Research On Motion Detection Technology Of Tower Crane

Tower crane(hereinafter referred to as tower crane)is a large high-risk special equipment.How to ensure that tower crane meets the operation specifications,locate the damage position of tower crane,and predict the life of tower crane is an urgent problem to be solved in the field of tower crane safety monitoring.Once the tower crane structure is damaged,the dynamic characteristics of the structure will change.The relationship between damage characteristics and signal can be found by studying the kinematic parameters such as attitude,acceleration,velocity and trajectory of tower crane components.The high-precision motion parameter detection device of tower crane can not only measure the kinematic parameters of tower crane,but also predict the damage status of tower crane by using the corresponding relationship mentioned above.The motion detection technology in this thesis refers to the use of inertial navigation technology to obtain the kinematic parameters of tower crane.The kinematics parameters of the carrier(the selected position of the tower crane)include acceleration,velocity and displacement.The acceleration and angular velocity are the direct measurement data of inertial navigation system,and the other parameters are derived from the direct measurement data.This thesis involves the selection of tower crane detection points,the study of sensor layout scheme,the analysis of attitude and position solution algorithm,computer simulation and experimental verification,the specific research content is as follows:This thesis describes the status quo of tower crane attitude acquisition technology and inertial navigation technology,discusses the advantages and disadvantages of strapdown inertial navigation technology in solving this problem.According to the requirements and characteristics of tower crane motion detection,the end and root of lifting boom,the end of balancing boom and the hook are selected as motion detection positions,and the overall detection scheme is proposed.This thesis analyzes the similarities and differences between the direction cosine method and the quaternion method and chooses the quaternion method to solve the carrier attitude.The core process of attitude solution in this thesis is that gyroscope signal is sampled by the binary sample algorithm,the equivalent rotation vector is solved by the fourth order Longo Kutta method,and quaternions are updated by the equivalent rotation vector.SINS toolbox is used to simulate the attitude solution algorithm in cone motion environment.The function in SINS toolbox is used to establish the general rotation motion of the carrier,simulate the error of inertial devices,and study the relationship between the error of attitude solution algorithm and the error of components.The simulation results show that the influence of the attitude algorithm error is much smaller than that of the gyroscope error.The position detection of tower crane can be divided into tower crane arm and top of tower body.This thesis studies these two cases by simulation and experiment.A tower crane model was established by Adams,and the integral algorithm of position acquisition by acceleration was simulated under the lifting and turning conditions of the tower crane model,and the reliability of the integral algorithm was verified.In this thesis,the performance and characteristics of inertial devices suitable for this environment are summarized.Finally,the experimental measuring device was made by combining JY901 S and BZ1193.The lifting,unloading and turning experiments were carried out on QTZ80 tower with this device.According to the movement characteristics of tower crane in lifting and unloading experiment,a pieceward displacement method is proposed.In the rotary experiment of tower crane,the trend errors of velocity data accumulated significantly over time.In this thesis,displacement parameters were obtained through three multi-style fitting curves and Kalman filter.Experimental results show that the accuracy of JY901 S can be used under the lifting and unloading movement of tower crane,and the average displacement measurement error is about 6%.In the rotary movement of tower crane,the error is large.In this thesis,kalman filter is used to optimize the position calculation algorithm in the rotary experiment,and the final error is about 6.1%.The above accuracy basically meets the demand of kinematics detection.