scholarly journals Gear Mapping Technology Based on Differential Envelope Principle

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yangpeng Liu ◽  
Jingyang Guo ◽  
Jianjun Ding ◽  
Duanzhi Duan ◽  
Yuerong Jiang ◽  
...  
Keyword(s):  
Intelligent Manufacturing ◽  
Machining Parameters ◽  
Molding Process ◽  
Cylindrical Gear ◽  
Intelligent Analysis ◽  
Mapping Technology ◽  
Contact Sensor ◽  
Complex Linear ◽  
Scale Difference ◽  
Reverse Method

It is proposed that the complex molding process and the scanning process should be unified through the differential envelope principle. After scanning the surface of the part with the contact sensor, the contour coordinates of the measured surface are calculated by the trajectory of the center of the ball, and the contour data of the complex linear surface is extracted. Then, the intelligent analysis and calculation of precision generating surface parameters and quantitative adjustment are carried out, and the exact reverse method of the special line parts with characteristic parameters is studied. There is only micron scale difference between the reverse result and the nominal value. This technology is applied to the closed-loop manufacturing process of gear parts, which reduces the dependence on the artificial experience when the machining parameters of the cylindrical gear processing equipment is adjusted and provides an effective solution for the digital and intelligent manufacturing of the parts.

Development of a Laser Structuring Process for Ceramic Coatings on Injection Molding Tools Produced by MOCVD

2019 ◽  
Vol 809 ◽  
pp. 303-308
Author(s):  
Michaela Sommer ◽  
Gregor Fornalczyk ◽  
Frank Mumme
Keyword(s):  
Thin Films ◽  
Injection Molding ◽  
Laser Processing ◽  
Chemical Vapor ◽  
Ceramic Materials ◽  
Ceramic Coatings ◽  
Machining Parameters ◽  
Molding Process ◽  
Ultrashort Pulse Laser ◽  
Free Process

To increase product quality injection molding tools are equipped with innovative tempering technologies. The customers strive for the technology with the lowest energy consumption. Ceramic materials like yttria-stabilized zirconia (YSZ) are able to thermally insulate tool surfaces providing a more precise temperature regulation with intent to shorten cycle times as well as to decrease energy demands during the molding process. High quality ceramic thin films could be applied by metalorganic chemical vapor deposition (MOCVD). Laser machining technologies have been developed for machining the ceramic materials. In this work we demonstrate the fabrication of zirconia based thin films on steel tools via MOCVD using solid metalorganic precursors. Shorter coating times and a solvent free process are some of the advantages of our new developed coating process. The ultrashort pulse laser processing (USPLP) was used to structure the developed MOCVD coating. Using this technology the ceramic material undergoes no thermal stress cracks, because USPLP is characterized by the preference of cold material removal. The laser processing procedure was developed by working out machining parameters for the different materials. The difference between steel and ceramic in the removal behavior was determined immediately so that a machining strategy for the ceramic CVD coating could be designed successfully. The implementation of defined roughness and a carbon fiber like structure in the coating were realized. Coated and laser-structured injection molding tools were tested regarding their desired properties under production conditions.

scholarly journals X-Ray Image Recognition Based on Improved Mask R-CNN Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jicun Zhang ◽  
Xueping Song ◽  
Jiawei Feng ◽  
Jiyou Fei
Keyword(s):  
Object Detection ◽  
Lower Layer ◽  
Detection Algorithm ◽  
Intelligent Manufacturing ◽  
Average Precision ◽  
X Ray ◽  
Detection Algorithms ◽  
Security Inspection ◽  
Scale Difference ◽  
The Stability

It is an important part of security inspection to carry out security and safety screening with X-ray scanners. Computer vision plays an important role in detection, recognition, and location analysis in intelligent manufacturing. The object detection algorithm is an important part of the intelligent X-ray machine. Existing threat object detection algorithms in X-ray images have low detection precision and are prone to missed and false detection. In order to increase the precision, a new improved Mask R-CNN algorithm is proposed in this paper. In the feature extraction network, an enhancement path is added to fuse the features of the lower layer into the higher layer, which reduces the loss of feature information. By adding an edge detection module, the training effect of the sample model can be improved without accurate labeling. The distance, overlap rate, and scale difference between objects and region proposals are solved using DIoU to improve the stability of the region proposal’s regression, thus improving the accuracy of object detection; SoftNMS algorithm is used to overcome the problem of missed detection when the objects to be detected overlap each other. The experimental results indicate that the mean Average Precision (mAP) of the improved algorithm is 9.32% higher than that of the Mask R-CNN algorithm, especially for knife and portable batteries, which are small in size, simple in shape, and easy to be mistakenly detected, and the Average Precision (AP) is increased by 13.41% and 15.92%, respectively. The results of the study have important implications for the practical application of threat object detection in X-ray images.

Performance Analysis on Eco-friendly Machining of Ti6Al4V using Powder Mixed with Different Dielectrics in WEDM

2020 ◽  
Vol 17 (3) ◽  
pp. 8128-8139
Author(s):  
S. Chakraborty ◽  
S. Mitra ◽  
D. Bose
Keyword(s):  
Metal Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Process Efficiency ◽  
Machining Parameters ◽  
Dielectric Fluids ◽  
High Emission ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The recent scenario of modern manufacturing is tremendously improved in the sense of precision machining and abstaining from environmental pollution and hazard issues. In the present work, Ti6Al4V is machined through wire EDM (WEDM) process with powder mixed dielectric and analyzed the influence of input parameters and inherent hazard issues. WEDM has different parameters such as peak current, pulse on time, pulse off time, gap voltage, wire speed, wire tension and so on, as well as dielectrics with powder mixed. These are playing an essential role in WEDM performances to improve the process efficiency by developing the surface texture, microhardness, and metal removal rate. Even though the parameter’s influencing, the study of environmental effect in the WEDM process is very essential during the machining process due to the high emission of toxic vapour by the high discharge energy. In the present study, three different dielectric fluids were used, including deionised water, kerosene, and surfactant added deionised water and analysed the data by taking one factor at a time (OFAT) approach. From this study, it is established that dielectric types and powder significantly improve performances with proper set of machining parameters and find out the risk factor associated with the PMWEDM process.

Sign in / Sign up

Export Citation Format

Share Document