An Experimental Methodology to Determine Components of Power Losses of a Gearbox

2021 ◽  
Vol 143 (11) ◽  
Author(s):  
A. Dindar ◽  
K. Chaudhury ◽  
I. Hong ◽  
A. Kahraman ◽  
C. Wink
Keyword(s):  
Power Loss ◽  
Spur Gear ◽  
Rolling Element Bearing ◽  
Experimental Methodology ◽  
Total Power ◽  
Gear Pair ◽  
Rolling Element Bearings ◽  
Power Losses ◽  
Rolling Element ◽  
The One

Abstract In this study, an experimental methodology is presented to separate various components of the power loss of a gearbox. The methodology relies on two separate measurements. One is designed to measure total power loss of a gearbox housing a single spur gear pair under both loaded and unloaded conditions such that load-independent (spin) and load-dependent (mechanical) components can be separated. With the assumption that gear pair and rolling element bearings constitute the bulk of the gearbox power loss, a second measurement system designed to quantify rolling element bearing losses is proposed. With this setup, spin and mechanical power losses of rolling element bearings used in the gearbox experiments are measured. Combining the sets of gearbox and bearing data, power loss components attributable to the gear pair and rolling element bearings are quantified as a function of speed and torque. The results indicate that all gear and bearing related components are significant and a methodology such as the one proposed in this study is warranted.

Oil Churning Power Losses of a Gear Pair: Experiments and Model Validation

2009 ◽  
Vol 131 (2) ◽  
Author(s):  
S. Seetharaman ◽  
A. Kahraman ◽  
M. D. Moorhead ◽  
T. T. Petry-Johnson
Keyword(s):  
Power Loss ◽  
Spur Gear ◽  
Companion Paper ◽  
Design Parameters ◽  
Measured Parameter ◽  
Gear Pair ◽  
Power Losses ◽  
Gear Design ◽  
Face Width ◽  
Wide Range

This paper presents the results of an experimental study on load-independent (spin) power losses of spur gear pairs operating under dip-lubricated conditions. The experiments were performed over a wide range of operating speed, temperature, oil levels, and key gear design parameters to quantify their influence on spin power losses. The measurements indicate that the static oil level, rotational speed, and face width of gears have a significant impact on spin power losses compared with other parameters such as oil temperature, gear module, and the direction of gear rotation. A physics-based gear pair spin power loss formulation that was proposed in a companion paper (Seetharaman and Kahraman, 2009, “Load-Independent Spin Power Losses of a Spur Gear Pair: Model Formulation,” ASME J. Tribol., 131, p. 022201) was used to simulate these experiments. Direct comparisons between the model predictions and measurements are provided at the end to demonstrate that the model is capable of predicting the measured spin power loss values as well as the measured parameter sensitivities reasonably well.

Power Loss Predictions in Geared Transmissions Using Thermal Networks-Applications to a Six-Speed Manual Gearbox

2005 ◽  
Vol 128 (3) ◽  
pp. 618-625 ◽  
Author(s):  
C. Changenet ◽  
X. Oviedo-Marlot ◽  
P. Velex
Keyword(s):  
Power Loss ◽  
Rolling Element Bearings ◽  
Power Losses ◽  
Uniform Temperature ◽  
Manual Gearbox ◽  
Transient Conditions ◽  
Numerical Predictions ◽  
Rolling Element ◽  
Power Inputs ◽  
Lumped Elements

A model is presented which makes it possible to predict power losses in a six-speed manual gearbox. The following sources of dissipation, i.e., power inputs in the model, are considered: (i) tooth friction; (ii) rolling element bearings; (iii) oil shearing in the synchronizers and at the shaft-free pinion interfaces; and (iv) oil churning. Based upon the first principle of Thermodynamics for transient conditions, the entire gearbox is divided into lumped elements with a uniform temperature connected by thermal resistances which account for conduction, convection, and radiation. The numerical predictions compare favorably with the efficiency measurements from the actual gearbox at different speeds and torques. The results also reveal that, at lower temperatures (about 40°C), power loss estimations cannot be disassociated from the accurate prediction of temperature distributions.

Power Loss Measurements of Rolling Element Bearings Subject to Combined Radial and Axial Loads

2019 ◽  
Author(s):  
Kevin Vedera ◽  
Isaac Hong ◽  
David Talbot ◽  
Ahmet Kahraman ◽  
Sen Zhou
Keyword(s):  
Power Loss ◽  
Research Area ◽  
Test Machine ◽  
Rolling Element Bearings ◽  
Power Losses ◽  
Axial Loads ◽  
Gear Mesh ◽  
Test Methodology ◽  
Rolling Element ◽  
Different Types

Abstract Power losses of load carrying gear and bearing components of automotive transmissions have become a major research area in recent years. Measurement of power loss of a gearbox is a routine task where losses from rolling element bearings, gear meshes and seals collectively define the total loss. However, separating bearing and gear mesh losses is not possible, as a gear mesh cannot be operated without support bearings. This study aims at developing a methodology for measuring power losses of rolling element bearings of different types operated under realistic load, speed and temperature conditions. A test machine concept is implemented to apply combined radial and axial loads to a pair of test bearings in a stable and repeatable manner, with rotational speed and lubrication parameters controlled tightly during tests. The proposed test methodology is employed to evaluate power loss for three different types of bearings. Load-dependent and load-independent components of power loss are separated, and influence of speed and load values on bearing mechanical loss are quantified. A repeatability study of the machine and methodology is also presented to demonstrate the accuracy of the proposed setup.

Load-Independent Spin Power Losses of a Spur Gear Pair: Model Formulation

2009 ◽  
Vol 131 (2) ◽  
Author(s):  
S. Seetharaman ◽  
A. Kahraman
Keyword(s):  
Power Loss ◽  
Spur Gear ◽  
Companion Paper ◽  
Total Spin ◽  
Operating Conditions ◽  
Gear Pair ◽  
Power Losses ◽  
Gear Mesh ◽  
Drag Forces ◽  
Mechanics Model

A physics-based fluid mechanics model is proposed to predict spin power losses of gear pairs due to oil churning and windage. While the model is intended to simulate oil churning losses in dip-lubricated conditions, certain components of it apply to air windage losses as well. The total spin power loss is defined as the sum of (i) power losses associated with the interactions of individual gears with the fluid, and (ii) power losses due to pumping of the oil at the gear mesh. The power losses in the first group are modeled through individual formulations for drag forces induced by the fluid on a rotating gear body along its periphery and faces, as well as for eddies formed in the cavities between adjacent teeth. Gear mesh pumping losses will be predicted analytically as the power loss due to squeezing of the lubricant, as a consequence of volume contraction of the mesh space between mating gears as they rotate. The model is applied to a unity-ratio spur gear pair to quantify the individual contributions of each power loss component to the total spin power loss. The influence of operating conditions, gear geometry parameters, and lubricant properties on spin power loss are also quantified at the end. A companion paper (Seetharaman et al., 2009, “Oil Churning Power Losses of a Gear Pair: Experiments and Model Validation,” ASME J. Tribol., 131, p. 022202) provides comparisons to experiments for validation of the proposed model.

Two-step fault diagnosis framework for rolling element bearings with imbalanced data based on GSA-WELM and GSA-ELM

2017 ◽  
Vol 232 (16) ◽  
pp. 2937-2947 ◽  
Author(s):  
Yuan Lan ◽  
Xiaohong Han ◽  
Weiwei Zong ◽  
Xiaojian Ding ◽  
Xiaoyan Xiong ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Extreme Learning Machine ◽  
Gravitational Search Algorithm ◽  
Imbalanced Data ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Misclassification Cost ◽  
Weighted Extreme Learning Machine ◽  
Rolling Element ◽  
Learning Machine

Rolling element bearings constitute the key parts on rotating machinery, and their fault diagnosis is of great importance. In many real bearing fault diagnosis applications, the number of fault data is much less than the number of normal data, i.e. the data are imbalanced. Many traditional diagnosis methods will get low accuracy because they have a natural tendency to favor the majority class by assuming balanced class distribution or equal misclassification cost. To deal with imbalanced data, in this article, a novel two-step fault diagnosis framework is proposed to diagnose the status of rolling element bearings. Our proposed framework consists of two steps for fault diagnosis, where Step 1 makes use of weighted extreme learning machine in an effort to classify the normal or abnormal categories, and Step 2 further diagnoses the underlying anomaly in detail by using preliminary extreme learning machine. In addition, gravitational search algorithm is applied to further extract the significant features and determine the optimal parameters of the weighted extreme learning machine and extreme learning machine classifiers. The effectiveness of our proposed approach is testified on the raw data collected from the rolling element bearing experiments conducted in our Institute, and the empirical results show that our approach is really fast and can achieve the diagnosis accuracies more than 96%.

Wigner–Ville distribution based on cyclic spectral density and the application in rolling element bearings diagnosis

2011 ◽  
Vol 225 (12) ◽  
pp. 2831-2847 ◽  
Author(s):  
Y Zhou ◽  
J Chen ◽  
G M Dong ◽  
W B Xiao ◽  
Z Y Wang
Keyword(s):  
Fault Diagnosis ◽  
Spectral Density ◽  
Wigner Distribution ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Accurate Analysis ◽  
Time Frequency ◽  
Bearing Fault ◽  
Rolling Element ◽  
Cross Terms

The vibration signals of rolling element bearings are random cyclostationary when they have faults. Also, statistical properties of the signals change periodically with time. The accurate analysis of time-varying signals is an essential pre-requisite for the fault diagnosis and hence safe operation of rolling element bearings. The Wigner distribution is probably most widely used among the Cohen’s class in order to describe how the spectral content of a signal changes over time. However, the basic nature of such signals causes significant interfering cross-terms, which do not permit a straightforward interpretation of the energy distribution. To overcome this difficulty, the Wigner–Ville distribution (WVD) based on the cyclic spectral density (CSD) is discussed in this article. It is shown that the improved WVD, based on CSD of a long time series, can render the time–frequency distribution less susceptible to noise, and restrain the cross-terms in the time–frequency domain. Simulation and experiment of the rolling element-bearing fault diagnosis are performed, and the results indicate the validity of WVD based on CSD in time–frequency analysis for bearing fault detection.

scholarly journals Chaotic prediction of vibration performance degradation trend of rolling element bearing based on Weibull distribution

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041989219
Author(s):  
Li Cheng ◽  
Xintao Xia ◽  
Liang Ye
Keyword(s):  
Weibull Distribution ◽  
Relative Error ◽  
High Reliability ◽  
Prediction Method ◽  
Performance Degradation ◽  
Rolling Element Bearing ◽  
Maximum Relative Error ◽  
Rolling Element Bearings ◽  
Rolling Element ◽  
Vibration Performance

Rolling element bearings are used in all rotating machinery, and the degradation performance of rolling element bearings directly affects the performance of the machine. Therefore, high reliability prediction of the performance degradation trend of rolling element bearings has become an urgent research problem. However, the degradation characteristics of the rolling element bearings vibration time series are difficult to extract, and the mechanism of performance degradation is very complicated. The accurate physical model is difficult to establish. In view of the above reasons, based on the vibration performance data of rolling element bearings, a model of bearing performance degradation trend parameter based on wavelet denoising and Weibull distribution is established. Then, the phase space reconstruction of the series of bearing performance degradation trend parameter is carried out, and the prognosis is obtained by the improved adding weighted first-order local prediction method. The experimental results show that the bearing vibration performance degradation parameter can accurately depict the degradation trend of the bearing, and the reliability level is 91.55%; and the prediction of bearing performance degradation trend parameter is satisfactory: the mean relative error is only 0.0053% and the maximum relative error is less than 0.03%.

scholarly journals OPTIMASI PENEMPATAN KAPASITOR BANK UNTUK PERBAIKAN RUGI DAYA PADA PENYULANG SABA MENGGUNAKAN ALGORITMA GENETIKA

2019 ◽  
Vol 6 (2) ◽  
pp. 7
Author(s):  
I. K. A. Wijaya ◽  
R. S. Hartati ◽  
I W. Sukerayasa
Keyword(s):  
Genetic Algorithms ◽  
Power Loss ◽  
Voltage Drop ◽  
Electrical Energy ◽  
Total Power ◽  
Network Reconfiguration ◽  
Power Losses ◽  
Combined Method ◽  
Capacitor Banks ◽  
Distribution Transformers

Saba feeder is a feeder who supplies 78 distribution transformers with feeder length 38,959 kms, through this Saba feeder electrical energy is channeled radially to each distribution substation. In 2017 the voltage shrinkage at Saba feeder was 9.88% (18,024 kV) while the total power loss was 445.5 kW. In this study an attempt was made to overcome the voltage losses and power losses using the method of optimizing bank capacitors with genetic algorithms and network reconfiguration. The best solution obtained from this study will be selected for repair of voltage losses and power losses in Saba feeders. The results showed that by optimizing bank capacitors using genetic algorithms, the placement of capacitor banks was placed on bus 23 (the channel leading to the BB0024 transformer) and successfully reduced the power loss to 331.7 kW. The network reconfiguration succeeded in fixing the voltage on the Saba feeder with a voltage drop of 4.75% and a total power loss of 182.7 kW. With the combined method, reconfiguration and optimization of bank capacitors with genetic algorithms were obtained on bus 27 (channel to transformer BB0047) and managed to reduce power losses to 143 kW.

Effect of Design Parameters on Lubrication Behavior of Spur Gear Pairs

2017 ◽  
Author(s):  
Yanfang Liu ◽  
Qiang Liu ◽  
Peng Dong
Keyword(s):  
Power Loss ◽  
Elastohydrodynamic Lubrication ◽  
Spur Gear ◽  
Design Parameters ◽  
Curvature Radius ◽  
Gear Pair ◽  
Sliding Velocity ◽  
Rolling Velocity ◽  
Lubrication Performance ◽  
Meshing Process

An involute spur gear pair meshing model is firstly provided in this study to achieve relevant data such as rolling velocity, sliding velocity, curvature radius etc. These data are needed in a transient, Newtonian elastohydrodynamic lubrication (EHL) model which is provided later. Based on these two models, the behavior of an engaged spur gear pair during the meshing process is investigated under dynamic conditions, film thickness, pressure, friction coefficient etc. could be achieved through the models. Then, power loss under certain operating condition is calculated. Relationship between power loss and lubrication performance is also analyzed.

Rolling Element Bearing Monitoring and Diagnostics Techniques

1989 ◽  
Vol 111 (2) ◽  
pp. 251-256 ◽  
Author(s):  
R. G. Harker ◽  
J. L. Sandy
Keyword(s):  
Case Studies ◽  
Fluid Film ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Film Type ◽  
Rolling Element ◽  
Element Bearing ◽  
Monitoring And Diagnostics ◽  
Bearing Monitoring

Rolling element bearings require distinctly different techniques for monitoring and diagnostics from those used for fluid-film type bearings. A description of these techniques and the instrumentation used to acquire the necessary data is provided for comparison. Also included are some case studies to illustrate how these techniques are applied.

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