Design of a Servo Mechanical Press with Redundant Actuation

A servo press is a new type of mechanical press that is driven by programmable motors and offers superior performance such as low noise, excellent efficiency and high precision for metal forming operations. Similar to multi-link mechanical presses, a servo mechanical press tends to grow in size as the tonnage increases that calls for larger, heavy duty servo motors, which could be expensive and may not even be available. In this paper, a new concept of servo mechanical press with redundant actuation is proposed firstly using two servo motors driving one input shaft, i.e. one-point-two-motor mode that makes it possible to produce a larger press with available servomotors. Then the punching mechanism design is detailed. The performance indices are set up including mechanical advantage reciprocal and link force ratios. A bounded feasible solution space is constructed for dimensional synthesis based on non-dimensional link lengths and assembly conditions. The performance atlases are depicted over the bounded feasible solution space that lead to a visual solution of the punching mechanism with global optimization. Finally, case studies are given to illustrate the design method with visual global optimization, and a prototype with 200 t punching force is being developed in our laboratory to demonstrate efficacy of the new concept for servo mechanical press. The presented research provides a feasible solution to the development of heavy-duty servo mechanical presses and finds potential applications in the development of other types of heavy equipments with electric drive.

Rock characterization while drilling and application of roof bolter drilling data for evaluation of ground conditions

Despite recent advances in mine health and safety, roof collapse and instabilities are still the leading causes of injury and fatality in underground mining operations. Improving safety and optimum design of ground support requires good and reliable ground characterization. While many geophysical methods have been developed for ground characterizations, their accuracy is insufficient for customized ground support design of underground workings. The actual measurements on the samples of the roof and wall strata from the exploration boring are reliable but the related holes are far apart, thus unsuitable for design purposes. The best source of information could be the geological back mapping of the roof and walls, but this is disruptive to mining operations, and provided information is only from rock surface.Interpretation of the data obtained from roof bolt drilling can offer a good and reliable source of information that can be used for ground characterization and ground support design and evaluations. This paper offers a brief review of the mine roof characterization methods, followed by introduction and discussion of the roof characterization methods by instrumented roof bolters. A brief overview of the results of the preliminary study and initial testing on an instrumented drill and summary of the suggested improvements are also discussed.

Planning-oriented optimization strategy for visualizing power distribution networks:from global to local

The spatial distribution of power facilities is uneven,thereby making the topology of geographical wiring diagrams(GWDs)based on the actual coordinates unclear.A single-line diagram has the advantage of a clear topology but it lacks spatial locations.A GWD has the advantage of accurate spatial locations but it lacks a clear topology.Visualizing distribution networks for planning requires both features.We proposed a new planning-oriented method for optimizing the visualization of distribution networks.From the global perspective,we proposed an improved force-directed(FD)algorithm by introducing a space restriction strategy and node–edge repulsion strategy to promote the expansion of the distance between distribution facilities within a limited buffer.We then constructed the constrained Delaunay triangulation to identify the compact districts(CDs)and used a genetic algorithm to optimize the parameters for the improved FD algorithm.A novel visualization evaluation indicator was also proposed for quantitatively assessing the visualizations.From a local perspective,the fisheye algorithm was used to optimize the CDs to further improve the visualization of the distribution network.We verified the proposed methods with real-world data.We used limited spatial displacement in exchange for maximum topology clarity to balance the accurate spatial location and topology clarity.