MONITORING OF HYPOID GEAR MESHING BASED ON A THERMAL NETWORK MODEL WITH HIGH-SPEED VIDEO THERMOGRAPHY

Author(s):  
Susumu ARAO ◽  
Mitsuhiko SUZUKI ◽  
Toshiki HIROGAKI ◽  
Eiichi AOYAMA
Author(s):  
Mitsuhiko Suzuki ◽  
Toshiki Hirogaki ◽  
Eiichi Aoyama

Hypoid gears, used in automobile differentials, have a complex shape; thus, it is difficult to estimate tooth contact conditions. Therefore, a non-contact method of analysis is proposed for determining tooth contact conditions by using high-response thermography to analyze temperature distribution during meshing between the pinion and the gear. High-speed photography was performed using thermography and an extraction line was defined in the obtained thermal images to extract temperature data from them. Furthermore, we constructed a novel model to predict tooth surface temperature distribution during tooth meshing based on a thermal network model that represents the thermal conductivity of an object by a simple RC circuit. In this report, by comparing the temperature changes obtained from the thermal images with the calculated results, we identify the thermal properties of a material from the thermal images, and discuss the effects of parameters such as heat capacity and thermal resistance. The comparison shows that infrared tooth surface imagery is effective in estimating hypoid gear tooth meshing. That is, by using infrared image and a thermal network model, heat conduction in a gear can be considered. It was confirmed that it is possible to predict temperature rise on tooth surfaces due to gear meshing.


2020 ◽  
Vol 140 (9) ◽  
pp. 625-632
Author(s):  
Yoshiaki Taguchi ◽  
Satoshi Kadowaki ◽  
Gaku Yoshikawa ◽  
Kenji Hatakeda ◽  
Takashi Kaneko

2019 ◽  
Vol 85 (6) ◽  
pp. 53-63 ◽  
Author(s):  
I. E. Vasil’ev ◽  
Yu. G. Matvienko ◽  
A. V. Pankov ◽  
A. G. Kalinin

The results of using early damage diagnostics technique (developed in the Mechanical Engineering Research Institute of the Russian Academy of Sciences (IMASH RAN) for detecting the latent damage of an aviation panel made of composite material upon bench tensile tests are presented. We have assessed the capabilities of the developed technique and software regarding damage detection at the early stage of panel loading in conditions of elastic strain of the material using brittle strain-sensitive coating and simultaneous crack detection in the coating with a high-speed video camera “Video-print” and acoustic emission system “A-Line 32D.” When revealing a subsurface defect (a notch of the middle stringer) of the aviation panel, the general concept of damage detection at the early stage of loading in conditions of elastic behavior of the material was also tested in the course of the experiment, as well as the software specially developed for cluster analysis and classification of detected location pulses along with the equipment and software for simultaneous recording of video data flows and arrays of acoustic emission (AE) data. Synchronous recording of video images and AE pulses ensured precise control of the cracking process in the brittle strain-sensitive coating (tensocoating)at all stages of the experiment, whereas the use of structural-phenomenological approach kept track of the main trends in damage accumulation at different structural levels and identify the sources of their origin when classifying recorded AE data arrays. The combined use of oxide tensocoatings and high-speed video recording synchronized with the AE control system, provide the possibility of definite determination of the subsurface defect, reveal the maximum principal strains in the area of crack formation, quantify them and identify the main sources of AE signals upon monitoring the state of the aviation panel under loading P = 90 kN, which is about 12% of the critical load.


2020 ◽  
Vol 12 (12) ◽  
pp. 168781402098468
Author(s):  
Xianbin Du ◽  
Youqun Zhao ◽  
Yijiang Ma ◽  
Hongxun Fu

The camber and cornering properties of the tire directly affect the handling stability of vehicles, especially in emergencies such as high-speed cornering and obstacle avoidance. The structural and load-bearing mode of non-pneumatic mechanical elastic (ME) wheel determine that the mechanical properties of ME wheel will change when different combinations of hinge length and distribution number are adopted. The camber and cornering properties of ME wheel with different hinge lengths and distributions were studied by combining finite element method (FEM) with neural network theory. A ME wheel back propagation (BP) neural network model was established, and the additional momentum method and adaptive learning rate method were utilized to improve BP algorithm. The learning ability and generalization ability of the network model were verified by comparing the output values with the actual input values. The camber and cornering properties of ME wheel were analyzed when the hinge length and distribution changed. The results showed the variation of lateral force and aligning torque of different wheel structures under the combined conditions, and also provided guidance for the matching of wheel and vehicle performance.


Author(s):  
Hirokazu Takahashi ◽  
Takahiro Murooka ◽  
Kan Toyoshima ◽  
Hitoshi Uematsu ◽  
Tetsuro Fujii

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