation unit capable of deriving information on the number of branch breakers 52 by calculation may be provided.

[0092] The switch input unit may be, for example, a dip switch formed on the surface of the discharge detection unit. The switch estimation unit may be, for example, a unit that can collect information such as the rated current of the branch breakers 52 and the rated current of the main switch and perform calculations to estimate the number of branch breakers 52.

[0093] As can be understood from these descriptions, it is preferable for the power distribution system 3 to be one in which the discharge detection unit is electrically connected to a plurality of branch breakers 52, in which the relationship between the number of detections and the location where a discharge event occurs is stored to correspond to the number of branch breakers 52, and which is equipped with a switch input unit that inputs information regarding the number of branch breakers 52, or a switch estimation unit that estimates the number of branch breakers 52, and which is equipped with an occurrence location estimation unit that can estimate the location where a discharge event occurred using the input or estimated number of branch breakers 52 and the number of detections measured by the counting unit.

[0094] However, when the number of detections obtained at each timing to obtain an integrated value is examined, it is found that there is variation in the number of detections. For example, even if the integrated value in one cycle of the voltage or current on which noise is superimposed is as shown in FIG. 20, the number of detections per unit time during that period is as shown in FIG. 28. Furthermore, when data on such number of detections and the frequency included in the discharge (only high frequencies) is collected, it is found that there is a relationship between such number of detections and the frequency included in the discharge. More specifically, as can be seen from FIG. 29, it is found that there is an approximately proportional relationship between such number of detections and the frequency included in the discharge.

[0095] By utilizing this relationship, it is possible to estimate the frequency of the noise generated by a discharge event from the number of detections measured by the counter. For example, it is possible to estimate the dominant frequency or the maximum frequency.

[0096] Here, an example of identifying a frequency using the information shown in FIG. 29 obtained from experience will be described. For example, if the number of detections in a specific duration time period is about 90, the frequency component can be estimated to be C (Hz). By doing this, the diagram shown in FIG. 28 can be rewritten as shown in FIG. 30. Note that in the example shown in FIG. 28, the vertical axis represents the number of detections and the horizontal axis represents time, whereas in the example shown in FIG. 30, the vertical axis represents frequency and the horizontal axis represents time.

[0097] The dominant frequency band and maximum frequency can be identified from Figure 30. If the frequency band can be identified, it can be estimated whether the noise is caused by a device such as a home appliance or a discharge event.

[0098] In order to make this possible, it is preferable to provide a frequency estimation unit used for estimating the frequency. More specifically, it is preferable to provide a frequency estimation unit that stores the relationship between the number of detections and the frequency and is capable of identifying the frequency of the discharge event using the number of detections counted by the counting unit. It is preferable that the frequency estimation unit is capable of estimating the dominant frequency and the maximum frequency.

[0099] In the example shown in Figure 30, the data is distributed so that there are two peaks, but this is because two peaks appear in one cycle of a sine wave. In this example, the positive peak time zone (the time zone of the first peak) and the negative peak time zone (the time zone of the second peak) have similar frequency distributions, but this may not always be the case. In this case, it is preferable to use the data in the frequency band with the larger numerical value to determine the discharge event.

[0100] Incidentally, noise caused by a discharge event attenuates depending on the distance between the location where the discharge event occurred and the location where the noise is measured. The manner in which this attenuation occurs differs for each frequency band. However, once the frequency is identified, the relationship between the "distance between the location where the discharge event occurred and the location where the noise is measured" and the "attenuation rate" can be derived empirically (see Figure 31).

[0101] Therefore, if the "distance between the location where the discharge event occurred and the location where the noise is measured" and the "frequency" are known, the attenuation rate can be estimated (see Figure 32). If the attenuation rate can be estimated, it can be detected even if a dangerous discharge occurs at a location somewhat distant from the discharge detection unit.

[0102] Meanwhile, as described above, by analyzing the number of detections, it is possible to estimate "the distance between the location where the discharge event occurred and the location where the noise is measured" and "the frequency" (see Fig. 26 and Fig. 29). Note that Figs. 20 to 22, 24, 26 to 32 are diagrams showing the relationship between the number of detections and the frequency, and the relationship between the number of detections and the estimated distance. These are merely examples, and the numerical values ​​of the number of detections, frequency, and estimated distance may be different.

[0103] To make this possible, the example shown in Fig. 33 is provided with a second calculation processing unit 21. The second calculation processing unit 21 shown in Fig. 33 is provided with a switch estimation unit or a switch input unit. In addition, the second calculation processing unit 21 is also provided with a generation location estimation unit, a frequency estimation unit, and a damping rate specification unit.

[0104] The switch estimation unit, the switch input unit, the generation location estimation unit, the frequency estimation unit, and the attenuation rate identification unit do not need to be configured to be included in the second calculation processing unit 21. For example, some or all of them may be provided in a location separate from the discharge detection unit.

[0105] As can be understood from these descriptions, the power distribution system 3 stores the relationship between the generation distance and the attenuation rate for each frequency, and is preferably configured to include a generation location estimation unit and an attenuation rate determination unit that can determine the attenuation rate of the discharge noise from the generation distance estimated by the frequency estimation unit and the frequency estimation unit.

[0106] Although the present invention has been described above by taking the embodiment as an example, the present invention is not limited to the above embodiment and can be embodied in various forms. For example, it is possible to change the order of some of the judgment logic, delete some of it, or add new ones. [Explanation of symbols]

[0107] 1 Discharge detection unit 6 Electrical circuit 8. Load 11 Filter section 12 Counting section 13 Processing unit 14 Setting section 52 Branch breaker

Claims

1. A discharge detection unit capable of detecting noise superimposed on a voltage or current of an electric path to which a load is connected by being electrically connected to the electric path, a filter section that cuts out noise below a predetermined frequency that is superimposed on the voltage or current of an electric circuit, thereby preventing commercial frequency and low-frequency band noise from passing and enabling output of a waveform of high-frequency band noise that has been passed; a counting unit capable of calculating the number of times a waveform is detected within a predetermined time from the waveform that has passed through the filter unit; a calculation processing unit capable of determining the presence or absence of noise caused by discharge in the electric circuit by using the number of detections calculated by the counting unit; A discharge detection unit comprising:

2. The discharge detection unit according to claim 1, which is capable of determining which of the following is occurring, when either equipment noise caused by a load or discharge noise in an electrical circuit, is occurring, using the number of detections obtained by the counting unit.

3. 3. The discharge detection unit according to claim 2, further comprising a setting section for setting a time period during which the counting section calculates the number of times the waveform is detected.

4. 4. The discharge detection unit according to claim 3, wherein the number of detections is judged a plurality of times, and when it is confirmed that the number of detections is greater than a set number of times consecutively, it is possible to judge that noise due to a discharge event is occurring.

5. A discharge detection unit as described in any one of claims 1 to 4, which is capable of identifying the cause of a discharge event using both the regularity of noise occurrence over a long period of time that is one cycle or more, or the regularity of output over a long period of time that is one cycle or more, and the number of detections by the counting unit over a short period that is shorter than the long period of time.

6. 2. The discharge detection unit according to claim 1, wherein an upper limit is set for the number of detections by the counting section, and when a detection count exceeding the upper limit is detected, it can be determined that the noise is caused by electromagnetic waves.

7. The number of detections measured by the counting unit can be obtained for each period of the voltage or current on which noise is superimposed, The discharge detection unit according to claim 1 , wherein the calculation processing unit is capable of determining the presence or absence of noise caused by discharge in the electrical circuit using at least one of the increase in the number of detections per cycle and the variation in the increase in the number of detections per cycle.

8. At least one threshold value is provided for the number of detections measured by the counting unit, and at least one threshold value is provided for the measurement time of the counts measured by the counting unit; 2. The discharge detection unit according to claim 1, wherein the calculation processing unit is capable of determining the presence or absence of noise caused by discharge in the electric circuit by using a threshold value of the number of detections and a threshold value of the measurement time of the count.

9. A power distribution system in which the discharge detection unit according to claim 1 is electrically connected to a plurality of branch breakers, The relationship between the number of detections and the location where the discharge event occurred is stored so as to correspond to the number of branch breakers, A switch input unit that inputs information regarding the number of branch breakers or a switch estimation unit that estimates the number of branch breakers, A power distribution system including an occurrence location estimation unit capable of estimating the location where a discharge event occurred using an input or estimated number of branch breakers and a detection count measured by a counting unit.

10. The relationship between the number of detections and the frequency is stored. The power distribution system according to claim 9 , further comprising a frequency estimation unit capable of identifying a frequency of the discharge event using the number of detections counted by the counting unit.

11. For each frequency, the relationship between the distance between the discharge detection unit and the location where the discharge event occurs and the attenuation rate is stored. The power distribution system according to claim 10 , further comprising: an occurrence location estimating unit; and an attenuation rate specifying unit capable of specifying an attenuation rate of the discharge noise from the occurrence distance estimated by the frequency estimating unit and the frequency estimating unit.

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