When the wind turbine pitch system is in operation, due to the strong coupling of the internal structure of the system, it is difficult to accurately locate the fault only relying on prior knowledge. And when using the data-driven contribution graph method for fault location, due to the influence of the fault variable, the contribution value of the non-fault variable will become larger, which will cause a tailing effect and misdiagnosis. In this paper, a multiblock kernel principal component algorithm (MBKPCA) is proposed. In this algorithm, the variables of the pitch system operation process are divided into several variable blocks based on the historical fault data and perform faults based on the kernel principal component algorithm for each variable block diagnosis. Taking historical data of an area in North China as an actual calculation example, the proposed block kernel principal component analysis algorithm is compared with the traditional kernel principal component analysis algorithm. The results show that the MBKPCA can effectively reduce the "tailing effect" of the fault variable on the non-fault variable when the contribution graph method is used to identify the fault source, and the method can accurately locate the fault source and achieves higher detection accuracy. INDEX TERMS fault diagnosis， kernel principal component algorithm，wind turbine pitch system， characteristic variables

To assess the roller coaster multi-body system security, it is need to extract the running process of kinematics, dynamics, load spectrum and other features, as basis dates of the roller coaster structural design. Based on Solidworks/motion software and in the 3D model, the calculation formula of the carrying car velocity and acceleration is derived, and the five risk points of the roller coaster track section are found by simulation in the running, and the simulation results of roller coaster axle mass center velocity are compared with theoretical calculation results, which error is less than 4.1%, indicating that the calculation and simulation have a good fit and providing the evidence for the roller coaster structure design analysis.