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In conventional gasoline automobiles, the engine powers the air conditioning system and engine noise can somewhat mask the noise and vibration of the air conditioning system. In pure electric vehicles, however, the absence of an engine makes the air conditioning system's noise more noticeable, concentrated in a limited frequency range at constant speeds. As a result, aerodynamic noise from the air conditioning system is a primary noise source in electric vehicles. Pipeline silencers are the main method for reducing this noise. The current silencer design uses plane wave acoustic theory but when cavity modal resonance occurs, the transmission loss error is relatively high. This article addresses the issue of non-planar wave cavity resonance, studying the cavity modal of a muffler using the finite element method to reveal the transmission loss under cavity mode resonance. A dual cavity expansion structure of an impedance composite muffler is proposed, with sound-absorbing materials placed in the cavity to enhance acoustic performance. The analysis of the transmission loss characteristics of the impedance composite muffler provides a theoretical basis for noise control in pure electric vehicle air conditioning systems. [ABSTRACT FROM AUTHOR]

Clarifying the noise source and the contribution of each path is essential for the system's noise control. The auxiliary converter cabinet, which is a crucial component of rail transportation, has numerous intricate noise sources. The contribution of each path point must be inverted-solved using known transfer functions and target point test values when identifying noise sources. This article suggests a method for diagnosing noise using transfer path analysis and neural networks (TPA-NN). Firstly, the principle and scheme for analyzing the transmission path of the converter cabinet are proposed. The transfer function of each path is obtained by selecting suitable path points, reference points, and target points for air and structure acoustic vibration experiments. The external target point data are then combined with the neural network's linear fitting function, and the contribution of each path is used as an output for network training while some path point contributions are rebuilt. The results indicate that the method's outcomes are most accurate when the converter cabinet's path point is 13 and the target point is 6. This approach offers an innovative technique for locating noise sources in intricate systems. [ABSTRACT FROM AUTHOR]

Featured Application: The methodology proposed in this paper studies the mobility of a multi-loop spherical mechanism with a spherical slider containing a spherical prismatic pair. By analyzing the motion of each closed kinematic chain that the mechanism consists of, not only can the proposed methodology thoroughly and accurately identify the mechanism's singularity configurations, but the method can also demonstrate the mechanism's range of motion. Therefore, the proposed method ultimately identifies the mechanism's motion continuity and smoothness, which are two of the most essential characteristics a multi-loop spherical mechanism possesses. Hence, the proposed methodology can help mechanism designers create multi-loop mechanisms with spherical sliders without motion deficiencies by avoiding the mechanisms' singularity configurations. Multi-loop spherical mechanisms are extremely beneficial for creating versatile mechanical devices, including robotic joints and surgical tools, since multi-loop spherical mechanisms possess unique capabilities to operate in spatial situations with relatively simple movement. Nevertheless, the research on multi-loop spherical mechanisms with spherical sliders containing spherical prismatic pairs is lacking. Therefore, the main innovation of this paper is to propose the Stephenson-III two-loop spherical mechanism that possesses a spherical slider containing a spherical prismatic pair and to analyze the proposed spherical mechanism's motion characteristics. An algebraic approach was employed to obtain the branch graphs of the proposed spherical mechanism with a spherical slider. The branch graphs were categorized into two types, according to whether branch points existed. With the algebraic approach, loop equations of the two spherical kinematic chains inside the proposed spherical mechanism were established to identify the input–output curves and singularity curves, with which the branch graphs were obtained. With the branch graphs, the joint rotation spaces (JRSs) of the proposed mechanism were recognized and so were the dead center positions, branches, sub-branches, and branch points. The results from the mathematical analysis were simulated and verified by three-dimensional (3D) models of the proposed spherical mechanism. The analytical results demonstrate that the spherical prismatic pair diversifies the motion of the proposed spherical mechanism by producing rotational sliding movement, which can cover the entire circumference of a specific greater circle on the proposed mechanism's sphere. [ABSTRACT FROM AUTHOR]

Product performance, function, cost, and the level of module generalization are all significantly influenced by product modular design, but different goods require different division indicators and techniques. The purpose of this study is to provide a set of appropriate modular division techniques for FDM 3D printers. This research offers an ecologically friendly module division index and uses module clustering as the module division principle in accordance with the current industrial development trend and the fundamental requirements of FDM 3D printer consumers in the current market. The K-means algorithm is used to use the Jaccard similarity coefficient as the metric of similarity of the DSM clustering process to realize the module division of the FDM 3D printer after studying the function–behavior–structure mapping model of the 3D printer. Additionally, the elbow method–cluster error variance and average contour coefficient evaluation systems were built, respectively, in order to verify the viability of the FDM 3D printer module division method and obtain the best module division results. By analyzing these two systems, it was discovered that when the FDM 3D printer was divided into three modules, the in-cluster error variance diagram obviously had an inflection point, and the average profile coefficient and other modular approaches that need to be adjusted to their respective goods can use this division method as a theoretical foundation and point of reference. [ABSTRACT FROM AUTHOR]

Active control of structural modal vibration is an effective strategy to enhance the sound quality of cabs in commercial vehicles. However, accurate determination of the positioning and quantity of modal active control sensors and actuators is crucial for cabs with intricate structures, owing to the presence of multiorder modes and their coupling. The study presented herein focuses on the cab of a commercial vehicle and contemplates the features of the irregular large-space structure of the cab. By capitalizing on the modal frequency and mode shape of the cab, utilizing the piezoelectric control principle and modal vibration energy as the assessment index, an advanced multimode composite control criterion is postulated to ascertain the configuration of primary sensors and actuators. The particle swarm optimization (PSO) objective function is constructed to accomplish the optimal position matching of the actuator/sensor, using the multimodal surface velocity vector of the vibration sensor as the core parameter. Furthermore, an improved linear adaptive particle swarm optimization (LA-PSO) technique is advanced to satisfy the requirements of optimal convergence performance and accuracy of the complex cab structure. The optimization culminates in a 9 × 9 multichannel active control scheme for determining the optimal position of the actuators/sensors. This investigation provides a technical foundation for the active control of sound quality in automotive cabs and presents an innovative method for implementing effective noise control systems in large-scale machinery and equipment. [ABSTRACT FROM AUTHOR]

Two algorithms that are distinct from the closed algorithm are proposed to create the inverse kinematics model of the UR10 robot: the Sequential Quadratic Programming (SQP) algorithm and the Back Propagation-Sequential Quadratic Programming (BP-SQP) algorithm. The SQP algorithm is an iterative algorithm in which the fundamental tenet is that the joint's total rotation radian should be at a minimum when the industrial robot reaches the target attitude. With this tenet, the SQP algorithm establishes the inverse kinematics model of the robot. Since the SQP algorithm is overly reliant on the initial values, deviations occur easily and the solution speed, and the accuracy of the algorithm is undermined. To assuage this disadvantage of the SQP algorithm, a BP-SQP algorithm incorporating a neural network is introduced to optimize the initial values. The results show that the SQP algorithm is an iterative algorithm that relies excessively on the initial values and has a narrow range of applications. The BP-SQP algorithm eliminates the limitations of the SQP algorithm, and the time complexity of the BP-SQP algorithm is greatly reduced. Subsequently, the effectiveness of the SQP algorithm and the BP-SQP algorithm is verified. The results show that the SQP and BP-SQP algorithms can significantly reduce the operation time compared with the closed algorithm, and the BP-SQP algorithm is faster but requires a certain number of samples as a prerequisite. [ABSTRACT FROM AUTHOR]

Aiming to achieve resonance suppression of a controllable mechanism welding robot end using dynamic modeling and experimental verification, this paper applies a central composite design methodology to optimize suppression resonance using three variables: excitation source, rod stiffness and damping. Considering the coupling effects of the excitation source, member stiffness and damping, a combination optimization is carried out, and the optimal control result of the end is obtained, for which the optimized peak amplitudes are significantly reduced. The research provides an important technical basis for the dynamic design and resonance suppression control of controllable welding robot mechanisms. [ABSTRACT FROM AUTHOR]

Active control is currently a hot-button issue in the research of reducing vibration and noise created by rolling piston compressors. Active control can effectively suppress the modal vibration of the structure and reduce the modal resonance acoustic radiation. This paper, which focuses on the active control of the compressor shell's multiple modes with the control of acoustic radiation power being the research objective, studies the relationship between vibration modes and acoustic radiation modes of the compressor shell and the primary sources of noise. An improved Filtered-U least mean square (FULMS) algorithm for compressor vibration and noise control, which is based on the Nesterov accelerated adaptive moment estimation (NADAM) optimization algorithm, is proposed to determine the multi-order modes to be controlled from the perspective of sound energy, and a particle swarm algorithm is used to determine the location and number of secondary sources. The active control model of the compressor shell was established by using the joint simulation platform, and the performance of the improved algorithm was verified and analyzed by the simulation test process. The results show that compared with the traditional FULMS algorithm, the improved FULMS algorithm has better active vibration control effect, higher convergence speed and can effectively suppress structural mode vibration in a short period time. [ABSTRACT FROM AUTHOR]

The hinge and suction dredger is widely used in the construction field such as in river and lake management, water dredging, and port infrastructure projects, etc. With the continuous development of modern dredging technology, the traditional hinge and suction dredger cannot adapt to the complex environment during the construction process and there are problems such as large energy consumption and over-excavation and leakage excavation. In this paper, a double cutter dredger was designed that has a wider adaptability to water than a single cutter dredger. At the same time, based on the principle of passive adaptive control, the working parameters of the control system were calculated and determined, and an adaptive control algorithm was proposed to determine the water environment by using the current difference between the two cutters. Finally, the feasibility of the structure and algorithm was verified by experiments. The efficiency of cutter suction dredger was improved, and the energy consumption was reduced by 9–25% in the ideal state. [ABSTRACT FROM AUTHOR]

In this paper, a new type of composite gradient sandwich plate structure is proposed, which embeds the pre-strained shape memory alloy (SMA) into the surface layer and the core layer composed of epoxy resin and graphite-reinforced materials. In the core layer, graphite-reinforced material has a continuous gradient distribution along the thickness direction of the sandwich plate. Dynamic behavior of composite gradient sandwich plate in thermal environment is investigated. The equations of motion and frequency equation are derived based on the Reddy shear deformation theory and the constitutive equation for a composite sandwich plate, via the Hamilton principle. Some analytical study is depicted to provide an insight into the effects of volume fraction of material composition, gradient distribution of graphite in the core layer, and pre-strain of SMA in the surface layer on the dynamic behavior of a sandwich composite plate. This study investigates the modal performance of a sandwich composite plate with two aspects, a gradient core layer of graphite-reinforced material and surface layer-embedded SMA wires, which provide a new design idea for dynamic behavior of sandwich plates. [ABSTRACT FROM AUTHOR]