Optimal Sensor Placement for Fault Diagnosis Using Magnitude Ratio

Abstract

Major performance losses occur in process industries due to failures that are not identified at the incipient stage.Early detection of such faults is also critical for the safety of the equipment, operating personnel, and other resources. When a fault occurs in a system, it can propagate and affect several process variables. Variables that need to be measured in order to detect and diagnose the faults have to be identified and chosen economically. An algorithmic approach for identifying the optimal number, type, and location of the sensors for fault detection and diagnosis is useful, particularly for large-scale, chemical process plants. In this work, previous algorithms for sensor placement that use signed directed graph (SDG) models for the process are enhanced to include magnitude ratio (MR) information to identify more promising sensor locations. Further, we also study the combination of fault evolution sequences (FES) already introduced in the literature and the MR information for effective fault diagnosis. This is achieved by including the idea of artificial sensors that represent pairwise sensors from the original list of possible sensors. Based on the MR and FES, the artificial sensors can assume discrete values, much like the SDG approach. A symmetric difference operator is used on both the original sensors (whose behaviors are modeled as before using SDG) and the artificial sensors to identify sensor placements. This approach elegantly incorporates the new MR and FES information in the original well-accepted SDG based sensor placement algorithms. Several case studies are presented to demonstrate the usefulness of the proposed approach.

Online Bearing Fault Diagnosis Based on a Novel Multiple Data Streams Transmission Scheme

“…In [12], position optimization of sensors method based on bond graph to digraph transformation for the small modulus gear life experiment of a spacecraft was proposed. Mobed et al [13] integrated the magnitude ratio and the fault evolution sequences and proposed an optimization algorithm for sensor location, type and number. The above research on the sensitive measuring points concentrated upon the sensor location optimization of the complete machine, and the impact from sensitivities of measuring point to fault diagnosis still exists.…”

State and Parameter Estimation in Distributed Constrained Systems. 2. GA-EKF Based Sensor Placement for a Water Gas Shift Reactor

“…Sensor placement has been carried out for different objectives, such as parameter estimation, − state estimation, − and fault detection. , Most sensor placement techniques optimize a performance criterion. Many contributions in the literature can be found that consider the steady-state behavior of the systems, including the sensor placement by qualitative analysis. ,− In the existing literature, many works on sensor placement belong to linear distributed parameter systems (DPS). Distributed parameter systems represent the dynamical systems governed by partial differential equations (PDEs).…”

Sensor Location for Enhancing Fault Diagnosis

“…Comprehensive reviews about the variety of methods proposed to locate instruments with fault diagnosis purposes have been presented. − The instrumentation selection strategies for processes to be monitored using PCA satisfy at least the observability and resolution of a predetermined set of faults. In this way, the detection and isolation of those failures are partially ensured. , It has been suggested to select sensors at the design stage by applying directed-graph-based procedures or a technique that assumes the fault probability values for the instruments and the process .…”