故障检测的可靠性描述及传感器分布优化算法

Reliability Description of Fault Detection and Optimization Algorithm of Sensor Location

研究利用概率SDG模型来描述大规模复杂系统故障检测的可靠性问题,并针对系统中每种传感器的不同故障概率,分析传感器的选择和分布对故障检测可靠性的影响.系统发生故障时,变量值的偏差可被传感器检测到,但由于传感器本身的故障及其分布不同,系统故障有可能被漏检或错检,直接影响系统故障检测的可靠性.本文在概率SDG模型的描述方法下给出故障检测的可靠性描述,研究在有限资源条件下传感器的优化分布及其算法.在此基础上,对65t/h锅炉系统建立了概率SDG模型,并应用了所给的优化算法,确定了系统的传感器优化分布方案.仿真实验表明,这样确定的传感器分布对提高故障检测可靠性是有效的.

Reliability problems in fault detection for large-scale complicated systems are studied by using a probabilistic signed directed graph （SDG） model. Influences of sensor selection and location on reliability with respect to different sensor fault probabilities are analyzed. When system faults occur, the sensors can detect the departure of variances, but the system faults may be ignored or misdiagnosed because of the sensor faults, directly affecting the fault detection reliability. With description of the probabilistic SDG model, the reliability description of fault detection is given. Optimal sensor location and the corresponding algorithm are studied under restricted resources. Furthermore, a probabilistic SDG model is established for a typical 65 t/h boiler, on which the above algorithm is executed to determine an optimization scheme. Simulation experiment shows that sensor location solved in this way is effective in improving fault detection reliability.