Gearbox Efficiency Research Articles

Using TOPSIS Method for Solving Multi-Objective Optimization of a Two-stage Helical Gearbox with First Stage Double Gear-sets

In order to build a two-stage helical gearbox (THG) with first stage double gear-sets (FSDG), the multi-criteria decision-making (MCDM) method is introduced in this research as a new approach to solving the multi-objective optimization problem (MOOP). The study's objective is to deter-mine the best primary design factors that simultaneously satisfy two goals: maximal gearbox ef-ficiency and minimal gearbox mass. To that end, the first stage's gear ratio and the first and sec-ond stages' CWFW were chosen as the three main design elements. Furthermore, two distinct goals were analyzed: the lowest gearbox mass and the highest gearbox efficiency. Additionally, the MOOP is carried out in two steps: phase 1 solves the single-objective optimization problem to close the gap between variable levels, and phase 2 solves the MOOP to determine the optimal primary design factors. Furthermore, the TOPSIS approach was selected to address the MOOP problem. For the first time, an MCDM technique is used to solve the MOOP of a helical gearbox with FSDG. Additionally, this is the first investigation of the total gearbox efficiency, which includes the power losses during idle. When designing the gearbox, the optimal values for three crucial design parameters were ascertained using the study's results.

The new constructive design of the planetary gearbox winches

Although the constructions of planetary reducers are complex, their technical indicators are higher than other gear boxes, and their overall dimensions are smaller. In this article, the constructions of planetary gearboxes were investigated, and an in-depth literature analysis was conducted on their modernization. Application of these gearboxes with high technical indicators and compact dimensions in lifting mechanisms would be suitable for the purpose. Thus, small overall size, large efficiency, and high reliability are the main requirements for winches, and planetary gearboxes can also provide these features. But for some reason, traditionally, geared elevator winches are mainly made with worm gearboxes. This is mainly due to the fact that they provide a high gear ratio in single stage and self-braking. But the efficiency of worm gear box is small, and the friction losses are larger. Therefore, it is time and necessity to replace them with other progressive designed gearboxes in the lifing winches. Taking these into account, in the article, as a result of structural and kinematic analysis and synthesis of planetary gearboxes, new constructions were developed and structural schemes were proposed for their application in the lifting mechanisms. For each of these schemes, the transmission ratio and efficiency were evaluated and compared with each other. The proposed schemes can be applied in the different types of lifting winches. The application fields of winches are different. Winches are more commonly used in drilling equipment and elevators. Winches are the main units of these equipments. Winches and their braking systems must meet operational requirements and operating conditions. Their strength and traction must be sufficient to perform the most demanding technological operations. Lifting and lowering speeds should ensure accident-free operations, be economically efficient and highly productive.

Solving a Multi-Objective Optimization Problem of a Two-Stage Helical Gearbox with Second-Stage Double Gear Sets Using the MAIRCA Method

This paper provides a novel application of the multi-criteria decision-making (MCDM) method to the multi-objective optimization problem (MOOP) of creating a two-stage helical gearbox (TSHG) with second-stage double gear sets (SDGSs). The aim of the study is to determine the optimum major design components for enhancing the gearbox efficiency while reducing the gearbox volume. In this work, three primary design parameters are chosen to accomplish this: the gear ratio of the first stage and the coefficients of the wheel face width (CWFW) of the first and second stages. Additionally, the study is conducted with two distinct objectives in mind: the lowest gearbox volume and the maximum gearbox efficiency. Moreover, phase 1 and phase 2, respectively, are the two stages of the MOOP. Phase 2 handles the MOOP to identify the ideal primary design factors as well as the single-objective optimization problem to minimize the difference between the variable levels. Additionally, the Multi-Attributive Ideal–Real Comparative Analysis (MAIRCA) approach is selected to deal with the MOOP. The results of the study are utilized to determine the ideal values for three crucial design parameters in order to create a TSHG with SDGSs.

Multi-Objective Optimization of a Two-Stage Helical Gearbox with Second Stage Double Gear-Sets Using TOPSIS Method

The multi-criteria decision-making (MCDM) method was applied in a novel way in this study to the multi-objective optimization problem (MOOP) of designing a two-stage helical gearbox with double gear-sets in the second stage. Finding the best fundamental components to increase gearbox efficiency and decrease gearbox cross-section area was the aim of this study. Three main design factors were chosen for investigation in this work: the first stage gear ratio and the first and second stage coefficients of wheel face width (CWFW). Phase 1 solves the single-objective optimization problem to reduce the gap between variable levels, and phase 2 solves the MOOP to determine the optimal critical design factors. This additionally splits the MOOP into two phases. Additionally, the TOPSIS method was used as an MCDM approach to address the multi-objective optimization issue, and the entropy approach was used to compute the weight criteria. In this study, gearbox efficiency is calculated by considering power losses during idle motion. The multi-objective optimization of a helical gearbox with second stage double gear-sets is addressed using the TOPSIS technique for the first time.

Multi-Objective Optimization of a Two-Stage Helical Gearbox Using MARCOS Method

In order to address the Multi-Objective Optimization Problem (MOOP) in building a two-stage helical gearbox, this work presents a novel application of the Multi-Criterion Decision-Making (MCDM) method. The aim of the study is to determine the optimal primary design factors that will increase gearbox efficiency while decreasing gearbox volume. Three main design parameters were chosen for assessment in this work: the first stage’s gear ratio, and the first and second stages’ Coefficients of Wheel Face Width (CWFW). In addition, the MOOP is divided into two phases: phase 1 solves the single-objective optimization problem to reduce the gap between variable levels, and phase 2 solves the MOOP to determine the optimal primary design factors. Furthermore, the Entropy approach was picked to compute the weight criteria, and the MARCOS method was chosen as an MCDM method to handle the multi-objective optimization issue. The following are important characteristics of the study: Firstly, the MCDM method (MARCOS technique) was successfully applied to solve a MOOP for the first time. Secondly, this work has looked into power losses during idle motion to calculate the efficiency of a two-stage helical gearbox. The results of the study were used in the design of a two-stage helical gearbox in order to identify the optimal values for three important design parameters.

Application of a Multi-Criterion Decision-Making Method for Solving the Multi-Objective Optimization of a Two-Stage Helical Gearbox

This paper provides a novel application of a multi-criterion decision-making (MCDM) method to the multi-objective optimization problem of designing a two-stage helical gearbox. This study’s goal is to identify the ideal primary design elements that increase gearbox efficiency while reducing the gearbox cross-section area. In this work, three primary design parameters were selected for investigation: the gear ratio of the first stage and the coefficients of wheel face width (CWFW) of the first and second stages. The multi-objective optimization problem was further split into two phases: phase 1 solved the single-objective optimization problem of minimizing the gap between the variable levels, and phase 2 solved the multi-objective optimization issue of identifying the ideal key design factors. Moreover, the multi-objective optimization problem was handled by the SAW method as an MCDM approach, and the weight criteria were computed using the entropy approach. This study’s significant characteristics are as follows: First, a multi-objective optimization problem was successfully solved using the MCDM approach (SAW technique) for the first time. Second, the power losses in idle motion were investigated in this work in order to determine the efficiency of a two-stage helical gearbox. From this study’s findings, the ideal values for three major design parameters can be determined for the design of a two-stage helical gearbox.

The investigation of the effect of operating conditions in gearboxes on efficiency

Efficiency is a concept that evaluates the optimal utilization of resources, including time, energy, finances, or materials, in order to accomplish a particular goal or objective. As widely acknowledged, energy losses occur in systems involving relative motion between interacting machine elements due to friction. In the case of a gearbox, these losses can arise from tooth friction in the gear mechanism, friction in sealing elements, friction in roller bearings, and the influence of the lubricant used in the system, all of which are subject to environmental conditions. This study aims to experimentally determine the efficiency of the gearbox under various operating conditions by considering the gearbox as a comprehensive system encompassing all its components. A measurement system was designed in order to obtain the efficiency of a gearbox. Experiments and measurements were carried out via software support. The measurement system contains two torque transducers, electrical resistive load device, an electrical motor with temperature measurement thermocouple, and two stage helical gearbox. In experiments conducted through computer commands, input revolutions were incrementally increased with 400 rpm intervals within the range of 700–2700 rpm. Moreover, experiments were carried out at different lubricant levels in the gearbox. At the same time lubricant temperature was measured and effects to the gearbox efficiency were investigated. Subsequently, different lubricant with distinct viscosity indices were employed. As a result of this experimental design, regime efficiency values were obtained for each case. Thus, power loss of the gearbox system has been determined. These results were examined using a general full factorial design. Analysis of variance (ANOVA) tables were created and the effects of the parameters on the system and the efficiency results were determined by checking whether the parameters were interacting or not. Finally, regression analysis was performed and the regression function was obtained in order to develop a predictive model to estimate the efficiency of a gearbox.

Optimization of a Two-stage Bevel Helical Gearbox using Multiple Objectives to Increase Efficiency and Reduce Gearbox Bottom Area

This study aims to look at multi-target optimization of two-stage bevel helical gearboxes to determine the best major design factors for reducing gearbox bottom area (GBA) and increasing gearbox efficiency (GE). Grey relation analysis (GRA) and the Taguchi technique were used to address the problem in two steps. Prioritizing the closure of the variable level gap, the single-objective optimization problem was addressed, followed by the multi-objective optimization problem, which identified the ideal primary design variables. Additionally, the first-stage gear ratio, allowable contact stresses (ACS), and first and second-stage coefficients of wheel face width (CWFW) were calculated. The outcomes of the study were used to determine the best values for five essential design features of a two-stage bevel helical gearbox (BHG).

Optimization of a Two-stage Helical Gearbox with Second Stage Double Gear Sets to Reduce Gearbox Mass and Increase Gearbox Efficiency

This work aims to identify the key design components for lowering gearbox mass and raising gearbox efficiency by multi-target optimizing a two-stage helical gearbox (THG) with second-stage double gear sets (SSDGS). In the study, the Taguchi technique and grey relation analysis (GRA) were applied to handle optimization work in two phases. The single-target problem was addressed first to narrow the separation between variable levels, and then multi-target work was addressed to establish the best primary design variables. The first and second-stage CWFW coefficients, as well as the allowed contact stresses (ACS) and the gear ratio of the first stage, were computed. The outcomes of the study can be applied to determine the best values for the main essential design factors of a THG with SSDGS.

Wear and friction of self-lubricating coatings applied to spur gears in fluid-free aerospace actuation gearboxes

Aerospace actuation gearboxes operate in low-temperature environments where increased lubricant viscosity leads to significant no-load power losses. Replacing fluid lubricants with coatings applied to the gear teeth is one potential approach to improving gearbox efficiency. Here we develop an approach to determining average wear rates of coated gears using a power-recirculating test stand, profile measurements and a model of the tooth contact. Worn gears are inspected using scanning electron imagery, and energy dispersive X-ray and Raman spectroscopy to understand the wear mechanisms and failure modes. Average coefficients of friction are determined at 20°C and −40°C using a power-absorbing test stand and isolation of tooth friction losses by calculation. These methods are then demonstrated on a promising C/Cr composite coating.

Application of the Taguchi Method and Grey Relational Analysis for Multi-Objective Optimization of a Two-Stage Bevel Helical Gearbox

This paper introduces a novel approach to deal with the multi-objective optimization of a two-stage bevel helical gearbox by applying the Taguchi method and Grey Relation Analysis (GRA). The goal of the study is to find optimal main design factors that minimize the gearbox volume and maximize the gearbox efficiency. To accomplish this, five main design parameters were selected: the coefficients of wheel face width (CWFW) of the bevel and the helical gear sets, the allowable contact stresses (ACS) of the first and the second stages, and the gear ratio of the first stage. Furthermore, two single targets were investigated: minimum gearbox volumes, and maximum gearbox efficiency. Also, the multi-objective optimization problem is solved through two steps: Step 1 for closing the gap between variable levels and Step 2 for determining the optimal main design factors. The study’s findings were used to introduce the optimum values of five major design parameters for designing a two-stage helical gearbox.

Multi-Objective Optimization of a Two-Stage Helical Gearbox Using Taguchi Method and Grey Relational Analysis

This paper presents a novel approach to solve the multi-objective optimization problem designing a two-stage helical gearbox by applying the Taguchi method and the grey relation analysis (GRA). The objective of the study is to identify the optimal main design factors that maximize the gearbox efficiency and minimize the gearbox mass. To achieve that, five main design factors. including the coefficients of wheel face width (CWFW) of the first and the second stages, the allowable contact stresses (ACS) of the first and the second stages, and the gear ratio of the first stage were chosen. Additionally, two single objectives, including the maximum gearbox efficiency and minimum gearbox mass, were analyzed. In addition, the multi-objective optimization problem is solved through two phases: Phase 1 solves the single-objective optimization problem in order to close the gap between variable levels, and phase 2 solves the multi-objective optimization problem to determine the optimal main design factors. From the results of the study, optimum values of five main design parameters for designing a two-stage helical gearbox were first introduced.

A Theoretical and Experimental Study on the Power Loss of Gearbox Based on Dimensionless Analysis

Abstract A prediction model of gearbox power loss based on dimensionless analysis is proposed. First, the dimensional model of gearbox power loss is established based on similarity criterion, dimensional harmony principle, and fluid mechanics π theorem. Then, the experimental study is carried out on a power loss test bench. Based on the measured data and multiple linear regression method, the coefficients of the influencing factors are calculated, including gear design parameters, lubrication oil parameters, and operating conditions. To validate the prediction model, the gear pairs were tested under various operating conditions, and two new gear sets with different helical angles were also included. The comparison results show good consistency between the measured data and predicted values. The proposed model can be employed to effectively predict the power loss of gearbox and improve the gearbox efficiency.

Development and research of the efficiency of a tractor transmission with a disc type gearbox

BACKGROUND: Modern tractors are equipped with gearboxes that are divided into three ranges, such as slow, operating and transport, for the sake of better power usage and fuel efficiency of the engine as well as getting higher performance. In addition, gearboxes must have a large number of gears, that leads to an increase in their mass and dimensions. An increasing mass of gearbox leads to additional high-quality metal consumption as well as energy costs for self-propelling of a tractor, which reduces its operational capabilities.
 AIMS: Increasing the number of gears and reducing the weight of gearboxes for agricultural tractors.
 METHODS: A disc-type gearbox (Patent RF No. 208805) has been developed to make it possible to increase the number of gears and reduce the weight of gearboxes for agricultural tractors. The feature of this gearbox is the gear disk with three gear rims on top and three on the bottom that is installed in its housing in addition to the usual gears and shafts. The implementation of the gear disk with gear rims makes it possible to reduce the number of gearwheels by more than half. The experimental gearbox is manual and interrupted-drive. It gives 18 forward gears and 18 reverse gears. Laboratory studies of a tractor with the experimental gearbox were carried out on a roller test bench. Load condition was arranged with the STEU-40 electric brake test rig in order to determine the transmission efficiency. During the testing, the torques on the gearbox input shaft and the tractor half shafts were measured. Reliability testing of the experimental gearbox, built in the LTZ-55 tractor, lasted for 2714 hours under the normal operation condition.
 RESULTS: The results of the transmission efficiency study at the 1st, 5th and 10th gears with different drive wheels torques as well as different oil temperatures revealed that the transmission efficiency is in the range of 0.75-0.96 at the transmission oil temperature of 16 to 60C, which corresponds to the numerical values of fixed-ratio transmissions of stock tractors. Operational tests of the tractor, equipped with the experimental gearbox, showed efficiency of gearbox during operation of 2714 hours.
 CONCLUSIONS: Laboratory studies of the LTZ-55 tractor, equipped with the experimental gearbox (Patent No. 208805), showed that the transmission efficiency improves with an increase in the drive wheels torque and the transmission oil temperature, and deteriorates with an increase in the gear number. The efficiency of the experimental transmission is in the range from 0.75 to 0.96, which corresponds to stock manual interrupted-drive transmissions of tractors. With an increase in oil temperature up to 60 C, the efficiency of the transmission greatens.

Performance Monitoring of Wind Turbines Gearbox Utilising Artificial Neural Networks — Steps toward Successful Implementation of Predictive Maintenance Strategy

Manufacturing and energy sectors provide vast amounts of maintenance data and information which can be used proactively for performance monitoring and prognostic analysis which lead to improve maintenance planning and scheduling activities. This leads to reduced unplanned shutdowns, maintenance costs and any fatal events that could affect the operations of the overall system. Performance and condition monitoring are among the most used strategies for prognostic and health management (PHM), in which different methods and techniques can be implemented to analyse maintenance and online data. Offshore wind turbines (WTs) are complex systems increasingly needing maintenance. This study proposes a performance monitoring system to monitor the performance of the WT power generation process by exploiting artificial neural networks (ANN) composed of different network designs and training algorithms, using simulated supervisory control and data acquisition (SCADA) data. The performance monitoring is based on different operating modes of the same type of wind turbine. The degradation models were developed based on the generated active power resulting from different degradation levels of the gearbox, which is a critical component of the WTs. The deviations of the wind power curves for all operating modes over time are monitored in terms of the resulting power residuals and are modelled using ANN with a unique network architecture. The monitoring process uses the recursive form of the cumulative summation (CUSUM) change detection algorithm to detect the state change point in which the gearbox efficiency is degraded by evaluating the power residuals predicted by the ANN model. To increase the monitoring effectiveness, a second ANN model was developed to predict the gearbox efficiency to monitor any failure that could happen once the efficiency degrades below a threshold. The results show a high degree of accuracy in power and efficiency prediction in addition to monitoring the abnormal state or deviations of the power generation process resulting from the degraded gearbox efficiency and their corresponding time slots. The developed monitoring method can be a valuable tool to provide maintenance experts with alarms and insights into the general state of the power generation process, which can be used for further maintenance decision-making.

The Impact of Lubricant Viscosity and Materials on Power Losses and Efficiency of Worm Gearbox

The Impact of Lubricant Viscosity and Materials on Power Losses and Efficiency of Worm Gearbox

Theoretical transmission analysis to optimize Gearbox for a 2.6 kW automatic pepper transplanter

A gearbox is an essential component of an automatic transplanter to transmit engine power to the transplanter components. It is necessary to find the appropriate gearbox dimensions and materials for the pepper transplanter to minimize transmission losses. Therefore, the objectives of this research were to simulate the power transmission efficiency of the gearbox, and to determine a suitable number of stages, and materials and the dimensions of the spur gears. A 2.6 kW gasoline engine was considered as the prime source to power the entire transplanter. The available maximum length between the engine and transplanter subsystem was 422 mm. By considering design issues, a simulation model was created to determine the efficiency of the pepper transplanter gearbox, including various types of mechanical losses in the gearing system. Three different modules (1, 2, and 3 mm) and two materials were used to evaluate the effects on transmission. The analysis results indicated that the gearbox transmission efficiency levels of seven to twelve stages were in the range of 93.0–98.7%, whereas the eight-stage gearbox yielded the maximum efficiency of 98.7%, greater than our target efficiency of 98.0%. Therefore, an eight-stage gearbox was selected for power transmission to the components. The power transmission simulation results showed that the overall efficiency from engine to transplanting mechanism shaft varied in range of 95.2–95.9% owing to contact of the gear meshes. The analysis results also indicated that the 25CrMo4 carbon steel material with a 2-mm module gear was appropriate for the pepper transplanter. The analysis in this paper can be used as reference in the design of pepper transplanter gears and gearboxes with suitable material properties to provide the desired efficiency.

Fault Diagnosis of Wind Turbine Gearbox Based on Multisensor Data Fusion

In order to improve the operation efficiency of wind turbine gearbox and reduce the operation and maintenance cost of wind farm, a fault diagnosis system for wind turbine gearbox based on multisensor data fusion was proposed. First, the different time-domain statistical characteristic parameters of the original vibration signal were calculated, and the information fusion of the feature level and the data level was carried out by means of parallel superposition to obtain the fused data set. Second, a fault classification and recognition model based on GMO-KELM was established by using the fusion data set. Finally, the proposed method was used to monitor the status of the measured data of the gearbox on the vibration test bed of rotating machinery. The experimental results showed that the average training accuracy and the average test accuracy of GMO-KELM method were 100% and 95.58%, respectively, which were much higher than those of other methods. Through experiments and analyses, it was shown that the proposed method was effective and feasible. Compared with other similar methods, the proposed method had the best classification performance.

Measuring the Efficiency of Reduction Gearboxes for Electric Utility Vehicles during Specific Driving Cycles

This paper presents the results and the procedure for measuring the efficiency of a single-speed reduction gearbox developed for an autonomous electric utility vehicle. The resulting efficiency of the gearbox was investigated on three different driving cycles, which were selected because their speed profiles most closely matched the expected use of the autonomous vehicle. The required torque for each cycle was obtained from simulations of the vehicle’s driving behaviour including its predicted mass and dimensional parameters after a given driving cycle. The results of this research represent the achieved efficiency and average power loss of the gearbox on each driving cycle. The resulting gearbox efficiency was around 50 % in the predominant areas of driving cycles.

Improved design of experiments method for machine-learning-based modelling of gearbox efficiency in a test rig environment

Knowledge of the efficiency of the subsystems in the drive train is essential for development in drive technology. Experiments have confirmed that the efficiency gradient of gearboxes is particularly high in the partial load range. Conventional test planning does not adequately reflect the influence of the efficiency gradient in the partial load range. To adequately represent the partial load range, it must be recorded with a particularly high number of measuring points. Map ranges with a low gradient are recorded with a smaller number of measuring points. This paper describes a method for the design of experiments, not with but for neural networks, with regard to modelling the efficiency of a two-stage spur transmission. In order to determine the test data, an optimized design of experiments is carried out. The test planning is divided into preliminary tests and main tests. The measuring points are optimally distributed in the characteristic diagram for use in neural networks. The measurement data is generated with the planned test data on a road to rig vehicle test rig. Suitable methods are used to prepare the data for further processing. The modelling is done experimentally with the help of neural networks. The result is a function for the continuous description of the efficiency at each operating point. The procedure is compared with the conventional method and validated with statistical methods. It was proven that the optimised experimental design method for neural networks gives better results than the conventional approach.