Keqing Lu

Bio: Keqing Lu is an academic researcher from Hangzhou Dianzi University. The author has contributed to research in topics: Capacitive sensing & Hysteresis. The author has an hindex of 5, co-authored 27 publications receiving 83 citations.

A new hysteresis modeling and optimization for piezoelectric actuators based on asymmetric Prandtl-Ishlinskii model

Abstract: Piezoelectric actuators are core components in micromanipulation systems in the field of biomedicine. The asymmetrical hysteresis of piezoelectric actuators greatly affects its performance, and the existing asymmetric hysteresis models are either inaccurate or complicated. In this paper, an accurate and simple asymmetric hysteresis model is proposed based on the Prandtl-Ishlinskii (PI) model. Firstly, the Play operator is modified to be asymmetric to enhance its flexibility, and the influence of parameters on the operator is analyzed. Secondly, the Asymmetric Prandtl-Ishlinskii (API) model is proposed based on the asymmetric Play operator and verified by experiment. Compared with several existing models, the API model can describe the asymmetric hysteresis in a more accurate and simple manner under the same conditions. Thirdly, the parameters of the API model are optimized. Compared with the unoptimized API model, the optimized one can reduce the number of parameters and maintain high accuracy. Furthermore, the influence of the order on accuracy is discussed, and a guidance for selection of the order is provided. Last but not least, the optimized API model is used to compensate for the hysteresis. The experimental results show that the compensator based on this model can effectively suppress the hysteresis of the piezoelectric actuator.

A multi-sensor approach for rapid and precise digitization of free-form surface in reverse engineering

Abstract: Reverse engineering (RE) has emerged as a crucial tool in product design for facilitating reuse of design and relevant knowledge, by which new design can be accelerated. Reconstruction of free-form surface is the main focus of RE. To meet the demand of rapidly and precisely digitizing unknown complex free-form surface, which is the first step of RE, a multi-sensor approach characterized by an integrated use of a contact scanning probe (SP) and a point laser probe (PLP) is proposed. Both of the two digitizers are mounted on the Z axis arm of a coordinate measuring machine (CMM), and the distance between the laser beam of the PLP and the stylus of the SP in feed motion direction is adjusted to be equal to the specified scanning line spacing, so that the PLP is capable of measuring SP’s next scanning path as the SP is performing digitization task. With the priori path information acquired using PLP, measurement path planning algorithms are applied to program the next scanning path for SP real-timely. The planned scanning path can be subsequently used to automatically guide the SP and the CMM for fast and precise digitization of complex surfaces. A prototype system has been developed to demonstrate the feasibility of the proposed new method through experiment. Experimental results indicate that the proposed approach enables rapid, flexible, and high-precision digitization of complex free-form surface in reverse engineering.

Cavitation and flow forces in the flapper-nozzle stage of a hydraulic servo-valve manipulated by continuous minijets:

Abstract: Electro-hydraulic servo-valves play key roles in modern electro-hydraulic power systems in many industrial applications. As one of the widely used hydraulic servo-valves, cavitation in the flapper-...

Advances in self-powered triboelectric pressure sensors

Abstract: Pressure sensors have attracted much attention for their potential applications in health monitoring, wearable devices, electronic skins, smart robots, etc. With the rapid development of the Internet of Things, considering the large number and small scale of sensors, power consumption has become a key factor in large-scale applications. A new generation of self-powered pressure sensors based on a triboelectric nanogenerator has been developed in terms of its incomparable advantages in power consumption and potential performance. Based on the coupling effects of triboelectrification and electrostatic induction, it enables obtaining information on the mechanical input, e.g., magnitude and frequency, by analyzing the electrical output signals. Intensive efforts have been devoted to improving the sensing performance of triboelectric pressure sensors to meet the demands of practicality. In this review, the key advancements in materials, structures and applications of self-powered triboelectric pressure sensors are systematically reviewed. Then, the theoretical basis, impact mechanism and approaches to optimize the pressure sensing performance have been comprehensively analyzed. Finally, the future perspectives of self-powered triboelectric pressure sensors have also been discussed.

Review of reverse engineering systems – current state of the art

Abstract: Reverse engineering (RE) has been widely applied in many segments of industry when digital or geometric models of existing physical objects are unavailable. This paper details components of RE systems and describes the needs for RE in manufacturing industries. Commonly used contact and non-contact scanning techniques are described. Possible interfaces with other manufacturing processes, especially 3D printing (3DP), are discussed. This paper also describes new trends in the field that include increased speed, accuracy, and level of automation in the future. Finally, a discussion on two major tolerance issues in terms of integrating RE and 3DP are presented.

Adaptive machining for curved contour on deformed large skin based on on-machine measurement and isometric mapping

Abstract: Curved contour on large thin-walled skin is difficult to be machined since severe deformations usually occur on real skin. It is critical to determine the real geometry of the deformed contour. Under the assumption that only the normal deformation of the large thin-walled skin occurs and the shear deformation is ignored, a novel isometric mapping based adaptive machining method is developed. While straightness distance or local angle is preserved in traditional surface mapping methods, arc-length is preserved in proposed isometric mapping to improve the contour cutting accuracy. The proposed method consists of three steps. (1) The real geometry of the deformed surface is obtained by using a laser scanner based on-machine measurement (OMM) system. The measured point cloud is then transformed into triangular mesh to represent the deformed surface. Some points on the nominal surface are sampled based on uniform sampling strategy, and the corresponding sampling points in the deformed surface are also allocated. (2) Isometric mapping between the two groups of points is constructed. Matching accuracy between nominal surface and real surface is defined based on the deviation of the geodesic distances of the two groups of points. A surface matching optimization model is developed to adjust the mapping point location in the triangular mesh and achieve a minimum surface mismatch error. (3) The toolpath is adaptively adjusted to compensate the deformation error based on the isometric surface mapping results. Both simulation and machining experiments are conducted to demonstrate the feasibility and validity of the proposed method. The experiment results show that accuracy of the machined curved contour on the deformed skin has been significantly improved.

Laser-based directed energy deposition (DED-LB) of advanced materials

Abstract: Directed energy deposition (DED) has matured into an essential additive manufacturing (AM) branch. DED has been broadly implemented in the design and fabrication of novel materials. These include metals, ceramics, and composites. Successful DED operation requires a good understanding of many critical phenomena, including laser-material interactions, fundamentals of casting and solidification of alloys, welding metallurgy and joining interfaces, along with microstructure-mechanical properties relations. Also critical are powder flowability, heat transfer, and various machine-related parameters. Several review articles have been published in recent years on metal AM via powder bed fusion (PBF) and DED, focusing on either a specific material system, mapping the recent technologies for AM, or issues related to the deposition process or material properties. Yet, no recent review is dedicated to a comprehensive presentation of material systems, design, fabrication, challenges, and the relationship between microstructures and mechanical properties of various DED'ed material families. Since the DED-based approach is becoming popular to manufacture bimetallic and multi-material structures, repair high-value structures, and alloy design, this comprehensive review focuses on materials design via DED, including a survey of a variety of monolithic and multi-material compositions. Finally, the critical challenges and opportunities in this area are highlighted.

Neuro-intelligent networks for Bouc–Wen hysteresis model for piezostage actuator

Abstract: Piezoelectric stage has become promising actuator for wide applications of micro-/nano-positioning systems represented mathematically with Bouc–Wen hysteresis model to examine the efficiency. In this investigation, the numerical study of piezostage actuator based on nonlinear Bouc–Wen hysteresis model is presented by neurocomputing intelligence via Levenberg–Marquardt backpropagated neural networks (LMB-NNs). Numerical computing strength of Adams method is implemented to generate a dataset of LMB-NNs for training, testing and validation process based on different scenarios of input voltage signals to piezostage actuator model. The performance of LMB-NNs of nano-positioning system model is validated through accuracy measures on means square error, histogram illustrations and regression analysis.