Gear Wear Research Articles

Novel Methodology for Condition Monitoring of Gear Wear Using Supervised Learning and Infrared Thermography

In gearboxes, the occurrence of unexpected failures such as wear in the gears may occur, causing unwanted downtime with significant financial losses and human efforts. Nowadays, noninvasive sensing represents a suitable tool for carrying out the condition monitoring and fault assessment of industrial equipment in continuous operating conditions. Infrared thermography has the characteristic of being installed outside the machinery or the industrial process under assessment. Also, the amount of information that sensors can provide has become a challenge for data processing. Additionally, with the development of condition monitoring strategies based on supervised learning and artificial intelligence, the processing of signals with significant improvements during the classification of information has been facilitated. Thus, this paper proposes a novel noninvasive methodology for the diagnosis and classification of different levels of uniform wear in gears through thermal analysis with infrared imaging. The novelty of the proposed method includes the calculation of statistical time-domain features from infrared imaging, the consideration of a dimensionality reduction stage by means of Linear Discriminant Analysis, and automatic fault diagnosis performed by an artificial neural network. The proposed method is evaluated under an experimental laboratory data set, which is composed of the following conditions: healthy, and three severity degrees of uniform wear in gears, namely, 25%, 50%, and 75% of uniform wear. Finally, the obtained results are compared with classical condition monitoring approaches based on vibration analysis.

Quenching Process Simulation of Spur Gear Based on ANSYS

Gear transmission is one of the most common mechanical transmissions in contemporary machinery. It is the main form of transmission of mechanical power and movement, and it is an important part of all kinds of machinery. For gear transmission, better hardness and wear resistance are required, which can be achieved by quenching process. But the spur gear in quenching process, its size and shape will appear different degree of deformation, this paper uses the Pro/Engineering software to establish solid parameterized model of the spur gears. Then, the simplified single tooth solid model of the spur gear imported to ANSYS software to obtain the finite element model. The temperature field of the single tooth spur gear during quenching were carried out. Thus, it is concluded that the relationship between the factors influencing the quenching. The results provide a certain reference basis for the establishment of the hot working processes of the spur gear.

Dynamic modeling of planetary gear set with tooth surface wear

Wear commonly occurs in planetary gear transmission systems. Fundamentally, the tooth wear could cause tooth profile deviation, which would increase the vibration and noise of gearbox. In order to monitor and forecast the wear condition of gears via vibration-based methods, it is necessary to establish the dynamics model of a planetary gear set with tooth surface wear, which can provide a prior about the vibration characteristics of gear wear. In this study, a purely torsional dynamics model of a planetary gear set with tooth surface wear is proposed to analyze the fault mechanism of tooth surface wear. The tooth surface wear is incorporated into the dynamics model through unloaded static transmission error (USTE) and time-varying mesh stiffness (TVMS), which are evaluated by Archard’s wear equation. Subsequently, the vibration responses of the planetary gear set with tooth surface wear are analyzed. It is revealed that tooth wear would change the vibration responses in both time- and frequency-domain and the condition indicators present different trends.

A new method for testing polymer gear wear rate and performance

This paper provides details of a new test rig design and methodology intended for, and successfully applied to, measuring the gear wear rate and performance of polymer composite gears under both dry and lubricated conditions. One of its unique contributions is that it continuously measures the gear wear rate, a feature essential for understanding polymer gear behaviour. While sharing some concepts with the traditional back-to-back test configuration used for steel gears, the new method introduces a rotary freedom to the block supporting the polymer gears under test. This block rotates if the gear tooth thickness is reduced, which aids control of the test load. The gear surface wear rate is recorded continuously by using a capacitance transducer to measure the pivot block motion. A second unique contribution of the new test method involves splitting the support block so that controlled misaligned gear engagements (not reported in other designs) can be introduced and subsequent changes to wear behaviour studied. The paper first outlines the test rig concepts and design before discussing in more detail the gear wear rate measuring principles, the methods of centre distance adjustment and the achievement of virtually constant gear loading. Finally, a selection test results are presented in summary to further validate the new test method and illustrate potential applications.

Calculation of the resource of spiroid transmissions from wear in the step of loading mode

The analysis of the failure causes of the mechanisms and drives of lifting, construction, road machines on the basis of gearing gears, as well as gears of the worm class, which are contact destruction of the active surfaces of gear teeth, leading to malfunctions, breakdowns, failures in the form of wear and scuffing. A cyclogram describing the mode of operation of the gear pair, taking into account the effect of maximum load on the contact endurance and on the endurance of the teeth during bending, and which is used in strength calculations of spur and helical gears, is given. The necessity of creating a method for calculating the wear of spiroid gears based on the variable loading mode and load time taking into account the loading schedule analysis of mechanisms and drives of hoisting-and-transport machines and equipment where this type of gear is used, in particular, in the drive of stop valve mechanisms, in the drive of screw horizontal conveyor, the cable-assembly mechanism of the electric loader, in the drive of the traction winch of the packing crane UK-25/9-18 for tugging packages of rail track panel, is substantiated. The developed method makes it possible, taking into account the actual operation modes of hoisting-and-transport machines, equipment and mechanisms, by experimentally obtained dependence of the wear rate of the spiroid wheel teeth on the torque values on the output shaft of the spiroid gearbox, to determine the values of wear intensity and calculate the duration of the resource of the spiroid gearbox in accordance with the established schedule of variable mechanism loading for lifting, construction and road cars.

Automated gear fault detection of micron level wear in bevel gears using variational mode decomposition

Gearboxes have an important role in power transmission systems. For such systems, vibration-based fault diagnosis techniques are frequently used to prevent premature failure and to ensure smooth transmission. We automated the fault diagnosis of gears having level of wear fault at micron using variational mode decomposition (VMD). VMD has been applied iteratively with specific input parameters. VMD decomposes the gear vibration signal into different narrowband components (NBCs) or obtained components (OCs). Various statistical features, namely kurtosis, skewness, standard deviation, root mean square, and crest factor, were extracted from the different OCs. Kruskal-Wallis test based on probability values was used to identify the significant features. For the automation of fault detection system, a comparative study was done using the random forest, multilayer perceptron, and J48 classifiers. The proposed method exhibits 96.5 % accuracy using random forest classifier with combined kurtosis, skewness, and standard deviation features.

Assessment of modern rolling stock pulling drive gear reliability

This paper presents an issue of rolling stock pulling drive gear (PDG) reliability assessment in operation, considering the gear and pitch wheel wear. Among main damages attributive to gear and pitch wheel reject are cheeping of teeth, peeling, plastic deformation. It is noted that the PDG reliability assessment shall be reasonably carried out upon a significant probability of their fail-safe operation that is determined by the rolling contact fatigue resistance. The provided mathematical study design on the PDG reliability assessment of ER-2 electrical multiple train and the corresponding mathematical model PH.=f(Δ1, Δ2) is developed. The auxiliary curve is added to the reasonable selection of gear-pitch wheel pair. The provided materials allow to reasonably select gear-pitch wheel pairs obtaining the maximum pulling drive gear fail-safe operation probability values that result in the reliability increase. Recommendations on the further application of the suggested approach during repair of pulling drive gears of modern rolling stock are provided.

Research on a diagnostic method of gear wear fault degree based on ultra‐complete independent component analysis

In this study, a diagnostic method for gear wear fault is proposed, which is based on the ultra-complete independent component analysis. The ultra-complete analysis model is constructed, and the similar source signals more than mixing signals are separated. Based on the typical features of the fault source signal, the useful component of the mixing signals can be found. As the fault source signal and similar fault source signal are similar, the magnification range of similar shapes can be estimated by using the interval estimation method. The mapping between one-way varying magnification time domain and rotary component fault degree is identified, and the fault degree judgment standard can be established. Thus, the fault degree can be determined. The method is used to deal with the state monitoring data of the gear, and the analysis results show that the diagnostic method is of practical value.

Анализ вибрационного состояния редукторов энергоблоков

The reducers of power units are being studied. Dynamic analysis of the basic structural elements of reducers has been carried out. There have been found the possible causes of the increased wear of surfaces of toothed linkages of herringbone transfer. There are given the results of studying dynamic interactions by vibration characteristics of measuring the vibration level in bearing blocks and elements of reducers of power units at their technological operation mode. To analyze the frequency interaction of structural elements of the studied reducers there were used the results of modal analysis of earlier conducted researches of the reducer power unit. It has been stated that for conducting vibrodiagnostic control the third class machines were chosen due to their powerful primary engines, and other machines with rotating masses mounted on massive foundations, rigid in the direction of vibration measurement. Phase angles of high-speed and low-speed shaft wheels for the purpose of defining a corner of phase shift (torsional fluctuations of shaft wheels) at reverse frequencies and frequencies of toothed linkage have been studied. In terms 
 of dynamic analysis it allows to trace trajectories of linkages in toothed couples of divided wheels of herringbone gearing. The diagrams of gear trajectories are illustrated for bending vibrations 
 of the shaft-wheels. The research results confirming the nonlinear relationship between the level 
 of axial vibrations and the displacement angle of instantaneous phase angle are presented. It has been recommended to reduce the level of axial vibration transmitted from the coupling to 0.1–0.2 mm/s for eliminating uneven wear in the chevron gear; carry out structural improvements to the high-speed and low-speed shaft-wheels with increasing rigidity between the elements of chevron transmission; operate gearboxes within critical values; timely monitor the technical condition of gearboxes.

Optimization of the operating parameters to minimize gear tooth wear rate and surface temperature of glass fiber filled HDPE based homogeneous and FGM gears

This study emphasis on the optimization of the operating parameters viz. gear fabrication technique, rotational speed and applied torque on fabricated gears to improve their performance. Polymer gears are injection molded using conventional and horizontal centrifugal casting technique known as homogeneous and FGM gears, respectively. Material used to fabricate the gear is High Density Polyethylene (HDPE). Taguchi technique is used to optimize the performance output of homogeneous and FGM gears with respect to input parameters such as torque and rotational speeds. Three different rotational speeds of 400, 700 and 1000 rpm along with three different torque levels of 1, 2 and 3 Nm are selected for this investigation. Number of cycles of 1.5×105 was fixed for the experimentation. The influence of input control parameters on performance output is analysed by ANOVA analysis. The results finding show that the thermal behavior of gear is very much affected by torque whereas the specific wear rate (WR) is utmost pointedly influenced by the gear fabrication technique i.e. FGM gear has small tooth wear in the compression of homogeneous and neat HDPE gears.

Roar Aboard: Protecting Service Members' Ears on Aircraft Carriers

Roar Aboard: Protecting Service Members' Ears on Aircraft Carriers

Fault identification technology for gear tooth surface wear based on MPE method by MI and improved FNN algorithm

Multiscale Permutation Entropy (MPE) is a presented nonlinear dynamic technology for measuring the randomness and detecting the nonlinear dynamic change of time sequences and can be used effectively to extract the nonlinear dynamic wear fault feature of gear tooth surface from vibration signals of gear set. To solve the subjectivity drawback of threshold parameter selection process in MPE method, a joint calculation method based on the Mutual Information (MI) and improved False Nearest Neighbor (FNN) principle for calculating threshold parameters for MPE method was presented in this article. Then, the influence of threshold parameters on the identification accuracy of fault features with the MPE was studied by analyzing simulation data. Through the simulation analysis, the effectiveness of the proposed MPE method is validated. Finally, the wear failure test of spur gear was carried out, and the proposed method was applied to analyze the experimental data of fault signal. Meanwhile, the vibration characteristics of the fault signal are acquired. The analysis results show that the proposed method can effectively realize the fault diagnosis of gear box and has higher fault identification accuracy than the existing methods.

Influence of Housing Stiffness of the Slewing Reducer of a Tower Crane on the Load Distribution Pattern over the Gear Tooth Flank

To increase the life of slewing reducers, the reliability of their gearboxes is essential. They should be designed, simulated, and tested considering the installation environment and actual load conditions. Many studies have been conducted on the reliability improvement of gearboxes for reducers; however, a few studies have considered actual input load conditions. Furthermore, there is insufficient research on the effects of housing stiffness on gear misalignment, gear life, and load distribution and maximum contact load of the gear tooth flank. In this study, the effects of housing stiffness were analyzed using input torque measurements to investigate the causes of ring gear damage during durability tests on a slewing reducer. The contact pattern of the gear tooth flank was analyzed by applying dyes to all gears inside the reducer, and the results were compared with simulation results. A large edge contact in the first-stage ring gear of conventional slewing reducers was suggested as the cause of the ring gear damage. A new simulation model using a gearbox housing with an increased stiffness showed that edge contact was improved by the decreased gear misalignment. No abnormal wear and/or partial fracture of the ring gear occurred during the durability test on the improved model under the same conditions as those of the initial model. These results indicate that an increase in the stiffness of the housing reduced the gear misalignment, improved the load distribution, decreased the maximum load of the tooth flank, and increased the gear life.

Hypoid gear integrated wear model and experimental verification design and test

Hypoid gear abrasive wear significantly influences transmission error which may worsen gearing performance. Wear and transmission error are best studied jointly. This paper reports on a proposed integrated hypoid gear wear model which combines Archard's wear equation with a conjugate approach, tooth contact analysis. Transmission error calculation is included in this integrated wear model. The model is also tested and verified by an experimental design in which transmission error measures wear rate. This allows hypoid gear wear prediction simulation to be controlled by transmission error. It can be examined, calibrated, and synchronized with solid hypoid gear wear progress. Identical no-wear and used some-wear vehicle hypoid gears with different wear times are applied experimentally. Statistical analysis standard deviations and geometric means are used to quantify transmission error magnitude and fluctuation. Magnitude controls wear prediction geometry updates. Fluctuation examines integrated wear model accuracy by comparing transmission errors. The test suggests that the accuracy of this integrated hypoid gear wear model is acceptable as there is minimal difference between predicted gear wear and actual gear wear.

Contact analysis of a planetary gear train using linear complementarity

The current computation models for gear contact analysis and wear prediction are mostly based on finite element principles which consumes a lot of computation time and effort. In this paper, an alternate approach of linear complementarity is used for gear contact analysis. This approach was successfully applied for a pair of rigid spur gears in our previous paper. In this paper, we are extending this to a planetary gear train. The linear complementarity problem formulation is revised to take bilateral constraints into consideration. A linear complementarity solver computes the contact forces between meshing teeth of gears in gear train. From the contact forces, sliding wear in gear teeth is predicted. Archard’s wear model is used for the wear prediction.

Nonlinear dynamics of planetary gear wear in multistage gear transmission system

With the increasing service life of a gear transmission system, the gear teeth become constantly worn, and the gear clearance increases. The increase in the clearance will produce a series of nonlinear changes that change the stability of the system and can even result in loss of stability. In this paper, dimensionless dynamic equations of a multistage gear transmission system that contains a two-stage fixed-axis gear and a one-stage planetary gear were established. Planetary wear fault was simulated by changes in the gear clearance. System bifurcation diagrams with an increase in the clearance were studied. The frequency characteristics of planetary gears under different excitation frequencies and different degrees of wear were studied. The influence of planetary gear wear on the fixed-axis was discovered. The vibration mechanism and a fault diagnostic method in a multistage gear transmission system were obtained.

Regularized Deep Clustering Method for Fault Trend Analysis

Effective fault feature extraction is the key of fault diagnosis. In previous works, it is shown that some embedding methods and unsupervised deep learning methods have the ability to extract fault features from raw signals directly, such as PCA and deep autoencoder. Particularly, deep autoencoder has been shown in relevant research that it caneffectively extract the hidden ‘trend’ associated with machinery health states which can be useddirectly for online anomaly detection and prediction. However, in practical online fault diagnosis, the discrimination between successive signals is small due to the slow degradation progress and the external noise. Therefore,it is important to optimize the feature extraction process to achieve better online fault tracking. In this paper, a regularized deep clustering algorithm is proposed to guide the optimization process of feature extraction which combines embedding method and semi-guided learning. A regularization term for the cluster center points is proposed to make the feature optimization convergein a monotonic linear trend. In order to verify the effectiveness of the method, an accelerated gearbox run-to-failure experiment is carried out. The result shows that the feature optimization method can optimize the fault features on the basis of the deep autoencoder algorithm in two aspects: a better distinction of the fault features in short term and a more consistent trend of the gear wear in the long term.

A physical investigation of wear and thermal characteristics of 3D printed nylon spur gears

Abstract The use of 3D printing to manufacture nylon polymer gears is evaluated in this paper. More specifically, Nylon spur gears were 3D printed using Nylon 618, Nylon 645, alloy 910 filaments, together with Onyx and Markforged nylon proprietary materials, with wear rate tests performed on a custom-built gear wear test rig. The results showed that Nylon 618 provided the best wear performance among the 5 different 3D printing materials tested. It is hypothesised that the different mechanical performance between nylon filaments was caused by differences in crystallinity and uniqueness of the Fused Deposition Modelling (FDM) process. SEM (Scanning Electron Microscopy) revealed dramatically different wear behaviour for the 3D printed gears when compared to literature reports of injection moulded gears. Monitoring with a thermal camera during wear tests was used to analyse the thermal performance of gears during wear tests and together with SEM was used to analyse gear failure mechanisms. The performance results showed that gears 3D printed using Nylon 618 actually performed better than injection moulded nylon 66 gears when low to medium torque was applied.

Transmission characteristics of planetary gear wear in multistage gear transmission system

Gear tooth surface wear is a common failure mode. It takes a long time and can cause other major faults. The wear fault signal is weak and hard to identify. This paper reveals the transmission characteristics of the planetary gear wear and the relationship between multistage gear meshing through the transmission characteristic analysis. Taking the multistage gear transmission system fault simulation test rig as the research object, a three-dimensional solid rigid-flexible coupling model of the system was established. The contact force signals from each pair of gears in the state of planetary gear wear were obtained by dynamic simulation. The test signals of the fixed-axis gearbox and planetary gearbox were obtained under normal and planetary gear wear states. Comparing the transmission characteristics of the system under normal and planetary gear wear states, the vibration mechanism of the wear fault and the correlative characteristic between gearboxes were revealed.

Influence of the metalworking fluid on the micropitting wear of gears

Boundary layers can protect tooth flanks from metal-to-metal contacts. The characteristics of boundary layers and the resulting frictional and wear behavior are determined by the processes of manufacturing and running-in. This paper focuses on the influence of the metalworking fluid on the boundary layer formation of gear surfaces and the resulting wear behavior of the gears in terms of micropitting. Therefore, test gears were manufactured with different metalworking fluids consisting of mineral oil, ester oil and additives. The test gears were measured regarding their boundary layer properties, e.g. microstructure, reaction layers and residual stresses, which correlated with the choice of metalworking fluids in the respective grinding processes. In the subsequent tests of the wear behavior, repeatable differences in the degree of micropitting were observed. Especially the use of ester oil or chemically active sulfur additives in the grinding oils led to better tribological performances of the gears in the later application. Carry-over effects of the grinding oil from manufacturing into application as well as the need of a certain degree of mechanical and chemical energy to improve the precondition process of the gears are possible explanations for the observations made in this study.