KR20210117419A - Insulation status monitoring equipment of power cables and method - Google Patents

Abstract

The present invention relates to a device for monitoring the insulation state of a power cable and a method therefor. A device for monitoring the insulation status of a power cable according to the present invention includes a detection sensor part; a filter amplification digital conversion part; a standard deviation calculation part; a kurtosis calculation part; a recalculation determination part; a final data confirmation part; and an insulation state determination part. It is possible to accurately determine whether the insulation state of a terminal of a power supply part is poor in a power cable system by removing noise data.

Description

Insulation status monitoring equipment of power cables and method

The present invention relates to an insulation state monitoring device and method for monitoring the insulation state of a power cable in a live state. In more detail, in order to monitor the insulation state of the power cable during operation of the power cable, the kurtosis value (kurt) and the standard deviation value (std) are calculated by reading the data of the signal detected through the sensor installed on the power cable. In order to check whether the kurtosis value (kurt) and the standard deviation value (std) are large due to the inclusion of external environmental noise, the calculated kurtosis value (kurt) and the standard deviation value (std) are set to a value larger than the preset constant value. The preset recognition rate (j) is the value of the j kurtosis values or j standard deviation values greater than the preset constant value, which is re-detected and re-calculated by reading data through the sensor repeatedly a preset number of times (j times) at a time interval. Q%), the maximum value among the recalculated j kurtosis values or j standard deviation values is determined as the final value, and the recalculated j kurtosis values or j standard deviation values are larger than the preset constant value. If the value is smaller than the preset recognition rate (Q%), the final value is 0 (zero) or the first calculated value is confirmed as the final value by disregarding the re-calculated j kurtosis values or standard deviation values. And it relates to a power cable insulation state monitoring apparatus and method for determining the insulation state using the finally determined value, thereby removing the element caused by external environmental noise to determine the correct insulation state of the electric power cable.

In recent years, as the industry develops rapidly, the possibility of various types of accidents that can occur in various facilities continues to increase as power facilities become high-voltage and large-capacity. Therefore, in order to prevent accidents on power facilities or to improve the reliability of operation, the need for a power cable insulation state monitoring device during operation is very urgent. In order to monitor the status of the power cable during such operation, a sensor is installed on the power cable. The sensor is different depending on the type of the power cable and there are several types depending on the status monitoring signal to be detected. Sensor , Shunt type sensor. Antenna sensor, UV sensor, thin-film electrode sensor, ultrasonic sensor, vibration sensor, etc. are used, and the power cable system includes the power cable body and the power cable body as shown in FIG. It consists of a load-side terminal for connecting and connecting with the load-side equipment and an intermediate connecting portion for connecting and connecting the main body of the power cable and the main body of the power cable because the length of the power cable is long.

On the other hand, since the signal detected through the sensor installed on the power cable to monitor the insulation state of the power cable is weak and contains a noise signal, the signal converted through amplification and filter is read several times (in the present invention, even the received data marked) is subjected to statistical processing to determine In general, statistically processed values include the average for indicating the value of the received data, the median value and the standard deviation for indicating the variability of the received data (referred to as std in the present invention), variance, skewness, and kurtosis. (referred to as kurt in the present invention), the maximum value, the minimum value, and the like are used.

In Registered Patent No. 10-1299183 (registration date August 16, 2013, power quality classification method using name speech processing technique, power quality monitoring device and power quality monitoring system), average, variance, maximum and minimum values of received data It uses statistically processed data such as, and in Patent Registration No. 10-1070832 (registration date September 29, 2011, the name of the method for detecting abnormalities in switchgear with self-diagnosis function), the peak value, the effective value, and the average value of the received data Although statistically processed data such as , kurtosis, skewness, and standard deviation are used, it is effective to judge noise, but power cable system components (cable body, power side terminal, load side terminal) If a sensor is not installed for each part, intermediate connection), there is a problem in that it is not possible to accurately determine whether the terminal on the power side is bad, whether the terminal on the load side is bad, or whether the intermediate connection part is bad.

In addition, in Registered Patent No. 10-1291595 (registration date July 25, 203, titled Power cable insulation state monitoring device and method) applied by the present inventor, statistically processed data of standard deviation of received data is used. , there is a problem in that it is not possible to accurately determine whether the power supply side terminal part is bad, the load side terminal part is bad, or the intermediate connection part is bad among the components of the power cable system.

In addition, in Patent Publication No. 10-2017-0085462 applied by the present inventor (published on July 24, 2017, titled Power cable insulation state monitoring device and method), statistical processing of kurtosis and standard deviation of received data Using the data obtained from the power cable system, it is judged whether the power supply terminal is bad, the load terminal is bad, or the intermediate connection is bad. There was a problem in that it was not possible to accurately determine whether the noise generated in the environment surrounding the power cable installation had an effect on the kurtosis value or the standard deviation value or whether it occurred in the power cable system.

Therefore, when the insulation state is judged to be defective using the signal detected from the sensor installed in the power cable in a state in which the sensor is installed at the minimum in the power cable system, whether the power supply side terminal is bad, the intermediate connection part is bad, or the load side terminal part There is a need for a method that can accurately determine whether the noise is bad or not by distinguishing the noise in the field.

The present invention is to solve the problems of the prior art, and an object of the present invention is to monitor the insulation state of the power cable, the standard deviation value (std) or the kurtosis value ( kurt) and if the calculated standard deviation (std) or kurtosis (kurt) is greater than a preset constant value, repeat several times (j times) at regular time intervals to check whether noise data is included. Repeat the redetection and recalculation process, and the number of j kurtosis values (kurt) or j standard deviation values (std) that are recalculated by repeating j times is greater than the preset constant value is the preset recognition rate (Q%) ), the maximum value among the recalculated j kurtosis values (kurt) or j standard deviation values (std) is determined as the final data and reflected in the insulation state judgment, and the recalculated j kurtosis values (kurt) or If the number of j standard deviation values (std) greater than the preset constant value is less than the preset acceptance rate (Q%), recalculated j kurtosis values (kurt) or j standard deviation values (std) Insulation status monitoring device for power cable, which determines the final value as 0 (zero) or the initial calculated value for disapproval, and allows the final data to be reflected in the insulation status data so that the insulation status of the power cable can be accurately determined to provide a way.

Insulation state monitoring device of the power cable of the present invention for achieving the above object includes a detection sensor unit for detecting a signal related to the insulation state from the power cable;

a filter amplification digital conversion unit extracting a signal of a preset frequency band from the signals detected by the detection sensor unit and amplifying and converting the signal into a digital value;

a standard deviation calculation unit for calculating a standard deviation value (std) of the n pieces of received data read from the filter amplification digital conversion unit;

a kurtosis calculation unit for calculating a kurtosis value (kurt) of the n pieces of received data read from the filter amplification digital conversion unit;

If the kurtosis value (kurt_0) calculated by the kurtosis calculator is greater than a preset constant threshold_K (that is, kurt_0 > threshold_K ), the detection sensor unit as many as j times a preset number of repetitions at a preset waiting time interval to check whether the data is noise-like. standard deviation value (std) of the n received data read by the filter amplification digital conversion unit in the kurtosis calculating unit, re-sensing the signal in The process of re-calculating the kurt and kurt values (kurt) is repeated for a preset number of times (j times), and if the kurtosis value (kurt_0) calculated by the kurtosis calculator is not greater than the preset constant threshold_K (that is, kurt_0 ≤ threshold_K) ) a re-calculation determination unit for not repeating the preset number of repetitions by the number of j times;

If the re-calculation determination unit does not repeat the pre-set j number of times, the standard deviation value (std_0) calculated in the standard deviation calculation unit and the kurtosis value (kurt_0) calculated in the kurtosis calculation unit are final standard deviations If the value (std) and the final kurtosis value (kurt) are determined, and the recalculation judgment unit repeats a preset j number of times, the j kurtosis values (kurt_j) that are repeated several times in the recalculation judgment unit If the number greater than this preset constant threshold_K is greater than the preset recognition rate (Q %), the j recalculated kurtosis values (kurt_j) are recognized and the largest kurtosis among the recalculated j kurtosis values (kurt_j) repeated several times. The value (kurt_j) is substituted and confirmed with the final kurtosis value (kurt), and the j kurtosis values recalculated by the recalculation decision unit repeatedly several times while iterating as many times as preset j times in the recalculation decision unit If the number of (kurt_j) greater than the preset constant threshold_K is less than the preset recognition rate (Q %), the final kurtosis value (kurt) is set to 0 (zero) by rejecting the j number of kurtosis values (kurt_j) recalculated repeatedly several times. ), and the final standard deviation value (std) is the standard deviation value (std_0) calculated in the standard deviation calculator a final data determining unit for storing data by replacing and confirming the data;

The final standard deviation value (std) determined and stored in the final data determination unit is compared with a preset constant threshold_S, and the final kurtosis value determined and stored in the final data determination unit (kurt) and a preset constant threshold_K and size are compared and an insulation state determination unit that compares and determines the insulation state of the power cable.

Insulation state monitoring device of the power cable of the present invention for achieving the above object includes a detection sensor unit for detecting a signal related to the insulation state from the power cable;

a filter amplification digital conversion unit extracting a signal of a preset frequency band from the signals detected by the detection sensor unit and amplifying and converting the signal into a digital value;

a standard deviation calculation unit for calculating a standard deviation value (std) of the n pieces of received data read from the filter amplification digital conversion unit;

a kurtosis calculation unit for calculating a kurtosis value (kurt) of the n pieces of received data read from the filter amplification digital conversion unit;

If the kurtosis value (kurt_0) calculated by the kurtosis calculator is greater than a preset constant threshold_K (that is, kurt_0 > threshold_K ) or the standard deviation value (std_0) calculated by the standard deviation calculator is greater than the preset constant threshold_S (i.e. std_0 > threshold_S ) Re-sensing the signal in the detection sensor unit as many as j times a preset number of repetitions at a preset waiting time interval to check whether it is noise data, and amplifying the signal re-detected by the filter amplification digital converter and Converting to a digital value, and repeating the process of recalculating the standard deviation value (std) and kurtosis value (kurt) of the n received data read from the filter amplification digital conversion unit in the kurtosis calculator by the number of times (j times) , if the kurtosis value (kurt_0) calculated by the kurtosis calculator is not greater than the preset constant threshold_K (that is, kurt_0 ≤ threshold_K ) and the standard deviation value (std_0) calculated by the standard deviation calculator is not greater than the preset constant threshold_S ( That is, std_0 ≤ threshold_S ) a re-calculation determining unit for not repeating as many times as the preset number of repetitions j;

If the re-calculation determination unit does not repeat the preset j number of times, the standard deviation value (std_0) calculated in the standard deviation calculation unit and the kurtosis value (kurt_0) calculated in the kurtosis calculation unit are the final standard deviation value. (std) and the final kurtosis value (kurt), and if the recalculation judgment unit repeats the preset j number of times in the recalculation judgment unit, the j standard deviation values (std_j) that are repeated several times in the recalculation judgment unit The number greater than the preset constant threshold_S is greater than the preset recognition rate (Q %), or the number of j kurtosis values (kurt_j) recalculated by repeating the recalculation judging unit several times is greater than the preset constant threshold_K is greater than the preset recognition rate (Q %), the recalculated j standard deviation values (std_j) are recognized and the largest standard deviation value (std_j) among the recalculated j standard deviation values (std_j) repeated several times is the final standard deviation value (std), and the j recalculated kurtosis values (kurt_j) are recognized and the largest kurt_j value (kurt_j) among the j recalculated kurtosis values (kurt_j) Substituted and confirmed with the final kurtosis value (kurt), the j standard deviation values (std_j) recalculated by the recalculation decision unit repeatedly several times while iterating for a preset j number of times in the recalculation decision unit are The number greater than the preset constant threshold_S is smaller than the preset recognition rate (Q %), and the number of j number of kurtosis values (kurt_j) recalculated repeatedly in the recalculation judgment section above is larger than the preset constant threshold_K is preset. If it is less than one acceptance rate (Q %), the standard deviation value (std_j) and kurt_j value (kurt_j), which were repeated several times and recalculated, are rejected, and both the final standard deviation value (std) and the final kurtosis value (kurt) are set to 0 (zero). ) by substituting and confirming; a final data determining unit for storing data;

The final standard deviation value (std) determined and stored in the final data determination unit is compared with a preset constant threshold_S, and the final kurtosis value determined and stored in the final data determination unit (kurt) and a preset constant threshold_K and size are compared and an insulation state determination unit that compares and determines the insulation state of the power cable.

In the insulation state determination unit, the final standard deviation value (std) determined and stored by the final data determination unit is greater than a preset constant threshold_S, and the final kurtosis value determined and stored by the final data determination unit (kurt) is a preset constant. If it is greater than threshold_K (that is, if std > threshold_S and kurt > threshold_K), it is determined that the insulation state of the power-side terminal of the power cable is defective, and the final standard deviation value (std) determined in the final data determining unit is higher than the preset constant threshold_S If it is large and the final kurtosis value (kurt) determined by the final data determining unit is not greater than a preset constant threshold_K (that is, if std > threshold_S and kurt ≤ threshold_K), the insulation state of the intermediate connection part of the power cable is determined to be defective, and the If the final standard deviation value (std) determined in the final data determining unit is not greater than the preset constant threshold_S, and the final kurtosis value (kurt) determined in the final data determining unit is greater than the preset constant threshold_K (that is, std ≤ threshold_S and If kurt > threshold_K ) It is characterized in that the insulation state of the load-side connection part of the power cable is judged as defective.

In order to achieve the above object, a method for monitoring the insulation state of a power cable of the present invention includes an initialization step of initializing various data and setting the number of repetitions (j) of recalculation to 0 (zero);

A signal detection step of detecting a signal related to the insulation state generated in the power cable to be measured in the detection sensor for detecting a signal related to the insulation state of the power cable;

a filter amplifying digital conversion step of extracting a signal of a preset frequency band from among the signals related to the insulation state detected in the signal monitoring step and amplifying and converting the signal into a digital value;

a standard deviation kurtosis calculation step of calculating and storing the standard deviation (std) and kurtosis (kurt) of the data that reads the digital value converted in the filter amplification digital conversion step a set number of times (n);

If the kurtosis value (kurt_0) calculated in the standard deviation kurtosis calculation step is greater than the preset constant threshold_K (that is, kurt_0 > threshold_K ), as many as j times the preset number of repetitions at a preset waiting time interval to check whether it is noise data. The signal is re-sensed in the signal detection step, the signal re-detected in the filter amplification digital conversion step is amplified and converted into a digital value, and the n number of received data read by the filter amplification digital conversion unit in the standard deviation kurtosis calculation step is obtained. a recalculation determination step of repeatedly performing the process of recalculating the standard deviation value (std_j) and the kurtosis value (kurt_j);

If the recalculation determination step is not repeated as many times as preset j times, the kurtosis value (kurt_0) calculated in the standard deviation kurtosis calculation step is determined as the final kurtosis value (kurt), and in the recalculation determination step, the If it is repeated as many times as set j times, the number of j number of kurtosis values (kurt_j) recalculated repeatedly in the recalculation judgment step (j times) is larger than the preset constant threshold_K is higher than the preset recognition rate (Q %). If there are many, the j recalculated kurtosis values (kurt_j) are recognized, and the largest kurt_j value (kurt_j) among the j recalculated kurtosis values (kurt_j) repeated several times (j times) is replaced and confirmed with the final kurtosis value (kurt). And, if the number of j number of kurtosis values (kurt_j), which is repeated several times (j times) and recalculated in the recalculation judgment step, is greater than the preset constant threshold_K is less than the preset recognition rate (Q %), the recalculation is performed The j number of kurtosis values (kurt_j) are rejected and the final kurtosis value (kurt) is substituted and confirmed with 0 (zero), and the final standard deviation value (std) is the standard deviation above regardless of whether the recalculation judgment step is repeatedly performed. a final data determination step of storing data by substituting and determining the standard deviation value (std_0) calculated in the kurtosis calculation step with the final standard deviation value (std);

The final standard deviation value (std) determined and stored in the final data determination step is compared with a preset constant threshold_S, and the final kurtosis value (kurt) determined and stored in the final data determination step and a preset constant threshold_K and size are compared and an insulation state determination step of comparing the insulation state of the power cable.

The method for monitoring the insulation state of a power cable of the present invention for achieving the above object includes a signal detection step of detecting a signal related to the insulation state occurring in the power cable to be measured in a detection sensor for detecting a signal related to the insulation state of the power cable; ;

a filter amplifying digital conversion step of extracting a signal of a preset frequency band from among the signals related to the insulation state detected in the signal monitoring step and amplifying and converting the signal into a digital value;

a standard deviation kurtosis calculation step of calculating and storing the standard deviation (std) and kurtosis (kurt) of the data that reads the digital value converted in the filter amplification digital conversion step a set number of times (n);

The kurtosis value (kurt_0) calculated in the step of calculating the standard deviation kurtosis is greater than the preset constant threshold_K (that is, kurt_0 > threshold_K ), or the standard deviation value (std_0) calculated in the step of calculating the standard deviation kurtosis is a preset constant threshold_S If greater than (that is, std_0 > threshold_S ), the signal is re-detected in the signal detection step as many as j times a preset number of repetitions at a preset waiting time interval to check whether it is noise-like data, and re-detected in the filter amplification digital transformation step The signal is amplified and converted into a digital value, and the standard deviation value (std) and kurtosis value (kurt) of n (80 in the embodiment of the present invention) received data read by the filter amplification digital conversion unit in the standard deviation kurtosis calculation step ) a recalculation determination step of repeatedly performing the process of recalculating;

If the recalculation judgment step is not repeated as many times as preset j times, the standard deviation value (std_0) and the kurtosis value (kurt_0) calculated in the standard deviation kurtosis calculation step are combined with the final standard deviation value (std) and the final kurtosis value. (kurt), and if repeated as many times as j preset in the recalculation determination step, the number of times the j number of kurtosis values (kurt_j) that are recalculated repeatedly in the recalculation determination step are greater than the preset constant threshold_K is greater than the preset recognition rate (Q %), or the number of j standard deviation values (std_j) recalculated repeatedly in the recalculation judgment step above is greater than the preset constant threshold_S If it is higher than the acceptance rate (Q %), the j recalculated kurtosis values (kurt_j) are recognized and the largest kurtosis value (kurt_j) among the j recalculated kurtosis values (kurt_j) repeated a number of times (j times) is selected as the final kurtosis The largest standard deviation value ( std_j) is substituted and confirmed with the final standard deviation value (std), and the j kurtosis values ( The number of kurt_j) greater than the preset constant threshold_K is smaller than the preset recognition rate (Q %), and even though the recalculation judgment step has been repeated as many times as the preset j times in the recalculation judgment step, it is repeated several times in the recalculation judgment step. If the number of recalculated j standard deviation values (std_j) greater than the preset constant threshold_S is less than the preset acceptance rate (Q %), the j recalculated kurtosis values (kurt_j) and a final data determination step of rejecting j standard deviation values (std_j), replacing and confirming both the final kurtosis value (kurt) and the final standard deviation value with 0 (zero), and storing the data;

The final standard deviation value (std) determined and stored in the final data determination step is compared with a preset constant threshold_S, and the final kurtosis value (kurt) determined and stored in the final data determination step and a preset constant threshold_K and size are compared and an insulation state determination step of comparing the insulation state of the power cable.

In the insulation state determination step, the final standard deviation value (std) determined and stored in the final data determination step is compared with a preset constant threshold_S, and the final kurtosis value determined and stored in the final data determination step (kurt) is compared. and a first comparison step of comparing the magnitude of a preset constant threshold_K;

As a result of the first comparison step, when the final standard deviation value (std) is greater than the constant threshold_S and the final kurtosis value (kurt) is greater than the constant threshold_K (that is, if std > threshold_S and kurt > threshold_K), it is said that the insulation state of the power-side terminal is poor. a power-side terminal failure determination step of judging;

As a result of the first comparison step, if the final standard deviation value (std) is not greater than the constant threshold_S or the final kurtosis value (kurt) is not greater than the constant threshold_S (that is, if std ≤ threshold_S or kurt ≤ threshold_K), the final data determining step a second comparison step of comparing the final standard deviation value (std) determined in , and the size of a preset constant threshold_S;

If the final standard deviation value (std) is greater than the constant threshold_S as a result of the second comparison step (ie, if std > threshold_S), an intermediate connection defect determination step of judging that the insulation state of the intermediate connection part is poor;

As a result of the second comparison step, if the final standard deviation value (std) is not greater than the constant threshold_S (that is, if std ≤ threshold_S), the final kurtosis value (kurt) determined in the final data determination step determines the size of the preset constant threshold_S a third comparison step of comparing;

When the final kurtosis value (kurt) is greater than the constant threshold_K (that is, if kurt > threshold_K) as a result of the comparison in the third comparison step, the load-side terminal defective determining step of determining that the insulation state of the load-side terminal is poor;

If the final kurtosis value (kurt) is not greater than the constant threshold_K as a result of the comparison in the third comparison step (that is, if kurt ≤ threshold_K ), the insulation state good judgment step of determining that the insulation state is good; characterized.

On the other hand, the present invention for achieving the above object provides a computer-readable recording medium containing a computer program for performing the method for monitoring the insulation state of the power cable.

According to the present invention, in monitoring the insulation state of the power cable, the standard deviation value (std) and the kurtosis value (kurt) are calculated from the data detected from the detection sensor that detects the signal related to the insulation state, and the calculated kurtosis value ( kurt) is greater than the preset constant, it is repeatedly re-detected and re-calculated several times to determine whether the calculated standard deviation or kurtosis value is large because of noise from the field and power cable installation environment, and data containing noise is rejected. That is, by removing the noise data, the power cable system accurately determines whether the insulation state of the terminal part on the power supply side is bad, whether the insulation state of the intermediate connection part is poor, whether the insulation state of the terminal part on the load side is poor, and the insulation state is good. There is a judging effect.

Figure 1 schematically shows a system of a power cable for explaining the insulation state monitoring method of the power cable of the present invention and the related art.
Figure 2 shows a schematic configuration diagram of an embodiment of the device for monitoring the insulation state of the power cable of the present invention.
3 is a schematic configuration diagram of an embodiment of an operation unit, which is a main part of the insulation state monitoring device for a power cable of the present invention.
Figure 4 is a schematic flowchart for explaining an embodiment of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.
5 is a detailed flowchart for explaining the first embodiment of FIG. 4 which is an embodiment of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.
6 is a detailed flowchart for explaining the second embodiment of FIG. 4 which is an embodiment of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.
7 is a flowchart for explaining the first embodiment of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.
8 is an example of data when the insulation state of the load-side terminal is poor in the conventional method to explain the present invention, but in the present invention, it is determined that noise has occurred, and in the recalculation decision unit 60 80 data that is converted by the filter amplification digital conversion unit 20 before re-detection j times (5 times in this embodiment) and read by the calculation unit 200 by setting the set number to 80 is shown graphically.
9 is a kurtosis of the results of re-sensing and re-calculating j times (five times in this embodiment) in the recalculation determination unit 60 to check whether the data of FIG. 8 has noise in order to explain the present invention. The value (kurt_j) is data that is smaller than a preset value (threshold_K, 5.0 in this embodiment) for all five times, is converted by the filter amplification digital conversion unit 20, and sets the set number to 80, and the operation unit 200 It is a graph showing 80 data read from .
10 is an example of data when the insulation state of the power-side terminal in the power cable system is poor in order to explain the present invention. ) is a graph of 80 data read from
11 is an example of data when the insulation state of the intermediate connection part in the power cable system is poor in order to explain the present invention. ) is a graph of 80 data read from
12 is a flowchart for explaining a second embodiment of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.
13 is a flowchart illustrating a third embodiment of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.
14 is a table showing the first embodiment and the third embodiment of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention to help understanding.
15 is a table showing a second embodiment of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention to help understanding.
Figure 16 is a table showing the first embodiment of the final data confirmation flow of the power cable insulation state monitoring apparatus and monitoring method of the present invention to help understanding.
17 is a table showing the second embodiment of the final data confirmation flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention to help understanding.
18 is a flowchart illustrating a first embodiment of the final data confirmation flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.
19 is a flowchart for explaining a second embodiment of the final data final flow of the power cable insulation state monitoring apparatus and monitoring method of the present invention.

Hereinafter, an insulation state monitoring apparatus and monitoring method of a power cable of the present invention will be described with reference to the accompanying drawings.

The terms and preset values used in the description in the present invention are only used for the purpose of describing the present invention and are not used to limit the meaning or scope of the present invention described in the claims, and also described in the drawings In some cases, parts not related to kurtosis value are omitted. And in the part marked as kurt_j in the kurtosis value or std_j in the standard deviation value, j means the number of repetitions j, 0 is the calculated value when j = 0, and 1 is j=1, that is, the first re-detection and re-calculation values, and 2, 3, 4, 5 mean the second, third, fourth, fifth re-detection and re-calculation values.

Figure 2 shows a schematic configuration diagram of an embodiment of the device for monitoring the insulation state of a power cable of the present invention, Figure 3 is a schematic diagram of an embodiment of an operation unit which is a main part of the device for monitoring the insulation state of a power cable of the present invention 4 and 5 are schematic overall flowcharts for explaining an embodiment of an insulation state monitoring apparatus and monitoring method of a power cable of the present invention, and FIG. A flowchart is shown in detail to explain the first embodiment, FIG. 6 is a flowchart in detail to explain the second embodiment of FIG. 4, and FIGS. 16 and 17 and 18 and 19 are It is a table and flow arranged to explain the final data determination method in an embodiment of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention, and FIGS. 2 and 3 and 4 and 5 and 6 are already published. Although it may be schematically similar to the conventional techniques, in the present invention, the standard deviation value (std) and the kurtosis value (kurt) are calculated, and the standard deviation value (std_0) or the kurtosis value (kurt_0) calculated above is previously calculated. As a result of comparing the set constant value with each other, if it is greater than the preset constant value (threshold_S or threshold_K), re-detection and standard deviation value (std) and kurtosis value (kurt) for each preset waiting time as much as the preset constant repetition number (j) ), the number of times greater than the preset threshold_S or trheshold_K among the kurt_j of the recalculated number of iterations (j) or the recalculated standard deviation (std,j) is the preset acceptance rate ( Q %), the largest value among the standard deviation values recalculated j times (std_j) or kurtosis values (std_j) recalculated j times is selected as the final standard deviation (std) or final kurtosis (kurt) value. , and the number greater than the preset threshold_S or threshold_K among the kurt_j values (kurt_j) of the recalculated number of repetitions (j) or the recalculated standard deviation values (std, j) is the preset recognition rate ( Q %), the standard deviation calculated above The difference value (std_0) or 0 (zer0) is determined as the final standard deviation value (std) or the final kurtosis value (kurt), and the final determined final standard deviation value (std) is compared with a preset constant value (threshold_S) and the final kurtosis value (kurt) value is compared with the preset constant value (threshold_K) to determine whether the insulation state of the terminal part on the power supply side is poor, whether the insulation state of the intermediate connection part is poor, or the load side insulation state is poor, Otherwise, an advanced function of accurately determining whether the insulation state is good is added, and this advanced additional function will be understood by understanding the contents described below, and detailed description of the previously disclosed prior art is omitted.

7 is a schematic flowchart for explaining a first embodiment of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.

8 is an example of data when the insulation state of the load-side terminal part is poor in the conventional method in the power cable system to explain the present invention, but j times (in this embodiment, the recalculation judgment part 60) 5 times) before repeated re-detection (j = 0), converted by the filter amplification digital conversion unit 20, setting the set number to 80, and showing 80 received data read by the operation unit 200 as a graph, For 80 pieces of received data, the calculation result as a standard deviation value (std_0) is 0.2, and as a kurtosis value (kurt_0), the calculation result is 10.0.

9 shows that the kurt_0 (= 10.0) value in the std_0=0.2 and kurt_0=10.0 values of FIG. 8 is larger than a preset threshold_k (5.0 in the embodiment of the present invention). The calculation and determination unit 60 repeatedly re-detects j times (5 times in this embodiment), is converted in the filter amplification digital conversion unit 20, and sets the set number to 80 and reads 80 As a graph of the data, it was recalculated as kurt_1=0.2, std_1=0.1 when j=1, which was recalculated for the first iteration, and kurt_2=0.3, std-2=0.1 for j=2, which was recalculated for the second iteration. and recalculated as kurt_3=0.6, std_3=0.1 when j=3 was recalculated the third iteration When j = 5, which was recalculated for the fifth iteration, it represents recalculation as kurt_5 = 0.5 and std_5 = 0.1.

10 is an example of data when the insulation state of the power-side terminal in the power cable system is poor in order to explain the present invention. ) is a graph of 80 received data read from, and for 80 received data, the calculation result is std_0=231.3 as the standard deviation value (std), and the calculation result is kurt_0=10.0 as the kurtosis value (kurt).

11 is an example of data when the insulation state of the intermediate connection part in the power cable system is poor in order to explain the present invention. ) is a graph showing the 80 received data read from ). For 80 received data, the calculation result is std_0=18.7 as the standard deviation value (std), and the calculation result is kurt_0= -1.08 as the kurtosis value (kurt).

12 is a schematic flowchart for explaining a second embodiment of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.

13 is a schematic flowchart for explaining a third embodiment of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.

14 is a schematic table for helping understanding the first and third embodiments of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.

15 is a schematic table to help understand the second embodiment of the insulation determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention.

16 is a table showing the first embodiment of the final data confirmation flow of the power cable insulation state monitoring device and monitoring method of the present invention as a table to help understand the advanced function in the present invention, and this advanced addition The function will be understood by understanding the content described below.

17 is a table showing the second embodiment of the final data confirmation flow of the insulation state monitoring device and monitoring method of the power cable of the present invention. The function will be understood by understanding the content described below.

18 is a flowchart for explaining the first embodiment of the final data final flow of the power cable insulation state monitoring apparatus and monitoring method of the present invention, and the advanced functions are added in the present invention, and this advanced Additional functions can be understood by understanding what is described below.

19 is a flowchart for explaining a second embodiment of the final data final flow of the insulation state monitoring device and monitoring method of the power cable of the present invention, an advanced function is added in the present invention, and this advanced The additional functions will be known by understanding the contents described below.

2 and 3, the insulation state monitoring device of the power cable of the present invention includes a detection sensor unit 15 for detecting a signal related to the insulation state in the power cable 10 to be monitored; a filter amplification digital conversion unit 20 for extracting, amplifying, and converting a signal of a preset frequency band among the signals detected by the detection sensor unit 15 into a digital value; n received data read from the filter amplification digital conversion unit 20 (in the embodiment of the present invention, the value of n is set to 80, but this value is not limited.) and various settings such as threshold_S and threshold_K values a storage unit 100 for storing data, received data, and calculation results; a standard deviation calculation unit 50 for calculating the standard deviation value (std) of the n pieces of received data read from the filter amplification digital conversion unit 20; a kurtosis calculation unit 55 for calculating the kurtosis value (kurt) of the n pieces of received data read from the filter amplification digital conversion unit 20; The kurtosis value kurt_0 calculated by the kurtosis calculator 55 is greater than or greater than a preset constant threshold_K (the threshold_K value is set to 5.0 in the embodiment of the present invention, but this value is not limited) (that is, kurt_0 > threshold_K ) or the standard deviation value (std_0) calculated by the standard deviation calculator 50 is a preset constant threshold_S (in the embodiment of the present invention, the threshold_S value is set to 10.0, but this value is not limited thereto) .) is greater than (that is, std_0 > threshold_S ), a preset waiting time (in the embodiment of the present invention, it is set to 1 hour, but this value is not limited) to check whether it is noise data. Repeat preset at an interval The number of times j times (in the embodiment of the present invention, the j value is set to 5, but this value is not limited.) Re-sensing the signal in the detection sensor unit 15, the filter amplification digital conversion unit ( 20) amplifies and converts the re-sensed signal into a digital value, and the standard deviation calculator 50 and the kurtosis calculator 55 read the standard deviation of n received data from the filter amplification digital converter 20 in the standard deviation calculator 50 and the kurtosis calculator 55 a recalculation determination unit 60 that repeats the process of recalculating the value (std_j) and the kurtosis value (kurt_j);

16 and 18, if the recalculation determination unit 60 does not repeat the preset j number of times, the standard deviation value (std_0) calculated by the standard deviation calculation unit 50 and the kurtosis If the kurtosis value (kurt_0) calculated by the calculation unit 55 is determined as the final standard deviation value (std) and the final kurtosis value (kurt), and the recalculation determination unit 60 repeats the predetermined number of j times, The number of the kurtosis value (kurt_j) recalculated by repeating the recalculation determination unit 60 several times is greater than the preset constant threshold_K is set as the preset recognition rate (Q%, in the embodiment of the present invention, 60%) However, this value is not limited.), the recalculated kurtosis value (kurt_j) is recognized, and the largest kurtosis value (kurt_j) among the recalculated kurtosis values (kurt_j) is the final kurt value (kurt) , and the recalculation determination unit 60 repeats the recalculation a number of times when the recalculation determination unit 60 repeats the predetermined number of j times. If the larger number is less than the pre-set acceptance rate (Q %), the kurt_j value (kurt_j) that is repeated several times and recalculated is rejected and the final kurtosis value (kurt) is replaced and confirmed with 0 (zero), and the final standard deviation The value std is determined as the standard deviation value std_0 calculated by the standard deviation calculating unit 50; or, as shown in FIGS. 16 and 18, in the recalculation determining unit 60 in advance If it is not repeated for the set j number of times, the standard deviation value (std_0) calculated by the standard deviation calculator 50 and the kurtosis value (kurt_0) calculated by the kurtosis calculator 55 are converted to the final standard deviation value (std) and the final kurtosis value (kurt), and if the recalculation determination unit 60 repeats a preset j number of times, the recalculation determination unit 60 repeatedly recalculates the kurtosis value (kurt_j) The number greater than this preset constant threshold_K is higher than the preset recognition rate (Q %). If the number of standard deviation values (std_j) recalculated repeatedly by the recalculation determination unit 60 is greater than the preset constant threshold_S is greater than the preset recognition rate (Q %), the recalculated kurtosis value (kurt_j) and standard deviation (std_j) are recognized and repeated several times and the largest kurt_j among the recalculated values (kurt_j) is replaced and confirmed with the final kurtosis value (kurt). The largest standard deviation value (std_j) among the calculated standard deviation values (std_j) is substituted and confirmed with the final standard deviation value (std), and the recalculation determination unit 60 repeats the preset j number of times. The number of the kurtosis value (kurt_j), which is repeated several times and recalculated by the recalculation determination unit (60) of If the number of recalculated standard deviation (std_j) is smaller than the preset accreditation rate (Q %), the standard deviation value (std_j) repeated several times is smaller than the preset accreditation rate (Q %). All the deviation values (std_j) are rejected and the final kurtosis value (kurt) and the final standard deviation value (std) are both replaced and confirmed with 0 (zero), and the final standard deviation value (std) is the standard deviation calculator ( 50) a final data determining unit 70 for storing data by replacing and confirming the standard deviation value (std_0) calculated in the above;

The final standard deviation value (std) stored in the final data determiner 70 is compared with is smaller than a preset constant threshold_S, and the final kurtosis value (kurt) stored in the final data determiner 70 is a preset constant threshold_K Compare the larger and smaller values to determine whether the insulation state of the terminal part of the power cable is poor, the insulation state of the intermediate connection part of the power cable is poor, the insulation state of the load-side connection part of the power cable is poor, or the insulation state is good Insulation state determination unit 90 having a function to; is composed of.

In addition, the insulation state monitoring apparatus of the power cable of the present invention may be configured by the arithmetic unit 200 including the configuration of the standard deviation calculating unit 50 to the insulation state determining unit 90 described above.

In addition, the insulation state monitoring apparatus of the power cable of the present invention visually displays the received data or the calculated values determined by the final data determining unit 70 at all times, or the value determined by the insulation state determining unit 90 . may further include a display unit 110 for visually displaying the may include In addition, it may further include a remote communication means for communicating with an administrator computer that can be remotely checked or controlled using the insulation state monitoring device of the power cable and wired/wireless communication means.

The detection sensor unit 15 may be configured as a configuration including a coupling capacitor, a CT-type sensor, a current sensor, or a shunt-type sensor. The detection sensor unit 15 may also be installed on the ground wire of the power cable to detect a signal related to the insulation state.

4 and 5 are flowcharts for explaining the first embodiment of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention. As shown in FIG. 4, the method for monitoring the insulation state of the power cable of the present invention includes an initialization step (S600) of initializing and recalculating various data and setting the number of repetitions (j) to 0 (zero); a signal detection step (S605) of detecting a signal related to the insulation state of the power cable in a detection sensor for detecting a signal related to the insulation state of the power cable; a filter amplifying digital conversion step (S610) of extracting a signal in a preset frequency band from the signals detected in the signal detecting step (S605) and amplifying and outputting the signal as a digital value; The digital value converted in the filter amplification digital conversion step (S610) is set a preset number of times (n, in the embodiment of the present invention, 80 is used, but 80 or more or 80 or less is used. a received data storage step (S620) of reading and storing the received data read as much as there may be); The standard deviation of calculating the standard deviation value (std) and the kurtosis value (kurt) of the n received data stored in the received data storage step (S620) or the data converted in the filter amplification digital conversion step (S610) is read. a kurtosis calculation step (S630); If the kurt_0 calculated in the standard deviation kurtosis calculation step S630 is greater than a preset constant threshold_K (in the embodiment of the present invention, a value of 5.0 is used, but this value is not limited). The preset number of repetitions (j, although j = 5 times is used in the embodiment of the present invention, but this value is not limited) as much as a preset waiting time (in the embodiment of the present invention, a value of 1 hour is used, This value is not limited.) After waiting, the signal is re-sensed in the signal detecting step (S605), and then converted to a digital value in the filter amplifying digital conversion step (S610), and then the reception The value is stored in the data storage step (S620), and then the standard deviation value (std) recalculated in the standard deviation kurtosis calculation step (S630) is stored as a std_j value, and in the standard deviation kurtosis calculation step (S630) The recalculated kurtosis value (kurt) is stored as the kurt_j value, and if the kurtosis value (kurt_0) calculated in the standard deviation kurtosis calculation step (S630) is less than the preset constant threshold_K, the preset number of repetitions (j) is executed a recalculation decision step (S640) not to be performed; As shown in FIGS. 16 and 18, the kurtosis calculated in the standard deviation kurtosis calculation step (S630) when the preset number of repetitions (j) is not executed in the recalculation step (S640), that is, when j = 0. The value (kurt_0) and the standard deviation value (std_0) are determined as the final kurtosis value (kurt) and the final standard deviation value (std), and the number of repetitions (j) preset in the recalculation determination step (S640) is executed. That is, when j = 5, the signal is sensed in the standard signal detecting step (S605), then converted to a digital value in the filter amplifying digital conversion step (S610), and then in the receiving data storage step (S620). After storing the received data, the number of data in which the size of the kurt_1 to kurt_5 recalculated in the standard deviation kurtosis calculation step (S630) is greater than the preset threshold_K is a preset recognition rate ( Q%), the largest value among the recalculated kurtosis values (kurt_1) to kurt_5 values is substituted and confirmed with the final kurtosis value (kurt), and the standard deviation kurtosis calculation step (S630) is recalculated. If the number of data whose size of kurt_1 to kurt_5 is greater than the preset threshold_K is less than the preset recognition rate (Q%), the final kurtosis value (kurt) is replaced with 0 (zero) and confirmed Oh, the final standard deviation value (std) is a final data determination step (S650) of determining and storing the standard deviation value (std_0) calculated in the standard deviation kurtosis calculation step (S630) when j = 0; Whether the final standard deviation value (std) determined in the final data determination step (S650) is greater than a preset constant threshold_S (in the embodiment of the present invention, a value of 10.0 is used, but this value is not limited) The final kurtosis value (kurt) determined in the final data determination step (S650) is smaller than the preset constant threshold_K (in the embodiment of the present invention, a value of 5.0 is used, but this value is not limited). Insulation state determination step (S660) for determining the insulation state of the insulation state of the power cable by comparing whether it is large or small;

4 and 6 are flowcharts for explaining a second embodiment of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention. As shown in FIG. 5, the method for monitoring the insulation state of a power cable of the present invention includes an initialization step (S600) of initializing and recalculating various data and setting the number of repetitions (j) to 0 (zero); a signal detection step (S605) of detecting a signal related to the insulation state of the power cable in a detection sensor for detecting a signal related to the insulation state of the power cable; a filter amplifying digital conversion step (S610) of extracting a signal in a preset frequency band from the signals detected in the signal detecting step (S605) and amplifying and outputting the signal as a digital value; a receiving data storing step (S620) of reading and storing the received data that has been read as many times as a preset number of times (n) the digital values converted in the filter amplifying digital conversion step (S610); The standard deviation of calculating the standard deviation value (std) and the kurtosis value (kurt) of the n received data stored in the received data storage step (S620) or the data converted in the filter amplification digital conversion step (S610) is read. a kurtosis calculation step (S630); The kurtosis value (kurt_0) calculated in the standard deviation kurtosis calculation step (S630) is greater than the preset constant threshold_K, or the standard deviation value (std_0) calculated in the standard deviation kurtosis calculation step (S630) is a preset constant If it is greater than threshold_S (a value of 10.0 is used in the embodiment of the present invention, but this value is not limited), the signal detection step (S605) ), the signal is re-sensed, and then converted to a digital value in the filter amplification digital conversion step (S610), then the received data storage step (S620) stores the value, and then the standard deviation kurtosis calculation step The standard deviation value (std) recalculated in (S630) is stored as the std_j value, and the kurtosis value (kurt) recalculated in the standard deviation kurtosis calculation step (S630) is stored as the kurt_j value, and the standard deviation kurtosis If the kurtosis value kurt_0 calculated in the calculation step S630 is less than the preset constant threshold_K and the standard deviation value std_0 calculated in the standard deviation kurtosis calculation step S630 is smaller than the preset constant threshold_S, the preset constant threshold_S a recalculation determination step (S640) of not executing the number of repetitions (j); As shown in FIGS. 17 and 19, when the preset number of repetitions j is not executed in the recalculation step S640, that is, when j = 0, the kurtosis calculated in the standard deviation kurtosis calculation step S630. The value (kurt_0) and the standard deviation value (std_0) are determined as the final kurtosis value (kurt) and the final standard deviation value (std), and the number of repetitions (j) preset in the recalculation determination step (S640) is executed. That is, when j = 5, the signal is sensed in the standard signal detecting step (S605), then converted to a digital value in the filter amplifying digital conversion step (S610), and then in the receiving data storage step (S620). After storing the received data, the number of data whose kurt_1 to kurt_5 recalculated in the standard deviation kurtosis calculation step (S630) is greater than the preset threshold_K is a preset recognition rate (Q%) ) or the standard deviation value (std_1) to the standard deviation value (std_5) recalculated in the standard deviation kurtosis calculation step (S630) is greater than the preset threshold_S, the preset recognition rate (Q%) ), the largest value among the recalculated kurtosis values (kurt_1) - kurt_5 (kurt_5) is replaced and confirmed with the final kurtosis value (kurt), and the recalculated standard deviation (std_1) - standard deviation (std_5) The largest value is substituted and confirmed with the final standard deviation value, and the number of data in which the recalculated kurt_1 to kurt_5 in the standard deviation kurtosis calculation step (S630) is greater than the preset threshold_K The number of data smaller than the preset recognition rate (Q%) and the standard deviation value (std_1) to the standard deviation value (std_5) recalculated in the standard deviation kurtosis calculation step (S630) is larger than the preset threshold_S in advance If it is less than the set recognition rate (Q%), the final kurtosis value (kurt) is replaced with 0 (zero), and the final standard deviation value (std) is replaced and confirmed with 0 (zero) and stored. (S650) and; It compares whether the final standard deviation value (std) determined in the final data determination step (S650) is greater than or less than a preset constant threshold_S, and the final kurtosis value (kurt) determined in the final data determination step (S650) is set in advance. Insulation state determination step (S660) for determining the insulation state of the insulation state of the power cable by comparing whether it is greater than or less than the set constant threshold_K;

7 is a flowchart for explaining the first embodiment of the insulation state determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention. As shown in FIG. 7 in detail in the insulation state determination step S660, the standard deviation value std finally determined in the final data determination step S650 and the preset constant threshold_S are compared and the above a first comparison step (S661) of comparing the kurtosis value (kurt) finally determined in the final data determination step (S650) with the size of a preset constant threshold_K; As a result of the first comparison step (S661), if the standard deviation value (std) is greater than the constant threshold_S and the kurtosis value (kurt) is greater than the constant threshold_S (that is, if std > threshold_S and kurt > threshold_K), the insulation state of the terminal on the power supply side is poor a power supply-side terminal failure determination step (S665); If the standard deviation value (std) of the result of the first comparison step (S661) is not greater than the constant threshold_S or the kurtosis value (kurt) is not greater than the constant threshold_K (that is, if std ≤ threshold_S or kurt ≤ threshold_K), the final data is determined a second comparison step (S662) of comparing the final determined standard deviation value (std) in step (S650) with the size of a preset constant threshold_S; If the result of the second comparison step (S662) the standard deviation value (std) is greater than the constant threshold_S (that is, if std > threshold_S), the intermediate connection bad judgment step (S666) of determining that the insulation state of the intermediate connection portion is poor; If the standard deviation value (std) of the result of the second comparison step (S662) is not greater than the constant threshold_S (that is, if std ≤ threshold_S), the kurtosis value (kurt) calculated in the final data determining step (S650) is a preset constant a third comparison step of comparing the sizes of threshold_S (S663); When the kurtosis value (kurt) is greater than the constant threshold_K as a result of the comparison in the third comparison step (S663) (that is, if kurt > threshold_K), the load-side terminal failure determination step (S667) of judging that the insulation state of the load-side terminal part is poor; In the third comparison step (S663), if the kurtosis value (kurt) is not greater than the constant threshold_K (ie, kurt ≤ threshold_K ), it is determined that the insulation state is good (S668).

12 is a flow for explaining a second embodiment of the insulation state determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention. As shown in FIG. 12 in the insulation state determination step (S660), a third comparison step of comparing the final kurtosis value (kurt) determined in the final data determination step (S650) with the size of a preset constant threshold_K ( S663) and; When the final kurtosis value (kurt) is greater than the constant threshold_K as a result of the third comparison step (S663) (that is, if kurt > threshold_K), the terminal insulation state bad judgment step ( S669) and; As a result of the third comparison step (S663), if the final kurtosis value (kurt) is not greater than the constant threshold_K (that is, if kurt ≤ threshold_K), the final standard deviation value (std) determined in the final data determination step (S650) a second comparison step (S662) of comparing the magnitude of the preset constant threshold_S with the threshold_S; As a result of the second comparison step (S662), if the final standard deviation value (std) is greater than the constant threshold_S (that is, if std > threshold_S), the intermediate connection bad judgment step (S666) and ; As a result of the second comparison step (S662), if the final standard deviation value (std) is not greater than the constant threshold_S (that is, if std ≤ threshold_S), the insulation state good judgment step (S668) of determining that the insulation state is good; do.

13 is a flowchart for explaining a third embodiment of the insulation state determination flow of the insulation state monitoring apparatus and monitoring method of the power cable of the present invention, which is a modification of the first embodiment described above, FIG. 7 . As shown in FIG. 13 in detail in the insulation state determination step (S660), a second comparison between the final standard deviation value (std) determined in the final data determination step (S650) and the size of a preset constant threshold_S a comparison step (S662); As a result of the second comparison step (S662), if the final standard deviation value (std) is greater than the constant threshold_S, the first comparison of the final kurtosis value (kurt) determined in the final data determination step (S650) with the size of a preset threshold_K 4 a comparison step (S664) and; As a result of the second comparison step (S662), if the final standard deviation value (std) is not greater than the constant threshold_S (that is, if std ≤ threshold_S), the final kurtosis value (kurt) determined in the final data determination step (S650) and previously a third comparison step of comparing the size of the set threshold_K (S663); When the final kurtosis value (kurt) is greater than a constant threshold_K as a result of the fourth comparison step (S664), a power-side terminal failure determination step (S665) of judging that the insulation state of the power-side terminal unit is poor; As a result of the fourth comparison step (S664), if the final kurtosis value (kurt) is not greater than the constant threshold_K (that is, if kurt ≤ threshold_K), an intermediate connection defect determination step (S666) of determining that the insulation state of the intermediate connection part is poor; When the final kurtosis value is greater than the constant threshold_K as a result of the third comparison step (S663), the load-side terminal failure determination step (S667) of determining that the insulation state of the load-side terminal portion is poor; As a result of the comparison in the third comparison step (S663), if the final kurtosis value (kurt) is not greater than the constant threshold_K (that is, if kurt ≤ threshold_K), the insulation state good judgment step (S668) of determining that the insulation state is good; .

In the received data storage step (S620), 80 received data are stored as shown in Figs. , In the received data storage step (S620), the received data repeated 5 times for explaining in the present invention, which is repeatedly re-sensed and re-calculated, that is, when j = 5, is 80 for each data repeated 5 times in FIG. Each received data is stored, and FIG. 8 shows that the condition kurt_0>threshold_K in FIG. 7 is met, and thus the recalculation is repeated 5 times. Although it is shown in graph form to help understanding of the description, data in HEX (hexadecimal) or DECIMAL (decimal) or BINARY (binary) values are actually stored.

In the standard deviation kurtosis calculation step (S630), the standard deviation value (std) and the kurtosis value (kurt) are calculated using the 80 pieces of data stored in the received data storage step (S620), the data example of FIG. Calculation results in std_0=0.2, the standard deviation value, and kurt_0=10.0, the kurtosis value. In the data of FIG. 9, which is detected and recalculated j=5 times by repeating FIG. 8, the first re-detection and re-calculation results are kurt_1=0.2, std_1=0.1, and the second re-detection and re-calculation results are kurt_2=0.3, std -2=0.1, the third rediscovery and recalculation result is kurt_3=0.6, std_3=0.1, the fourth rediscovery and recalculation result is kurt_4=0.1, std_4=-0.1. The fifth rediscovery and recalculation result is kurt_5=0.5, std_5=0.1 .

In the recalculation determination step (S640), when j = 0, the condition kurt_0 > threshold_K is satisfied or the condition kurt_0 > threshold_K is satisfied by comparing the kurt_0 value calculated in the standard deviation kurtosis calculation step S630 with the size of a preset constant threshold_K. By comparing the standard deviation value (std_0) calculated in the standard deviation kurtosis calculation step (S630) of It stores the recalculated kurt_j and standard deviation (std_j) values through detection, reconversion, re-storage, and re-calculation. In the data example of FIG. 8, kurt_0=10.0 when j=0 , std_0=0.2 and kurt_0=10.0, which is the kurtosis value, is greater than the preset threshold_K=5.0, so an example of data stored and recalculated by repeating j=5 times at regular waiting time intervals is shown in FIG. 9 . In the data example of FIG. 9 , the first rediscovery and recalculation results are kurt_1=0.2, std_1=0.1, the second rediscovery and recalculation results are kurt_2=0.3, std-2=0.1, and the third rediscovery and recalculation results are kurt_3=0.6, std_3=0.1, and the fourth redetection and recalculation results are kurt_4=0.1, std_4=-0.1. The fifth redetection and recalculation results are kurt_5=0.5, std_5=0.1. Therefore, in the data of FIG. 8, the kurtosis value is calculated to be higher than threshold_K and, as shown in FIG. 9, in order to check whether noise data is included, the results of re-sensing and re-calculation are all recalculated to be smaller than threshold_K, so that the data in FIG. 8 is noise. It can be determined that the data contains There will be.

5, 16, and 18 showing the first embodiment of the present invention of the final data determining unit 70 and the final data determining step (S650), the preset number of repetitions in the recalculation board step (S640) When (j) is not executed, that is, when j = 0, the kurtosis value (kurt_0) and the standard deviation value (std_0) calculated in the standard deviation kurtosis calculation step (S630) are combined with the final kurtosis value (kurt) and the final standard deviation value. (std), and when the number of repetitions j preset in the recalculation determination step S640 is executed, that is, when j = 5, the signal is detected in the standard signal detection step S605 and the next In the filter amplification digital conversion step (S610), the digital value is converted to a digital value, and then the received data is stored in the received data storage step (S620), and then the kurtosis value recalculated in the standard deviation kurtosis calculation step (S630). If the number of data (kurt_1) - kurtosis value (kurt_5) is larger than the preset threshold_K is greater than the preset acceptance rate (Q%), the largest value among the recalculated kurtosis values (kurt_1) - kurtosis value (kurt_5) is replaced and confirmed with the final kurtosis value (kurt), and the size of the kurtosis value (kurt_1) to the kurt_5 value (kurt_5) recalculated in the standard deviation kurtosis calculation step S630 is greater than the preset threshold_K. If it is less than the preset recognition rate (Q%), the final kurtosis value (kurt) is replaced with 0 (zero) and confirmed, and when the final standard deviation value (std) is j = 0, the standard deviation kurtosis calculation step (S630) 6 and 17 and Figs. 6 and 17 showing the second embodiment of the present invention in the final data determining unit 70 and the final data determining step (S650) and storing the standard deviation value (std_0) calculated in In 19, when the preset number of iterations j is not executed in the recalculation step S640, that is, when j = 0, the kurtosis value (kurt_0) and the standard deviation value calculated in the standard deviation kurtosis calculation step S630 (std_0) is determined as the final kurtosis value (kurt) and the final standard deviation value (std), and in the recalculation judgment step (S640), in advance When the set repetition number (j) is executed, that is, when j = 5, the signal is detected in the standard signal detection step (S605), and then converted to a digital value in the filter amplification digital conversion step (S610), and then In the received data storage step (S620), the received data is stored, and the size of the kurtosis value (kurt_1) to the kurt_5 value (kurt_5) recalculated in the standard deviation kurtosis calculation step (S630) is larger than the preset threshold_K. The number of data is greater than the preset recognition rate (Q%), or the size of the standard deviation value (std_1) to the standard deviation value (std_5) recalculated in the standard deviation kurtosis calculation step (S630) is a preset threshold_S If the larger number of data is greater than the preset recognition rate (Q%), the largest value among the recalculated kurtosis values (kurt_1) to kurt_5 values is substituted and confirmed with the final kurtosis value (kurt), and the recalculated The largest value among the standard deviation values (std_1) to the standard deviation values (std_5) is substituted and confirmed with the final standard deviation value (std), and the kurtosis value (kurt_1) recalculated in the standard deviation kurtosis calculation step (S630) ~ The number of data whose size of the kurtosis value (kurt_5) is larger than the preset threshold_K is smaller than the preset recognition rate (Q%), and the standard deviation value (std_1) recalculated in the standard deviation kurtosis calculation step (S630) ) to standard deviation (std_5), if the number of data larger than the preset threshold_S is less than the preset acceptance rate (Q%), both the final kurtosis value (kurt) and the final standard deviation value (std) are set to 0 ( zero), the first embodiment of the final data determining unit 70 and the final data determining step (S650) of the present invention will be described in detail with reference to FIGS. 8 and 9 and FIGS. 16 and 18 . 8, when j = 0, kurt_0 = 10.0, std_0 = 0.2, and kurt_0 = 10.0, which is the kurtosis value, is greater than the preset threshold_K = 5.0. In the data example of Fig. 9, the first re-sensing and The recalculation result is kurt_1=0.2, std_1=0.1, the second rediscovery and recalculation results are kurt_2=0.3, std-2=0.1, the third rediscovery and recalculation result is kurt_3=0.6, std_3=0.1, and the fourth The rediscovery and recalculation results are kurt_4=0.1, std_4=-0.1. The fifth rediscovery and recalculation results are kurt_5=0.5, std_5=0.1. When the final data determination method of FIGS. 16 and 18 is applied, among the five recalculated kurt_1 to kurt_5 data, the number greater than threshold_K=5.0 is 0, so the preset recognition rate (Q%, = 60% 3) Since it is smaller than that, the final kurtosis value (kurt) is determined as 0 (zero), and the final standard deviation value (std) is determined as 0.2, which is the std_0 value. Next, the second embodiment of the final data determining unit 70 and the final data determining step (S650) of the present invention will be described in detail with reference to FIGS. 8 and 9 and FIGS. 17 and 19. In FIG. 8, when j = 0 The data of kurt_0=10.0, std_0=0.2 and standard deviation of std_0=0.2 are smaller than the preset threshold_S=10.0, but the kurt_0=10.0 of kurt_0=10.0 is greater than the preset threshold_K=5.0, so j= at regular waiting time intervals In the data example of FIG. 9 that was repeatedly stored and recalculated five times, the first rediscovery and recalculation results are kurt_1=0.2, std_1=0.1, and the second rediscovery and recalculation results are kurt_2=0.3, std-2=0.1 , the third rediscovery and recalculation results are kurt_3=0.6, std_3=0.1, and the fourth rediscovery and recalculation results are kurt_4=0.1, std_4=-0.1. The fifth rediscovery and recalculation result is kurt_5=0.5, std_5=0.1. When the final data determination method of FIGS. 17 and 19 is applied, among the five recalculated kurt_1 to kurt_5 data, the number greater than threshold_K=5.0 is 0, and among the five recalculated standard deviation values std_1 to std_2 data, threshold_d=10.0 Because the large number is 0, it is smaller than the preset acceptance rate (Q%, = 60%, 3), so the final kurtosis value (kurt) is set to 0 (zero), and the final standard deviation value (std) is also 0 ( zero) is confirmed.

In the insulation state determination step (S660), the final standard deviation value (std) determined in the final data determination step (S650) and the size of a preset constant threshold_S are compared, and the final kurtosis value (kurt) and a preset constant threshold_K The insulation state is determined by comparing the size of Because the result of the conditions shown in FIGS. 7 and 13 is std < threshold_S and kurt > threshold_K, it is determined that the load-side terminal insulation state is poor, but in the present invention, j times (5 times) to check whether noise is included ) Repeatedly re-detected, re-received, and re-calculated data displayed in FIG. 9 as a result of confirming the final data in FIGS. 5, 16 and 18, which are the first embodiment of the present invention, the final kurtosis value (kurt) = 0 Since the value is less than threshold_K=5.0 and the standard deviation value (std)=0.2 is smaller than threshold_S=10.0, the result of the conditions shown in FIGS. Thus, it was possible to remove the error in determining data including noise, and as a result of confirming the final data in FIGS. 6, 17, and 19, which are the second embodiment, the final kurtosis value (kurt)=0 is smaller than threshold_K=5.0. Since the standard deviation value (std) = 0 value is less than threshold_S = 10.0, the result of the conditions shown in FIGS. 7, 12, and 13 is std < threshold_S and kurt < threshold_K. Therefore, the insulation state is judged to be good and the data containing noise is determined error could be eliminated.

On the other hand, in the data example of FIG. 10, std_0=231.3, kurt_0=10.0, std_0 > threshol_S, and kurt_0 > threshold_K. Therefore, in the embodiment of the present invention, the re-sensing and re-calculation process is repeated 5 times, and the re-calculation data result The data should be finally determined according to ) is 231.3, and the final kurtosis value (kurt) = 10.0. When the insulation state determination step S660 is described, std > threshold_S, kurt > threshold_K, and in FIGS. 7 and 13, which are examples of insulation determination, It is determined that the insulation state of the power supply-side terminal is poor, and in FIG. 12, it is determined that the insulation state of the terminal is poor, and in the data example of FIG. 11, std_0=18.7, kurt_0=-1.08, and the embodiment of FIGS. Since the kurt_0 value is smaller than the threshold_K value, the kurt_0 value is determined as the final kurt value (kurt), and the std_0 value is also determined as the final standard deviation value (std). In the embodiment of the state determination step (S660) in FIGS. 7, 12, and 13, it is determined that the insulation state of the intermediate connection part is poor.

Here, in the embodiment of the present invention, a preset threshold_S value is used as 10.0, a preset threshold_K value is used as 5.0, a preset repetition number j is set to 5, and a preset waiting time is used. Although it is set to 1 hour and the preset accreditation rate (Q%) is set to 60%, these values are not limited.

The embodiments related to the apparatus and method for monitoring insulation state of a power cable of the present invention described above are only some of the various embodiments of the present invention. The signal related to the insulation state of the power cable of the present invention is monitored, the standard deviation value and the kurtosis value of digital data related to the signal component of the preset frequency band are calculated, and the calculated kurtosis value or standard deviation value is higher than a preset constant When it is large, it is re-detected and re-calculated as many times as the preset number of repetitions to check whether the data contains noise. The value (not described in the present invention, dskgdkT, but there may be embodiments in which values such as average or median values are calculated.) is recognized as final data, and if it is less than a predetermined number of times (Q), iteratively recalculated data As long as it is included in the technical idea of monitoring the insulation state of the power cable by removing noise by determining the final data as 0 (zero) or the first calculated data for disapproval, embodiments other than the above-described embodiments also fall within the protection scope of the present invention. is natural

10: power cable
15: detection sensor unit
20: filter increase digital conversion unit
50: standard deviation calculator
55: kurtosis calculator
60: recalculation judgment unit
70: final data confirmation unit
90: insulation state judgment part
100: storage
110: display unit
120: data input unit
130: alarm output unit
200: arithmetic unit

Claims (7)

a detection sensor unit for detecting a signal related to an insulation state from the power cable;
a filter amplification digital conversion unit extracting a signal of a preset frequency band from the signals detected by the detection sensor unit and amplifying and converting the signal into a digital value;
a standard deviation calculation unit for calculating a standard deviation value (std) of the n pieces of received data read from the filter amplification digital conversion unit;
a kurtosis calculation unit for calculating a kurtosis value (kurt) of the n pieces of received data read from the filter amplification digital conversion unit;
If the kurtosis value (kurt_0) calculated by the kurtosis calculator is greater than a preset constant threshold_K (that is, kurt_0 > threshold_K ), the detection sensor unit as many as j times a preset number of repetitions at a preset waiting time interval to check whether the data is noise-like. standard deviation value (std) of the n received data read by the filter amplification digital conversion unit in the kurtosis calculating unit, re-sensing the signal in and the process of re-calculating the kurtosis value (kurt) is repeated a preset number of times (j times), and if the kurtosis value (kurt_0) calculated by the kurtosis calculator is not greater than the preset constant threshold_K (i.e., kurt_0 ≤ threshold_K) ) a re-calculation determination unit for not repeating the preset number of repetitions by the number of j times;
If the re-calculation determination unit does not repeat the pre-set j number of times, the standard deviation value (std_0) calculated in the standard deviation calculation unit and the kurtosis value (kurt_0) calculated in the kurtosis calculation unit are final standard deviations If the value (std) and the final kurtosis value (kurt) are determined, and the recalculation judgment unit repeats a preset j number of times, the j kurtosis values (kurt_j) that are repeated several times in the recalculation judgment unit If the number greater than this preset constant threshold_K is greater than the preset recognition rate (Q %), the j recalculated kurtosis values (kurt_j) are recognized and the largest kurtosis among the recalculated j kurtosis values (kurt_j) repeated several times. The value (kurt_j) is substituted and confirmed with the final kurtosis value (kurt), and the j kurtosis values recalculated by the recalculation decision unit repeatedly several times while iterating as many times as preset j times in the recalculation decision unit If the number of (kurt_j) greater than the preset constant threshold_K is less than the preset recognition rate (Q %), the final kurtosis value (kurt) is set to 0 (zero) by rejecting the j number of kurtosis values (kurt_j) recalculated repeatedly several times. ), and the final standard deviation value (std) is the standard deviation value (std_0) calculated in the standard deviation calculator a final data determining unit for storing data by replacing and confirming the data;
The final standard deviation value (std) determined and stored in the final data determination unit is compared with a preset constant threshold_S, and the final kurtosis value determined and stored in the final data determination unit (kurt) and a preset constant threshold_K and size are compared Insulation state monitoring device of a power cable comprising a; an insulation state determination unit to determine the insulation state of the power cable by comparison.
a detection sensor unit for detecting a signal related to an insulation state from the power cable;
a filter amplification digital conversion unit extracting a signal of a preset frequency band from the signals detected by the detection sensor unit and amplifying and converting the signal into a digital value;
a standard deviation calculation unit for calculating a standard deviation value (std) of the n pieces of received data read from the filter amplification digital conversion unit;
a kurtosis calculation unit for calculating a kurtosis value (kurt) of the n pieces of received data read from the filter amplification digital conversion unit;
If the kurtosis value (kurt_0) calculated by the kurtosis calculator is greater than a preset constant threshold_K (that is, kurt_0 > threshold_K ) or the standard deviation value (std_0) calculated by the standard deviation calculator is greater than the preset constant threshold_S (i.e. std_0 > threshold_S ) Re-sensing the signal in the detection sensor unit as many as j times a preset number of repetitions at a preset waiting time interval to check whether it is noise data, and amplifying the signal re-detected by the filter amplification digital converter and Converting to a digital value, and repeating the process of recalculating the standard deviation value (std) and kurtosis value (kurt) of the n received data read from the filter amplification digital conversion unit in the kurtosis calculator by the number of times (j times) , if the kurtosis value (kurt_0) calculated by the kurtosis calculator is not greater than the preset constant threshold_K (that is, kurt_0 ≤ threshold_K ) and the standard deviation value (std_0) calculated by the standard deviation calculator is not greater than the preset constant threshold_S ( That is, std_0 ≤ threshold_S ) a re-calculation determining unit for not repeating as many times as the preset number of repetitions j;
If the re-calculation determination unit does not repeat the preset j number of times, the standard deviation value (std_0) calculated in the standard deviation calculation unit and the kurtosis value (kurt_0) calculated in the kurtosis calculation unit are the final standard deviation value. (std) and the final kurtosis value (kurt), and if the recalculation judgment unit repeats the preset j number of times in the recalculation judgment unit, the j standard deviation values (std_j) that are repeated several times in the recalculation judgment unit The number greater than the preset constant threshold_S is greater than the preset recognition rate (Q %), or the number of j kurtosis values (kurt_j) recalculated by repeating the recalculation judging unit several times is greater than the preset constant threshold_K is greater than the preset recognition rate (Q %), the recalculated j standard deviation values (std_j) are recognized and the largest standard deviation value (std_j) among the recalculated j standard deviation values (std_j) repeated several times is the final standard deviation value (std), and the j recalculated kurtosis values (kurt_j) are recognized and the largest kurt_j value (kurt_j) among the j recalculated kurtosis values (kurt_j) Substituted and confirmed with the final kurtosis value (kurt), the j standard deviation values (std_j) recalculated by the recalculation decision unit repeatedly several times while iterating for a preset j number of times in the recalculation decision unit are The number greater than the preset constant threshold_S is smaller than the preset recognition rate (Q %), and the number of j number of kurtosis values (kurt_j) recalculated repeatedly in the recalculation judgment section above is larger than the preset constant threshold_K is preset. If it is less than one acceptance rate (Q %), the standard deviation value (std_j) and kurt_j value (kurt_j), which were repeated several times and recalculated, are rejected, and both the final standard deviation value (std) and the final kurtosis value (kurt) are set to 0 (zero). ) by substituting and confirming; a final data determining unit for storing data;
The final standard deviation value (std) determined and stored in the final data determination unit is compared with a preset constant threshold_S, and the final kurtosis value determined and stored in the final data determination unit (kurt) and a preset constant threshold_K and size are compared Insulation state monitoring device of a power cable comprising a; an insulation state determination unit to determine the insulation state of the power cable by comparison. an initialization step of initializing and recalculating various data and setting the number of repetitions (j) to 0 (zero);
A signal detection step of detecting a signal related to the insulation state generated in the power cable to be measured in the detection sensor for detecting a signal related to the insulation state of the power cable;
a filter amplifying digital conversion step of extracting a signal of a preset frequency band from among the signals related to the insulation state detected in the signal monitoring step and amplifying and converting the signal into a digital value;
a standard deviation kurtosis calculation step of calculating and storing the standard deviation (std) and kurtosis (kurt) of the data that reads the digital value converted in the filter amplification digital conversion step a set number of times (n);
If the kurtosis value (kurt_0) calculated in the standard deviation kurtosis calculation step is greater than the preset constant threshold_K (that is, kurt_0 > threshold_K ), as many as j times the preset number of repetitions at a preset waiting time interval to check whether it is noise data. The signal is re-sensed in the signal detection step, the signal re-detected in the filter amplification digital conversion step is amplified and converted into a digital value, and the n number of received data read by the filter amplification digital conversion unit in the standard deviation kurtosis calculation step is obtained. a recalculation determination step of repeatedly performing the process of recalculating the standard deviation value (std_j) and the kurtosis value (kurt_j);
If the recalculation determination step is not repeated as many times as preset j times, the kurtosis value (kurt_0) calculated in the standard deviation kurtosis calculation step is determined as the final kurtosis value (kurt), and in the recalculation determination step, the If it is repeated as many times as set j times, the number of j number of kurtosis values (kurt_j) recalculated repeatedly in the recalculation judgment step (j times) is larger than the preset constant threshold_K is higher than the preset recognition rate (Q %). If there are many, the j recalculated kurtosis values (kurt_j) are recognized, and the largest kurt_j value (kurt_j) among the j recalculated kurtosis values (kurt_j) repeated several times (j times) is replaced and confirmed with the final kurtosis value (kurt). And, if the number of j number of kurtosis values (kurt_j), which is repeated several times (j times) and recalculated in the recalculation judgment step, is greater than the preset constant threshold_K is less than the preset recognition rate (Q %), the recalculation is performed The j number of kurtosis values (kurt_j) are rejected and the final kurtosis value (kurt) is substituted and confirmed with 0 (zero), and the final standard deviation value (std) is the standard deviation above regardless of whether the recalculation judgment step is repeatedly performed. a final data determination step of storing data by substituting and determining the standard deviation value (std_0) calculated in the kurtosis calculation step with the final standard deviation value (std);
The final standard deviation value (std) determined and stored in the final data determination step is compared with a preset constant threshold_S, and the final kurtosis value (kurt) determined and stored in the final data determination step and a preset constant threshold_K and size are compared Insulation state monitoring method of a power cable comprising; an insulation state determination step of determining the insulation state of the power cable by comparison. A signal detection step of detecting a signal related to the insulation state generated in the power cable to be measured in the detection sensor for detecting a signal related to the insulation state of the power cable;
a filter amplifying digital conversion step of extracting a signal of a preset frequency band from among the signals related to the insulation state detected in the signal monitoring step and amplifying and converting the signal into a digital value;
a standard deviation kurtosis calculation step of calculating and storing the standard deviation (std) and kurtosis (kurt) of the data that reads the digital value converted in the filter amplification digital conversion step a set number of times (n);
The kurtosis value (kurt_0) calculated in the step of calculating the standard deviation kurtosis is greater than the preset constant threshold_K (that is, kurt_0 > threshold_K ), or the standard deviation value (std_0) calculated in the step of calculating the standard deviation kurtosis is a preset constant threshold_S If greater than (that is, std_0 > threshold_S ), the signal is re-detected in the signal detection step as many as j times a preset number of repetitions at a preset waiting time interval to check whether it is noise-like data, and re-detected in the filter amplification digital transformation step The signal is amplified and converted into a digital value, and the standard deviation value (std) and kurtosis value (kurt) of n (80 in the embodiment of the present invention) received data read by the filter amplification digital conversion unit in the standard deviation kurtosis calculation step ) a recalculation determination step of repeatedly performing the process of recalculating;
If the recalculation judgment step is not repeated as many times as preset j times, the standard deviation value (std_0) and the kurtosis value (kurt_0) calculated in the standard deviation kurtosis calculation step are combined with the final standard deviation value (std) and the final kurtosis value. (kurt), and if repeated as many times as j preset in the recalculation determination step, the number of times the j number of kurtosis values (kurt_j) that are recalculated repeatedly in the recalculation determination step are greater than the preset constant threshold_K is greater than the preset recognition rate (Q %), or the number of j standard deviation values (std_j) recalculated repeatedly in the recalculation judgment step above is greater than the preset constant threshold_S If it is higher than the acceptance rate (Q %), the j recalculated kurtosis values (kurt_j) are recognized and the largest kurtosis value (kurt_j) among the j recalculated kurtosis values (kurt_j) repeated a number of times (j times) is selected as the final kurtosis The largest standard deviation value ( std_j) is substituted and confirmed with the final standard deviation value (std), and the j kurtosis values ( The number of kurt_j) greater than the preset constant threshold_K is smaller than the preset recognition rate (Q %), and even though the recalculation judgment step has been repeated as many times as the preset j times in the recalculation judgment step, it is repeated several times in the recalculation judgment step. If the number of recalculated j standard deviation values (std_j) greater than the preset constant threshold_S is less than the preset acceptance rate (Q %), the j recalculated kurtosis values (kurt_j) and a final data determination step of rejecting j standard deviation values (std_j), replacing and confirming both the final kurtosis value (kurt) and the final standard deviation value with 0 (zero), and storing the data;
The final standard deviation value (std) determined and stored in the final data determination step is compared with a preset constant threshold_S, and the final kurtosis value (kurt) determined and stored in the final data determination step and a preset constant threshold_K and size are compared Insulation state monitoring method of a power cable comprising; an insulation state determination step of determining the insulation state of the power cable by comparison. A computer-readable recording medium containing a computer program for performing the method for monitoring the insulation state of a power cable according to any one of claims 3 to 4. The method according to claim 1 or 2, wherein the insulation state determining unit
If the final standard deviation value (std) determined and stored in the final data determination unit is greater than a preset constant threshold_S, and the final kurtosis value determined and stored in the final data determination unit (kurt) is greater than a preset constant threshold_K (i.e., std > If threshold_S and kurt > threshold_K ) it is determined that the insulation state of the power-side terminal of the power cable is defective, and the final standard deviation value (std) determined by the final data determining unit is greater than the preset constant threshold_S and is determined by the final data determining unit If the final kurtosis value (kurt) is not greater than the preset constant threshold_K (that is, if std > threshold_S and kurt ≤ threshold_K), the insulation state of the intermediate connection part of the power cable is judged as defective, and the final If the standard deviation value (std) is not greater than the preset constant threshold_S and the final kurtosis value (kurt) determined by the final data determining unit is greater than the preset constant threshold_K (that is, if std ≤ threshold_S and kurt > threshold_K) of the power cable Insulation status monitoring device for power cables, characterized in that the insulation status of the load-side connection part is judged as defective 5. The method of claim 3 to 4, wherein the insulating state determining step
The final standard deviation value (std) determined and stored in the final data determining step is compared with the preset constant threshold_S, and the final kurtosis value (kurt) determined and stored in the final data determining step and the preset constant threshold_K size are compared. a first comparison step of comparing
As a result of the first comparison step, when the final standard deviation value (std) is greater than the constant threshold_S and the final kurtosis value (kurt) is greater than the constant threshold_K (that is, if std > threshold_S and kurt > threshold_K), it is said that the insulation state of the power-side terminal is poor. a power-side terminal failure determination step of judging;
As a result of the first comparison step, if the final standard deviation value (std) is not greater than the constant threshold_S or the final kurtosis value (kurt) is not greater than the constant threshold_S (that is, if std ≤ threshold_S or kurt ≤ threshold_K), the final data determining step a second comparison step of comparing the final standard deviation value (std) determined in , and the size of a preset constant threshold_S;
If the final standard deviation value (std) is greater than the constant threshold_S as a result of the second comparison step (ie, if std > threshold_S), an intermediate connection defect determination step of judging that the insulation state of the intermediate connection part is poor;
As a result of the second comparison step, if the final standard deviation value (std) is not greater than the constant threshold_S (that is, if std ≤ threshold_S), the final kurtosis value (kurt) determined in the final data determination step determines the size of the preset constant threshold_S a third comparison step of comparing;
When the final kurtosis value (kurt) is greater than the constant threshold_K (that is, if kurt > threshold_K) as a result of the comparison in the third comparison step, the load-side terminal defective determining step of determining that the insulation state of the load-side terminal is poor;
If the final kurtosis value (kurt) is not greater than the constant threshold_K as a result of the comparison in the third comparison step (that is, if kurt ≤ threshold_K ), the insulation state good judgment step of determining that the insulation state is good; A method for monitoring the insulation state of a power cable, characterized in that it.

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