Health condition is a vital factor affecting printing quality for a 3D printer. In this work, an attitude monitoring approach is proposed to diagnose the fault of the delta 3D printer using support vector machines (SVM). An attitude sensor was mounted on the moving platform of the printer to monitor its 3-axial attitude angle, angular velocity, vibratory acceleration and magnetic field intensity. The attitude data of the working printer were collected under different conditions involving 12 fault types and a normal condition. The collected data were analyzed for diagnosing the health condition. To this end, the combination of binary classification, one-against-one with least-square SVM, was adopted for fault diagnosis modelling by using all channels of attitude monitoring data in the experiment. For comparison, each one channel of the attitude monitoring data was employed for model training and testing. On the other hand, a back propagation neural network (BPNN) was also applied to diagnose fault using the same data. The best fault diagnosis accuracy (94.44%) was obtained when all channels of the attitude monitoring data were used with SVM modelling. The results indicate that the attitude monitoring with SVM is an effective method for the fault diagnosis of delta 3D printers.

The problems on designing time-optimal motion profile in the motion system with elasticity are briefly reviewed. Related positioning error and robustness constraints are constructed based on the analytic envelope of residual vibration response which is formulated by the proposed energy-based approach. The time-optimal model under such constraints is applied in the proposed freeform S-curve profile, which is the superset of symmetric S-curve and AS-curve profiles, and to minimize the positioning time while keeping positioning accuracy under a neighborhood range of modeling frequency. The optimized motion profile shows that the proposed freeform S-curve profile allows the time-optimal model to simultaneously optimize the magnitude and phase terms in residual vibration response in order to obtain an optimal trade-off between shortening positioning time and keeping positioning accuracy. The experiment results show that the proposed optimization model can significantly reduce the positioning time compared with traditional S-curve under the same physical limits. The universality of the optimization model is verified by experiments with short distance and long distance cases. The robustness of the proposed optimization model is also validated by these experiments. Moreover, the analysis on the optimized freeform S-curve profile reveals that perfect waveform cancellation is not always necessary to limit the residual vibration.

In this article, in order to improve the tracking ability of traditional active disturbance rejection control (ADRC) to the reference signal, the parallel multiple extended state observers (multi-ESOs) based ADRC is proposed. First, the way in which the estimation error of the ESO affects the tracking error of closed-loop system is studied, and it is shown that the tracking accuracy is not completely consistent with the estimation accuracy. Next, a novel switching ADRC approach with parallel multi-ESOs is proposed, in which the control law is constructed by automatically selecting different ESOs' estimations from the perspective of reducing tracking error, instead of reducing estimation error. Furthermore, the stability of the proposed algorithm is rigorously proved under some reasonable assumptions. In addition, the proposed ADRC is applied to the high-speed precision motion stage, which has complicated nonlinear uncertainties and elastic deformation disturbances. The experimental results show that the parallel multi-ESOs based ADRC has higher tracking performance than the traditional single ESO based ADRC.

The guiding mechanism based on flexure hinges (FHs) is widely used in micro/nano-manufacturing technology. Both the stiffness and the frequency of FHs play significant roles in their dynamic performance, so the design task of such a structure is to find the optimal topology and corresponding size of FHs under stiffness and frequency constraints. However, the existing optimization methods pay more attention to the stiffness than to the frequency constraint owing to difficulties in dynamic topology optimization. In this article, with the symmetrical layout assumption of FHs and the analytical equivalent stiffness and mass expression of a single FH, the simultaneous topology and size optimization problem is converted to an analytical optimization formula with both discrete and continuous variables. Finally, the tension stiffening effect is used to compensate for manufacturing errors. A design case is used to illustrate the efficiency of the proposed method.

Traditional high-speed precision motion stage (HSPMS) design pursues high-stiffness structure to achieve fast response. However, such structure leads to high-frequency disturbance near dead zone of friction, which causes poor performance in controlling HSPMS. To this end, this paper proposes the active disturbance rejection control (ADRC)-based mechanical design to reduce the bandwidth of friction disturbance and improve the control performance of HSPMS. It is proved that the low-frequency disturbance can be more effectively tackled by the extended state observer (ESO) in the frame of ADRC. In particular, rigid-flexible coupling (RFC) positioning stage is presented for converting the high-frequency friction disturbance into the low-frequency elastic deformation disturbance by flexure hinges. The experimental tests are carried out for both traditional stage and RFC stage. It is clearly shown that compared with traditional design, the control performance of RFC stage is remarkably promoted.

The voice-coil-motor (VCM) is widely adopted in chip packaging to achieve high-speed, large-stroke, and high-precision bonding operations. However, the inertial vibration, induced by high-speed high-acceleration motions, may cause significant impact on the chip pad, and affect the packaging efficiency and quality. To achieve a soft-landing chip contacting, the current method usually adopts a micro-gap searching area to tolerate the inertial vibration, and a low-speed uniform-motion is applied after the bonding head is settled down. In order to improve the operation efficiency and reduce the time used in the searching area, this paper presents a VCM active actuation (VAA) method to enable switching to the uniform-motion in advance and interfering the inertial vibration through the defined actuation conditions. The actuation moment condition is determined by the direction and energy of the inertial vibration, and the actuation amount condition is determined by the effect of the uniform-motion speed on the soft-landing performance. The VCM can be actuated at the right moment with a proper amount in the inertial vibration process to reduce the vibration and searching time, without affecting the rest low-speed soft-landing operation. Based on the simulations, the VAA method is tested experimentally and validated at different velocities, accelerations, and displacements.