Discharge detection unit

Abstract

Provided is a discharge detection unit 1 capable of detecting noise superimposed on a voltage or a current of an electric path to which a load is connected, by being electrically connected to the electric path to which the load is connected, the discharge detection unit 1 being provided with a filter part 11 capable of outputting a waveform of noise in a passed high-frequency band without passing noise in a commercial-frequency and a low-frequency band by cutting noise of a predetermined frequency or lower that is superimposed on the voltage or current of the electric path, a count part 12 capable of calculating the number of detections of a waveform in a predetermined time from the waveform passing through the filter part, and an arithmetic processing part 13 capable of determining the presence or absence of noise caused by discharge in the electric path by using the number of detections calculated by the count part.

Description

Discharge Detection Unit

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

[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 using a current sensor or a voltage sensor. The technology disclosed in Patent Document 1 utilizes the fact that noise is always superimposed when using a specific electric drill or hand mixer to determine whether a discharge has been detected. Specifically, the technology disclosed in Patent Document 1 distinguishes between a peak time region, which includes the region before and after a peak in the commercial frequency, and a zero value time region, which includes the region before and after the output of the commercial frequency becomes zero, and determines whether discharge noise is present by comparing the output at the timing of the peak time region with the output at the timing of the zero value time region.

[0003] Japanese Patent Application Laid-Open No. 2022-89758

[0004] The technology disclosed in Patent Document 1 determines whether noise output exceeds a threshold. Therefore, to distinguish between equipment noise and discharge noise, the discharge event must be large enough. Furthermore, the noise attenuates with distance from the source of the discharge noise, making it difficult to detect discharge noise occurring at a distance.

[0005] The inventors of the present invention have made extensive research into this issue and have attempted to solve it. 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.

[0006] In order to solve the above problem, the discharge detection unit 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 comprises: 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 passed; a counting section that can calculate 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 can determine the presence or absence of noise due to discharge in the electric circuit, using the number of detections calculated by the counting section.

[0007] Furthermore, when either equipment noise caused by the load or discharge noise in the electrical circuit is occurring, it is preferable to configure the device so that it can determine which is occurring using the number of detections obtained by the counting unit.

[0008] It is also preferable to have a configuration including 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] Furthermore, it is preferable to have a configuration in which the number of detections is judged multiple times, and when it is confirmed that the number of detections is greater than a set number of times consecutively, it can be judged 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, which is one cycle or more, or the regularity of output over a long period of time, which is one cycle or more, and the number of detections by the counting unit over a short period of time, which is shorter than the long period of time.

[0011] It is also preferable to set an upper limit on the number of detections by the counting unit, and to have a configuration in which, if a detection count exceeding the upper limit is detected, it can be determined that the noise is caused by electromagnetic waves.

[0012] Furthermore, 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 that the calculation processing unit can determine 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.

[0013] Furthermore, it is preferable that the counting unit has at least one or more thresholds for the number of detections measured, and at least one or more thresholds 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 caused by discharge in the electrical circuit using the thresholds for the number of detections and the thresholds for the measurement time of the counts.

[0014] Furthermore, it is preferable that the power distribution system be one in which the discharge detection unit is electrically connected to a plurality of branch breakers, in which the relationship between the number of detections and the location of the discharge event is stored so as to correspond to the number of branch breakers, and which 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 which is equipped with an occurrence location estimation unit that can estimate the location of the discharge event 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 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 measured by the counting unit.

[0016] Furthermore, 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.

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

[0018] 1 is a diagram illustrating an example of a discharge event detection system equipped with a discharge detection unit. FIG. 2 is a diagram illustrating an example of a discharge detection unit attached to a distribution board. FIG. 3 is a schematic diagram illustrating an example of the configuration of a discharge detection unit. FIG. 4 is a diagram illustrating the superposition of equipment noise on a voltage waveform and the extraction of a waveform of a specific frequency using a high-pass filter or the like, with an enlarged view of a portion of the extracted waveform. FIG. 5 is a diagram illustrating the superposition of discharge noise on a voltage waveform and the extraction of a waveform of a specific frequency using a high-pass filter or the like, with an enlarged view of a portion of the extracted waveform. FIG. 6 is a diagram illustrating extracted equipment noise and extracted discharge noise side by side. FIG. 7 is a diagram illustrating an example of a confirmed voltage output entered into a table. FIG. 8 is a diagram illustrating an example where the output value of discharge noise is small. FIG. 9 is a diagram illustrating an example where both discharge noise and equipment noise are occurring. FIG. 10 is a diagram illustrating an example where the time for count accumulation is a quarter cycle of the commercial frequency. FIG. 11 is a diagram illustrating an example where the time for count accumulation is only around the peak of the commercial frequency. FIG. 12 is a diagram illustrating an example where the time for count accumulation is a quarter cycle of the commercial frequency. 17 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. The time period for integrating the count is one cycle of the commercial frequency. This diagram illustrates the superposition of noise caused by a partial disconnection (or disconnection) on a voltage waveform, and the extraction of a waveform of a specific frequency using a high-pass filter or the like, and also shows an enlarged portion of the extracted waveform. This diagram summarizes 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 disconnection." This diagram illustrates an example in which a threshold A for distinguishing between equipment noise and discharge noise, and a threshold B for distinguishing between discharge noise and electromagnetic noise, etc., are set. This diagram illustrates an example of judgment logic when the threshold A and threshold B shown in FIG. 16 are set. This diagram illustrates an example of judgment logic different from that shown in FIG. 17 when the threshold A and threshold B shown in FIG. 16 are set. This diagram illustrates 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. Note that all five sets of data show similar changes over time.29 is a diagram showing an example of time-dependent change in the integrated value of the number of detections measured by the counting unit when AC discharge noise occurs. Five samples are shown. Arrows are added to FIG. 20 to indicate the trend in time-dependent change. FIG. 29 is a diagram showing an example of time-dependent change in the integrated value of the number of detections measured by the counting unit when AC discharge noise occurs. All five sets of data show similar time-dependent change. FIG. 29 is a diagram showing an example of setting a threshold value for the number of detections. FIG. 29 is a diagram showing an example of the relationship between noise type, number of detections, and noise measurement time. (a) shows a case where equipment noise occurs, (b) shows a case where AC discharge noise occurs, and (c) shows a case where DC discharge noise occurs. FIG. 29 is a conceptual diagram showing how noise is dispersed due to the presence of a branch circuit. FIG. 29 is a diagram showing an example of information used when estimating the location of noise generation. FIG. 29 is a diagram showing an example of deriving an estimated distance from the number of detections using the information shown in FIG. 26. FIG. 29 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. (five samples are shown). FIG. 29 is a diagram showing an example of the relationship between the number of detections and frequency. FIG. 29 is a diagram showing an example of rewriting the data shown in FIG. 28 using the information shown in FIG. 29. 31 is a diagram showing an example of the relationship between the distance from the generation location to the detection location and the attenuation rate for each frequency. It is a diagram showing an example of deriving the attenuation rate from the distance from the generation location to the detection location using the information shown in FIG. 31. It is a schematic diagram showing an example of the configuration of the discharge detection unit. However, a second calculation processing unit is added to the configuration shown in FIG.

[0019] An embodiment of the invention is described below. As can be seen from FIGS. 1 to 4 , the discharge detection unit 1 of this embodiment is electrically connected to an electric circuit 6 to which a load 8 is connected, thereby enabling it to detect noise superimposed on the voltage or current of the electric circuit 6 to which the load 8 is connected. The discharge detection unit 1 also includes a filter unit 11 that cuts out noise below a predetermined frequency superimposed on the voltage or current of the electric circuit 6, thereby blocking commercial frequency and low-frequency noise and outputting a waveform of the passed high-frequency noise; a count unit 12 that calculates the number of detections of the waveform from the waveform passed by the filter unit 11 within a predetermined period of time; and a calculation processing unit 13 that uses the number of detections calculated by the count unit 12 to determine whether or not there is noise due to discharge in the electric circuit 6. This allows the occurrence of a discharge event to be detected even in situations that were previously difficult to detect. For example, because the cause can be determined based on the number of detections calculated by the count unit 12, smaller noise can be used for the determination. This reduces the effects of the magnitude and distance of the discharge (the effect of attenuation). Therefore, it becomes possible to determine whether or not discharge noise has occurred in the early stages of a 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 installed, for example, inside a house. The discharge detection unit 1 may be placed 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 electric discharge detection unit 1 of the embodiment will be described. The electric 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 noise at commercial frequencies or in low-frequency bands, but allows noise in high-frequency bands to pass. The electric discharge detection unit 1 also includes a waveform generation section 15 that generates a noise waveform in the high-frequency band 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 wave detections measured by the counting section 12. The discharge detection unit 1 of the example shown in FIG. 3 also includes a resetting section 17 that can reset the count of the counting section 12 and reset the information in the memory section 16. Note that the resetting section 17 may only be able to reset the count of the counting section 12 or reset the information in the memory section 16. The discharge detection unit 1 may also 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, by setting a shorter measurement time, it is possible to finish measurement more quickly. Furthermore, by setting a longer measurement time, it is possible to increase the accuracy of judging whether or not noise is occurring.

[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 that is 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 any other device as long as it is capable of performing the calculations described above.

[0027] The discharge detection unit 1 shown in FIG. 3 also includes an output unit 18 that is used to notify the outside of the discharge detection unit 1 after the result of the arithmetic processing unit 13 is obtained. The output unit 18 may be configured to provide visual notification. In this case, the output unit 18 may be configured using an LED. The output unit 18 may also be configured to provide auditory notification. In this case, the output unit 18 may be configured using a buzzer. The output unit 18 may also output a signal. For example, it may be a signal output unit that outputs the detection result to an external measuring instrument or monitoring device. The output unit 18 may also be a signal output unit that can output a tripping 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 the filter unit 11 will be described (see FIG. 4). Note that, because the handling of a current waveform with noise superimposed thereon and the handling of a voltage waveform with noise superimposed thereon are similar, the explanation here will be given using a voltage waveform with noise superimposed thereon as an example.

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

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

[0032] Here, we will explain specific examples 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 in the range of 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 / 10,000 seconds = 0.1 milliseconds. Furthermore, when the commercial frequency is 60 Hz, one cycle lasts 16.7 milliseconds, so 167 waves (= 16.7 milliseconds / 0.1 milliseconds) are output during this cycle due to switching.

[0033] Next, we will explain discharge noise. Discharge noise caused by a short circuit between electrodes, such as tracking, is detected in a frequency band (for example, megahertz or gigahertz) that is an order of magnitude different from the frequency of switching noise (for example, kilohertz level).

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

[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 zero-value time region. However, even when discharge noise is output for 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 discharge event noise 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 cycle is, for example, 167, and when discharge noise occurs, the number of waves detected in one cycle is, for example, half of 16,700, or 8,350. Taking note of this difference, in this embodiment, a threshold value for the number of detected waves measured by the counting unit is set by the setting unit 14, and the set threshold value is used by the calculation processing unit 13 to determine whether it is equipment noise or discharge noise.

[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 this embodiment, if noise is present, 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 storage unit 16. The number of detections stored in the storage unit 16 is compared with the threshold value of the number of detections set in the setting unit 14, and it is determined using the calculation processing unit 13 whether equipment noise or discharge noise is occurring. In this way, by checking the number of waves, it is possible to determine whether the noise is due to a discharge event or equipment noise.

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

[0040] The counting method used by the counting unit 12 may be any, but for example, the presence or absence of voltage output for each time period may be confirmed in a matrix (see FIG. 7). In the example shown in FIG. 7, the number of detections is incremented 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 electrodes will be described. Regarding discharge noise in a short circuit between electrodes, when the measurement position is far from the occurrence point or in the early stages of discharge, the detected output value of the discharge noise tends to be small (see Figure 8). However, even if the detected noise value is small, the number of occurrences can be confirmed. Therefore, when determining whether there is a discharge, the influence of factors such as the distance between the occurrence point and the measurement position or the smallness of the generated noise can be suppressed. In other words, it is possible to determine whether there is discharge noise even when the distance between the discharge detection unit 1 and the occurrence point of the discharge event is long or if 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 whether discharge noise is present or not from the magnitude of the count. In other words, even when discharge noise and equipment noise coexist, it is possible to determine whether discharge noise is occurring using the number of detections. Whether equipment noise is occurring or not is not so important, but what is important is whether discharge noise is occurring or not, so 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 cycle. For example, if no noise is detected in one cycle, 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 cycle (approximately 16.7 ms for 60 Hz) has been detected, but the time period for measuring the number of waves does not need to be limited to one cycle. For example, the number of waves per quarter cycle (approximately 4.2 ms for 60 Hz) may be measured instead of one cycle (see FIG. 10). Furthermore, because discharge noise is most prominent around the peaks of the commercial frequency of current and voltage, it is also possible to measure only the time around the peak of the commercial frequency waveform (see FIG. 11). Furthermore, to improve the accuracy of distinguishing between equipment noise and discharge noise, it is also possible to measure the number of waves per two cycles (approximately 33.4 ms for 60 Hz) (see FIG. 12). Of course, it is not necessary to limit the time period to these cycles.

[0045] It should be noted that the number of detections may increase due to momentary problems. Therefore, when determining whether or not a discharge event exists based on the number of detections per cycle, even if such a situation occurs, it is still determined that a discharge event has occurred. For this reason, it is conceivable 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 "number of detections exceeds the predetermined number" state occurs multiple times (multiple hours) in a row, it may be determined to be discharge noise (see FIG. 13). This reduces the possibility of false detections due to momentary problems. In other words, it is possible to more accurately determine whether or not a discharge event has occurred. When determining whether or not the "number of detections exceeds the predetermined number" state occurs multiple times in a row (multiple hours), even if the "number of detections exceeds the predetermined number" state does not exceed the predetermined number for a predetermined time (e.g., one cycle), it may be determined that the "count exceeds the predetermined number" state occurs again during the measurement time of the next cycle.

[0046] For example, if it is determined that noise has occurred when the "number of detections exceeds a predetermined number" state has occurred four times in a row, and the "number of detections exceeds a predetermined number" state has occurred three times in a row, but the "number of detections exceeds a predetermined number" state does not occur at the next timing, but the "number of detections 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 times in a row.

[0047] As can be understood from these descriptions, it is preferable that the discharge detection unit 1 be 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, we will explain discharge noise caused by partial disconnections. Discharges can occur not only due to short circuits between poles, but also due to partial disconnections (or breaks) at the same pole. In the case of a partial disconnection (or break), the wires repeatedly connect and disconnect, leading to sparks and irregular output (see Figure 14). However, discharge noise caused by partial disconnections (or breaks) occurs in the same frequency band as discharge noise caused by short circuits between poles. Furthermore, like short circuits between poles, the number of detections is different in magnitude from equipment noise. Therefore, by using the number of detections, it is possible to determine whether discharge noise caused by partial disconnections (or breaks) is suspected, regardless of whether equipment noise is occurring.

[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 disconnection." Equipment noise and discharge noise (caused by a short circuit between electrodes or a partial disconnection) 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] Furthermore, 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 the output waveform is checked for one to two cycles and it is confirmed that noise is being continuously output during that time, 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 are a relatively small number of detections, but it can 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 can 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 there are a relatively small number of detections.

[0052] On the other hand, for example, when checking the output waveform for one or more cycles and it is found 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] Furthermore, 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 whether 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 (for example, one to two cycles of the commercial frequency) but also the detection results of the output waveform over a short period (for example, 1 ms). Note that the long period is preferably one cycle or more, and the short period is preferably less than one cycle. The long period and 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 be 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 over a short period of time that is shorter than the long period.

[0056] It may be determined that noise due to a discharge event is occurring if the number of detections exceeds a predetermined value set in the setting unit 14, 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 cycle), it means that an output that is not discharge noise has been detected.

[0057] For this reason, it is preferable to set a lower limit (threshold A) and an upper limit (threshold B) for the threshold of the number of detections (see Fig. 16). In this case, for example, if the number of detections is below the lower limit (below threshold A), it is determined to be equipment noise, if the number of detections is equal to or greater than the upper limit (equipment noise), it is determined to be radio wave 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, it is possible that equipment noise may occur that falls between threshold A and threshold B. Taking this into consideration, it may be possible 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 is possible to incorporate a step to check the pattern (see Figure 18). Note that if the equipment is used in an environment where noise in a frequency band larger than the frequency band corresponding to discharge noise does not occur, 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 has an upper limit on the number of detections by the counting section 12, and that if a number of detections 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 all cycles (see Figure 19). In contrast, in the case of discharge noise, the magnitude 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 increase in the number of detections 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 over one cycle of the voltage or current on which noise is superimposed, if the variation therebetween is small, it can be estimated to be equipment noise, and if the variation therebetween is large, it can be estimated to be discharge noise.

[0063] 19 and 20, in the case of equipment noise, the integrated value of the number of detections and time are roughly proportional, 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 in which the integrated value increases sharply and time periods in which the integrated value stagnates (see FIG. 21). It can also be seen that there are two time periods in one cycle in which the integrated value increases sharply. 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 it cannot be inferred from FIG. 21, the duration of noise occurrence near the peak region usually changes depending on the magnitude of the discharge.

[0064] As can be seen from these descriptions, equipment noise and discharge noise have different increasing trends in the integrated value of the number of times the voltage or current on which the noise is superimposed is detected over a certain period of time. 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 the noise is equipment noise or discharge noise. For example, by checking the increase in 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 can be estimated to be equipment noise, and if the integrated value is not proportional to time, it can be estimated to be discharge noise. The difference in the increasing trend can also be confirmed by simply checking half a 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 "trend in the growth of the integrated count value" and use this to estimate equipment noise and discharge noise, or it is also possible to check both and use this to estimate equipment noise and discharge noise. To make this possible, it is preferable that the number of detections measured by the counting unit can be acquired for each cycle of the voltage or current on which noise is superimposed, and that 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 trend in 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] Up to this point, we have presented examples of detecting discharge events in AC systems, but discharge events also occur in DC systems. In DC systems, when noise is superimposed on the voltage output or current output of a wiring circuit, the cumulative value of the number of detections is approximately proportional to the time (see Figure 22). However, the number of detections is significantly greater than when equipment noise is present, and the cumulative 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, thresholds A and B are set for the number of detections, and a range AA is set for values ​​less than threshold A, a range BB is set for values ​​equal to or greater than threshold A and less than threshold B, and a range CC is set for values ​​equal to or greater than threshold B. In this case, if the number of detections is in range AA, it may be determined to be equipment noise, if it is in range BB, it may be determined to be AC ​​discharge noise, and if it is in range CC, it may be determined to be 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).

[0069] Furthermore, even if the number of detections is in the BB region, if there is no variation from period to period and the increase in the number of detections is proportional and linear, it can be determined to be equipment noise or DC discharge noise. Even in this case, whether it is equipment noise or DC discharge noise can be distinguished based on the magnitude of the number of detections. 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 number of detections 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 number of detections is proportional and linear, it can be determined to be DC discharge noise.

[0070] Furthermore, even if the number of detections is in the AA region, it is also possible to determine whether it is equipment noise or AC discharge noise by further checking the variation in each period and the increase in the number of detections.

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

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

[0073] The information obtained incidentally when the counting unit counts can include, for example, the measurement time when noise is detected. The measurement time when noise is detected here refers to the timing 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 cannot be detected. In the case of DC discharge noise, there are no regular intervals between periods when noise due to discharge cannot be detected. For this reason, the noise measurement time is affected by the type of noise. Therefore, it is 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 times of detection, and the noise measurement time will be described. Fig. 24 shows an example of the relationship between the number of times of detection 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 noise is measured over five cycles (five cycles of the voltage or current on which the noise is superimposed), and the number of times of detection counted within that 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 noise measurement time and number of detections under the above conditions are acquired (see FIG. 24 ), and the acquired multiple pieces of data are used to determine the type of noise. It is not necessary to use all of the acquired 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 the system so that if the acquired data meets 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 Figure 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 there is equipment noise by checking whether or not "the obtained number of detections 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, other conditions can also be set, such as checking whether or not there is equipment noise by checking whether or not either "the obtained number of detections 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 Figure 24 shows data obtained when AC discharge noise occurs. In this example, the obtained detection counts are all greater than the set threshold A and less than the set threshold B. Also, the obtained noise measurement times are all greater than the set threshold X and less than the set threshold Y.

[0080] It is preferable to determine whether or not the noise is AC discharge noise by checking whether or not the following occurs consecutively a predetermined number of times: "the obtained number of detections 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, other conditions can also be set, such as "the obtained number of detections 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 number of detections 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] The example shown in (c) of Figure 24 shows data obtained when DC discharge noise occurs. In this example, the obtained detection counts are all greater than the set threshold value B. Also, the obtained noise measurement times are all greater than the set threshold value Y.

[0082] It is preferable to determine whether or not the noise 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, other conditions can also be set, such as 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 to determine whether or not the noise is DC discharge noise.

[0083] If it is only necessary to determine whether or not discharge noise occurs, the condition for the determination can be "the obtained number of detections 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 number of detections 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 that the counting unit has at least one or more thresholds for the number of detections measured, and at least one or more thresholds 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 caused by 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 determining the type of discharge using multiple pieces of data, 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 is characterized by its tendency to attenuate the longer the electrical wiring. By taking this attenuation into account in the detection and determination, it is possible to estimate the actual magnitude of the discharge even if it occurs far away. 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 is possible to monitor the power distribution system of the entire building.

[0087] In the course of investigating these issues, 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 Figure 25). When 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] Although discharge noise itself attenuates not only with the number of circuits but also with distance, 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 ​​or the like, it is possible to use this relationship to estimate the location where 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 counter 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-dotted line, and it can be seen that the part of the information represented by the dashed-dotted line where the number of detections is 600 is the part 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] To make this possible, it is preferable to provide a configuration including an occurrence location estimation unit that estimates the location of the discharge event based on the number of branch breakers 52 and the number of detections by the counting unit.

[0091] Furthermore, in order for such a fault location estimation unit to function, information on the number of branch breakers 52 is required. The number of branch breakers 52 may be input directly 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 through 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 breaker, 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 the discharge event occurred is stored so as 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 the discharge event occurred using the input or estimated number of branch breakers 52 and the number of detections measured by the counting unit.

[0094] Incidentally, 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 of 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 the number of detections and the frequencies included in the discharge (only high frequencies) is collected, it is found that there is a relationship between the number of detections and the frequencies included in the discharge. More specifically, as can be seen from FIG. 29, it is found that there is an approximately proportional relationship between the number of detections and the frequencies included in the discharge.

[0095] By utilizing this relationship, it is possible to estimate the frequency of 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 maximum frequency.

[0096] Here, an example will be described in which the information shown in Fig. 29 is obtained from experience and the information is used to identify the frequency. For example, if the number of detections in a specific duration time period is approximately 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 coming from a device such as a home appliance or from a discharge event.

[0098] To achieve this, 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 be 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. This is because two peaks occur in one cycle of a sine wave. In this example, the positive peak time period (the time period of the first peak) and the negative peak time period (the time period 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 whether a discharge event has occurred.

[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 FIG. 31).

[0101] Therefore, if the "distance between the location where the discharge event occurred and the location where the noise is being measured" and the "frequency" are known, the attenuation rate can be estimated (see FIG. 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] On the other hand, as described above, the "distance between the location where the discharge event occurred and the location where the noise is being measured" and the "frequency" can be estimated by analyzing the number of detections, etc. (See FIGS. 26 and 29). Note that FIGS. 20 to 22, 24, and 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. The second calculation processing unit 21 also is provided with a generation location estimation unit, a frequency estimation unit, and an attenuation factor identification unit.

[0104] The switch estimation unit, switch input unit, generation location estimation unit, frequency estimation unit, and 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 these units 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 using the embodiments as examples, the present invention is not limited to the above embodiments and can be embodied in various forms. For example, it is possible to change the order of some of the decision logic, delete some, or add new logic.

[0107] REFERENCE SIGNS LIST 1 discharge detection unit 6 electric circuit 8 load 11 filter section 12 counting section 13 calculation processing section 14 setting section 52 branch breaker

Claims

1. 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, 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 outputting a waveform of the high-frequency band noise that has been passed; a counting section that is capable of calculating the number of times a waveform has been detected in a predetermined period of time from the waveform that has passed the filter section; and a calculation 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.

2. A discharge detection unit as described in claim 1, which is capable of determining which is occurring when either equipment noise caused by the load or discharge noise in the electrical circuit is occurring, using the number of detections obtained by the counting section.

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

4. The discharge detection unit according to claim 3, which is capable of determining that noise caused by a discharge event is occurring when the number of detections is determined to be greater than a set number of times for a predetermined number of consecutive times.

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.

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

7. The discharge detection unit according to claim 1, wherein the number of detections measured by the counting section can be acquired for each cycle of the voltage or current on which noise is superimposed, and the calculation processing section can determine 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. A discharge detection unit as described in claim 1, comprising at least one or more thresholds for the number of detections measured by the counting section, and at least one or more thresholds for the measurement time of the counts measured by the counting section, and the calculation processing section is capable of determining 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.

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 a discharge event occurs being stored so as to correspond to the number of branch breakers, the power distribution system is provided with a switch input unit for inputting information regarding the number of branch breakers or a switch estimation unit for estimating the number of branch breakers, and an occurrence location estimation unit capable of estimating the location where a discharge event occurred using the input or estimated number of branch breakers and the number of detections counted by the counting unit.

10. A power distribution system as described in claim 9, further comprising a frequency estimation unit that stores the relationship between the number of detections and the frequency and is capable of identifying the frequency of a discharge event using the number of detections measured by the counting unit.

11. A power distribution system as described in claim 10, in which the relationship between the distance between the discharge detection unit and the location where a discharge event occurs and the attenuation rate is stored for each frequency, and the system is provided with an occurrence location estimation unit and an attenuation rate determination unit capable of determining the attenuation rate of the discharge noise from the occurrence distance estimated by the frequency estimation unit and the frequency estimation unit.

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