Detection and location of faults in a multiconductor transmission line
Published : 27 February 2019
The proper functioning of a distribution network depends on the ability to quickly detect the occurrence of faults, such as discharges, short circuits or the penetration of moisture in the cables. If the nature of these defects depends on the application context, the techniques used to detect them depend essentially on the ability to request a cable with test signals, and to monitor the appearance of response signals that would testify to the existence of a modification in the cables. While this approach is clear in the case of standard cables consisting of two conductors, the case of Multiconductor cables remains more complex to deal with. Indeed, applying test signals to a pair of conductors typically causes parasitic excitation of nearby conductors, because of the electromagnetic coupling that connects them.
This phenomenon can considerably complicate the interpretation of the results of a test, by creating an ambiguity in the identification of the faulty driver, because several drivers can couple with those actually under test.
In this thesis, the coupling will be considered as an opportunity, because it allows to probe a larger number of drivers at the same time. The intrinsic ambiguity of such a proposition can be removed by repeating the tests on several pairs of conductors. It then seems interesting to define optimum choice strategies of drivers to test to cover the largest number of neighboring drivers, without testing all possible combinations. In this sense, this proposal is parsimonious, introducing the concept of effective test surface covered from a pair of conductors.
A promising decision strategy for identifying a failing driver is provided by Bayesian tree and graph-based approaches. These tools make it possible to cross the information obtained in order to identify an explanatory model, here the faulty driver. Among the advantages of this approach we can count on their ability to integrate qualitative information, such as the typology of the defect, and to provide a result formulated in terms of probabilities associated with each possible scenario, thus qualifying the interpretation of results and to assess their reliability, unlike purely numerical methods.
It will then be necessary to carry out a preparatory work, making it possible to evaluate the probability a priori of observing parasitic signals from a fault on a neighboring conductor. This work will be based on the study of line theory and will provide the link between the physical aspects of Multiconductor propagation and the observables considered during the tests.