Deformation of thin-walled titanium alloys can occur during the milling process due to the cutting force and chatter vibration, which can influence the precision of the finished parts. In this research, a new milling method without auxiliary support for machining of thin-walled parts was proposed. A large cutting depth and layered milling technology were used during rough machining, with a different machining allowance for each subsequent remaining layer. In the finishing stage, the surface of the previous layer needed to be dressed before processing the next layer. A TiAlSiN-coated, cemented carbide milling cutter was used to machine titanium alloy thin-walled parts, which are characterized by continuous multilayers of unequal thickness. The processing path was simulated using HyperMILL software, and the machining accuracy was detected by the 3D optical scanner. The measurement results indicated that the surface contour accuracy of the parts was ±0.21 mm, within a range of ±0.30 mm. The machining efficiency was increased by 40%, while guaranteeing machining accuracy.

Tool wear and breakage detection technologies are of vital importance for the development of automatic machining systems and improvement in machining quality and efficiency. The monitoring of integral spiral end milling cutters, however, has rarely been investigated due to their complex structures. In this paper, an image acquisition system and image processing methods are developed for the wear and breakage detection of milling cutters based on machine vision. The image acquisition system is composed of three light sources and two cameras mounted on a moving frame, which renders the system applicable in cutters of different dimensions and shapes. The images captured by the acquisition system are then preprocessed with denoising and contrast enhancing operations. The failure regions on the rake face, flank face and tool tip of the cutter are extracted with the Otsu thresholding method and the Markov Random Field image segmentation method afterwards. Eventually, the feasibility of the proposed image acquisition system and image processing methods is demonstrated through an experiment of titanium alloy machining. The proposed image acquisition system and image processing methods not only provide high quality detection of the integral spiral end milling cutter but can also be easily converted to detect other cutting systems with complex structures.

As for the gantry-type machine tools, the forces of the slide blocks supporting the beam are different for different saddle locations, which would further affect the stiffness of the slider–guide joints and the dynamic characteristics of the whole machine tools. Therefore, the beam kinematic joints (the slider–guide joints) on the gantry-type machine tools are crucial for the dynamics prediction of traveling bridge systems. In this article, considering the effect of axis coupling force on the slider–guide joints’ stiffness, an equivalent dynamic model of traveling bridge systems for the gantry-type machine tools is established using hybrid element method. The additional load variation in the four slider blocks is analyzed for different locations of the saddle, and the variation in the slider–guide joints’ stiffness and traveling bridge system natural frequency are also studied. Finally, validation experiments are conducted on the traveling bridge systems of the gantry-type milling machine tools, and the results show that the dynamic modeling proposed in this article can reach a higher accuracy.

Strong shear force developed in the lubrication film in the high-speed spindles will resulting high temperature rise and expanding the mandrel, which would arouse safe servicing problem. This study aimed to address the temperature rise issue in spindles through the use of substitutes in the spindle bearing material. To this end, we developed a spindle with a water-lubricated ceramic hydrodynamic and hydrostatic journal bearing. To support the selection of ceramic materials for the water-lubricated journal bearing, we initially performed application-oriented tests; to this end, the water absorption and porosity among alumina, silicon nitride, and silicon carbide were considered. To investigate the performance, and particularly the temperature characteristics of the hybrid bearing, a water-lubricated ceramic hydrodynamic and hydrostatic bearing test rig was designed to include temperature sensors. At the test rig, the radial clearance was measured for solving the temperature distribution of the bearing during the simulation. The experimental results helped verify that the water temperature increased by approximately 0.7°C as the rotation speed increased from 1200 rpm to 5400 rpm without an external radial load. The increase in temperature with and without radial load under a rotation speed of 3600 rpm was compared, and the results revealed a difference of 0.14°C. This indicates that the developed ceramic bearing improves the thermal stability of the spindle which shows its potential for industrial application in machine tools or other high rotation speed machines.

Extraction and enhancement of weak impulse signature is the key of rolling bearing fault prognostics in which case the features are often weak and covered by noise. Tunable Q-factor wavelet transform (TQWT), as an emerging wavelet construction theory developed in a frequency domain explicitly, has the advantages of matching with the specific oscillation behavior of signal components. In this article, an adaptive sparse representation (ASR) method is proposed, which integrates the sparse code shrinkage (SCS) and parameter optimization into TQWT. However, direct application of ASR is difficult to extract fault signatures at the early stage or low-speed operation due to weak fault symptoms and background noise. A novel fault diagnosis strategy based on continuous wavelet transform (CWT) and ASR is investigated. CWT owns significant advantages on multiscale subdivision and weak signal detection. The results of simulated and experimental vibration signal analyses verify the effectiveness of the proposed method in accurately extracting weak impulse features from the noise environment.