Locating Sensors in Complex Engineering Systems for Fault Isolation Using Population-Based Incremental Learning

Fault diagnostics aims to locate the origin of an abnormity if it presents and therefore maximize the system performance during its full life-cycle. Many studies have been devoted to the feature extraction and isolation mechanisms of various faults. However, limited efforts have been spent on the optimization of sensor location in a complex engineering system, which is expected to be a critical step for the successful application of fault diagnostics. In this paper, a novel sensor location approach is proposed for the purpose of fault isolation using population-based incremental learning (PBIL). A directed graph is used to model the fault propagation of a complex engineering system. The multidimensional causal relationships of faults and symptoms were obtained via traversing the directed path in the directed graph. To locate the minimal quantity of sensors for desired fault isolatability, the problem of sensor location was firstly formulated as an optimization problem and then handled using PBIL. Two classical cases, including a diesel engine and a fluid catalytic cracking unit (FCCU), were taken as examples to demonstrate the effectiveness of the proposed approach. Results show that the proposed method can minimize the quantity of sensors while keeping the capacity of fault isolation unchanged.

Using Rio-Paris Flight 447 Crash to Assess Human Error and Failure Propagation Analysis Early in Design

While a majority of system vulnerabilities such as performance losses and accidents are attributed to human errors, a closer inspection would reveal that often times the accumulation of unforeseen events that include both component failures and human errors contribute to such system failures. Human error and functional failure reasoning (HEFFR) is a framework to identify potential human errors, functional failures, and their propagation paths early in design so that systems can be designed to be less prone to vulnerabilities. In this paper, the application of HEFFR within the complex engineering system domain is demonstrated through the modeling of the Air France 447 crash. Then, the failure prediction algorithm is validated by comparing the outputs from HEFFR and what happened in the actual crash. Also, two additional fault scenarios are executed within HEFFR and in a commercially available flight simulator separately, and the outcomes are compared as a supplementary validation.

The Problems and Countermeasures in Construction Management

Construction is a multi-type, multi-disciplinary and complex engineering system. In order to smoothly conduct construction process and to achieve the intended goal, it is necessary to carry out construction management in a scientific way. However, in the implementation of the system, there is often mismanagement which caused major safety accidents and the quality of construction has become a general concern. This paper analyzes some problems in the construction site, and proposed solutions to promote standardized law and safety measures for the construction management system.