Research On Vibration Monitoring And Analysis System Of Rapier Loom Spindle

Rapier loom is widely used in textile industry.In the process of weaving,the tension of the yarn should be kept in a proper range,and the vibration of the loom will cause the fluctuation of the tension of the yarn,and then affect the quality of the textile.At present,the loom embedded control system does not have the function of vibration detection,which needs to be checked manually.The main shaft is the power source of the loom,which directly affects its vibration.Therefore,a set of embedded vibration monitoring and analysis system is developed in this project.The system can monitor the vibration of the main shaft of the loom,find out the abnormal vibration in time and analyze the cause of the failure.Firstly,a set of embedded vibration acquisition system is designed.The system mainly includes three parts: vibration acquisition,conditioning circuit module,system communication module and data storage module.It has the characteristics of system simplification,Wi Fi transmission,flexibility and expansibility,low cost and so on.Secondly,mechanical vibration signals are often analyzed from the frequency domain,so this paper studies the principle and calculation method of fast Fourier transform(FFT),which is commonly used in industry,and compiles and optimizes the algorithm sequence of FFT embedded C language,so as to apply it to the embedded platform with weak performance,After the vibration signal is collected,the vibration spectrum of the system can be obtained by itself for analysis.Finally,due to the diversity and complexity of mechanical vibration,its spectrum needs to be analyzed by professionals.In order to improve the automation and intelligence level of the system and reduce the labor cost,the system also introduces BP neural network to study and fit the relationship between the vibration spectrum characteristics and fault types of the main shaft of the loom,so that the system can intelligently analyze and judge the vibration fault causes after obtaining the vibration spectrum of the main shaft,and timely notify the equipment maintenance personnel for maintenance.In this paper,the embedded system hardware is used to collect the vibration spectrum of the rapier loom spindle,and the comparative analysis method is used to analyze and determine the cause of the abnormal vibration.The designed BP neural network can also identify the vibration spectrum and determine the fault cause.The feasibility and reliability of the embedded vibration detection and analysis system are proved.Because BP neural network needs a lot of calculation,which requires high hardware performance and low-cost embedded system can not meet its operation requirements,so neural network is generally based on PC platform.In this paper,the principle of BP neural network is studied,and it is found that the learning results of BP neural network can be expressed by mathematical formula.Therefore,this system uses PC platform to complete the learning process of BP network,and then extracts BP learning results as mathematical mapping formula,which can be used by embedded system to realize intelligent spectrum analysis and BP fault prediction.In this paper,the embedded system hardware is used to collect the vibration spectrum of the rapier loom spindle,and the comparative analysis method is used to analyze and determine the cause of the spindle vibration abnormality.The designed BP neural network can also identify the vibration spectrum and determine the fault cause.The experiment proves the feasibility and reliability of the embedded vibration detection and analysis system.