Insulation status monitoring equipment of power cables and method

摘要

The present invention relates to a power cable insulation state monitoring device and method therefor. In the present invention, 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 ), a preset waiting time (in the embodiment of the present invention, a value of 1 hour is used, but this value is not limited) to check whether it is noise data, a preset number of repetitions at intervals The process of recalculating the standard deviation value (std) and the kurtosis value (kurt) of the received data as many times as j (in the embodiment of the present invention, j = 5 is used, but this value is not limited) a recalculation determination step of repeatedly performing; If the recalculation determination step is not repeated as many times as preset j (j=5 in the embodiment of the present invention), the standard deviation value (std_0) and the kurtosis value (kurt_0) calculated in the standard deviation kurtosis calculation step are calculated. If the final standard deviation value (std) and the final kurtosis value (kurt) are determined, and the recalculation judgment step is repeated as many as j times (j=5 in the embodiment of the present invention) preset in the recalculation judgment step, the recalculation judgment step The number of times the kurtosis value (kurt_j), which is repeated several times and recalculated in , is greater than the preset constant threshold_K is the preset recognition rate (Q%, in the embodiment of the present invention, a value of 60% is used, but this value ) or the number of times the standard deviation value (std_j) recalculated repeatedly in the recalculation judgment step is greater than the preset constant threshold_S is the preset recognition rate (Q %, the present invention) In the example of , if it is greater than 60%), the recalculated kurtosis value (kurt_j) is recognized and the largest kurtosis value (kurt_j) among the recalculated kurtosis values (kurt_j) is repeated several times (j times) as the final kurtosis value (kurt). ), or the largest standard deviation value (std_j) among the recalculated standard deviation values (std_j) repeated several times (j times) by recognizing the recalculated standard deviation value (std_j) as the final standard deviation value (std), and the kurt_j value (kurt_j) recalculated repeatedly in the recalculation judgment step several times in the recalculation judgment step while iterating for a preset number of j times in the recalculation judgment step is greater than the preset constant threshold_K The number is smaller than the preset recognition rate (Q %, 60% in the embodiment of the present invention), and the re-calculation judgment step is repeated several times in the re-calculation judgment step, even though it is repeated the preset number of j times in the re-calculation judgment step. If the number of the calculated standard deviation value (std_j) is greater than the preset constant threshold_S is less than the preset acceptance rate (Q%, 60% in the embodiment of the present invention), the kurtosis value is repeated several times (j times) and recalculated. (kurt_j) and standard deviation (std_j) Either the final kurtosis value (kurt) and the final standard deviation value are both substituted and confirmed with 0 (zero) in disapproval; If the standard deviation value (std_0) and the kurtosis value (kurt_0) calculated in If the number of times the kurtosis value (kurt_j), which is repeated several times in the recalculation judgment step, is greater than the preset constant threshold_K is greater than the preset recognition rate (Q %), the recalculated kurtosis value (kurt_j) is The largest kurtosis value (kurt_j) among the kurtosis values (kurt_j) that has been recognized and recalculated a number of times (j times) is substituted and confirmed with the final kurtosis value (kurt), and the final standard deviation value (std) is the standard deviation above The kurtosis value (kurt_j) that is determined as the standard deviation value (std_0) calculated in the kurtosis calculation step and repeated several times in the recalculation judgment step while repeating the preset j number of times in the recalculation judgment step If the number greater than the preset constant threshold_K is less than the preset recognition rate (Q %), the kurtosis value (kurt_j) that is repeated several times (j times) is rejected and the final kurtosis value (kurt) 0 (zero) a final data determination step of substituting and confirming with , and storing the data by determining the final standard deviation value (std) as the standard deviation value (std_0) calculated in the standard deviation kurtosis calculation step; First comparing the standard deviation value (std) stored in the final data determining step and the size of a preset constant threshold_S, and comparing the kurtosis value (kurt) calculated in the final data determining step and the preset constant threshold_K size a comparison step; As a result of the first comparison step, if the standard deviation value (std) is greater than the constant threshold_S and the kurtosis value (kurt) is greater than the constant threshold_K (that is, if std > threshold_S and kurt > threshold_K), it is determined that the insulation state of the power-side terminal is poor. a power-side terminal failure determination step; If the standard deviation value (std) as a result of the first comparison step is not greater than the constant threshold_S or the kurtosis value (kurt) is not greater than the constant threshold_S (that is, if std ≤ threshold_S or kurt ≤ threshold_K), in the standard deviation kurtosis calculation step a second comparison step of comparing the calculated standard deviation value (std) with the size of a preset constant threshold_S; an intermediate connection defect determination step of judging that the insulation state of the intermediate connection part is poor when the standard deviation value (std) of the second comparison step is greater than the constant threshold_S (ie, std >threshold_S); As a result of the second comparison step, if the standard deviation value (std) is not greater than the constant threshold_S (that is, if std ≤ threshold_S), the kurtosis value (kurt) calculated in the standard deviation kurtosis calculation step is compared with the preset threshold_S size. a third comparison step; a load-side terminal failure determining step of determining that the insulation state of the load-side terminal is poor when the kurtosis value (kurt) is greater than a constant threshold_K (ie, kurt > threshold_K) as a result of the comparison in the third comparison step; Insulation condition monitoring device of a power cable comprising a; if the kurtosis value (kurt) of the third comparison step is not greater than the constant threshold_K (that is, if kurt ≤ threshold_K) and methods thereof are provided.