振动特征值算法库应用服务数据

振动特征值及算法库是公司在重资产流程行业关键设备预测性维护深耕多年总结的一套知识库，包含了该领域设备振动诊断分析中所常见的特征库、特征算法库；具体包含基本时域特征、基本频域特征、电机故障特征、滚动轴承故障特征、齿轮故障特征、其他故障特征（如油膜涡动段能量和、叶片通过频率及其谐波、导叶叶片通过频率及其谐波、旋转失速叶轮故障能量和、旋转失速导叶故障能量和等），可为需要对设备振动数据分析，却不知道提取具体关键参数的人群进行使用。同时也可为同行业提供快速计算特征值服务，避免自研开发算法，节约人力物力、维护成本。该算法库中还包含有设备故障数据集如轴承内圈、外圈、滚动体、保持架故障；齿轮不均匀磨损、齿根折断、轴系类不平衡、不对中基座松动等故障。

The Vibration Feature Value and Algorithm Library is a knowledge base accumulated by the company after years of in-depth engagement in predictive maintenance of key equipment in heavy-asset process industries. It encompasses the feature database and feature algorithm library commonly applied in equipment vibration diagnosis and analysis within this sector, specifically including basic time-domain features, basic frequency-domain features, motor fault features, rolling bearing fault features, gear fault features, and other fault features such as the total energy of oil film whirl segments, blade pass frequency and its harmonics, guide vane blade pass frequency and its harmonics, total energy of rotating stall impeller faults, total energy of rotating stall guide vane faults, etc. It can assist users who need to conduct equipment vibration data analysis but are unaware of how to extract specific key parameters. Meanwhile, it provides rapid feature value calculation services for peers, eliminating the need for in-house algorithm development and saving manpower, material resources and maintenance costs. The algorithm library also contains equipment fault datasets covering faults of bearing inner rings, outer rings, rolling elements and cages; uneven gear wear, tooth root fracture, shafting imbalance, misalignment, base looseness and other typical faults.