Journal of Mechanical Science and Technology

Zhang, Wei; Huang, Fen

doi: 10.1007/s12206-022-1201-8pmid: N/A

Owing to increasing attention and investigation of bio-inspired rules for generating innovative design with the aid of additive manufacturing, a concise introduction to bioinspired generative design is given. The state of the field is briefly reviewed, and open questions, challenges, and opportunities for further development are highlighted.

Guo, Minglong; Wei, Zhaocheng; Wang, Jia; Wang, Minjie; Wang, Xiaoyu; Liu, Shengxian

doi: 10.1007/s12206-022-1202-7pmid: N/A

Cutting force is the most intuitive reflection of various influencing factors in the milling process, which is important for improving machining quality and efficiency. For the wide-row milling with flat-end mill of free-form surface, an analytical in-cut cutting edge (ICCE) algorithm is studied in detail, and overall cutting force model is further constructed. The cutter location points along tool path are discretized into small oblique planes. Taking the oblique plane machining as the new object, the relative position of flat-end mill and workpiece in five-axis machining is defined parametrically. By constructing a semi-enclosed space in which the cutting edge participates in cutting, the ICCE is directly obtained. By analyzing the cutting force of oblique plane, the cutting force model of free-form surface can be established by spatial coordinate transformation. The simulation and experiment have demonstrated the correctness and effectiveness of the proposed ICCE algorithm and force prediction model.

Abedinilaksar, Mohammadjavad; Yang, Jianming

doi: 10.1007/s12206-022-1203-6pmid: N/A

The free in-plane vibration of a thin-walled ring with elastic supports is investigated in this work. These supports are represented as linear springs in radial, tangential, and torsional directions to mimic bolt supports in the real world. With the Euler-Bernoulli theory and the assumption of inextensibility, the natural frequency and mode shape are obtained. Finally, the effects of model parameters such as radius-to-thickness ratio and support stiffness are studied. The model is verified by comparing results against available publications on simpler boundary conditions.

Kim, Hyun-Guk; Kim, Sin-Ho; Wang, Semyung; Lee, Jong-Hyun

doi: 10.1007/s12206-022-1204-5pmid: N/A

The micro-electro-mechanical system (MEMS) technology has led to improvements in the manufacturability and scalability of the semiconductor-based sensors and actuators. This study proposes a framework for topology optimization to improve the dynamic stability of a resonant MEMS scanner for a light detection and ranging (LiDAR) system installed on an autonomous vehicle. The microscanner must have excellent dynamic stiffness and rigidity for in-plane disturbances because the vehicle system is subjected to several types of disturbances owing to road harshness and power train vibration. This paper is the first one to apply the topology optimization method to the design of torsional spring of the microscanner to maximize the lateral yawing mode frequency, which might degrade stable operation. The optimization was constrained to the mode frequencies for the torsional and the two bending modes, similar to the reference model. The proposed framework can facilitate the systematical design of a torsional resonant microscanner that satisfies frequency requirements with improved dynamic stability for in-plane disturbance.

Cui, Ben; Guo, Panpan; Zhang, Wenbin

doi: 10.1007/s12206-022-1205-4pmid: N/A

To address challenges in fault diagnosis of rolling bearing caused by great noise contamination and difficult extraction of fault character frequency, a fault diagnosis method of rolling bearing based on the maximum correlation kurtosis deconvolution (MCKD), singular spectral decomposition (SSD) and teager energy operator (TEO) with optimal parameters was proposed in this study. First of all, denoising was performed as a preprocessing to the original vibration signals which were collected by using the MCKD with optimal parameters to highlight the impact component. Next, SSD was performed to the preprocessed signals and the optimal components were selected according to variance contribution. Finally, the energy spectra of optimal components were calculated and characteristic frequency was extracted to realize fault diagnosis of bearing. Through simulation and experimental analysis, the proposed method was proved feasible. It was further compared with empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD), which proved superiority and validity of the proposed method.

Guo, Xiang; Wu, Xing; Liu, Xiaoqin; Tang, Linjiang

doi: 10.1007/s12206-022-1206-3pmid: N/A

Using microphone array to detect the fault of rotating machinery is an effective method. Compared with the fault diagnosis based on vibration analysis, the advantage of this method is that it does not need the direct contact between the sensor and the machine. In addition, acoustic location can be realized by using microphone array, to accurately identify the sound radiation source on the machine surface. Conventional beamforming (CBF) is widely applied in noise source identification because of its fast speed. In the local reverberation environment, the conventional beamforming is disturbed by the image source, causing inaccurate judgment of the fault location and low imaging resolution. In this paper, an acoustic imaging method of averaged generalized inverse beamforming (AGIB) is proposed. Compared with CBF, generalized inverse beamforming (GIB) possess higher location accuracy. First, the spectral kurtosis (SK) can enhance the impact characteristics of fault signals. According to the center frequency and bandwidth estimated by the spectral kurtosis diagram, the impact information which adopt in beamforming location can be extracted in time domain and frequency domain by spectral kurtosis matched filter. Then the average amplitude and standard deviation of generalized inverse beamforming output at different positions are calculated. Finally, the normalized standard deviation is used for the beamforming output weighting of the central measurement position, so as to enhance the spatially invariant source contribution and effectively attenuate the ghost caused by the local reverberation environment. Through defect location of low-speed large bearing, compared with the averaged conventional beamforming (ACBF), AGIB can not only overcome the influence of local reverberation environment and accurately locate the fault location, but also improve the resolution significantly.

Tong, Chengbiao; Sepehri, Nariman; Zhou, Jiang

doi: 10.1007/s12206-022-1207-2pmid: N/A

Check valves are key components required to ensure that fluid flows in one direction. Internal cross-port leakage is a common fault that affects the service performance of check valves. Cross-port leakage occurs due to defects in the valve spool. Early detection of this fault and its root cause is important to prevent downtime and subsequent costs. This research presents a multi-scale signal enhancement method based on spool impact and pressure signal analysis for leakage identification and its root causes. The impact signals obtained by accelerometers attached to the valve body are segmented from the entire vibration signal to capture the variations in the inherent characteristics of the valve. Subsequently, wavelet packet decomposition and reconstruction are performed to extract the energy distribution and energy entropy of signals. The time-frequency domain is used to extract features for leakage identification faults. Correlation analysis was applied to select 45 sensitive features out of 105 features. The performance of the method was verified using the RCYCS-G experimental hydraulic platform, and the recognition rate of four modes was found to be 100 % accurate. The proposed method accurately identifies the root causes of leakage in the check valve, lays a foundation for leakage rate prediction, and has significant engineering application value in predictive maintenance.

Zhang, Yahui; Li, Siyan; Li, Aimin; Zhang, Gaoxiang; Wu, Mingzhuang

doi: 10.1007/s12206-022-1208-1pmid: N/A

Damage to a belt conveyor idler will increase the downtime and maintenance cost, so it is very important to diagnose its fault. At present, the fault diagnosis of the idler of a belt conveyor is mostly based on vibration and temperature signal. However, contact fault diagnosis approaches are severely limited when sensors are inconvenient to install or when vibration and temperature signals cannot be returned. In this special case, the non-contact fault diagnosis method, represented by measuring acoustic signals, becomes a necessary means. To effectively extract mechanical state information from sound signals of belt conveyors and identify typical mechanical faults, we propose a fault detection method based on sample center distance weighted (support vector data description (SVDD)) and multi-frame fusion (Mel-frequency cepstral coefficient (MFCC)) features. Aiming at the disadvantage that single frame MFCC features and traditional SVDD are susceptible to noise, multi-frame fusion MFCC optimization features are used as samples, and the weighted SVDD model based on sample center distance is used for fault detection. Finally, the overall recognition accuracy of the experiment is greatly improved. It is proved that MFCC features of multi-frame fusion sound signal and weighted SVDD fault detection based on sample center distance can effectively determine whether there is a fault in the of belt conveyor idler.

Zhang, Xinqian; Kou, Farong; Wang, Guohong; Xu, Jianan

doi: 10.1007/s12206-022-1209-0pmid: N/A

In this paper, the parameter optimization and error analysis of the rack and pinion steering mechanism are carried out on the basis of considering the influence of kingpin parameters. The steering characteristic equation describing the motion of the steering mechanism is calculated by analyzing the spatial geometrical relationship between the wheel and kingpin and unifying the projection relation between the kingpin and the equivalent steering trapezoid. The ideal Ackermann equation is modified by the Ackermann rate and the kingpin parameters. The modified Ackermann equation is used as the objective function. The segmented fitness function and the evaluation function with weighted factors are designed. A genetic algorithm containing the three functions is used to optimize the parameters of the steering characteristic equation. The error analysis of the numerical example shows that the accuracy of steering trapezoid structure parameters, steering characteristic equation, and Ackermann equation is improved compared with that before optimization.

Zhang, Lufan; Jiang, Boshi; Zhang, Pengqi

doi: 10.1007/s12206-022-1210-7pmid: N/A

In this paper, the ultra-high acceleration macro-micro motion platform flexible positioning platform is taken as the research object. First, the finite element modal analysis is performed using the finite element technique, and the natural frequencies and mode shapes of the flexible positioning platform are obtained. Then, using the response surface optimization design method, the low-order natural frequency of the flexible positioning platform is increased, and its mass is decreased. Finally, the experimental modal analysis of the flexible positioning platform is carried out, and the experimental modal parameters of the flexible positioning platform are calculated. The experimental results are basically consistent with the finite element analysis results, which verify the accuracy of the finite element modal analysis. The research results are of great significance to the development of the ultra-high acceleration macro-micro motion platform.