Fault Diagnosis of Ship Low Freshwater Cooling System LFCS Based on SSA-SVM Algorithm
As a power system to ensure the safe operation of the ship's power plant,the ship's fresh water cooling-system is difficult to troubleshoot in time only by the engineer crew once a failure occurs.Aiming at the problem that the support vector machine(SVM)is greatly affected by its own parameter selection in pattern recognition,a fault di-agnosis method based on sparrow search algorithm(SSA)optimized support vector machine was proposed.The SSA was used to optimize the penalty parameters and kernel parameters of support vector machine,and the fault diagnosis model of ship lowfresh water coolingsystem based on SSA-SVM was established.The results show that the accuracy of SSA-SVM model is 28%and 5%higher than that of traditional SVM and particle swarm optimization(PSO),respec-tively,and the convergence rate is faster.The SSA-SVM algorithm can effectively diagnose the common faults of the ship's fresh water cooling system,and can provide certain guidance for the health management of marine equipment and the diagnostic decision of the engineer.
Support vector machineSparrow search algorithmFault diagnosisAlgorithm to optimize
NETL
NSTL
万方数据
维普
