Gear Wear Research Articles

Application of Kriging Model to Gear Wear Calculation under Mixed Elastohydrodynamic Lubrication

The calculation of tooth wear under mixed elastohydrodynamic lubrication is very complex and requires consideration of many conditions such as load distribution in the tooth meshing zone, micro-convex elastoplastic deformation and tooth surface temperature. The accurate calculation of tooth wear requires a lot of time and effort. In order to calculate tooth face wear under mixed elastomeric flow lubrication quickly and accurately, a new proxy model of tooth face wear is developed using the Kriging method. The pressure distribution required for the wear calculation was obtained utilizing the modified Reynolds equation and ZMC elasto-plastic model. The numerical calculation model of gear wear was derived using the modified Archard wear model. The Kriging model was used to construct a proxy model between gear parameters and tooth wear, and the degree of approximation and goodness of fit of the Kriging model were investigated. The results are as follows. The wear depth at each position is different, the smallest at the pitch, the largest near the tooth root, and the pinion has a larger wear depth than the gear. The Kriging model is highly efficient and accurate in its computation and overcomes the shortage of excessive time spent on the calculation of numerical calculation models.

Proximate Model of Gear Drive Units Based on Dimensional Analysis for Wear Process Evaluation

Excessive wear of gears will not only cause noise and vibration in the transmission system, but also reduce transmission efficiency and accuracy in severe cases, causing irreversible losses to the transmission system. It is desirable to develop a micro-gear unit model for evaluating the wear process and predicting the failure time of large gear units (such as wind turbine gear units), reducing losses due to sudden failures. Based on the Buckingham pi-theorem of dimensional analysis and Hertz formula, the similarity ratio of each parameter of the gear wear process was proposed. The maximum equivalent stress is calculated by establishing the FEM model and comparing it with the theoretical contact stress calculated by the Hertz formula, and the results were relatively consistent. Two pairs of gear friction and wear experiments with similar parameters were carried out to compare the wear evolution performance of two similar gears. The friction performance process of the test gears was observed by particle counter and analytical ferrograph. The results show that the friction and wear processes of the two groups of gears with similar parameters have a certain correlation, which was consistent with the proposed similarity model. The similarity model combined with the observation results of abrasive particles has a certain application value for the evaluation of the wear state of the transmission system.

Study on Wear Mechanism of Helical Gear by Three-Body Abrasive Based on Impact Load.

This study aimed to explore the wear characteristics and evolution mechanisms of large-scale wind power gears under the impact load of particles of the three-body abrasive Al2O3 (0.2 mg/mL) from four aspects: oil analysis, vibration analysis, amount of gear wear, and tooth-surface-wear profile analysis. A magnetic powder brake was used to simulate the actual working conditions. Combined with the abrasive particle monitoring and the morphology analysis of the tooth-surface-wear scar, by setting quantitative hard particles in the lubricating oil, the gears are mainly operated in the abrasive wear state, and wear monitoring and wear degree analysis are carried out for the whole life cycle of the gears. Oil samples were observed and qualitatively analyzed using a particle counter, a single ferrograph, a metallographic microscope, and a scanning electron microscope. The experiments demonstrate that the initial hard particles have a greater impact in the early wear stage of the gears (<20 h), and abrasive particle concentration increases by 30%. This means that Al2O3 particles accelerate the gear wear during the running-in period. The loading method of the impact load on the oblique gear exacerbates the abrasion particle wear and expands the stress concentration, which reduces the surface of large milling particles on the surface, and reduces the width of the tooth (the part above the pitch line is severely worn), which causes the gear to break into failure. The research provides help for analyzing the mechanism of abrasive wear of gears and predicting wear life.

Experimental research of wear-fatigue interaction of gears

Gear failures are commonly caused by wear and fatigue and past research on gear failures has primarily focused on individual failures. A gear testing machine was developed to explore the mechanism of gear wear-fatigue interaction, and four sets of wear-fatigue interaction tests were performed by changing the operating conditions of the gear drive by regulating the quantity of lubricant in the test gearbox. The K-S test method was used to investigate the gear life distribution under wear-fatigue interaction. The frequency domain properties of the wear-fatigue interaction were compiled and analyzed using Fast Fourier Transform (FFT) analysis. A coordinate measuring machine was implemented to obtain the exact amount of wear at each stage of the gear test. The mechanism of gear wear-fatigue interaction was analyzed by scanning electron microscope observation of tooth surfaces. The results are as follows. The life distribution under wear-fatigue interaction obeys a log-normal distribution. With the increase of the lubrication the pitting fault occurs, the fault gear rotation frequency and its harmonic frequency appear in the low frequency region, and its amplitude increases with the increase of the pitting fault. In the high-frequency region, a sideband with the faulty gear rotation frequency as the interval appears around the meshing frequency and its two times frequency, and its amplitude increases with the increase of the pitting fault. With the decrease of lubrication, the gear wear failure increases, the amplitude of the meshing frequency and its two times frequency increases in the high frequency region. In the gear transmission process, wear and fatigue exist in a competitive relationship of mutual constraints.

A prediction method for adhesive wear of herringbone gear

The centering error is a unique error in the manufacturing process of herringbone gear. The relationship between centering error and tooth wear and the influence of centering error on the service performance of herringbone gear are rarely reported. In this paper, a wear prediction method of herringbone gear with centering error is proposed by comprehensively considering the coupling relationship between tooth wear evolution and centering error. Based on the mixed elastohydrodynamic lubrication theory and Hertz contact theory, the calculation equation of asperity contact pressure of tooth surface after tooth wear is derived and the influence of centering error on load shared by both sides of herringbone gear is analyzed, then the coupling relationship between tooth wear depth and contact pressure is studied. The distribution of contact temperature, asperity contact pressure and wear depth on tooth surface is obtained, and the effect of centering error on them is discussed, then the effects of roughness, input torque and rotation speed on wear of herringbone gear with centering error is analyzed. The results show that the contact temperature, asperity contact pressure, sliding distance and tooth surface wear depth on the advanced contact side of herringbone gear is greater than those of the delayed contact side due to the influence of centering error. And the wear depth of both sides is not uniformly distributed along the tooth width direction and the maximum wear depth is located in the initial meshing area and decreases nonlinearly along the line of action. Besides, the greater the roughness and input torque, the greater the difference between the wear depth on both sides, and with the increase of rotation speed, the wear depth decreases. The results also show that the wear depth can change the centering error, which changed the contact characteristics and load shared by both sides of the herringbone gear. The wear depth and centering error have a significant impact on the meshing and contact performance of herringbone gears, and their influence cannot be ignored in the study of herringbone gears. The results of this paper can provide theoretical support for wear resistance design of herringbone gear.

ВЫБОР МАТЕРИАЛА ЗУБЬЕВ ШЕСТЕРЕН НА ОСНОВЕ ИЗНОСОСТОЙКОСТИ

This article reviews a method for selecting a gear material based on the wear resistance properties of teeth. The approach takes such properties as hardness, number of loading cycles leading the destruction a deformed layer of friction surface material and correlation of hardness of gear material and strength of abrasive particles in wedgeshaped gap of teeth, into account. The research has maintained principles of alteration of the wear rates and service life of open and closed gears, with and without abrasive particles in the process of gear teeth wear, depending on the meshing module and the type of hardening surface treatment, at volume hardening, hardening by current of high frequency and cementation.

Prevention of external auditory canal exostosis in the Colorado whitewater community.

External auditory canal exostoses (EACE) are bony formations that develop insidiously in the auditory meatus from chronic exposure to cold water and, in severe cases, require surgery. This condition has been understudied in the whitewater kayakers and not yet studied in the riverboarding population. Precautions such as earplugs are thought to prevent the formation of EACE because they mechanically block cold water from contacting the sensitive skin in the external auditory canal; however, earplugs are not commonly utilized by athletes. Inquiring about hobbies and the use of protective equipment can be done during osteopathic physicians' preventive care visits. This article aims to determine the prevalence of EACE in Colorado whitewater athletes and their attitudes about wearing ear protection before and after an educational intervention directed at increasing awareness and prevention of EACE. In July 2020, participants of this cross-sectional study completed a 10-min survey that collected demographics, whitewater experience, and perceptions of EACE, followed by an educational intervention. Participant ears were photographed utilizing a digital otoscope to assess EACE, and severity ratings were categorized into one of four occlusion levels: none (0%), mild (<25%), moderate (25-75%), or severe (>75%). Spearman correlation coefficientsand Wilcoxon signed-rank tests were utilized to assess changes in attitudes before and after the educational intervention. Eighty-one participants (mean [SD] age=36.3 [12.6] years, 25.9% female) completed the study: 74 kayakers and seven riverboarders. After the intervention, 60.5% (49/81) (p<0.001) reported greater understanding of EACE and 75.0% (60/80) were more likely to wear ear protection (p<0.001). Most (58.0%, 47/81) never wore ear protection. Of the 61 (75.0%) participants with at least one ear severity rating, most (55.7%, 34/61) had moderate EACE, 29.5% (18/61) had no to mild EACE, and 14.8% (9/61) had severe EACE (p<0.001). Impaired hearing was the biggest barrier to utilizing ear protection (51.6%, 33/64). Our results suggested that the educational intervention improved understanding of EACE and may increase utilization of ear protection in this population. Such prevention efforts may lead to better health of whitewater paddlers by reducing the incidence of EACE. Encouraging osteopathic physicians to inquire about hobbies and protective equipment during primary care preventive visits is essential to help keep athletes in the river doing what they love for longer, contributing to a healthier and happier whole person.

Nonlinear dynamic analysis of high-speed gear pair with wear fault and tooth contact temperature for a wind turbine gearbox

This paper aims to reveal the relationship between the high-speed gear wear and nonlinear dynamics for a wind turbine gearbox considering the tooth contact temperature. The temperature and deformation of the tooth surface are calculated respectively using the Blok's flash temperature theory and thermal deformation formula, and the meshing stiffness caused by the tooth contact temperature is obtained using the Hertz theory. The wear depth and time-varying meshing stiffness of high-speed gears are calculated using the Archard's equation and potential energy method, respectively. The nonlinear dynamic model of the gearbox is established to study the characteristics, and the frequency domain values of gear wear are compared with experimental data. The results show that the tooth contact temperature makes the time-varying meshing stiffness decrease, then affecting the dynamics of the system, the stability decreases with the increase of comprehensive transmission error, and for the gearbox considering the contact temperature, the gear wear makes the chaotic motion occur in advance and its region increase obviously. The research provides a basis for the wear fault diagnosis and detection of gear transmission systems.

A novel cyclic-correntropy based indicator for gear wear monitoring

Gearbox is a vulnerable component of a turbine’s drivetrain and plays a vital role in the power transmission in wind turbines. Wind turbines usually operate under harsh working environments, such as in deserts, oceans, and on hills. The adverse operating conditions (such as inevitable fluctuating wind loads and speeds) make the gearbox transmission prone to reliability degradation and premature failure. Gear wear is a common and unavoidable surface degradation phenomenon during the lifespan of the gear transmission system. The gear wear propagation can result in severe failures, such as gear surface spalling, gear root crack, and gear tooth breakage, all of which could lead to the failure of the drivetrain system of wind turbines and bring unexpected economic loss, even serious accidents. Thus, it is crucial to monitor the gear wear propagation progression in order to enable reliable and safe operation. To this end, this paper develops a novel vibration-based health indicator to monitor the gear surface degradation induced by gear wear progression. With the help of the novel indicator developed, the health status of the gearbox can be well evaluated and thus predictive maintenance-based decisions can be made to reduce maintenance costs and minimize gearbox failures in wind turbines. A series of endurance tests under different lubrication conditions and operational conditions are carried out to verify the effectiveness of the gear wear monitoring indicator.

Investigation of Spur Gear Dynamics with Gear MeshImpacts Induced by Tooth Wear

Abstract Tooth wear is one of the most common faults in gear transmission systems. However, due to its limited influences on gear dynamics, the condition monitoring of gear wear experiences more challenges. To investigate the relationship between tooth wear and gear dynamics, this study develops an eight-degree of freedom dynamic model which takes into account the gear mesh impact induced by tooth wear. In this model, the gear mesh impact force induced by tooth wear was calculated as an extra input excitation for the gear dynamic model. Besides, a comparative study was carried out to explore the real reason that causes the poor dynamic behaviour due to the wear from two points of view: 1) the reduction in gear mesh stiffness; 2) the increase in gear mesh impact force. The simulation results show that the wear causes a slight reduction in gear mesh stiffness, thus leading to the decrease in the amplitude of gear mesh frequency. This is not consistent with the phenomena observed in the lab experiment which shows the increase in the gear vibrations. The second simulation of impact force demonstrates that the wear causes an increase in the impact force which further leads to the increase in the amplitude of gear mesh frequency. This study investigates the cause for the deterioration in gear dynamics induced by gear wear, which can benefit the early condition monitoring and fault diagnosis of the gear tooth wear.

Mesh relationship modeling and dynamic characteristic analysis of external spur gears with gear wear

Mesh relationship modeling and dynamic characteristic analysis of external spur gears with gear wear

Rapid prototyping method for replacing non-circular gears

The paper presents a modern method of obtaining non-circular gearwheels from by means of additive technologies. Such a method is useful in case of wear or failure of a mechanical gear which has in its composition such non-circular metal gearwheels in the case of technical systems that must ensure continuous operation. With the help of the FDM technology (Fused Deposition Modeling) it will be created a model of the non-circular gearwheel that will constitute casting model for future gear, or they can even be used as functional gears if a suitable material and a precise execution technology with optimal printing conditions are considered.

Dynamic modelling of two-stage gear systems with localized wear defects

Abstract Considering the profile deviation induced by localized wear defects, a dynamic model of two-stage gear systems is established. In the proposed dynamic model, the time-varying mesh stiffness of worn gears is calculated by the loaded tooth contact analysis method. The mesh stiffness and the non-loaded transmission error are regarded as the time-varying stiffness excitation and the displacement excitation, respectively. Based on the proposed dynamic model, the dynamic responses of the two-stage gear system with localized wear defects are acquired. The simulated vibration responses are compared to the measured results to test the effectiveness of the proposed dynamic model. It is found that the proposed model can yield similar fault feature with the experiment, which shows the validity of the proposed dynamic model. This paper can afford theoretical basis for the fault mechanism and dynamic characterization of localized wear defects.

Use of transmission error for a quantitative estimation of root-crack severity in gears

Gear transmission error (TE) has been acknowledged as a prominent diagnostic tool in condition monitoring. Its advantages vs vibration include being closer to the source and less affected by transmission path effects. TE has recently demonstrated its enormous capabilities in gear wear severity assessment. For crack diagnostics, despite some promising preliminary results, a methodology for an accurate and reliable TE-based estimation of crack size was previously not available. In order to achieve this result two main obstacles needed to be overcome: (i) the removal of dynamic TE effects due to speed and (ii) the separation of profile error and compliance-related tooth deflections. This paper proposes a new crack-severity-estimation methodology that solves these problems. The proposed technique exploits different speeds and loads, often experienced by geared transmissions, and includes an automated identification of the cracked tooth and a crack-depth estimation based on a comparison with a theoretical tooth stiffness model. The proposed methodology is validated using experimental encoder measurements collected from a spur gear test rig with artificially seeded root cracks.

Study on the Lubrication Characteristics of Spur Gear Pairs With Low Sliding Ratio Under Mixed Elastohydrodynamic Lubrication

Abstract The relative sliding at the meshing point directly affects the contact and lubrication characteristics of the gear pair and is an important factor of gear wear and power loss. In this study, for investigation of a new type of low sliding ratio (LSR) gear pair whose tooth profile is constructed by a cubic function, a three-dimensional (3D) mixed elastohydrodynamic lubrication (EHL) line contact model was established with consideration of the effect of tooth profile geometry, transient motion characteristics, load distribution, and machining roughness. The distribution of the center film thickness of the LSR gear along the meshing line was predicted through an example the result of which was compared with a typical line contact EHL formula to verify the model. In addition, the difference was investigated in film thickness distribution of friction coefficient and temperature rise between LSR spur gears and involute spur gears. Hence, the effect of 3D rough tooth surface on the contact lubrication characteristics of LSR gears was discussed. The results demonstrated that the minimum center film thickness of the LSR gear appeared at the alternating point of the concave and convex tooth surfaces. At the same time, compared with the involute gear, the LSR gear significantly increased the film thickness at the start and ending points of the meshing and reduced the friction coefficient and the flash temperature rise.

Physics-Informed LSTM hyperparameters selection for gearbox fault detection

A situation often encountered in the condition monitoring (CM) and health management of gearboxes is that a large volume of CM data (e.g., vibration signal) collected from a healthy state is available but CM data from a faulty state unavailable. Fault detection under such a situation is usually tackled by modeling the baseline CM data and then detect the fault by examining any deviation of the baseline model versus newly monitored data. Given that the CM data is mostly time series, the long-short term memory (LSTM) neural network can be employed for baseline CM data modeling. The LSTM is free from the choice of the number of lagged input time series and can also store both long-term and short-term time series dependency information. However, we found that an LSTM with its hyperparameters selected whilst minimizing validation mean squared error (VAMSE) does not differentiate the faulty and healthy states well. There is still room for detectability improvement. In this paper, we propose a physics-informed hyperparameters selection strategy for the LSTM identification and subsequently the fault detection of gearboxes. The key idea of the proposed strategy is to select hyperparameters based on maximizing the discrepancy between healthy and physics-informed faulty states, as opposed to minimizing VAMSE. Case studies have been conducted to detect the gear tooth crack and tooth wear using laboratory test rigs. Results have shown that the proposed physics-informed hyperparameters selection strategy returns an LSTM that can better detect these faults than the LSTM returned from minimizing VAMSE.

A digital twin-driven hybrid approach for the prediction of performance degradation in transmission unit of CNC machine tool

• DT model based meta-action, collected data from multi-sensors on transmission unit. • Monitoring and simulation of performance degradation on the wear of transmission. • Combining the data-driven and the model-based method by particle filter algorithm . • Integrating mechanism and real-time data, mutual modified to a High fidelity model . Precision performance prediction of transmission system is considered as a key technology to modern equipment health management. Given the importance of maintaining a transmission system's precision, this paper presents a hybrid approach framework driven by digital twin technology (DT), to predict performance degradation. Firstly, a DT model based on meta-action theory is established, and real-time monitoring and digital simulation, driven by DT data, is realized in order to analyze the precision of the transmission units in machine tools. Secondly, the wear of gear in transmission unit is studied through Achard wear theory, which considered the comprehensive influence of gear load and speed on surface wear of the gear pair tooth, based on the model driving method. The performance degradation of the transmission unit is obtained by using the RBF neural network algorithm based on the data-driven method to extrapolate the wear data to the field-measurable precision index value. In addition, the hybrid predictive approach of the performance degradation model through the particle filter algorithm is built, and the real-time data is used to update the current state estimation to improve the prediction accuracy. By combining the mechanism of the physical degradation processes with the real-time and historical data and turning them into a cooperative architecture, this prediction method uses the complementary advantages offered by the fusion of these methods to bridge the link between data-driven prediction and model-based prediction. Finally, the method has been successfully applied to the precision prediction of the transmission unit in CNCMT turntable, and it is compared with the single prediction method to verify the effectiveness and feasibility.

Compensation of mounting error in in-situ wear measurement during gear pitting test

A profilometer can be used to monitor the tooth surface topography evolution during gear pitting tests. Due to the mounting relationship variation between the instrument and the gear, the tooth profile’s measurement position deviation from its theoretical location will introduce a measurement error. In this study, the tooth profile measurement error introduced by mounting using a tactile profilometer was theoretically analysed and experimentally confirmed as a fish shape. A mounting error compensation method based on projection onto the perpendicular plane to the gear’s datum axis was proposed. The results show that the fish-shaped tooth profile measurement error can be effectively compensated, benefitting the evaluation of the gear tooth surface wear during gear pitting tests.

An adhesive wear model of rough gear surface considering modified load distribution factor

The gear wear is closely relative to the rough tooth surface morphology and the load distribution; however, their interactions have been rarely given focus. In this work, an adhesive wear model of rough gear surface is proposed considering modified load distribution factor. The mesh stiffness and load distribution factor are modified by the tooth surface morphology and wear depth. Then, the mean pressure is obtained by Hertzian theory, and the wear depths of the pinion and gear are calculated using Archard model. The wear model is verified by comparing with the pervious works. The effects of surface morphologies, geometric and operating parameters on the wear depth, mesh stiffness, and load distribution factor are investigated. Results indicate that (1) the wear depth is determined by profile error rather than roughness, and the wear depth and the load distribution factor increase with the profile error. (2) The roughness decreases, remains unchanged and then increases with the increment of the mesh cycle. (3) As the module and tooth width decrease or the input torque and mesh cycle increase, the tooth wear depth increases. These findings are significant in reducing tooth wear and improving the service life of gear drive.

Study of the glass fibres and internal lubricants influence in a polyamide 66 matrix on the wear evolution of polyacetal and polyamide 66 based gears in a meshing process

When designing gear systems, it is crucial to select materials to meet functional requirements of the application. It is necessary to know characteristics of the materials that will be integrated into drive components of the entire system to ensure a precise calculation of the system. In gear applications, system performance does not depend on a single material, but on material pairs that form a gear system. Therefore, it is desirable to test gears of different polymer materials to obtain relevant information regarding material data which are integrated into advanced virtual models to optimize mechanical structure. Gears are usually exposed to cyclic fatigue spectrum load, which causes degradation of the tooth flanks shape, and consequently increased teeth flanks wear, which results in lower load-carrying capacity. In this paper, wear behavior of gear pairs POM-PA66 and POM-PA66 reinforced with 30% of glass fibres with internal lubricants (PTFE and silicone oil) are analyzed and discussed considering load conditions. The results showed higher wear rate on the POM gears in comparison to PA66 based gears. It has been deduced that wear progression is nearly connected to more elastic material properties related with higher elongation and coefficient of linear thermal expansion for POM material in comparison to to PA based materials. Wear coefficients for POM and PA based materials imply that wear and deformation of gears are inversely proportional with durability. When observing materials at higher loads, it can be noticed that POM/PA66 GF30 TF15 Si has longer lifetime compared to POM/PA66 and vice versa at lower load. The authors concluded that lower wear and deformation of gear teeth have a decisive influence on good durability performance of gears.