Research On Marine Diesel Engine Monitoring Alarm And Auxiliary Energy Saving System Based On .NET

As the main power output source on the ship,the diesel engine's working state can determine whether the ship is safe or not.However,because the marine diesel engine usually works in a harsh environment and its operation process is more complicated,it is easy to happen Failure,thereby reducing the safety of the ship.Therefore,it is extremely important to monitor the status of the diesel engine,find its abnormal status in time,and diagnose the fault.At the same time,under the situation of global energy depletion,the monitoring of diesel engine operating conditions and the adjustment of the operating conditions of other auxiliary systems can also significantly reduce the energy consumption of ships.Its research is also of great significance.Based on the Win Form platform in the.NET framework,this paper develops a monitoring system for marine diesel engines,which can perform real-time status monitoring on diesel engines,and implements fault alarm diagnosis based on the optimized PSO-RBF neural network.At the same time,an auxiliary system variable operating mode control scheme was designed to control the speed of the motor driving the pump or fan in each auxiliary system of the diesel engine,so that the output of the auxiliary system was matched with the operating conditions of the diesel engine,so as to achieve energy saving purpose.Through the analysis and design of the overall structure of the diesel engine monitoring system,the modules used to implement various functions are listed,and the particle optimization process of the Particle Swarm Optimization(PSO)algorithm is optimized to design the inertia in the algorithm Weights,learning factors,and speed update schemes to improve the convergence speed and accuracy of the PSO algorithm,and use the optimized PSO algorithm to the hidden layer neuron center in the Radial Basis Function(RBF)neural network,Field width,connection weight of hidden layer and output layer,three parameters are optimized to form an optimal RBF neural network.By optimizing the PSO-RBF neural network,the typical fault diagnosis of the diesel engine intake and exhaust system and the fuel system is carried out.Studies have shown that the optimized PSO-RBF neural network has a smaller fault diagnosis than the RBF neural network optimized by the basic PSO algorithm Error,higher reliability.By selecting a permanent magnet synchronous motor,a variable working condition control scheme is designed to match the actual working condition of the diesel engine with the output flow of the pump or fan of the required auxiliary system,thereby changing the flow of the pump or fan through the frequency conversion speed regulation of the motor,To reduce the energy consumption required by each pump or fan in the auxiliary system of the diesel engine,and achieve the purpose of energy saving.Finally,this paper develops a diesel engine monitoring system on the Win Form platform.The system collects data through sensors;S7-300 PLCs with sm331 and sm332 modules installed are used for data transmission through the adapter;Mod Bus protocol is used for data communication;through SQL Server2014 Carry out data storage and recall;be able to calculate by collecting data,and output data to control the speed of each motor in the diesel engine auxiliary system;in the interface can display the corresponding data in real time,view the historical data line graph and fault;through optimized PSO-The RBF neural network completes the fault diagnosis;the motor speed of the auxiliary system is controlled to form a complete monitoring system.