With the increasing awareness of the importance of environmental protection and the fierce competition in the construction machinery market, improving the vibration comfort of a whole construction machine has become a new focus of competition; therefore, optimizing the performance of cab mounts has become an urgent problem to be solved. At present, the problems of low modeling efficiency, serious technical difficulties, and long development cycles exist in the design and optimization of cab mounts. In this paper, a multi-target regression forests method is introduced into the design and optimization of the construction machinery installation system, which circumvents the traditional complex modeling process and establishes a mapping relationship between cab assembly parameters and the mounts’ stiffness, as well as introduces the system decoupling rate and vibration isolation rate as the boundary conditions. Furthermore, the MRFs method is compared and evaluated with MLRP and Multi-SVR prediction results. Finally, a complete, accurate, and efficient design method for the cab mount system optimization is developed, improving the decoupling rate and vibration isolation rate of the cab system. This design method can predict the stiffness of the mounts in multiple directions.
The seat of a construction machinery cab is used as the research object. For the current human-seat coupling system comfort research methods and optimization index deficiencies, the seat body pressure comfort and vibration comfort at the same time optimized. Based on the more specialized Toyota 50 percentile dummy model, a human-seat finite element simulation model is established, and the body pressure distribution and vibration response are simulated and calculated. The transverse and longitudinal pressure distributions of the backrest and seat cushion and the pressure map are used to verify the simulation model’s body pressure comfort evaluation indexes. At the same time, the vibration response test is used to verify the vibration comfort evaluation indexes of the simulation model. The test results show that the accuracy of each evaluation index of the established coupling model is greater than 85%, which can provide model support for the subsequent optimization work. In order to improve the comfort of the seat of construction machinery during operation, the hardness of the upper sponge and lower layer sponge is reduced and increased by 10% and 15%, respectively, on the original seat. The body pressure comfort evaluation indexes of the ischium peak pressure, ischium mean pressure, thigh peak pressure and thigh mean pressure are used to evaluate the improved seat. The proposed optimization scheme is to reduce the hardness of the upper sponge and lower layer sponge of the seat cushion by 10% to improve the seat body pressure comfort. Finally, the evaluation indexes of body pressure comfort and vibration comfort are verified by four subjects in an improved seat, and the cushion pressure of different subjects is reduced while the vibration isolation rate is increased, which shows the rationality of the proposed optimization scheme. In addition, the evaluation results of the improved seat are different for subjects of different body sizes, with the most significant improvement for the subject of greater height and weight. The modeling and comfort evaluation methods adopted in the paper can provide a reference for the design and development of the seat.
A 3D numerical simulation is built on heavy truck including cab, frame, and tires. And vehicle exterior flow field in steady state is computed by computational fluid dynamics software. In the computation process, the distribution of sound power levels on the surface of vehicle body as well as the connection between sound power level and vehicle speed are obtained from aerodynamic noise source, which is using broadband noise source models. Taking the steady flow field results as original values, the exterior flow field computations in transient state are performed by large eddy simulation. Based on the transient fluid field, the near field aerodynamic noise from cab accessories is predicted using FW-H model, and the comparison of the simulation results and the test results is carried out. The results show that the aerodynamic noise sources are from the upwind side with a great pressure gradient. Attentions should be paid more on rearview mirror, diversion trench and sun visor for Aerodynamic noise optimization of heavy truck. The maximum sound power level of aerodynamic noise in vehicle body accessories is quadratic to vehicle speed. And the aerodynamic noise of heavy trucks is analysed by numerical simulation, in which noise distribution law is consistent with the test. Therefore, the numerical simulation can be adopted to provide the guidance for the design of vehicle body with low noise.
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