Currently, the use of industrial seawater reverse osmosis desalination (ISROD) plants has increased in popularity in light of the growing global demand for freshwater. In ISROD plants, any fault in the components of their control systems can lead to a plant malfunction, and this condition can originate safety risks, energy waste, as well as affect the quality of freshwater. This paper addresses the design of a fault detection and isolation (FDI) system based on a structural analysis approach for an ISROD plant located in Lima (Peru). Structural analysis allows obtaining a plant model, which is useful to generate diagnostic tests. Here, diagnostic tests via fault-driven minimal structurally overdetermined (FMSO) sets are computed, and then, binary integer linear programming (BILP) is used to select the FMSO sets that guarantee isolation. Simulations shows that all the faults of interest (sensors and actuators faults) are detected and isolated according to the proposed design.

Fault detection and isolation (FDI) in oil pipeline systems (OPS) is a very critical issue because faults in these systems such as leaks or equipment malfunctions may cause significant safety accidents and economic losses. These are the challenging factors, along with the environmental regulations for developing efficient FDI approaches for OPS. This paper proposes a model-based distributed FDI approach, which uses a structural model of the system in conjunction with algorithms to generate diagnostic tests that may be implemented in local diagnosers along the OPS. The proposed approach allows detection and isolation of faults in pipeline sections (pipeline segments), pump stations, as well as process control equipment. In this way, simulation of the obtained diagnostic tests in a benchmark application shows that all faults of interest (pipeline segment faults and sensor faults) are detected and isolated.

Currently, the operation of modern industrial processes depends on many different components (systems and plant devices) all of which are tied together through communication systems. In large-scale systems, due to the difficulty of monitoring the communication infrastructure, the latter is vulnerable to external physical intervention, which could have, as a consequence, the loss of communication among process components. In some cases, to avoid loss of communication, redundancies or alternative paths are implemented, but this is not necessarily the most efficient solution. In this paper, a fault diagnosis approach based on structural analysis that makes effective use of its infrastructure in a communication-loss condition is proposed. This is accomplished by considering the communication structure in the proposed approach to apply optimization methods guaranteeing optimal use of the available communication structure. For this, diagnosers choose the best communication paths or, if necessary, change their design. The proposed approach is applied to a power distribution system achieving diagnosis goals in a communication-loss condition.