promote and foster the development of systematic power disturbance detection methods that can be used for equipment condition monitoring. Current Signature Based Methods Disturbances associated with equipment failures usually involve the abnormalities of current signals. As a result, most of the published detection methods use current waveforms or RMS trends. In this subsection, several different current-based methods are reviewed. Abnormal Component Methods Superimposed abnormal component is the current signal from which normal load component has been removed. According to reference [2] and [3], superimposed abnormal component can be derived with equation 1: 1 for instantaneous values of the phases A, B and C currents; iA, iB, iC stand for superimposed abnormal components of the phases A, B and C iFA, iFB, currents; iFC stands for a sample index and represents a present sample. k In equation should be an integer multiple of which stands for the number of 1, NM N1 samples per power cycle. In both [2] and [3], is equal to two times namely NM N1, = 2N1. NM Abnormal components are very small under steady state, normal operating conditions [2]. During faults and other switching events, the above signals will be relatively more significant. If the abnormal components exceed pre-established limits, then a disturbance can be considered to occur. There are two different methods to determine if the abnormal components have exceeded pre-established limits, as follows. (1) Magnitude of Fundamental Frequency Abnormal Component After superimposed abnormal components have been calculated, the magnitudes of fundamental frequency component can be derived with DFT/FFT. If any of the magnitudes of fundamental frequency component exceeds a certain threshold, a disturbance is detected. In other words, if any of equation and is satisfied, 2a), 2b) 2c) a disturbance is detected. The thresholds can be pre-established or be estimated by analyzing previous cycles of current signals. 2a 2b
promote and foster the development of systematic power disturbance detection methods that can be used for equipment condition monitoring. Current Signature Based Methods Disturbances associated with equipment failures usually involve the abnormalities of current signals. As a result, most of the published detection methods use current waveforms or RMS trends. In this subsection, several different current-based methods are reviewed. Abnormal Component Methods Superimposed abnormal component is the current signal from which normal load component has been removed. According to reference [2] and [3], superimposed abnormal component can be derived with equation 1: 1 iA, iB, iC for instantaneous values of the phases A, B and C currents; iFA, iFB, iFC stand for superimposed abnormal components of the phases A, B and C currents; k stands for a sample index and represents a present sample. In equation 1, NM should be an integer multiple of N1 which stands for the number of samples per power cycle. In both [2] and [3], NM is equal to two times N1, namely NM = 2N1. Abnormal components are very small under steady state, normal operating conditions [2]. During faults and other switching events, the above signals will be relatively more significant. If the abnormal components exceed pre-established limits, then a disturbance can be considered to occur. There are two different methods to determine if the abnormal components have exceeded pre-established limits, as follows. (1) Magnitude of Fundamental Frequency Abnormal Component After superimposed abnormal components have been calculated, the magnitudes of fundamental frequency component can be derived with DFT/FFT. If any of the magnitudes of fundamental frequency component exceeds a certain threshold, a disturbance is detected. In other words, if any of equation 2a), 2b) and 2c) is satisfied, a disturbance is detected. The thresholds can be pre-established or be estimated by analyzing previous cycles of current signals. 2a 2b
Signatures_Equipment_Failures_May2018.docx