Online shock sensing for rotary machinery using encoder signal

With the increasing of equipment interaction in the industry 4.0 era, the accidental shocks are inevitable during the device operation, resulting in a decline in equipment safety and product quality. Hence, it is very essential to sense external shock to ensure safety and stability. However, shock sensing by adding external sensors is not desirable due to costs and limitation of installation environment. Moreover, shock sensing in an online manner is also a challenge. In view of these bottlenecks, a framework of shock sensing for rotating machinery using encoder signal is constructed in this paper. We first investigated the feasibility and challenges of this framework. To capture the weak feature introduced by shock in encoder signal, a rank-estimated online RPCA method is proposed. Finally, static testing confirms that shock sensing can be effectively achieved using encoder signal without any additional sensors. On this basis, the results of dynamic testing further demonstrate that the proposed scheme is able to sense the external shock under different operating conditions, which is expected to provide a new idea for intelligent perception of rotating machinery.