Optical Waveform Probing – Strategies for Non-Fllpchlp Devices and Other Applications

2001 ◽  
Author(s):  
Siva Kolachina ◽  
Kendall Scott Wills ◽  
Tim Nagel ◽  
Aswin Mehta ◽  
Rand Carawan ◽  
...  
Keyword(s):  
Signal Analysis ◽  
Timing Analysis ◽  
Analog Signal ◽  
Analysis Tool ◽  
Critical Component

Abstract Optical waveform probing is a critical component in flipchip diagnostics. There is a dramatic increase in the need for backside silicon probing of non-flipchip packaged devices. The effective way to implement this strategy is to package the die in a BGA carrier that allows backside analysis. Optical waveform probing has been used primarily as a digital waveform timing analysis tool. The capability of optical waveform probers can be extended to failsite isolation and qualitative analog signal analysis.

Investigating Vibration Sources of Faulty Gear Units

2008 ◽  
Vol 385-387 ◽  
pp. 601-604
Author(s):  
Ales Belsak ◽  
Joze Flasker
Keyword(s):  
Signal Analysis ◽  
Analysis Tool ◽  
Tooth Root ◽  
Dynamic Parameters ◽  
Unit Operation ◽  
Time Frequency ◽  
Tooth Stiffness ◽  
Non Stationary Signal ◽  
High Degree ◽  
Very High

A crack in the tooth root is the least desirable damage of gear units, which often leads to failure of gear unit operation. A possible damage can be identified by monitoring vibrations. The influences that a crack in the tooth root of a single-stage gear unit has upon vibrations are dealt with. Changes in tooth stiffness are much more expressed in relation to a fatigue crack in the tooth root, whereas in relation to other faults, changes of other dynamic parameters are more expressed. Signal analysis has been performed in relation to a non-stationary signal, by means of the Time Frequency Analysis tool, such as Wavelets. Typical scalogram patterns resulting from reactions to faults or damages indicate the presence of faults or damages with a very high degree of reliability.

scholarly journals VASTA: A Wide Voltage Statistical Timing Analysis Tool Based on Variation-Aware Cell Delay Models

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 197194-197202
Author(s):  
Wenjie Fu ◽  
Leilei Jin ◽  
Ming Ling ◽  
Yu Zheng ◽  
Longxing Shi
Keyword(s):  
Timing Analysis ◽  
Analysis Tool ◽  
Statistical Timing Analysis ◽  
Delay Models ◽  
Statistical Timing ◽  
Cell Delay

scholarly journals Monitoring Machines by Using a Hybrid Method Combining MED, EMD, and TKEO

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Mourad Kedadouche ◽  
Marc Thomas ◽  
Antoine Tahan
Keyword(s):  
Spectrum Analysis ◽  
Signal Analysis ◽  
Energy Operator ◽  
Analysis Tool ◽  
Intrinsic Mode Functions ◽  
Minimum Entropy ◽  
Bearing Faults ◽  
Mode Decomposition ◽  
Analysis Technique ◽  
Envelope Spectrum

Amplitude demodulation is a key for diagnosing bearing faults. The quality of the demodulation determines the efficiency of the spectrum analysis in detecting the defect. A signal analysis technique based on minimum entropy deconvolution (MED), empirical mode decomposition (EMD), and Teager Kaiser energy operator (TKEO) is presented. The proposed method consists in enhancing the signal by using MED, decomposing the signal in intrinsic mode functions (IMFs) and selects only the IMF which presents the highest correlation coefficient with the original signal. In this study the first IMF1 was automatically selected, since it represents the contribution of high frequencies which are first excited at the early stages of degradation. After that, TKEO is used to track the modulation energy. The spectrum is applied to the instantaneous amplitude. Therefore, the character of the bearing faults can be recognized according to the envelope spectrum. The simulation and experimental results show that an envelope spectrum analysis based on MED-EMD and TKEO provides a reliable signal analysis tool. The experimental application has been developed on acoustic emission and vibration signals recorded for bearing fault detection.

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