机械密封的健康评估研究

Study on the Health Assessment of Mechanical Seals

机械密封端面膜厚状态是表征机械密封健康状况的重要参数,通过评估密封膜厚状态可以有效的延长机械密封的使用寿命,降低机械工作过程中的故障率。为了评估流体动压型机械密封开启过程的健康状态,该研究通过在实验平台上利用声发射和电涡流传感器对其信号进行实时监测并采集信号。将实验采集的信号进行处理,利用KPCA方法降维优化抽取的特征参数,采用DHMM算法建立模型进行训练并测试。结果表明,DHMM模型能够对机械密封的健康状态进行有效的评估。

Film thickness state of mechanical seal face mask is an important parameter to estimate the healthy condition of mechanical seal.By evaluating the sealing film thickness status,the service life of the mechanical seal can be prolonged effectively,and the failure rate of the machine can be reduced.In order to evaluate the healthy condition of the fluid dynamic pressure type mechanical seals during the opening process,we carried out this study to monitor the signal in real time by using acoustic emission and eddy current sensor on the experimental platform.Then the signal collected from the experiment was processed by using the KPCA method to realize dimension reduction optimization of the extracted characteristic parameters and the DH M M algorithm to build a model for training and testing.Results show that we can assess the healthy status of the mechanical seals effectively by making use of DH M M model.