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        Legged robots have potential advantages in mobility compared with wheeled robots in outdoor environments. The knowledge of various ground properties and adaptive locomotion based on different surface materials plays an important role in improving the stability of legged robots. A terrain classification and adaptive locomotion method for a hexapod robot named Qingzhui is proposed in this paper. First, a force-based terrain classification method is suggested. Ground contact force is calculated by collecting joint torques and inertial measurement unit information. Ground substrates are classified with the feature vector extracted from the collected data using the support vector machine algorithm. Then, an adaptive locomotion on different ground properties is proposed. The dynamic alternating tripod trotting gait is developed to control the robot, and the parameters of active compliance control change with the terrain. Finally, the method is integrated on a hexapod robot and tested by real experiments. Our method is shown effective for the hexapod robot to walk on concrete, wood, grass, and foam. The strategies and experimental results can be a valuable reference for other legged robots applied in outdoor environments.

        Yue ZHAO ,   Feng GAO   et al.
        Mechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented.

        Xingzheng CHEN ,   Congbo LI   et al.
        Ultrasonic cutting with a disc cutter is an advanced machining method for the high-quality processing of Nomex honeycomb core. The machining quality is influenced by ultrasonic cutting parameters, as well as tool orientations, which are determined by the multi-axis machining requirements and the angle control of the cutting system. However, in existing research, the effect of the disc cutter orientation on the machining quality has not been studied in depth, and practical guidance for the use of disc cutters is lacking. In this work, the inclined ultrasonic cutting process with a disc cutter was analyzed, and cutting experiments with different inclination angles were conducted. The theoretical residual height models of the honeycomb core, as a result of the lead and tilt angles, were established and verified with the results obtained by a linear laser displacement sensor. Research shows that the residual height of the honeycomb core, as a result of the tilt angle, is much larger than that as a result of the lead angle. Furthermore, the tearing of the cell wall on the machined surface was observed, and the effects of the ultrasonic vibration, lead angle, and tilt angle on the tear rate and tear length of the cell wall were studied. Experimental results revealed that ultrasonic vibration can effectively decrease the tearing of the cell wall and improve the machining quality. Changes in the tilt angle have less effect than changes in the lead angle on the tearing of the cell wall. The determination of inclination angles should consider the actual processing requirements for the residual height and the machining quality of the cell wall. This study investigates the influence of the inclination angles of a disc cutter on the machining quality of Nomex honeycomb core in ultrasonic cutting and provides guidelines for machining.

        Yidan WANG ,   Renke KANG   et al.
        Deep learning has achieved much success in mechanical intelligent fault diagnosis in recent years. However, many deep learning methods cannot fully extract fault information to recognize mechanical health states when processing high-dimensional samples. Therefore, a multi-model ensemble deep learning method based on deep convolutional neural network (DCNN) is proposed in this study to accomplish fault recognition of high-dimensional samples. First, several 1D DCNN models with different activation functions are trained through dimension reduction learning to obtain different fault features from high-dimensional samples. Second, the obtained features are constructed into 2D images with multiple channels through a conversion method. The integrated 2D feature images can effectively represent the fault characteristic contained in raw high-dimension vibration signals. Lastly, a 2D DCNN model with multi-layer convolution and pooling is used to automatically learn features from the 2D images and identify the fault mode of the mechanical equipment by adopting a softmax classifier. The proposed method, which is validated using the bearing public dataset of Case Western Reserve University, USA and a one-stage reduction gearbox dataset, has high recognition accuracy. Compared with other classical deep learning methods, the proposed fault diagnosis method has considerable improvements.

        Xin ZHANG ,   Tao HUANG   et al.

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