A Review on Incipient Fault Detection, Location and Classification in Underground Cable

Underground cables are replacing overhead systems nowadays. So disturbances like incipient faults in an underground cable are a concern that needs to be detected as rapidly as possible to protect the cable system. Due to the aberrant behavior of incipient faults, the relay can’t detect the abnormalities generated in the distributed cable. Hence, sometimes false tripping of the circuit breaker may be initiated. Mainly faulty current, as well as faulty voltage signals, are implemented for localization, detection, and fault classification in a distribution network. This paper discusses several signal processing techniques, Machine learning methods, and Deep Learning techniques for the fault detection, localization, and classification of various faults in underground cable systems. This consolidated and efficacious survey motivates the researchers to understand various state of art techniques as well as traditional techniques of fault analysis.