Ship Lock Herringbone Door Vibration Signal Monitoring System

With the rapid development of China's shipping industry in recent years,the ship lock herringbone gate is the water conservancy hub of the important node of inland navigation,Gezhouba as the main channel along the ship locks,the traffic volume increased rapidly.Increasing full load and even overload conditions,leading to structural safety hazards.Including the ship lock herringbone door,mushroom head and other ship lock main components,under the joint action of huge water pressure,dynamic water load and swell,there will gradually be a general deformation such as poor lubrication and fatigue damage,which will lead to serious consequences such as cracks and even fractures..It will not only affect the safety of navigation,but also bring serious social and economic losses.At present,there is no effective monitoring method for the safety of ship locks,especially the operation conditions of key components such as underwater gate body,door middle seam and bottom water stop.At present,the manual maintenance of interval suspension does not only affect the navigation of the channel.The most important thing is that the manual detection method cannot achieve real-time monitoring.Due to the complicated underwater environment,there is a possibility of missed detection.At present,the ship lock is full or even overloaded.There are serious safety hazards in the increased working conditions.In this paper,the left door of the Gezhouba 3#ship lock herringbone gate is taken as the main research object,and the fault diagnosis expert system of the miter gate is constructed.It is mainly responsible for the vibration monitoring system of the miter gate,and has completed the following work:(1)For the vibration signal preprocessing,the traditional Kalman filter and the improved Kalman filter method are used to denoise the vibration signal to reduce the influence of extermal interference on the effective vibration signal.The results show that the improved algorithm works well.Then the time domain parameter fault diagnosis analysis of the vibration signal is carried out,and the fault diagnosis of the herringbone gate is made by judging whether the parameters such as the average absolute deviation,kurtosis and skewness are abruptly changed.The time-frequency domain is selected by empirical mode decomposition and the improved integrated empirical mode decomposition is applied to the vibration signal analysis.The improved integrated empirical mode decomposition algorithm effectively suppresses the modal aliasing phenomenon and has better effect.(2)With the increasing popularity of artificial intelligence methods,neural network algorithms have begun to be applied to fault diagnosis of various structures.Therefore,neural network algorithms are applied to the vibration monitoring system of the gate,and BP neural network,RBF neural network and adaptive genetics are selected.The optimized RBF algorithm performs simulation experiments on the herringbone gate,and the analysis results verify the effectiveness of the diagnostic system.(3)The health monitoring system of the miter gate is constructed to realize the software design of the miter gate vibration monitoring system,and display and store the vibration signal of the miter gate.At the same time,the neural network fault diagnosis identification classification model of artificial intelligence is constructed,and the functional module requirements of the vibration monitoring system are completed,which provides the basis for the follow-up expert fault diagnosis system.