Research On Identification Of Gear Backlash Parameters Based On Current Signal

As a major manufacturing country that is in a critical period of economic structural transformation,the use of industrial robots in China has shown an explosive growth trend in recent years.Spur gears and planetary gear reducers are widely used in the field of industrial automation and are important components that support the joint operation of industrial robots.Its performance seriously affects the reliability of the equipment.Backlash and stiffness may cause the performance of planetary gears to decrease.Therefore,vibration,temperature and current are applied to planetary gear condition monitoring.Motor Current Signature Analysis(MCSA)is widely used in the monitoring of the motor itself,but there are few studies using this technology to monitor equipment connected to the motor.The object of this paper is the gear transmission system connected with the servo motor.The purpose of the research is to analyze the influence of the different side clearances of the meshing gear on the current by monitoring the current signal of the servo motor,so as to establish the mapping relationship between the clearance and the current.The servo motor is the power source of the entire gear transmission system,and its output torque is usually determined by the stator current.Theoretically,current analysis can be used to identify any operating state of mechanical components that changes the load torque.Experiments have proved that from the perspective of current signal analysis,for different gear side clearances,the effect of the clearance on the system can be effectively monitored.The purpose of this paper is to develop a practical and effective method based on MCSA for the identification of backlash in spur gear test benches and planetary gear reducers.For spur gear backlash,different analysis methods are proposed for different operating conditions,smooth operation and variable speed operation.In the stationary phase,multiple features are extracted from different tooth backlash current signals,and the sensitivity of the features is evaluated based on the Fisher feature discrimination method to find the best characterizing state quantity for the backlash.For the variable speed stage,the reciprocal of the time difference between the positive peaks of the signal at this stage is extracted as a feature index to describe this stage,and then combined with the polynomial principle to enhance the features of the extracted features.For the planetary gear reducer experiment,the sensitivity weight ratio(SWR)is proposed to optimize the introduced fisher discriminant analysis(FDA)algorithm for the extraction and screening of the current signal characteristics of the servo motor.Combined with the support vector machine(SVM),the identification of the backlash of the planetary gear reducer is realized.In addition,the application of deep learning model in backlash identification is introduced for the characteristic matrix of electrical parameters and the original signal set.The motor is connected to the planetary gear reducer,so the change of the planetary gear’s operating status can be monitored in the current of the motor.Compared with the traditional detection method of the health of mechanical equipment,the current and current sensor is a non-invasive detection method,which is low in cost and easy to install.In addition,in order to highlight the effectiveness of the SWR optimized FDA algorithm and the SVM classifier,the results obtained are compared with the results obtained by the other six algorithms.The identification result shows its superiority.Finally,the experimental tests were carried out under different backlash and load conditions to verify the effectiveness of the method.This article draws corresponding conclusions on both the spur gear test bench and the planetary gear reducer test bench,through servo motor current analysis,combined with feature extraction algorithms,and state identification algorithms such as SVM and deep learning algorithms.It can identify backlash of planetary gears and spur gears,and promote the application and promotion of current signals in the field of equipment health.