WAVELET TRANSFORM SYSTEM AND METHOD FOR VOLTAGE EVENTS DETECTION AND CLASSIFICATION

摘要

Wavelet transform systems and methods for voltage events detection and classification are provided and include a wavelet multiresolution analysis-based real time detection and classification for voltage events, as developed on a LabVIEW® platform. In the wavelet transform systems and methods for voltage events detection and classification, a finest detail level is utilized to detect the start time, the end time, and the duration of the voltage events, whereas a coarsest approximation level is used to classify the voltage event types. The wavelet transform systems and methods for voltage events detection and classification are applied on several typical short duration voltage events, such as sag, swell, and interruption.

主权项

1. A computer implemented wavelet transform method for voltage events detection and classification, comprising the steps of:
executing, with a processor, a program stored in a memory of a computer implemented device, the program directing the computer implemented device to perform the following: computing a first result(dj0k)Δj0of a finest detail level of a pure signal based on wavelet coefficients of said pure signal, computing a second result(d~j0k)Δj0of a coarsest level of a disturbance signal based upon wavelet coefficients ({tilde over (d)}jk)k ε Δj of said disturbance signal, and computing a third result r relating the second result of the coarsest level to the first result of the finest detail level, by calculation of:
a first formula calculating the first result of the finest detail level of said pure signal characterized by the relation:(dj0k)Δj0=(∑k∈Δj0dj0k2)12; a second formula calculating the second result of the coarsest level of said disturbance signal characterized by the relation:(d~j0k)Δj0=(∑k∈Δj0d~j0k2)12;and
a third formula calculating the third result r relating the second result of the coarsest level to the first result of the finest detail level, characterized by the relation:r=(d~j0,k)Δj0(dj0k)Δj0; selectively determining a no fault event type based on the relation:
(1−ε)≦r≦(1+ε),where ε is a preassigned threshold;
selectively determining a swell fault event type based on the relation:
r>(1+ε); selectively determining a sag fault event type based on the relation:
ε≦r<(1−ε); and selectively determining, when r<ε, that an interruption fault event type has occurred based on the computation of:Fj=∑k∈Δjdjkd~jk,j=1,…,j0-1 and the satisfaction of the relation:∑j=1JFj2≤ɛ2,wherein (djk) and ({tilde over (d)}j′k′) are orthogonal sequences, ({tilde over (d)}jk)k ε Δj are wavelet coefficients of the disturbance signal at the coarsest approximation level j0 over the disturbance interval Id, where Δj={k: supp ψjk⊂Id), k corresponds to the wavelet coefficients at a level, supp ψjk corresponds to a mother wavelet, and are wavelet coefficients of the pure signal at the scale level j and is a level group, and Fj corresponds to a result in the interruption fault event type determination.