No abstract

Laser-based additive manufacturing (LBAM) is a promising manufacturing technology that can be widely applied in solid freeform fabrication (SFF), component recovery and regeneration, and surface modification. The thermal behaviour of the molten pool is one of the critical factors that influences laser deposition indices such as geometrical accuracy, material properties and residual stresses. In this paper, a three-dimensional finite element model is developed using ANSYS to simulate the thermal behaviour of the molten pool in building a single-bead wall via a closed-loop controlled LBAM process in which the laser power is controlled to keep the width of the molten pool constant. The temperature distribution, the geometrical feature of the molten pool and the cooling rate under different process conditions are investigated. To verify the simulation results, the thermal behaviour of the molten pool is measured by a coaxially installed infrared camera in experimental investigations of a closed-loop controlled LBAM process. Results from finite element thermal analysis provide guidance for the process parameter selection in LBAM, and develop a base for further residual stress analysis.

No abstract

No abstract

Solid freeform fabrication (SFF) methods for metal part building, such as three-dimensional laser cladding, are generally less stable and less repeatable than other rapid prototyping methods. A large number of parameters govern the three-dimensional laser cladding process. These parameters are sensitive to the environmental variations, and they also influence each other. This paper introduces the research work in Research Center for Advanced Manufacturing (RCAM) to improve the performance of its developed three-dimensional laser cladding process: laser-based additive manufacturing (LBAM). Metal powder delivery real-time sensing is studied to achieve a further controllable powder delivery that is the key technology to build a composite material or alloy with a functionally gradient distribution. An opto-electronic sensor is designed to sense the powder delivery rate in real time. The experimental results show that the sensor's output voltage has a good linear relationship with the powder delivery rate. A closed-loop control system is also built for heat input control in the LBAM process, based on infrared image sensing. A camera with a high frame rate (up to 800frame/s) is installed coaxially to the top of the laser—nozzle set-up. A full view of the infrared images of the molten pool can be acquired with a short nozzle—substrate distance in different scanning directions, eliminating the image noise from the metal powder. The closed-loop control results show a great improvement in the geometrical accuracy of the built feature.

No abstract

The aging population is now a global challenge, and impaired walking ability is a common feature in the elderly. In addition, some occupations such as military and relief workers require extra physical help to perform tasks efficiently. Robotic hip exoskeletons can support ambulatory functions in the elderly and augment human performance in healthy people during normal walking and loaded walking by providing assistive torque. In this review, the current development of robotic hip exoskeletons is presented. In addition, the framework of actuation joints and the high-level control strategy (including the sensors and data collection, the way to recognize gait phase, the algorithms to generate the assist torque) are described. The exoskeleton prototypes proposed by researchers in recent years are organized to benefit the related fields realizing the limitations of the available robotic hip exoskeletons, therefore, this work tends to be an influential factor with a better understanding of the development and state-of-the-art technology.

This paper presents a novel algorithm for detecting pavement cracks from mobile laser scanning (MLS) data. The algorithm losslessly transforms MLS data into a regular grid structure to adopt the proven image-based methods of crack extraction. To address the problem of lacking topology, this study assigns a two-dimensional index for each laser point depending on its scanning angle or acquisition time. Next, crack candidates are identified by integrating the differential intensity and height changes from their neighbors. Then, morphology filtering, a thinning algorithm, and the Freeman codes serve for the extraction of the edge and skeleton of the crack curves. Further than the other studies, this work quantitatively evaluates crack shape parameters: crack direction, width, length, and area, from the extracted crack points. The F1 scores of the quantity of the transverse, longitudinal, and oblique cracks correctly extracted from the test data reached 96.55%, 87.09%, and 81.48%, respectively. In addition, the average accuracy of the crack width and length exceeded 0.812 and 0.897. Experimental results demonstrate that the proposed approach is robust for detecting pavement cracks in a complex road surface status. The proposed method is also promising in serving the extraction of other on-road objects.