This paper discusses the application of weighted fuzzy reasoning spiking neu-
ral P systems (WFRSN P systems) to fault diagnosis in traction power supply systems
(TPSSs) of China high-speed railways. Four types of neurons are considered in WFRSN P
systems to make them suitable for expressing status information of protective relays and
circuit breakers, and a weighted matrix-based reasoning algorithm (WMBRA) is intro-
duced to fulfill the reasoning based on the status information to obtain fault confidence
levels of faulty sections. Fault diagnosis production rules in TPSSs and their WFRSN P
system models are proposed to show how to use WFRSN P systems to describe different
kinds of fault information. Building processes of fault diagnosis models for sections and
fault region identification of feeding sections, and parameter setting of the models are
described in detail. Case studies including normal power supply and over zone feeding
show the effectiveness of the presented method.Ministerio de Economía y Competitividad TIN 2012-373
