Observer-based sensor fault detectability: about robust positive invariance approach and residual sensitivity

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper considers detectability of deviation of sensors from their nominal behavior for a class of linear time-invariant discrete-time systems in the presence of bounded additive uncertainties. Detectable sensor faults using interval observers are analyzed considering two distinct approaches: invariant-sets and classical fault-sensitivity method. It can be inferred from this analysis that both approaches derive distinct formulations for minimum detectable fault magnitude, though qualitatively similar. The core difference lies in the method of construction of the invariant set offline in the former method and the reachable approximation of the convergence set using forward iterative techniques in the latter. This paper also contributes in giving a formulation for minimum fault magnitudes with invariant sets using an observer-based approach. Finally, an illustrative example is used to compare both approaches.Peer ReviewedPostprint (author's final draft

Fault tolerant drives for safety critical applications

PhD ThesisThe correct operation of adjustable speed drives, which form part of a larger system, is often essential to the operation of the system as a whole. In certain applications the failure of such a drive could result in a threat to human safety and these applications are termed 'safety critical'. The chance of a component failure resulting in non-operation of the drive can be dramatically reduced by adopting a fault tolerant design. A fault tolerant drive must continue to operate throughout the occurrence of any single point failure without undue disturbance to the power output. Thereafter the drive must be capable of producing rated output indefinitely in the presence of the fault. The work presented in this thesis shows that fault tolerance can be achieved without severe penalties in terms of cost or power to mass ratio. The design of a novel permanent magnet drive is presented and a 'proof of concept' demonstrator has been built, based on a 20 kW, 13000 RPM aircraft fuel pump specffication. A novel current controller with near optimal transient performance is developed to enable precise shaping of the phase currents at high shaft speeds. The best operating regime for the machine is investigated to optimise the power to mass ratio of the drive. A list of the most likely electrical faults is considered. Some faults result in large fault currents and require rapid detection to prevent fault propagation. Several novel fault sensors are discussed. Fault detection and identification schemes are developed, including new schemes for rapid detection of turn to turn faults and power device short circuit faults. Post fault control schemes are described which enable the drive to continue to operate indefinitely in the presence of each fault. Finally, results show the initially healthy drive operating up to, through and beyond the introduction of each of the most serious faults.EPSR

Online Detection of Shutdown Periods in Chemical Plants: A Case Study.

In process industry, chemical processes are controlled and monitored by using readings from multiple physical sensors across the plants. Such physical sensors are also supplemented by soft sensors, i.e. adaptive predictive models, which are often used for computing hard-to-measure variables of the process. For soft sensors to work well and adapt to changing operating conditions they need to be provided with relevant data. As production plants are regularly stopped, data instances generated during shutdown periods have to be identified to avoid updating these predictive models with wrong data. We present a case study concerned with a large chemical plant operation over a 2 years period. The task is to robustly and accurately identify the shutdown periods even in case of multiple sensor failures. State-of-the-art methods were evaluated using the first half of the dataset for calibration purposes and the other half for measuring the performance. Results show that shutdowns (i.e. sudden changes) can be quickly detected in any case but the detection delay of startups (i.e. gradual changes) is directly related with the choice of a window size