This paper proposes an adaptive sliding mode observer(ASMO)-based approach for wind turbines subject to simultaneous faults in sensors and actuators.The proposed approach enables the simultaneous detection of actuator...This paper proposes an adaptive sliding mode observer(ASMO)-based approach for wind turbines subject to simultaneous faults in sensors and actuators.The proposed approach enables the simultaneous detection of actuator and sensor faults without the need for any redundant hardware components.Additionally,wind speed variations are considered as unknown disturbances,thus eliminating the need for accurate measurement or estimation.The proposed ASMO enables the accurate estimation and reconstruction of the descriptor states and disturbances.The proposed design implements the principle of separation to enable the use of the nominal controller during faulty conditions.Fault tolerance is achieved by implementing a signal correction scheme to recover the nominal behavior.The performance of the proposed approach is validated using a 4.8 MW wind turbine benchmark model subject to various faults.Monte-Carlo analysis is also carried out to further evaluate the reliability and robustness of the proposed approach in the presence of measurement errors.Simplicity,ease of implementation and the decoupling property are among the positive features of the proposed approach.展开更多
为预防失控类事故引发的灾难性后果,选取航空安全网(Aviation Safety Network,ASN)2015—2022年102起失控类事故为样本,以2018年“10·29”印尼客机坠毁事故为例,采用基于系统理论的因果分析(Causal Analysis based on System Theor...为预防失控类事故引发的灾难性后果,选取航空安全网(Aviation Safety Network,ASN)2015—2022年102起失控类事故为样本,以2018年“10·29”印尼客机坠毁事故为例,采用基于系统理论的因果分析(Causal Analysis based on System Theory,CAST)方法从系统角度梳理并识别失控类事故发生过程中涉及的安全控制缺陷。在此基础上,采用故障树分析(Fault Tree Analysis,FTA)法绘制失控类事故故障树模型,并对其进行定性、定量分析,得出失控类事故的主要致因。结果表明:基于CAST模型分析识别出25个系统缺陷;通过故障树定性分析得出16个最小割集;通过定量分析计算出失控类事故在所有事故中发生的概率为0.40086;确定机组操作不当、机组沟通不足、飞机系统缺陷及飞机制造商假设不全、制造商未提供相关文件为失控类事故的主要影响因素。展开更多
文摘This paper proposes an adaptive sliding mode observer(ASMO)-based approach for wind turbines subject to simultaneous faults in sensors and actuators.The proposed approach enables the simultaneous detection of actuator and sensor faults without the need for any redundant hardware components.Additionally,wind speed variations are considered as unknown disturbances,thus eliminating the need for accurate measurement or estimation.The proposed ASMO enables the accurate estimation and reconstruction of the descriptor states and disturbances.The proposed design implements the principle of separation to enable the use of the nominal controller during faulty conditions.Fault tolerance is achieved by implementing a signal correction scheme to recover the nominal behavior.The performance of the proposed approach is validated using a 4.8 MW wind turbine benchmark model subject to various faults.Monte-Carlo analysis is also carried out to further evaluate the reliability and robustness of the proposed approach in the presence of measurement errors.Simplicity,ease of implementation and the decoupling property are among the positive features of the proposed approach.
文摘为预防失控类事故引发的灾难性后果,选取航空安全网(Aviation Safety Network,ASN)2015—2022年102起失控类事故为样本,以2018年“10·29”印尼客机坠毁事故为例,采用基于系统理论的因果分析(Causal Analysis based on System Theory,CAST)方法从系统角度梳理并识别失控类事故发生过程中涉及的安全控制缺陷。在此基础上,采用故障树分析(Fault Tree Analysis,FTA)法绘制失控类事故故障树模型,并对其进行定性、定量分析,得出失控类事故的主要致因。结果表明:基于CAST模型分析识别出25个系统缺陷;通过故障树定性分析得出16个最小割集;通过定量分析计算出失控类事故在所有事故中发生的概率为0.40086;确定机组操作不当、机组沟通不足、飞机系统缺陷及飞机制造商假设不全、制造商未提供相关文件为失控类事故的主要影响因素。
