磨粒携带着发动机重要的状态信息，是其故障诊断的一个重要手段。由于受到检测技术的限制，目前只利用了磨粒大小、二维形状等，未涉及更微观层次的结构和电、化学分布相关信息。磨粒剥裂面的三维微观形貌反映了磨粒产生原因；剥裂面的感应电流分布和化学成份特性则记录了磨粒产生环境。两者的结合不仅能够展现磨粒产生的静态原因，还能够呈现其产生的动态过程，进而有效地揭示发动机的工作状态和故障成因。本项目拟通过扫描电镜高频振动夹持器的设计和轨迹规划的研究，得到磨粒SECM-SICM图像的快速采集方法，大量地收集磨粒剥落面上三维形貌和电位分布、化学成份特性图像，为故障诊断提供必需的数据集；并拟采用多目标优化的故障诊断方法，通过特征空间、多优化目标和算法结构的研究，实现故障诊断中复杂映射关系的解耦，最终完成基于磨粒SECM-SICM图像的发动机故障诊断方法，提高发动机故障监测与诊断的正确性和准确性。

Because debris carry work states of engine,debris analysis is an important method of engine fault diagnosis. Due to limitation of the detection device, only size, 2D shape and chemical composition of debris are usually used. Neither 3D micro-image of debris nor the electronic and chemic distribution of debris is used at present.However, 3D micro-image of debris can uncover the cause and processing of debris and the distribution of faradic current and chemical composition can reveal producing environment of debris. If 3D micro-image and electrochemical distribution information are hanged together, not only the static information of debris, but also the dynamical procedure of debris can be revealed. So the work state and the fault cause of engine can be acquired effectually. This study proposes to get the fast acquisition method of SECM - SICM image of debris by the high frequency vibration holder of scanning electron microscopy (SEM) and the trajectory planning. As a result, a lot of images about the 3D surface morphology and electrochemical distribution on the debris desquamating surface are obtained as the necessary data sets for engine fault diagnosis. The method of multi-objective optimal fault diagnosis is designed in this project. Complex mapping relationships are decoupled by selecting appropriate feature sets, researching multi-objective functions and designing the algorithm structure. Finally, engine fault diagnosis method based on SECM-SICM images of debris is presented to improve the correctness and accuracy of engine fault detection and diagnosis.