Multisensory measurement of the base circle radius as a fundamental shape parameter of large gears

2019 ◽  
pp. 1207-1214
Author(s):  
M. Pillarz ◽  
A. von Freyberg ◽  
A. Fischer
Keyword(s):  
Shape Parameter ◽  
Base Circle

scholarly journals Gear Shape Parameter Measurement Using a Model-Based Scanning Multi-Distance Measurement Approach

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3910
Author(s):  
Marc Pillarz ◽  
Axel von Freyberg ◽  
Andreas Fischer
Keyword(s):  
Shape Parameter ◽  
Spur Gear ◽  
Distance Measurement ◽  
Measuring Instruments ◽  
Single Digit ◽  
Promising Alternative ◽  
Model Based ◽  
Base Circle ◽  
The Mean ◽  
Measurement Approach

To reduce wind turbine failures by defective drive trains, deviations in the geometry of large gears (diameter ≳ 1 m) must be extensively determined with single-digit micrometer uncertainties. Fixed measuring volumes limit standard measuring methods like coordinate and gear measuring instruments for large gear measurements. Therefore, a model-based scanning multi-distance measurement approach for gear shape parameters is presented. The measurement approach has a scalable design and consists of a confocal-chromatic sensor, rotary table as a scanning unit and model-based signal processing. A preliminary study on a midsize spur gear demonstrates the general feasibility of the model-based scanning multi-distance measurement approach. As a result, the mean base circle radius as the fundamental gear shape parameter is determined with an uncertainty of <5 μm. The calibration and adjustment of the sensor arrangement were performed with a known calibration gear. Scalability is not experimentally validated in this article. However, simulations verify the scalability of the measurement approach in a first step. For gears with 1 m in diameter and varying tooth flank geometries, the estimated achievable uncertainty of the mean base circle radius is still <5 μm. Therefore, the model-based scanning multi-distance measurement approach is a promising alternative for gear inspection.

Effect of Kaiser Window Shape Parameter for the Enhancement of Rotor Faults Diagnosis

2017 ◽  
Vol 10 (6) ◽  
pp. 461
Author(s):  
Mohammed-El-Amine Khodja ◽  
Ahmed Hamida Boudinar ◽  
Azeddine Bendiabdellah
Keyword(s):  
Shape Parameter ◽  
Rotor Faults ◽  
Faults Diagnosis ◽  
Kaiser Window

Burn-In Acceleration Considerations in 130nm and 90nm Products

2005 ◽  
Author(s):  
Nobuyuki Wakai ◽  
Yuji Kobira ◽  
Takashi Setoya ◽  
Tamotsu Oishi ◽  
Shinichi Yamasaki
Keyword(s):  
Failure Analysis ◽  
Shape Parameter ◽  
Defect Density ◽  
Failure Mechanisms ◽  
Effective Procedure ◽  
Time Period ◽  
Related Defect ◽  
The Relationship

Abstract An effective procedure to determine the Burn-In acceleration factors for 130nm and 90 nm processes are discussed in this paper. The relationship among yield, defect density, and reliability, is well known and well documented for defect mechanisms. In particular, it is important to determine the suitable acceleration factors for temperature and voltage to estimate the exact Burn- In conditions needed to screen these defects. The approach in this paper is found to be useful for recent Cu-processes which are difficult to control from a defectivity standpoint. Performing an evaluation with test vehicles of 130nm and 90nm technology, the following acceleration factors were obtained, Ea&gt;0.9ev and β (Beta)&gt;-5.85. In addition, it was determined that a lower defect density gave a lower Weibull shape parameter. As a result of failure analysis, it is found that the main failures in these technologies were caused by particles, and their Weibull shape parameter “m” was changed depending of the related defect density. These factors can be applied for an immature time period where the process and products have failure mechanisms dominated by defects. Thus, an effective Burn-In is possible with classification from the standpoint of defect density, even from a period of technology immaturity.

scholarly journals Continuous window functions for NFFT

2021 ◽  
Vol 47 (4) ◽  
Author(s):  
Daniel Potts ◽  
Manfred Tasche
Keyword(s):  
Fourier Transform ◽  
Shape Parameter ◽  
Optimal Choice ◽  
Approximate Algorithm ◽  
Window Function ◽  
Truncation Parameter ◽  
Error Constant ◽  
Window Functions ◽  
Nonequispaced Fast Fourier Transform ◽  
Error Behavior

AbstractIn this paper, we study the error behavior of the nonequispaced fast Fourier transform (NFFT). This approximate algorithm is mainly based on the convenient choice of a compactly supported window function. Here, we consider the continuous Kaiser–Bessel, continuous exp-type, sinh-type, and continuous cosh-type window functions with the same support and same shape parameter. We present novel explicit error estimates for NFFT with such a window function and derive rules for the optimal choice of the parameters involved in NFFT. The error constant of a window function depends mainly on the oversampling factor and the truncation parameter. For the considered continuous window functions, the error constants have an exponential decay with respect to the truncation parameter.

scholarly journals Investigation of Feller-Buncher Performance Using Weibull Distribution

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 284
Author(s):  
Ebru Bilici
Keyword(s):  
Weibull Distribution ◽  
Shape Parameter ◽  
B Value ◽  
Productivity Analysis ◽  
Volume Data ◽  
Estimation Model ◽  
Distribution Method ◽  
Timber Volume ◽  
C Value ◽  
The Right

With the advancement of technology in forestry, the utilization of advanced machines in forest operations has been increasing in the last decades. Due to their high operating costs, it is crucial to select the right machinery, which is mostly done by using productivity analysis. In this study, a productivity estimation model was developed in order to determine the timber volume cut per unit time for a feller-buncher. The Weibull distribution method was used to develop the productivity model. In the study, the model of the theoretical (estimated) volume distributions obtained with the Weibull probability density function was generated. It was found that the c value was 1.96 and the b value was 0.58 (i.e., b is the scale parameter, and c is the shape parameter). The model indicated that the frequency of the volume data had moved away from 0 as the shape parameter of the Weibull distribution increased. Thus, it was revealed that the shape parameter gives preliminary information about the distribution of the volume frequency. The consistency of the measured timber volume with the estimated timber volume strongly indicated that this approach can be effectively used by decision makers as a key tool to predict the productivity of a feller-buncher used in harvesting operations.

scholarly journals Estimation of the G2P Design Storm from a Rainfall Convectivity Index

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1943
Author(s):  
Rosario Balbastre-Soldevila ◽  
Rafael García-Bartual ◽  
Ignacio Andrés-Doménech
Keyword(s):  
Shape Parameter ◽  
Rainfall Intensity ◽  
Analytical Relationship ◽  
Urban Drainage ◽  
Practical Application ◽  
Resolution Time ◽  
Simple Method ◽  
Design Storm ◽  
Intensity Duration Frequency ◽  
Two Parameter

The two-parameter gamma function (G2P) design storm is a recent methodology used to obtain synthetic hyetographs especially developed for urban hydrology applications. Further analytical developments on the G2P design storm are presented herein, linking the rainfall convectivity n-index with the shape parameter of the design storm. This step can provide a useful basis for future easy-to-handle rainfall inputs in the context of regional urban drainage studies. A practical application is presented herein for the case of Valencia (Spain), based on high-resolution time series of rainfall intensity. The resulting design storm captures certain internal statistics and features observed in the fine-scale rainfall intensity historical records. On the other hand, a direct, simple method is formulated to derivate the design storm from the intensity–duration–frequency (IDF) curves, making use of the analytical relationship with the n-index.

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