Subjects: Mechanical Engineering >> Mechanical Manufacture and Automation submitted time 2024-01-07
Abstract： In recent years, with the rapid development of the chemical industry and information combination, the data produced in the chemical refining system presents explosive growth. Alarm system is a kind of transmitting equipment abnormal state information to the operator of the system, but if the design is not reasonable, the equipment under abnormal state process may produce a large number of alarm and alarm saturation phenomenon, the serious influence the operator's information processing ability, thus increasing the probability of all kinds of industrial accidents. Therefore, how to mine useful information from the massive alarm logs is very important, and use the mined information to give positive guidance to the complex refining process. Deep learning is a method that can automatically learn and extract features from data. It does not require manual construction of complex and accurate physical and mathematical models, so it has been widely applied and paid attention to in the field of data prediction and classification.
Peer Review Status:
Awaiting Review
Subjects: Mechanical Engineering >> Mechanical Manufacture and Automation submitted time 2022-10-21
Abstract： With growing interest in Laser Additive Manufacturing (LAM) of High-entropy alloys (HEAs) during most recent years, compositional elements design and process strategies innovation are primary methods to overcome undesirable microstructures and defects. Here we propose a new approach, a novel real-time laser shock modulation of melt pool (LSMMP) to obtain melt pool modifications for yielding HEAs with desired characteristics. LSMMP utilizes a pulsed laser shocking a liquid melt pool caused by a continuous wave laser, enabling non-destructive and real-time modulations for high-performance HEAs. The numerical simulation reveals the convection mechanism of the melt pool in the LSMMP process, and the intervention of the pulsed laser promotes melt pool flow type to convert the Marangoni effect into a multi-convective ring, which accelerates melt pool flow and inhibits columnar crystal growth. Experimental results show the evolution law of the microstructure in the LSMMP process. The microstructure of CrFeCoNi HEAs undergoes a Columnar-Equiaxed Transition (CET), and higher hardness is obtained. Laser shock is demonstrated to be an effective in-situ modulative tool for controlled additive manufacturing.
Subjects: Mechanical Engineering >> Mechanical Manufacture and Automation submitted time 2022-09-26 Cooperative journals: 《桂林电子科技大学学报》
Abstract：
To test the rationality of the power system for a fuel cell commercial vehicle, the models of energy source (including fuel cell stack and battery pack), electric motor system (including electric motor and its controller) and driveline are built in Matlab. A global optimization energy management strategy based on dynamic programing is adopt to analysis the vehicle’s fuel economy with the European typical drive cycle under three load modes (including no-load, half-load and fullload). Simulation results show that the energy source employed satisfy the vehicle’s power requirements at the selected drive cycle, while with the increase of on-board load, the terminal SOC of battery gradually deviates from the initial value, which will limit the commercial vehicle’s dynamic performance in the long term cycles with a large on-board load. Verification results for the vehicle point that great power on-board fuel cell stack should be considered in the following research and vehicle verification.
Subjects: Mechanical Engineering >> Mechanical Manufacture and Automation submitted time 2022-09-26 Cooperative journals: 《桂林电子科技大学学报》
Abstract： Aiming at the problem of low efficiency caused by complex and redundant calculation of robot dynamics model, a
programmed modeling method is proposed. Taking the Stanford Arm with six degrees of freedom as an example, the dynamic
model based on Lagrangian equation is established by using this method. According to the core idea of "forward analysis,
reverse output", the recursive process of the model is analyzed emphatically. On the basis of verifying the correctness of
the model, the indexes such as the dimensions and running time of the Stanford Arm model based on the PMM and the conventional
Lagrange equation without the use of the PMM are compared. The results show that relative to the conventional
Lagrange method, the complexity of the model established by PMM is reduced by 67.6%, and the computational efficiency
is increased by 66.3%. Stanford Arm is a complete constrained system. PMM is extended to underactuated nonholonomic
constrained systems, numerical simulation and physical prototype experiment analysis are carried out by using partial feedback
linearization control algorithm which is closely related to the model, it’s reliability and effectiveness of the programmed
modeling method are verified, which provides a modeling method with higher efficiency and better versatility for different
types of robots.
Subjects: Mechanical Engineering >> Mechanical Manufacture and Automation submitted time 2022-05-31
Abstract：
With growing interest in Laser Additive Manufacturing (LAM) of High-entropy alloys (HEAs) during most recent years, the design of compositional elements and process strategies are primary methods to overcome undesirable microstructures and defects. Here we propose a new approach, a novel real-time Laser Shocking of Melt Pool (LSMP), to obtain melt pool modifications for yielding HEAs with desired characteristics. LSMP utilizes a pulsed laser shocking a liquid melt pool caused by a continuous wave laser, enabling non-destructive and real-time modulations for high-performance HEAs. The numerical simulation reveals the convection mechanism of the melt pool in the LSMP process, and the intervention of the pulsed laser promotes melt pool flow type to convert the Marangoni effect into a multi-convective ring, which accelerates melt pool flow and inhibits columnar crystal growth. Experimental results show the evolution law of the microstructure in the LSMP process. The microstructure of CrFeCoNi HEAs undergoes a Columnar-Equiaxed Transition (CET), and higher hardness is obtained. Laser shock is demonstrated to be an effective in-situ modulative tool for controlled additive manufacturing.
Peer Review Status:Awaiting Review
Subjects: Mechanical Engineering >> Mechanical Manufacture and Automation submitted time 2018-03-16
Abstract：根据移栽蔬菜田间锄草作业工况和要求，基于视觉伺服控制技术，设计了电驱锄草机器人系统。该系统以中小功率拖拉机为配套动力，由伺服电动机驱动月牙形锄草刀护苗锄草和对行，减少了能耗与污染物排放，提高了系统伺服特性。机器视觉系统实时采集田间图像并处理，对作物进行识别与定位。控制器结合视觉系统获取的刀苗距、锄草机器人前进速度、锄刀相位角度及机器人横向偏差信息，利用智能伺服驱动器精确控制锄草刀避苗和对行。试验表明，在前进速度不高于1.5km/h、作物株距不小于0.35m工况下，伤苗率小于10%，田间杂草锄净率约为90%。
Peer Review Status:Awaiting Review
Subjects: Mechanical Engineering >> Mechanical Manufacture and Automation submitted time 2018-03-16
Abstract：A machine-vision-based method of locating crops is described in this research. This method was used to provide real-time positional information of crop plants for a mechanical intra-row weeding robot. Within the normalized red, green, and blue chromatic coordinates (rgb), a modified excess green feature (g-r>T & g-b>T) was used to segment plant material from back ground in color images. The threshold T was automatically selected by the maximum variance (OTSU) algorithm to cope with variable natural light. Taking into account the geometry of the camera arrangement and the crop row spacing, the target regions covering the crop rows were defined based on a pinhole camera model. According to the statistical variation in the pixel histogram in each target region, locations of the crop plants were initially estimated. To obtain the accurate locations of crops, median filtering was conducted locally in the bounding boxes of the crops close to the bottom of the images. For the lateral guidance of the robot, a novel method of calculating lateral offset was proposed based on a simplified match between a template and the detected crops. Field experiments were conducted under three different illumination conditions. The results showed that the accurate identification rates on lettuce, cauliflower and maize were all above 95%. The positional error as within ±15 mm, and the average processing time for a 640×480 image was 31 ms. The method was adequate to meet the technical requirement of the weeding robot, and laid a foundation for robotic weeding in commercial production system.
Peer Review Status:Awaiting Review
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