Jiafan Zhang

A Novel Mechanical Gas-Tight Sampler for Hydrothermal Fluids

A new mechanical gas-tight sampler has been designed to collect hydrothermal fluids at the seafloor. A key feature of the sampler is the novel sample valve which is pressure balanced under deep sea, and actuated by the ram on a submersibles manipulator. The sampler is designed to be deployed at the seafloor 3000 m underwater and can be used to sample hydrothermal fluid with temperature up to 400degC. Compressed gas is used to compensate for pressure reduction of sample fluids. Simulation of the flow system was conducted to estimate the fill rate. The sampler has been tested successfully in the first Sino-American Cooperative Deep Submergence Project from August 13 to September 3, 2005.

A Novel DGO Based on Pneumatic Exoskeleton Leg for Locomotor Training of Paraplegic Patients

This work introduces a new driven gait orthosis (DGO) based on the pneumatical exoskeleton leg for locomotor training. This device can drive the lower-limb of a patient in a physiological way on the moving treadmill following the given gait which fits to the individual needs. Therefore, it can help a patient who suffers lower-limbs paralysis to recover his walking ability. Mechanisms were designed based on the optimization from the view of human gait and the Ergonomics. Displacement sensors were mounted to allow a closed-loop control consequently to make each limbs motion as similar as possible to that of the human specimen. Each actuator is controlled by an algorithm, which consists of fuzzy and bang-bang. This solution allowed the existing strong nonlinearities to be easily managed with high response. The satisfying experiments results demonstrated the effect of the hybrid algorithm.

LCM cycle based optimal scheduling in robotic cell with parallel workstations.

Robot-centered cells play a more and more important role in the fields of incorporate automation and repetitive processing in order to increase productivity and to improve quality. In practice, it is always desired to achieve maximum/near-maximum throughput in a robotic cell. Sometimes, even a small improvement in throughput will be one of the highlighted objectives in robot scheduling, for instance, in the 3C industry of communication, computer and consumer electronics. In this paper, the scheduling problem in an n-workstation (n<;=8) m-stage robotic cell with parallel workstations is discussed by considering the constraints in real engineering practice, including free/non-free pick-up, allowed time window, and free/non-free process. A new method is proposed for optimal scheduling by means of optimally arranging each blocked cycles in every LCM cycle (Least Common Multiple), and assembling them in a proper order. This method is applied to a practical scheduling problem for a 7-workstation robotic cell. It is shown that the throughput is dramatically enhanced after optimization in the engineering scenario. Moreover, by comparing the resultant increase in revenue with the additional equipment costs, the result diagrams also provide managerial insights into links between throughput and cell layout flexibility.