Shrinkage voids have a large influence on the quality of plastic gears, and it is still a problem to detect the voids inside gears accurately and conveniently. This paper presents a novel method for ...detecting shrinkage voids via magnetic levitation. The porosity levels of plastic gears can be calculated using magnetic levitation because the density of plastic gears is influenced by the shrinkage voids. The distribution of shrinkage voids is quantified by the moment of volume, hence a theoretical model for the distributions of shrinkage voids and levitating posture can be established. Computer tomography (CT) detections were also carried out to verify the accuracy of magnetic levitation for detecting the shrinkage voids. Experimental results show that the average relative error of calculated porosity level is less than 7%, and the theoretical model for distribution of shrinkage voids agrees well with the results from CT detections, with the correlation coefficient being up to 99.8%. The proposed method has great potential for mass detection of plastic gears.
•Propose a magnetic levitation device for detecting shrinkage voids.•Establish the theoretical model for analysing shrinkage voids of plastic gears.•Verify the accuracy of magnetic levitation with CT detections.•Calculate the porosity levels with the average error less than 7%.•Analyze the distributions of shrinkage voids with a correlation coefficient of 99.8%.
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•High-speed camera recordings used for polymer gear tooth deflection analysis.•Digital image correlation enables deflection analysis on the gear's side surface.•Edge displacement ...detection method provides accurate flank profile deflection results.•Edge displacement detection opens new possibilities for in-situ wear evaluation.
The engineering characteristics of polymer gears, such as wear and fatigue resistance, are dictated by the underlying processes that take place during the gear meshing phase. These are in turn dependent on the running load, speed, temperature, lubrication regime and other parameters. So far, the structural response of a meshing gear could only be analysed using numerical approaches, typically involving the finite element method. In this study, an optical experimental analysis approach is proposed to evaluate the in-mesh gear tooth deflection based on high-speed camera recordings. For this purpose, two image processing methods were implemented, namely the well-known Digital image correlation method and a newly proposed Edge displacement detection method.
Using an experimental setup with a camera resolution of 1024×1024px, an exposure time of 40 μs, a frame rate of 2·104fps and a 2000 lm focused light source, a measurement accuracy of ±5μm could be achieved. A good correlation between both methods and finite element analysis results was confirmed. Furthermore, the newly proposed Edge displacement detection method offers high potential for experimental analysis of long-term wear and strain accumulation processes.
•Innovative optimization strategy for tooth root geometrical profile is presented.•The proposed method was numerically validated by FE analysis.•The results are compared to the standard approach.•The ...goal is to provide the designer with a valid practical technical support.•This approach can thus be applied using different geometries of the tooth root.
The increasing diffusion of plastic gears in many industrial sectors makes it necessary to have a better knowledge of the bending strength properties of teeth in order to ensure an adequate design process. However, technological development has not gone hand in hand with the standard development necessary to carry out an optimized design process. To date, the specific standards for plastic gears refer mainly to design and calculation methods for the metal gears. So, the possible optimization strategy for the tooth root geometrical profile is also driven by the typical metal production processes. This paper presents an innovative approach, supported by an analytical procedure, to design optimized plastic gear wheels. The results obtained by the analytical approach is compared to the standardized one to highlight similarities and discrepancies. The goodness of the proposed results is verified also through finite element numerical analysis. The goal of the paper is to provide the designer with an analytical approach useful to optimize the root geometry design of plastic gears for lower root bending stress.
After injection molding, plastic gears often exhibit surface defects, including those on end faces and tooth surfaces. These defects encompass a wide range of types and possess complex ...characteristics, which pose challenges for inspection. Current visual inspection systems for plastic gears suffer from limitations such as single-category defect inspection and low accuracy. There is an urgent industry need for a comprehensive and accurate method and system for inspecting defects on plastic gears, with improved inspection capability and higher accuracy. This paper presents an intelligent inspection algorithm network for plastic gear defects (PGD-net), which effectively captures subtle defect features at arbitrary locations on the surface compared to other models. An adaptive sample weighting method is proposed and integrated into an improved Focal-IoU loss function to address the issue of low inspection accuracy caused by imbalanced defect dataset distributions, thus enhancing the regression accuracy for difficult defect categories. CoordConv layers are incorporated into each inspection head to improve the model’s generalization capability. Furthermore, a dataset of plastic gear surface defects comprising 16 types of defects is constructed, and our algorithm is trained and tested on this dataset. The PGD-net achieves a comprehensive mean average precision (mAP) value of 95.6% for the 16 defect types. Additionally, an online inspection system is developed based on the PGD-net algorithm, which can be integrated with plastic gear production lines to achieve online full inspection and automatic sorting of plastic gear defects. The entire system has been successfully applied in plastic gear production lines, conducting daily inspections of over 60,000 gears.
Plastic gears have been widely used in fields such as instruments, meters, and automotive electronics. In particular, metal–plastic gear pairs are commonly used in the low-speed stages of multi-stage ...gear transmissions to enhance load capacity and achieve lightweight design. However, due to the small elastic modulus and significant temperature sensitivity of plastic gears, off-line meshing phenomenon occurs in metal–plastic gear pairs during operation, which affects the overall system stiffness and dynamic behavior. Therefore, this study takes 45# steel-POM gear pair as the object of study, and considers the effect of temperature on the modulus of elasticity of the gear and the effect of out-of-line meshing on the time-varying stiffness of the gear pair , in which the 45# steel-POM gear pair refers to the combination of the steel and plastic gear pairs, with the pinion gear consisting of 45# steel gears, and the large gear made of POM gears. A lumped parameter method is used to establish a single-degree-of-freedom model of the gear transmission system, and the effect of load on the system’s dynamic behavior is investigated. Experimental validation shows that the stiffness varies linearly with the load, and the dynamic performance of the system deteriorates with increasing load. In the experimental study described in this article, as the load increased from 5 to 10 N m, the maximum dynamic transmission error increased by 62%. Under the same load, the system with consideration of off-line meshing exhibits better transmission accuracy compared to the one without consideration. Disregarding the dominant frequency of the system when there is no external meshing, the dominant frequency of the system increases by 1.4 times when considering external meshing. This study provides a theoretical basis for the design and transmission of plastic gears in the future.
This paper describes a new method for finding optimal process parameter values of plastic gears based on a small experimental dataset. Taking a polyamide 66 gear as an example, the simulation study ...and the real experiment have been designed based on the Taguchi approach. Then, the Levenberg-Marquardt back propagation (LMBP) neural network is built based on the data generated by the real experiment. This network is also used as the fitness function of the particle swarm optimization algorithm. The results show that, by using optimal parameter values, the comprehensive score of the polyamide 66 gear increases by 8.71%.
A new steel-plastic gear set testing methodology has been developed at the Institute of Polymer Technology (LKT). The in situ gear test rig analyses the timing differences between the index pulses of ...rotary encoders on the input and output shaft. This measurement principle enables the continuous measurement of the elastic tooth deflection on the one hand and permanent deformations and wear on the other hand by switching between a high loading torque and a low measuring torque. However, the elastic tooth deflection measurement using this principle has not yet been validated. Therefore, in situ gear tests using polybutylene terephthalate (PBT) gears were performed to evaluate the elastic tooth deflection of the plastic gear during operation. The results were compared to the results of pulsator tests. The comparison shows a very good correlation between the results of the newly developed in situ gear test rig and the well-established pulsator test rig. However, it has been shown that the test rig design creates a measuring offset due to angular displacements of the shafts due to torsion of test rig components.
This paper was aimed at finding out the solution to the problem of insufficient dimensional accuracy caused by non-linear shrinkage deformation during injection molding of small module plastic gears. ...A practical numerical approach was proposed to characterize the non-linear shrinkage and optimize the dimensional deviation of the small module plastic gears. Specifically, Moldflow analysis was applied to visually simulate the shrinkage process of small module plastic gears during injection molding. A 3D shrinkage gear model was obtained and exported to compare with the designed gear model. After analyzing the non-linear shrinkage characteristics, the dimensional deviation of the addendum circle diameter and root circle diameter was investigated by orthogonal experiments. In the end, a high-speed cooling concept for the mold plate and the gear cavity was proposed to optimize the dimensional deviation. It was confirmed that the cooling rate is the most influential factor on the non-linear shrinkage of the injection-molded small module plastic gears. The dimensional deviation of the addendum circle diameter and the root circle diameter can be reduced by 22.79% and 22.99% with the proposed high-speed cooling concept, respectively.
Under heavy loading and large numbers of revolutions, the most commonly encountered gear damage is the thermal damage that is caused by an accumulation of heat on the surface of the tooth. The ...maximum Hertzian surface stress occurs at the single tooth pair contact region. The aim of this study was to delay the formation of thermal damage in the region of single tooth meshing by decreasing the Hertzian surface pressure by increasing the tooth width. The
F/
b (N/mm) tooth load was decreased in the single tooth pair contact region. Experiments show that the appearance of thermal damage is delayed for the width-modified gear teeth in comparison with unmodified gear teeth.
The topic of this paper is the application of abrasive flow machining (AFM) to gear tool inserts polishing. Polished surface on plastic gear teeth improves surface geometry stability, and it ...increases the lifespan, which was proved on the gear testing rig. Experiments have shown that it is an efficient alternative to the hand polishing procedure. Besides significant cost and processing time savings, AFM generates constant surface quality. The achieved roughness is homogeneous on the entire machined surface; it is reduced from
R
a
= 0.68 μm to
R
a
= 0.08 μm in 120 s. At the same time, the tooth geometry profile is not damaged. The first time, surface polishing should be done at request because of individually manufactured tool inserts. Processing parameters depend on the type of the abrasive machine, the polishing paste and part geometry. Computer-aided abrasive flow analyses and practical experiments assist in setting optimum AFM process parameters. The paper presents a working set of parameters and a detailed report on machined surface measurement data. On the base of better understanding of AFM process, the surface roughness prediction model and thickness of removed material model was setup. It has high accuracy and reliability for specific applications. The use of plastic gears for various applications is widespread; the presented process improvement is an important innovation for injection molding tools manufacturers.
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