Sensor Fault Detection And Validation In Crawler Crane Systems

Crawler crane is an important mobile hoisting equipment widely used in industrial and economic fields. With the development of industry, the requirement for both the quantity and the performance of crawler crane has become increasingly higher, especially large scale ones. If the control system of crawler crane is out of control, it would lead to the huge economic loss and endanger the people's lives. The accurate and reliable sensor signal is a prerequisite for fault detection and diagnosis of crawler cranes, and a guarantee for state inspection and reliable control of crawler cranes. So, it is important to study the method of sensor fault detection and diagnosis in crawler crane systems.In this paper, a method which is based on the subject-350t crawler crane that is developed by school of mechanical engineering of DUT is developed to detect and diagnose the sensor faults.(1) The basic idea and theoretical foundation of the principal component analysis are studied in this paper. The method to determine the number of principal components is also studied in this paper.(2) The load limit device is an important part of the control system of crawler cranes. The models of the six configurations of the crawler crane are set up in this paper. The reference frame that makes the computing easy is used in the modeling process.(3) A strategy based on the principal component analysis method is developed to detect and diagnose the sensor faults. To test validity of the PCA method, this paper presents a PCA model based on simulink data of QUY 350 crawler crane that is used to detection, diagnosis and reconstruction sensor's hard fault and soft fault.(4) The platform of the hardware and software is briefly introduced, and the flowcharts of it are presented.In summary, this paper presents a sensor faults detection and diagnosis strategy in the control system of the crawler crane. The method is used to detect and diagnose the typical sensor faults in the load limit device system. All research results not only play an important theory-instructing role in sensor fault detection and diagnosis, but also have a good chance to be applied in practice.