Health status monitoring of ship rotating machinery based on sliding window and long-short term generative adversarial network

IntroductionShip rotating machinery is the core of the ship’s power system, and its health is crucial to the safety and economy of ship operation. However, the traditional operation and maintenance model is difficult to meet the intelligent needs of modern ships.MethodsThis study proposes an integrated solution of “data preprocessing-fault diagnosis-life prediction” to finish real-time monitoring and accurate prediction of the health condition of ship rotating machinery. First, the solution uses