Monitoring and Source Tracing of Machining Error Based on Built-in Sensor Signal

AbstractOnline monitoring and source tracing of machining error is of great significance for ensuring machining quality and improving machining efficiency. For an open numerical controller, the built-in sensors signals can be captured through driver interface in machining process. These signals contain various information of machining conditions of machine tool. The capture and analysis of the built-in sensors signals can be used for the online monitoring and source tracing of machining error. In this paper, an novel approach is developed for machining error monitoring and source tracing based on built-in sensor signal analysis and multi-body system theory. A ball screw grinding process was monitored, and the analysis results show the validity of the approach

Extended DMPs Framework for Position and Decoupled Quaternion Learning and Generalization

Abstract Dynamic movement primitives (DMPs) as a robust and efficient framework has been studied widely for robot learning from demonstration. Classical DMPs framework mainly focuses on the movement learning in Cartesian or joint space, and can't properly represent end-effector orientation. In this paper, we present an extended DMPs framework (EDMPs) both in Cartesian space and 2-Dimensional (2D) sphere manifold for Quaternion-based orientation learning and generalization. Gaussian mixture model and Gaussian mixture regression (GMM-GMR) are adopted as the initialization phase of EDMPs to handle multi-demonstrations and obtain their mean and covariance. Additionally, some evaluation indicators including reachability and similarity are defined to characterize the learning and generalization abilities of EDMPs. Finally, a real-world experiment was conducted with human demonstrations, the endpoint poses of human arm were recorded and successfully transferred from human to the robot. The experimental results show that the absolute errors of the Cartesian and Riemannian space skills are less than 3.5 mm and 1.0°, respectively. The Pearson’s correlation coefficients of the Cartesian and Riemannian space skills are mostly greater than 0.9. The developed EDMPs exhibits superior reachability and similarity for the multi-space skills’ learning and generalization. This research proposes a fused framework with EDMPs and GMM-GMR which has sufficient capability to handle the multi-space skills in multi-demonstrations

Femtosecond Laser Fabrication of Micro and Nano-Structures on CIGS/ITO Bilayer Films for Thin-Film Solar Cells

Cu(In, Ga)Se2 (CIGS) thin films have attracted considerable interest as potential photovoltaic solar cells. Moreover, several current studies are focusing on improving their conversion efficiency. This study proposes a method to process micro- and nanostructures onto the surface of CIGS/ITO bilayer films to broaden the field of solar cell application. The bilayer films exhibited optical characteristics different from those of a single-film during processing. Field intensities at different layer positions of the CIGS/ITO bilayer films were analyzed, and different structures were fabricated by varying a set of parameters. Ripples were obtained using a pulse energy of 0.15 μJ and scanning speeds in the range of 0.1–1 mm/s, but after increasing speed to 3–5 mm/s, ripple structures were produced that had a large period of several microns and spatial porous nanostructures. This pattern exhibited low reflectivity. Optimal structures were obtained at a scanning speed of 3.5 mm/s a pulse energy of 0.15 μJ, and a reflectivity lower than 5%. Large areas characterized by micron-sized ripple structures and accompanied by nanoscale porous structures presented high optical performance and efficiency, which can be used to broaden the application of thin film-based solar cells

A Novel Deep Learning Approach for Machinery Prognostics Based on Time Windows

Remaining useful life (RUL) prediction is a challenging research task in prognostics and receives extensive attention from academia to industry. This paper proposes a novel deep convolutional neural network (CNN) for RUL prediction. Unlike health indicator-based methods which require the long-term tracking of sensor data from the initial stage, the proposed network aims to utilize data from consecutive time samples at any time interval for RUL prediction. Additionally, a new kernel module for prognostics is designed where the kernels are selected automatically, which can further enhance the feature extraction ability of the network. The effectiveness of the proposed network is validated using the C-MAPSS dataset for aircraft engines provided by NASA. Compared with the state-of-the-art results on the same dataset, the prediction results demonstrate the superiority of the proposed network

Ablation experiment and threshold calculation of titanium alloy irradiated by ultra-fast pulse laser

The interaction between an ultra-fast pulse laser and a material's surface has become a research hotspot in recent years. Micromachining of titanium alloy with an ultra-fast pulse laser is a very important research direction, and it has very important theoretical significance and application value in investigating the ablation threshold of titanium alloy irradiated by ultra-fast pulse lasers. Irradiated by a picosecond pulse laser with wavelengths of 1064 nm and 532 nm, the surface morphology and feature sizes, including ablation crater width (i.e. diameter), ablation depth, ablation area, ablation volume, single pulse ablation rate, and so forth, of the titanium alloy were studied, and their ablation distributions were obtained. The experimental results show that titanium alloy irradiated by a picosecond pulse infrared laser with a 1064 nm wavelength has better ablation morphology than that of the green picosecond pulse laser with a 532 nm wavelength. The feature sizes are approximately linearly dependent on the laser pulse energy density at low energy density and the monotonic increase in laser pulse energy density. With the increase in energy density, the ablation feature sizes are increased. The rate of increase in the feature sizes slows down gradually once the energy density reaches a certain value, and gradually saturated trends occur at a relatively high energy density. Based on the linear relation between the laser pulse energy density and the crater area of the titanium alloy surface, and the Gaussian distribution of the laser intensity on the cross section, the ablation threshold of titanium alloy irradiated by an ultra-fast pulse laser was calculated to be about 0.109 J/cm2

A Refined Dynamic Model of Harmonic Drive and Its Dynamic Response Analysis

To highlight the key factors which influence the dynamic performance of the harmonic drive, a refined harmonic drive model considering nonlinear stiffness, kinematic error, and friction of the critical components is established. A dedicated experimental apparatus based on double motor twisting is constructed to measure the characteristics of harmonic drive, and the attribute parameters of the proposed model are identified. A series of experiments on the dynamic transmission error at different driving velocities are carried out to verify the proposed model. Based on the proposed model, the influence of different component stiffness on the velocity step response of the harmonic drive is analyzed. The results show that the influence of the component stiffness on the system dynamic response is more significant at high driving velocity, the increase of the stiffness of each component will decrease the dynamic transmission accuracy of harmonic drive, and the bearing radial stiffness is the most sensitive parameter to system’s dynamic response among all the stiffness factors

Investigation on a No Trial Weight Spray Online Dynamic Balancer

In order to suppress the spindle vibration with high efficiency and high precision, a no without trial weight spray online balance method is proposed in this paper. By analyzing the relationship between the unbalanced excitation and the unbalanced response of the spindle, the relationship between the dynamic influence coefficient and the system model is studied. A high-speed spindle finite element analysis model was established, and the dynamic influence coefficient matrix was identified. A no trial weight spray online dynamic balancing system was developed, which has the advantages of without trial weight and high-precision loading. A new type of integrated balancing terminal that was formed using 3D printing technology was first proposed by our research group, and its advantages in various aspects are significantly higher than traditional assembly balanced terminals. The experimental verification of the without trial weight spray online dynamic balancing system was performed on a high-speed spindle test stand. Experiments show that the no trial weight spray online balancing method proposed in this paper can achieve high-efficiency and high-precision vibration suppression, greatly reducing balance time and cost of the spindle. At the same time, the online balance test also verified the reliability of the integrated balanced terminal

Formation of Porous Structure with Subspot Size under the Irradiation of Picosecond Laser Pulses

A study was presented in this paper on porous structure with microsize holes significantly smaller than laser spot on the stainless steel 304 target surface induced by a picosecond Nd:van regenerative amplified laser, operating at 1064 nm. The target surface variations were studied in air ambience. The estimated surface damage threshold was 0.15 J/cm2. The target specific surface changes and phenomena observed supported a complementary study on the formation and growth of the subspot size pit holes on metal surface with dependence of laser pulse number of 50–1000 and fluences of 0.8 and 1.6 J/cm2. Two kinds of porous structures were presented: periodic holes are formed from Coulomb Explosion during locally spatial modulated ablation, and random holes are formed from the burst of bubbles in overheated liquid during phase explosion. It can be concluded that it is effective to fabricate a large metal surface area of porous structure by laser scanning regime. Generally, it is also difficult for ultrashort laser to fabricate the microporous structures compared with traditional methods. These porous structures potentially have a number of important applications in nanotechnology, industry, nuclear complex, and so forth

Microservices-based cloud-edge collaborative condition monitoring platform for smart manufacturing systems

10.1080/00207543.2022.2098075International Journal of Production Research60247492-750