Bowen Zhong

Automatic focusing Stage is an important part of automatic focusing system, a 3-DOF (z-axis displacement and XY axis tilt) Multi-Depth-Of-Field Carrier Automatic Focusing Stage (CAFS) is designed, manufactured and tested in this paper. The stage is driven by four piezoelectric (PZT) actuators. Based on four bridge amplifying mechanisms, large displacement travel and tilt Angle are obtained. Compared with other focusing stages, the developed stage adopts the focusing mode of directly adjusting the spatial position of the sample to realize focusing, which not only avoids the inherent defects of objective focusing mode, but also has the advantages of compact structure, low shape and overall manufacturing. In this paper, the structural parameters and the overall design of the stage are determined, and then the characteristics of the focusing stage are finite element analyzed. Finally, the performance of the focusing stage is studied experimentally. The maximum Z-axis output displacement of the focusing stage is 213.5 μm, and the maximum X-direction and Y-direction tilt angles are 1.5 and 1.7 mrad, respectively. For the application of CAFS, the practicability of CAFS is verified by Z-axis image superposition acquisition method in automatic focusing system.

Piezoelectric objective driver positioners are increasingly used in the field of microscopy. They have the advantages of high dynamic and fast response. This paper presents a fast autofocus algorithm for highly interactive microscope system. First, the Tenengrad gradient of the down‐sampled image is used to calculate the image sharpness, and Brent search method is adopted to quickly converge to the correct focal length. At the same time, the input shaping method is used to eliminate the displacement vibration of the piezoelectric objective lens driver and further accelerate the image acquisition speed. Experimental results show that the proposed scheme can improve the speed of the automatic focusing task of the piezoelectric objective driver and improve the real‐time focus of the automatic microscopic system.Highlights: A high real‐time autofocus strategy. A vibration control method suitable for a piezoelectric objective driver.

Piezoelectric actuators are characterized by high positioning accuracy, high stiffness and a fast response and are widely used in ultra-precision machining technologies such as fast tool servo technology and ultrasonic machining. The rapid response characteristics of piezoelectric actuators often determine the overall quality of machining. However, there has been little research on the fast response characteristics of piezoelectric actuators, and this knowledge gap will lead to low precision and poor quality of the final machining. The fast response characteristics of a piezoelectric actuator were studied in this work. Firstly, the piezoelectric actuator was divided into a no-load state and a load state according to the working state. A fast response analysis and output characteristic analysis were carried out, the corresponding dynamic model was established, and then the model was simulated. Finally, an experimental system was established to verify the dynamic model of the piezoelectric actuator’s fast response by conducting an experiment in which the piezoelectric actuator bounces a steel ball. The experimental results verify the correctness of the model and show that the greater the cross-sectional area and height of the piezoelectric actuator, the higher the bouncing height of the ball, and the better the dynamic performance of the piezoelectric actuator. It is believed that this study has guiding significance for the application of the dynamic characteristics of piezoelectric actuators in the machining field.

The piezoelectric actuator has been widely used in modern precision cutting technology due to its fast response speed and high positioning accuracy. In recent years, with the development of precision technology, modern cutting requires higher and higher cutting accuracy and efficiency. Therefore, this paper proposes a feedforward control method based on the modified Bouc–Wen (MBW) model. Firstly, a novel asymmetrical modified Bouc–Wen model with an innovative form of shape control function is developed to model the hysteresis nonlinearity property of piezoelectric actuators. Then, a self-adaptive cooperative particle swarm optimization (PSO) algorithm is developed to identify the parameters of MBW model. The comparative evaluation reveals that the MBW model outperforms the classical Bouc–Wen (CBW) model by 66.4% in modeling accuracy. Compared with traditional PSO algorithm, the self-adaptive cooperative PSO algorithm can obtain minimum fitness in parameter identification. Furthermore, the feedforward control strategy is realized to improve the position tracking accuracy. A position tracking experiment verifies that the feedforward control strategy improves the tracking accuracy of piezoelectric actuators significantly compared with the open-loop control strategy.

This paper presents an improved autofocus method for human red blood cell images in a microscope. The products of the sum modulus difference and the real-valued fast Fourier transform function are multiplied to obtain an improved sharpness evaluation using the properties of a Gaussian function. It is superior to traditional evaluations in terms of unimodality, steepness, and sensitivity. A new quantitative criterion is proposed to represent the ability of sharpness evaluation against noise. An adaptive focus window with great robustness is proposed that can reduce the computation cost and adverse effects of the background. The better performances of the proposed algorithms are all proved by experiment results, and they can help to find the quasi-focus position more quickly and accurately.