Research On Condition Monitoring And Assessment Method For Boom System Of Concrete Pump Truck Based On Heterogeneous Multi-Sensor Information Fusion

Concrete pump has the advantages of easy movement, simple control, high quality, casting and destruction of the environment and other characteristics, which is widely used in a variety of bridge construction, housing construction and highway construction. However due to concrete pump truck working environment changing, maintenance is not timely and work for a long time, easy to cause the fatigue damage, leading to boom cracking accident, so in the construction process of concrete pump truck, must be real-time monitoring and health evaluation is imperative. The traditional detection method is the hand-held ultrasonic testing, the human eye detection and designated location special instrument detection. Hand held and designated special instruments are based on a single sensor to detect, not only for a long time, and can not be real-time monitoring, and the human eye detection accuracy is low. In view of the existing concrete boom detection equipment is difficult to meet the real-time monitoring and diagnosis of the boom system of concrete pump car arm, based on heterogeneous multisensory data fusion of boom system of concrete pump truck health real-time monitoring and evaluation method is proposed in this paper, main research content includes:Study on the structural properties of the concrete pump truck boom. Firstly, the force of the arm frame structure is analyzed and calculated. Then through the finite element software ANSYS modal and static analysis, the natural frequency of the four common conditions, mode and stress distribution. Then through the dynamics software ADAMS vibration analysis, we get the each arm centroid displacement, acceleration curves and analyze the movement characteristics under the four conditions.Research on the optimal sensor placement methods. Firstly, through the optimization of position sensors in the analysis of the methods, we propose the combination optimization method for composite stacked optimal sensor., namely a cantilever beam as the object, we use ANSYS software to extract the modal correlation information, obtained the best combination of methods,and through the experimental verification of the method correctness,finally,the method is applied in the boom, it is concluded that the concrete boom of optimal sensor placement.Research on the concrete boom system failure type characterization parameters.Firstly, it is concluded that the fracture of the arm is the crack, and then we proposed to study on the basis of selecting two from the micro fatigue monitoring and he diagnosis of macroscopic crack.Monitoring the fatigue study fatigue life estimation, we get the parameters characterizing fatigue life. Macro crack diagnosis of the time domain parameters characterizing, we propose to use the multipoint control simulation method, namely a cantilever beam as the object, we obtain the time domain feature parameters, and then through experiment to verify the correctness of the proposed method, at last the method is applied on the boom system, we obtained the domain characterization parameters of it.Research methods heterogeneous multi-sensor data fusion. Firstly, we analyses the information fusion model, we propose fusion algorithm that is based on neural network feature recognition of D-S evidence theory Decision, and a cantilever beam as an object and use the fourth chapter of feature vectors obtain to verify the validity of the method, then it is applied in the concrete pump truck boom system.In this paper, a real-time monitoring and health evaluation method of concrete pump truck boom system based on heterogeneous sensor information fusion is proposed. It can satisfy the real time and the short time of the test of the concrete pump truck boom system, which lays a theoretical foundation for the monitoring and evaluation of the whole concrete pump truck.