Gear Failure Research Articles

Integration of Sensors for Enhanced Condition Monitoring in Polymer Gears: A Comparative Study of Acceleration and Temperature Sensors

As an integral part of a machine, gears are subject to wear, which is influenced by a number of factors. For polymer gears in particular, the uncertainties due to wear are high. These uncertainties outweigh the advantages of polymer gears, such as lower inertia. Improved condition monitoring, for example, with better data acquisition, could reduce these uncertainties and is therefore of great interest. This study addresses the challenges of condition monitoring in polymer gears by investigating the integration of sensors directly onto the gears for improved sensitivity. A compact sensor module mounted on a polymer gear is presented to demonstrate the benefits of integrated sensors. The research compares the effectiveness of integrated acceleration and temperature sensors with state of the art external methods. The results show that the in situ sensor module (ISM) provides reliable measurements for condition monitoring with integrated sensors. A comparative analysis with methods based on the current state of research highlights the increased sensitivity of condition monitoring based on the ISM acceleration sensors compared to traditional bearing block sensors. This increased sensitivity shows a clear advantage of integrated sensors over established methods. The temperature curve of the integrated sensors is sensitive to abrasive wear and gear failure, indicating the wider potential of integrated temperature sensors. In conclusion, this research lays the foundation for advanced condition monitoring using integrated sensors in polymer gears. The knowledge gained contributes to optimising gear applications, promoting cost-effectiveness and aligning with the principles of the Internet of Things and Industry 4.0.

Analysis of Helical Gear Failure in Off-Road 4x4 Gearbox

Analysis of Helical Gear Failure in Off-Road 4x4 Gearbox

Efficient semi-analytic method for single tooth contact analysis of loaded spiral bevel gears

Accurately and fast calculation of single tooth load contact state of a gear pair is the basis for accurate calculation of multi-tooth load contact analysis. Therefore, this study proposed a semi-analytical quick single tooth load tooth contact analysis (Q-SLTCA) method. First, the ease-off tooth contact analysis (ease-off TCA) method was established, and a numerically stable initial contact stress distribution and contact ellipse analytical model was derived. Then, considering the influence of edge contact, the real-time division method of gear tooth slice was derived. Based on this, the equivalent principle of contact elliptical node and the load correction strategy were innovatively proposed. Then, the calculation method of the meshing characteristics of the tooth slice was established by coupling the boundary element method (BEM) with the equivalent cylindrical Hertz contact theory. The bending deformation, tooth root stress distribution, contact stress, contact deformation and meshing stiffness of the tooth slice were analyzed and calculated, and the instantaneous meshing stiffness of the single tooth was determined by combining the parallel method of the gear tooth stiffness. Finally, a single-tooth finite element method (FEM) meshing model was created for comparison with the method in this study, which verified the calculation accuracy and efficiency of the proposed method. This method can be easily developed into a quick multi-tooth load contact analysis algorithm, which can provide a new method for gear tooth crack and failure analysis.

Experimental Study on High-Speed Aviation Gear Scuffing Based on Tooth Profile and Surface Treatment Improvements

Scuffing failure in high-speed aviation gears is a critical issue that hinders the improvement of operating performance and reliability in modern aviation equipment. The unclear failure mechanism limits the effective design of anti-scuffing measures. In this study, a scuffing test method was designed for high-speed aviation gears to investigate the effects of tooth profiles and surface treatment on the gear scuffing performance. The results indicate that both the pressure angle and surface treatment significantly affect gear scuffing behavior. Under different geometric treatment states, the range of the Ryder load stages at which gear scuffing initiated was between 5 and 13. The 25° pressure angle gear with barrel finishing treatment exhibited the optimal anti-scuffing performance. Compared to the ground state, barrel finishing increases gear scuffing loading capacity by 30% to 33%. Tooth profile optimization based on pressure angle changes improves gear loading capacity by 56.9%. This work provides an exploration of the anti-scuffing design of high-speed gears.

Analysing Bevel Gears for Efficient Power Transmission: A Study on Design, Simulation and Performance Assessment

Bevel gears find application in transmitting motion between unequally aligned shafts, typically forming a 90° angle relative to each other. Some of the several types that are available commercially are the straight bevel, the Zerol bevel, the spiral bevel, and the hypoid. Stainless steel, gray cast iron, titanium alloy and structural steel were used for the behavioural assessment. The design and modelling of the straight bevel gears were carried out using SolidWorks 2015, while ANSYS 18.2 was employed simulating to simulate the gears' stress and deformation. The 3D solid model generated using SolidWorks was imported into ANSYS, where the analysis was conducted using the finite element software, ANSYS Workbench. Stress distribution plot, deformation plot, and equivalent strain plot were generated. The highest stress, measuring 73.536 MPa, became evident as the load concentrated near the base of the gear teeth. The finite element analysis revealed a minimal likelihood of gear failure, and the least deformation was observed in the structural steel configuration, resulting in a deformation of 8.2354 x 10^-3 mm. Consequently, the gear pair can successfully transmit 6 kW of power without experiencing any failures with a good safety factor

Tooth surface analysis method based on thermo-mechanical coupling and its application in prediction of gear dry-running bearing capacity

In gear transmission, the continuous meshing of the teeth will lead to an increase in their temperature, which will have a certain impact on the working performance of the tooth surface. In order to explore the failure-bearing capacity of gears under dry-running conditions, temperature effects were considered in existing methods for determining tooth surface failure, making it more suitable for high-temperature working conditions caused by a lack of lubrication. The failure situation of gears within 35 min after losing lubrication was analyzed. The results indicate that when the gear loses lubrication, the tooth surface temperature of the gear pair has exceeded the material melting point after working at an input power of 2000 kW for 12 min. But when the power drops to 1000 kW, the instantaneous temperatures of the driving and driven gear tooth surfaces at the end of 35 min reach 1090 and 995°C, respectively, which are lower than the scuffing temperature of the tooth surface. The cumulative wear depths of the driving and driven gear tooth surfaces at the end of 35 min were 239 and 86.6 um, respectively, which were lower than the failure wear depth of the tooth surface; The allowable contact stress of the gear pair within 35 min is greater than its contact stress, meeting the judgment condition of no pitting failure. This indicates that reducing power can appropriately extend the failure time of gear teeth, thereby improving the ultimate working capacity of gears under dry-running conditions. In addition, a gear dry-running experiment was carried out. By comparing the theoretical calculation results with the measured gear failure degree, it shows that the improved method for determining gear surface failure is effective.

On the usage of pulsator data within the load spectra assessment of gears

Tooth root fatigue fracture is one of the most critical gear failure modes. This is due to the fact that it may cause a sudden interruption of the power flow within the gearbox, which typically results in the complete failure of the transmission. Therefore, a crucial design aspect is the accurate characterization of the gear bending fatigue strength. Here, designers can rely on experimental tests in order to obtain data related to their specific industrial reality.Within this context, pulsator test, also called Single Tooth Bending Fatigue (STBF) test, is the most adopted experimental methodology. As such tests are performed only on selected teeth within a testing device and not on all teeth of a running gear pair, the pulsator experimental outcome has to be elaborated before using it in the actual design phase.Depending on the elaboration methods, several SN curves can be obtained, and those curves will differ from the one predicted by the standards (e.g. ISO 6336 and ANSI AGMA 2001-D04). Furthermore, different SN curves will provide a different assessment when load spectra are considered. Here, the usage of data obtained from pulsator tests is analyzed within the phase in which load spectra are considered while designing a gear. In particular, this article discusses the differences between various elaboration methodologies and an assessment based on standardized curves.

Stress Distribution Analysis using ANSYS of the Nose Landing Gear of STOL Aircrafts Considering Runway Gradient: A Simulation Study

Landing gear failures are a major cause of aircraft failures because they are an integral part of the aircraft's development. According to the Federal Aviation Administration (FAA), 50% of all aircraft failures occur during take-offs and landing. The landing gear of a short take-offs and landing (STOL) aircraft has had its static and dynamic forces analyzed analytically and numerically. SOLIWORKS is used to model the landing gear, and ANSYS is used to perform the numerical simulation results. Following it, the model is examined for stress and deformation with the boundary conditions and computed loads into account. This study uses structural finite element analysis (FEA) to analyze the nose gear's stress behavior and displacement during landing, as well as to assess the effect of the runway gradient. Utilizing a comprehensive numerical simulation, the landing gear of a real material Twin-Otter STOL aircraft has been demonstrated to be subjected to a dynamic force of 3653.26N, a pneumatic pressure of 1.59MPa, a bead pressure of 7.97MPa, and a vertical force of 1672.31lbs on level runways, or runways with no gradient. These findings will increase the level of confidence of aircraft manufacturers to make necessary appropriate design of STOL aircraft’s landing gear. It may can decrease the aircraft accidents and increase human life safety ultimately saving valuable time and resources too.

Effect of Carburizing Composite Laser-Shock Processing on Properties and Microstructure of 20CrNiMo Steel

In the service process of gears, premature fatigue failure or fracture of gears is often caused by poor surface performance. 20CrNiMo steel is a commonly used material for gears. Laser-shock peening (LSP), carburizing treatment (CT), and hybrid modification of carburizing treatment and laser-shock peening (LSP + CT) were carried out to improve the performance of 20CrNiMo steel. The hardness, residual stress, microstructure, subgrain size, and toughness of the samples were analyzed following various modification methods. It was observed that the properties of the composite-modified gradient structure materials achieved through carburizing and laser-shock peening were superior to those modified using single methods. After the composite treatment of carburizing and laser shocking, the samples exhibited the most significant increase in hardness, up to 916HV0.1, with a surface layer experiencing residual compressive stress as low as −635 MPa. Simultaneously, a gradient microstructure was formed on the surface layer, with 80% of the crystallites being in the nanoscale range. Furthermore, the toughness was notably enhanced. Experimental results confirm the improvement in the properties of 20CrNiMo samples, resulting in the creation of a functionally graded material through the composite treatment of carburizing and laser shocking.

Investigation of parameters for fault detection of worm gear box using denoise vibration signature

In industrial applications, worm gearboxes are a key element. In a worm gearbox, as the material of a worm wheel is softer than that of a worm screw, the worm wheel gear is vulnerable to failure through various modes like pitting, wearing out, or tooth breakage during the sliding process. Due to this, it is essential to monitor the failure of the worm wheel gear of the worm gearbox, and it has gained importance for the diagnosis of faults in gearboxes. The present work focuses on the investigation of the effect of worm wheel tooth breakage, worm wheel bearing outer race, and varying load on vibration signature amplitude and frequency domain statistical features such as root mean square (RMS), crest factor, kurtosis, mean, peak to peak, skewness, sample variance, and standard deviation. The experimental setup is fabricated to conduct the experimental trials. An OR34 FFT analyzer with NVGate software is used to acquire the frequency domain vibration signature. Experimental results show that captured vibration signature amplitude for healthy worm wheel and bearing increased as fault occurred on the worm wheel, and bearing and frequency domain statistical features value changed with the change in fault location in the worm gearbox.

Tooth interior fatigue fracture in automotive differential gears

Tooth Interior Fatigue Fracture (TIFF) is an emerging gear failure mode with significant implications for gear lifetime and reliability, particularly in modern mechanical transmissions subjected to higher loads, smaller sizes, and increased Noise, Vibration, and Harshness (NVH) requirements. This paper investigates fatigue cracks initiated within the interior of pinion and/or side gear teeth in transmission differentials, representing a new area of recent failure detection. Conventional modeling has suggested that TIFF cracks originate in the case/core area of gear teeth, primarily seen in idler transmission gears. However, this study challenges this notion by presenting evidence that cracks often form closer to the middle of the tooth at various heights. These findings indicate the need for a deeper understanding of TIFF, as the existing theoretical descriptions may not fully explain the observed behaviors. By focusing on this novel area of failure, the paper highlights the importance of addressing TIFF to improve the reliability and durability of gears in modern mechanical transmissions.

Fault feature detection of planet gear in multi-stage planetary gearbox based on angle compensation synchronous averaging

Planetary gearboxes are often used for power transmission in wind turbines. It makes the gear fault detection of planetary gearboxes very useful and necessary. Generally, windowed synchronous averaging (WSA) is a widely used method to detect planet gear failure in planetary gearboxes. However, the WSA is not directly suitable for the multi-stage planetary gearbox since different planetary stages are working together and vibrations from different stages are coupled to each other. The coupled interference is the synchronous interference, which cannot be reduced by the WSA. It makes the faulty planet gear of interest difficult to detect. To address this issue, an angle compensation synchronous averaging (ACSA) scheme is proposed. The equi-angle resampling is applied to the obtained vibration first. Then, the synchronous interference can be constructed by applying the synchronous averaging-based angle compensation strategy, and removed by subtracting it from the resampled vibration. Subsequently, the fast spectral kurtosis is utilized on the residual vibration to obtain the envelope signal. Next, the WSA is further applied to the residual vibration and envelope signal for constructing the synthetic vibration and synthetic envelope signal corresponding to the planet gear of interest. Finally, the narrowband demodulation and envelope analysis are used to detect planet gear failure. Experiments on a two-stage planetary gearbox positively support the ACSA scheme.

Design, Load Analysis and Optimization of Epicyclic Gear Trains

Abstract: Mechanical power transmission systems rely heavily on Epicyclic gear trains, as their failure can compromise the entire system. Consequently, identifying and mitigating the causes of gear failure is crucial. Various gear failure modes, including bending pitting (contact stresses), failure (load failure), abrasive wear, and scoring, are discussed in literature by J.R. Davis(2005) [24], Khurmi & Gupta (2006) [23], and P. Kannaiah (2006) [21][22]. These failures are often linked to the loads acting on the gears. This research focuses on optimizing gear design to reduce gear load failure. Table 1 summarizes various research efforts on Epicyclic gear trains conducted by different authors. This study delves into the optimization of epicyclic gear trains in India to minimize load failure. The analysis focuses on optimizing the gear train through load analysis of the pinions, gears, and annulus, including the sun and planet gears. The goal is to determine the optimal load conditions for the gear train to function effectively without succumbing to load failure. Epicyclic Gear Trains are widely used in industry due to their numerous advantages, including high torque capacity, improved efficiency, relatively smaller size, lower weight, and a highly compact package. However, there has been no comprehensive study of their load-bearing performance with respect to various parameters such as rotational speed, material, and power. This research paper aims to fill this gap by investigating the load performance of epicyclic gear trains under different parameters such as loading conditions and rotational speeds. This process helps in identifying the optimized design of epicyclic gear trains, ensuring optimal performance and minimizing gear loads and choosing correct rotational speed. The primary objective of this research investigation is to optimize epicyclic gear trains through load analysis to prevent future load failures.

Root cause analysis of flywheel gear failure in a marine diesel engine

Engine gear failures are of significant concern across a wide range of industries. It is important to investigate each gear failure in light of its unique loading and operating conditions for root cause analysis (RCA) and further corrective actions to avoid such failures in the future. The aim of this study was to investigate the premature failure of a flywheel gear of a marine diesel engine and establish the root cause and damage mechanisms using experimental and numerical analysis techniques. A bottom-up creative approach was adopted to assess the loading conditions on the failed gear by first estimating the bending deformation of the failed securing bolt, assuming overload torque on the flywheel caused an equivalent bending moment permanently bending the bolt. Von Mises equivalent stress acting on the gear was numerically estimated as σVM = 737 MPa, which was found significantly more than the specified yield strength of gear governing material AISI 1055 (σY = 550 MPa). SEM fractography revealed a quasi-cleavage failure mechanism in the ‘case’ region near the gear root and a ductile failure mechanism inside the ‘core’ region of the flywheel gear. A crack was found to initiate from the gear root consisting of high-stress concentration under overload stresses. RCA established that the flywheel gears had failed by overload stresses, caused due to overload torque generated from sudden inertial thrust in the internal combustion (IC) engine due to excess fuel throttle opening.

Residual Strength Modeling and Reliability Analysis of Wind Turbine Gear under Different Random Loadings

A novel method is proposed to investigate the pattern of variation in the residual strength and reliability of wind turbine gear. First, the interaction between loads and the effect of the loading sequence is considered based on the fatigue damage accumulation theory, and a residual strength degradation model with few parameters is established. Experimental data from two materials are used to verify the predictive performance of the proposed model. Secondly, the modeling and simulation of the wind turbine gear is conducted to analyze the types of fatigue failures and obtain their fatigue life curves. Due to the randomness of the load on the gear, the rain flow counting method and the Goodman method are employed. Thirdly, considering the seasonal variation of load, the decreasing trend of gear fatigue strength under multistage random load is calculated. Finally, the dynamic failure rate and reliability of gear fatigue failure under multistage random loads are analyzed. The results demonstrate that the randomness of residual strength increases with increasing service time. The seasonality of load causes fluctuations in the reliability of gear, providing a new idea for evaluating the reliability of the wind turbine gear.

Analytical and Experimental Investigation to Resolve Surface Related Fatigue Failure in Helical Gears

With the improvement of metallurgical process and tools it became possible to modify the material property of the steel to a desired possible level where its torque transmission capability can be enhanced. Case hardening and surface grinding is one such method which is used to leverage the surface durability and core strength of gears. With the enhancement in the torque transmission capability the load per unit area of face width also increased causing huge surface pressure. They are subjected to various conditions of load, speed, temperature, and ambient conditions. Micropitting is one such surface related failure which starts on tooth flank in terms of surface texture change. This may further grow in magnitude and result in catastrophic failure. This research work is performed to compare the results of analytical and experimental investigation for the possible micropitting initiative zone. Analytical approach is carried out by using the KISSsys model and the experimental work is carried out by using a dynamometer test rig to apply the load on the gearbox shaft for a defined load cycle. It was clearly visible that the micropitting has initiated below the pitch line of pinion. Tooth profile is later modified with lead and crown modification. After the application of this modification the tooth profile related failure was not visible for similar load testing cycle.

Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network.

The industrial gearboxes usually work in harsh and variable conditions, which results in partial failure of gears or bearings. Accordingly, the continuous irregular fluctuations of gearbox under variable conditions maybe increase the intraclass difference and reduce the interclass difference for the monitored samples. To this end, a new intelligent fault diagnosis method of gearbox based on adaptive intraclass and interclass convolutional neural network (AIICNN) under variable working conditions is proposed. The core of the proposed algorithm is to apply the designed intraclass and interclass constraints to improve the distribution differences of samples. Meanwhile, the adaptive activation function is added into the 1-D convolutional neural network (1dCNN) to enlarge the heterogeneous distance and narrow the homogeneous distance of samples. Specifically, the training sample subset with intraclass and interclass spacing fluctuations under variable conditions is first converted into frequency domain through the fast Fourier transform (FFT), and the designed AIICNN algorithm is employed for model training. Afterward, the testing subset is provided to the trained AIICNN algorithm for fault diagnosis. The experimental data of the planetary gearbox test rig verify the feasibility of the proposed diagnosis method and algorithm. Compared with other methods, this method can eliminate the difference of sample distribution under variable conditions and improve its diagnostic generalization.

STATUS OF INSURANCE IN THE FISHERIES SECTOR OF INDIA

Indias fisheries sector has grown rapidly during the last six decades. Risks associated with capture fisheries include trawler damage or destruction, equipment and gear failure, catch loss, and maritime casualties. With the exception of a few tiny local public sector insurers and cooperatives, neither the federal nor state governments have paid attention to this industry. Since the Insurance Regulation and Development Authority liberalised the insurance industry, about 35 private enterprises have been registered (IRDA). A range of obstacles and concerns usually arise as a result of the adoption of fisheries insurance. Combined with governance reforms, technology has the potential to significantly improve efficiency, transparency, and moral hazard in fisheries insurance.

Advantages in the production of power transmitting gears by fineblanking

Fineblanking of gears has an enormous time and cost saving potential as well as the potential to significantly reduce CO2 emissions compared to conventional manufacturing of gears. Conventional manufacturing of gears consists of at least three steps such as milling, case hardening, and grinding. With fineblanking, only one manufacturing step is necessary. However, the load-carrying capacity regarding different gear fatigue failure modes, such as pitting or tooth root breakage, is stated significantly lower for the commonly used shear-cutting steels compared to the conventional case-hardened gears made out of high-strength hardened steels. This work shows the possibility of utilizing compressive residual stresses that are induced by the fineblanking process to increase the load-carrying capacity regarding tooth root breakage up to the level of case-carburized gears. Pinions and wheels made of S355MC (1.0976) and S500MC (1.0984) are fineblanked using parameters determined in previous works with a focus on the induction of high compressive residual stresses into the finished products. The variants are investigated regarding, e.g., cut surface characteristics, hardness, and residual stresses. For the two steels, as well as a stress relived variant, the tooth root bending strength is also determined in pulsator tests with the fineblanked pinions.

Optimization of Gearbox Fault Detection Method Based on Deep Residual Neural Network Algorithm.

Because of its long running time, complex working environment, and for other reasons, a gear is prone to failure, and early failure is difficult to detect by direct observation; therefore, fault diagnosis of gears is very necessary. Neural network algorithms have been widely used to realize gear fault diagnosis, but the structure of the neural network model is complicated, the training time is long and the model is not easy to converge. To solve the above problems and combine the advantages of the ResNeXt50 model in the extraction of image features, this paper proposes a gearbox fault detection method that integrates the convolutional block attention module (CBAM). Firstly, the CBAM is embedded in the ResNeXt50 network to enhance the extraction of image channels and spatial features. Secondly, the different time-frequency analysis method was compared and analyzed, and the method with the better effect was selected to convert the one-dimensional vibration signal in the open data set of the gearbox into a two-dimensional image, eliminating the influence of the redundant background noise, and took it as the input of the model for training. Finally, the accuracy and the average training time of the model were obtained by entering the test set into the model, and the results were compared with four other classical convolutional neural network models. The results show that the proposed method performs well both in fault identification accuracy and average training time under two working conditions, and it also provides some references for existing gear failure diagnosis research.