Considering the problem of residual noise and spurious modes in the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), a rolling element bearing malfunction diagnostic method based on improved CEEMDAN (ICEEMDAN) is proposed. First, different from the CEEMDAN, which directly adds Gaussian white noise with a mean of zero, the proposed method adds the kth component obtained from white noise decomposed by empirical mode decomposition (EMD) to the vibration signal, and then the ICEEMDAN is employed to decompose the signal into several intrinsic mode functions (IMFs). Second, aiming at the uncertainty problem of entropy estimation in multi-scale fuzzy entropy (MFE), a refined composite multi-scale fuzzy entropy (RCMFE) is proposed to obtain the characteristic from the selected IMFs. Finally, smoothing factor of PNN is determined by fruit fly optimization algorithm (FOA), and the extracted features are input into the FOA-PNN model to achieve condition identification. Experimental results illustrate that the identification accuracy is more than 99%, which indicates its high effectiveness and superiority.

For realizing the precision dressing of worm grinding wheel of face gear, this paper studies the over-cutting phenomenon of worm grinding wheel in forming dressing and puts forward the solution. Combined with the forming principle of face gear worm and forming dressing method, the influence of the continuous dressing method on the grinding wheel helix and the relative position between the dresser and the worm are expounded. Based on the numerical simulation model and the actual machining phenomenon, two kinds of over-cutting phenomenon are discovered. To ensure the surface integrity of grinding wheel in continuous processing, the reasons and laws of over-cutting are deeply analyzed. The first kind of over-cutting can be eliminated by increasing the angle between the extended line and the axis on the dresser, and a method of estimating the minimum angle is proposed for a more reasonable design of the dresser. The second kind of over-cutting can be eliminated by choosing proper dressing interval while ensuring the utilization efficiency of worm, and the selection criteria of dressing interval in continuous dressing are put forward. To verify the proposed methods, digital model, Vericut, and SolidWorks are applied, and the results show that the proposed method can effectively solve the over-cutting problem.

For a crossed beveloid gear pair with approximate line contact, the macroscopic geometric parameter is a dominant factor that affects meshing characteristics. However, geometric parameter design and reliability under misalignment are of great difficulty. To deal with these issues, an enhanced design method for a beveloid gear with approximate line contact is firstly proposed. Based on this, a robust optimization model of geometric parameters for crossed beveloid gear pairs with approximate line contact is developed. Three evaluation items are considered, namely the maximum contact pressure, contact trace offset distance and contact ratio. To reduce the calculation time, the influence coefficient method is applied to calculate the contact pressure. Considering the characteristics of installation deviation uncertainty and distribution, the mean maximum contact pressure, contact trace offset distance and ratio are considered as objective functions, formulated as a robust design optimization problem. Finally, robust optimization of a crossed beveloid gear pair based on a fast elitist nondominated sorting genetic algorithm (NSGA-II) is applied to solve the model to obtain the Pareto front of the macroscopic geometric parameters. A numerical example is provided to demonstrate the effectiveness of the proposed method.

Continuous generating grinding has become an important gear processing method owing to its high efficiency and precision. In this study, an adaptive design model is proposed for the continuous generation of beveloid gears in common gear grinding machines. Based on this model, a method for determining the installation position and grinding kinematics is developed alongside an analytical meshing model for grinding contact trace and derivation of key grinding parameters. By combining these aspects, a general mathematical model for the continuous generation of beveloid gears is presented, comprising the entire grinding process from worm wheel dressing to the evaluation of grinding deviation. The effects of the worm and dressing wheel parameters on the grinding deviation were analysed, facilitating the development of an approach to improve the grinding accuracy. The presented procedure represents a novel design method for the continuous generation of beveloid gears in common gear grinding machines, facilitating the appropriate selection of worm and dressing wheel parameters.

Exact contact pressure and load distribution are key evaluation indices for beveloid gear design. A numerical calculation approach of contact pressure and load distribution for crossed beveloid gears is proposed, as opposed to the traditional method based on a finite element modeling software package. To acquire the flexibility properties of beveloid gear tooth surfaces, an accurate finite element (FE) model about a beveloid gear tooth with root fillets is first built. A solution model for crossed beveloid gears is developed using the influence coefficients technique. An enhanced solving approach is presented to improve the robustness of the solving model by addressing the limitation of the influence coefficients method. In addition, a unique contact pressure is presented. The numerical example proposed can be used to test the proposed methodology.

为快速辨识数控机床转台位置相关几何误差,提出一种基于球杆仪的转台位置相关几何误差快速测量辨识方法。首先,基于齐次坐标变换建立转台位置相关几何误差模型,得到球杆仪杆长变化量与几何误差的关系;其次,设计球杆仪六次锥形安装方式,推导出误差辨识矩阵,记录球杆仪杆长变化量,快速辨识出转台位置相关几何误差,并提出一种球杆仪安装误差消除方法,有效剔除了安装误差的影响;最后,基于转台位置相关几何误差的辨识结果,对附加实验中球杆仪杆长变化量进行预测,预测精度较高;在此基础上,对转台位置相关几何误差进行补偿,补偿后的精度明显提高。结果表明:该方法可准确快速辨识出数控机床转台位置相关几何误差,对提高机床精度具有重要的意义。

A novel non-iterative denoising technique combining spectral graph wavelet transform and detrended fluctuation analysis is proposed to solve the filtering problem of non-linear and non-stationary mechanical vibration signals. The vibration signal is firstly converted to a graph signal defined on the path graph. Then, the graph signal is decomposed into scaling function coefficients and spectral graph wavelet coefficients by spectral graph wavelet transform. Finally, the threshold is adopted to shrink the spectral graph wavelet coefficients, and the denoised signal is obtained via the inverse transform. Besides, an efficient criterion based on detrended fluctuation analysis is designed to select the decomposition level of spectral graph wavelet transform. The denoising performance of the presented approach for mechanical vibration signal has been thoroughly evaluated through analog signals compared with five conventional methods. The developed technique is then applied to denoise the vibration signal collected in hob fault experiments, and the influence of different optional parameters on the denoising performance is analyzed by single factor experiments. Experimental results indicate that the proposed approach can remove noise well and retain the fine signatures of signal as much as possible, and Euclidean weight function and Minimax threshold can achieve desired denoising capability when combined with soft threshold function or hard threshold function.
© 2020 Elsevier Ltd

A design model for beveloid gears with modification is first developed. Then based on the ordinary gear shaving machine tools’ structure, a plunge shaving model for beveloid gears is proposed. Based on the model, the installation relationship of a shaving cutter relative to a beveloid gear is derived and a surface generation model of a shaving cutter for beveloid gear is established. In the next, considering the shaving cutter's installation errors, a shaved beveloid gear model in installation errors is proposed. The effect of the shaving cutter parameters on the geometrical characteristics and the beveloid gear shaving precision is analyzed. The results show that increasing the tooth number of the shaver and the shaft angle can decrease the undercut risk of the shaver surface. Increasing the number of the shaving cutter's teeth and decreasing the shaft angle can weaken the effect of installation errors on the shaving precision. In the end, a simulation platform is established in the Vericut software, the feasibility of the proposed models for beveloid gear plunge shaving is verified. The proposed models achieve plunge shaving of beveloid gears in common gear shaving machine tools and precision manufacturing without distortion of beveloid gears with modification.
© 2021 Elsevier Ltd