Search Results (10)

This paper presents a vibration analysis method for detecting typical faults in gears of the drive train of a 2 MW wind turbine. The data were collected over a one-year period from an operating wind turbine with a gearbox composed of one planetary stage and two helical gear stages. Failures in two pairs of helical gears were identified: one involving pitting and wear in the gears connecting the intermediate-speed shaft to the low-speed shaft, and another one involving significant material detachment in the gears connecting the intermediate-speed shaft to the high-speed shaft. The continuous evaluation of time signals, frequency spectra, and amplitude modulations allowed the most sensitive sensors and frequencies for predicting surface damage on gear teeth in this type of turbine to be determined. A steady-state frequency analysis was performed, enabling the detection of the aforementioned surface faults. This approach is simpler compared with more complex transient-state techniques. By tracking vibration signals over time, the importance of analyzing gear mesh frequencies and their harmonics was highlighted. Additionally, it was found that the progression of gear damage was dependent on the power output of the wind turbine. As a result, the most appropriate ranges of power were identified, within which the evolution of the vibration measurement was associated with the damage evolution. Since many turbines currently in operation have similar designs and power output levels, the present findings can serve as a guideline for monitoring an extensive number of units. Full article

When optimizing a mechanical device, the symmetry principle provides important guidance. Minimum gearbox mass and maximum gearbox efficiency are two single objectives that need to be achieved when designing a gearbox, and they are not compatible. In order to address the multi-objective optimization (MOO) problem with the above single targets involved in building a two-stage helical gearbox with second-stage double gear sets, this work presents a novel application of the multi-criteria decision-making (MCDM) method. This study’s objective is to identify the best primary design elements that will increase the gearbox efficiency while lowering the gearbox mass. To carry this out, three main design parameters were selected: the first stage’s gear ratio and the first and second stages’ coefficients of wheel face width (CWFW). Furthermore, a study focusing on two distinct goals was carried out: the lowest possible gearbox mass and the highest possible gearbox efficiency. Furthermore, the two stages of the MOO problem are phase 1 and phase 2, respectively. Phase 2 solves the single-objective optimization issue to minimize the difference between variable levels and the MOO problem to determine the optimal primary design factors. To solve the MOO problem, the EAMR (Evaluation by an Area-based Method of Ranking) method was also chosen. The following are important features of this study: First, a MCDM method (EAMR technique) was successfully applied to solve a MOO problem for the first time. Secondly, this work explored the power losses during idle motion to calculate the efficiency of a two-stage helical gearbox with second-stage double gear sets. This study’s findings were used to identify the optimal values for three important design variables to design a two-stage helical gearbox with second-stage double gear sets. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

This study is aimed at determining optimum partial gear ratios to minimize the cost of a three-stage helical gearbox. In this work, eleven input parameters were investigated to find their influence on the optimum gear ratios of the second and the third stages ( $u_2$ and $u_3$ ). To reach the goal, a simulation experiment was designed and implemented by a cost optimization program. The results revealed that in addition to the input parameters, their interactions also have important effects in which the total ratio gearbox ratio ( $u_t$ ) and the cost of shaft ( $C_s$ ) have the most impact on $u_2$ and $u_3$ responses, respectively. Moreover, the proposed models of the two responses are highly consistent to the experimental results. The proposed regression equations can be applied to solve optimization cost problems. Full article

A sample of healthy wind turbines from the same wind farm with identical sizes and designs was investigated to determine the average vibrational signatures of the drive train components during normal operation. The units were variable-speed machines with three blades. The rotor was supported by two bearings, and the drive train connected to an intermediate three-stage planetary/helical gearbox. The nominal 2 MW output power was regulated using blade pitch adjustment. Vibrations were measured in exactly the same positions using the same type of sensors over a six-month period covering the entire range of operating conditions. The data set was preliminary validated to remove outliers based on the theoretical power curves. The most relevant frequency peaks in the rotor, gearbox, and generator vibrations were detected and identified based on averaged power spectra. The amplitudes of the peaks induced by a common source of excitation were compared in different measurement positions. A wind speed dependency of broadband vibration amplitudes was also observed. Finally, a fault detection case is presented showing the change of vibration signature induced by a damage in the gearbox. Full article