Abstract
A critical aspect of water transport networks (WTN) is the vulnerability of the system. Water system security depends, among other factors, on the capability to detect as soon as possible accidental or intentional contamination, sensor and actuator malfunctions (faults) or incorrect operations. Fault diagnosis (FD) aims at carefully identifying which fault (including hardware or software faults and external perturbations) can be guessed to be the cause of monitored events. In general, when addressing the FD problem, two strategies can be found in the literature: hardware redundancy based on the use of redundancies (adding extra sensors and actuators), and software (or analytical) redundancy based on the use of software/intelligent sensors (or a model) combining the information provided by the sensor measurements and the actuator commands. In large-scale systems, the use of hardware redundancy is quite expensive and increases the number of maintenance and calibration operations. This is the reason why, in WTN applications, FD systems that combine both hardware and analytical redundancy are usually developed. In this chapter, a review of the state of the art in fault diagnosis applied to WTN will be provided. Next, model-based FD procedures will be reviewed and mathematically formalized. This framework is based on checking the consistency between the observed and the normal system behaviour using a set of analytical redundancy relations (ARRs) . ARRs compare the values of measured variables against the estimated values provided by a normal operation (fault-free) model of the monitored system. Finally, the Barcelona water transport network will be used as the case study to exemplify the FD methodologies.
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Escobet, T., Sarrate, R., Comasolivas, R. (2017). Fault Diagnosis. In: Puig, V., Ocampo-Martínez, C., Pérez, R., Cembrano, G., Quevedo, J., Escobet, T. (eds) Real-time Monitoring and Operational Control of Drinking-Water Systems. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-319-50751-4_11
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