An evidence for earthquake ocurence time related with geologic structure──Relations between local mean lunar times of earthquake ocurence and their fault trends

The relation between the local mean lunar time τ of earthquake occurrence and their fault trends is studied in this paper. The local mean lunar times τ of 53 earthquakes in 24 groups are calculated. Because the tidal generation force arisen by the moon is a cyclic function of about 12 hours 25 minutes in the main, the two tidal generation forces anywhere in the earth arising by the moon are equal in general when the moon lies to the two sites of 180° interval of local mean lunar time. Based on this phenomenon the values Δ τ of τ 1- τ 2 or τ 1-τ 2±180° of two earthquakes occurring repetitiously in the same place are also calculated. The calculated results show that if the fault trends of the two earthquakes in the same place is near, the Δ τ is usually smaller and if the fault trends of the two ones is not near, the Δ τ is usually larger and the distribution of the local mean lunar time τ of earthquakes in different places is dispersive even if fault trends of these earthquakes are near, and the τ does not concentrate on the lower and upper transit of the moon. The above phenomena clear up that the triggering earthquake of earth solid tide arisen by the moon is relative with the fault trends of earthquakes and we ought to think over the difference of environmental conditions of earthquake preparation of each seismogenic zone and can not make statistics to earthquakes in different places when we study the relation between the solid earth tide arisen by the moon and earthquakes.

Faulty Feeder Identification and Fault Area Localization in Resonant Grounding System Based on Wavelet Packet and Bayesian Classifier

Accurate fault area localization is a challenging problem in resonant grounding systems(RGSs).Accordingly,this paper proposes a novel two-stage localization method for single-phase earth faults in RGSs.Firstly,a faulty feeder identification algorithm based on a Bayesian classifier is proposed.Three characteristic parameters of the RGS(the energy ratio,impedance factor,and energy spectrum entropy)are calculated based on the zero-sequence current(ZSC)of each feeder using wavelet packet transformations.Then,the values of three parameters are sent to a pre-trained Bayesian classifier to recognize the exact fault mode.With this result,the faulty feeder can be finally identified.To find the exact fault area on the faulty feeder,a localization method based on the similarity comparison of dominant frequency-band waveforms is proposed in an RGS equipped with feeder terminal units(FTUs).The FTUs can provide the information on the ZSC at their locations.Through wavelet-packet transformation,ZSC dominant frequency-band waveforms can be obtained at all FTU points.Similarities of the waveforms of characteristics at all FTU points are calculated and compared.The neighboring FTU points with the maximum diversity are the faulty sections finally determined.The proposed method exhibits higher accuracy in both faulty feeder identification and fault area localization compared to the previous methods.Finally,the effectiveness of the proposed method is validated by comparing simulation and experimental results.

Fault Feeder Identification in Non-effectively Grounded Distribution Network with Secondary Earth Fault

Secondary earth faults occur frequently in power distribution networks under harsh weather conditions.Owing to its characteristics,a secondary earth fault is typically hidden within the transient of the first fault.Therefore,most researchers tend to focus on a feeder with single fault while disregarding secondary faults.This paper presents a fault feeder identification method that considers secondary earth faults in a non-effectively grounded distribution network.First,the wavelet singular entropy method is used to detect a secondary fault event.This method can identify the moment at which a secondary fault occurs.The zero-sequence current data can be categorized into two fault stages.The first and second fault stages correspond to the first and secondary faults,respectively.Subsequently,a similarity matrix containing the time-frequency transient information of the zero-sequence current at the two fault stages is defined to identify the fault feeders.Finally,to confirm the effectiveness and reliability of the proposed method,we conduct simulation experiments and an adaptability analysis based on an electromagnetic transient program.