Limits...
Novel Oversampling Technique for Improving Signal-to-Quantization Noise Ratio on Accelerometer-Based Smart Jerk Sensors in CNC Applications.

Rangel-Magdaleno JJ, Romero-Troncoso RJ, Osornio-Rios RA, Cabal-Yepez E - Sensors (Basel) (2009)

Bottom Line: The novelty of this work is the development of a smart sensor for jerk monitoring from a standard accelerometer, which has improved SQNR.The proposal is based on oversampling techniques that give a better estimation of jerk than that produced by a Nyquist-rate differentiator.Simulations and experimental results are presented to show the overall methodology performance.

View Article: PubMed Central - PubMed

Affiliation: Facultad de Ingeniería, Campus San Juan del Río, Universidad Autónoma de Querétaro / Río Moctezuma 249, Col. San Cayetano, 76807 San Juan del Río, Querétaro, Mexico; E-Mails: jjrangel@hspdigital.org (J.J.R.-M.); raosornio@hspdigital.org (R.A.O.-R.).

ABSTRACT
Jerk monitoring, defined as the first derivative of acceleration, has become a major issue in computerized numeric controlled (CNC) machines. Several works highlight the necessity of measuring jerk in a reliable way for improving production processes. Nowadays, the computation of jerk is done by finite differences of the acceleration signal, computed at the Nyquist rate, which leads to low signal-to-quantization noise ratio (SQNR) during the estimation. The novelty of this work is the development of a smart sensor for jerk monitoring from a standard accelerometer, which has improved SQNR. The proposal is based on oversampling techniques that give a better estimation of jerk than that produced by a Nyquist-rate differentiator. Simulations and experimental results are presented to show the overall methodology performance.

No MeSH data available.


Experiment setup. (a) Retrofitted CNC lathe. (b) Instrumentation system mounting. (c) FPGA-based signal processing unit.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3297130&req=5

f11-sensors-09-03767: Experiment setup. (a) Retrofitted CNC lathe. (b) Instrumentation system mounting. (c) FPGA-based signal processing unit.

Mentions: The instrumentation system with the accelerometer is encased in aluminum and mounted near the cutting tool of a retrofitted to CNC lathe. It is recommended to locate the accelerometer as close as possible to the cutting tool to properly sense chatter during the cutting process [19]. Figure 11a shows the retrofitted CNC lathe, Figure 11b shows the encased instrumentation system, mounted near the cutting tool, and Figure 11c shows the FPGA-based signal processing unit.


Novel Oversampling Technique for Improving Signal-to-Quantization Noise Ratio on Accelerometer-Based Smart Jerk Sensors in CNC Applications.

Rangel-Magdaleno JJ, Romero-Troncoso RJ, Osornio-Rios RA, Cabal-Yepez E - Sensors (Basel) (2009)

Experiment setup. (a) Retrofitted CNC lathe. (b) Instrumentation system mounting. (c) FPGA-based signal processing unit.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3297130&req=5

f11-sensors-09-03767: Experiment setup. (a) Retrofitted CNC lathe. (b) Instrumentation system mounting. (c) FPGA-based signal processing unit.
Mentions: The instrumentation system with the accelerometer is encased in aluminum and mounted near the cutting tool of a retrofitted to CNC lathe. It is recommended to locate the accelerometer as close as possible to the cutting tool to properly sense chatter during the cutting process [19]. Figure 11a shows the retrofitted CNC lathe, Figure 11b shows the encased instrumentation system, mounted near the cutting tool, and Figure 11c shows the FPGA-based signal processing unit.

Bottom Line: The novelty of this work is the development of a smart sensor for jerk monitoring from a standard accelerometer, which has improved SQNR.The proposal is based on oversampling techniques that give a better estimation of jerk than that produced by a Nyquist-rate differentiator.Simulations and experimental results are presented to show the overall methodology performance.

View Article: PubMed Central - PubMed

Affiliation: Facultad de Ingeniería, Campus San Juan del Río, Universidad Autónoma de Querétaro / Río Moctezuma 249, Col. San Cayetano, 76807 San Juan del Río, Querétaro, Mexico; E-Mails: jjrangel@hspdigital.org (J.J.R.-M.); raosornio@hspdigital.org (R.A.O.-R.).

ABSTRACT
Jerk monitoring, defined as the first derivative of acceleration, has become a major issue in computerized numeric controlled (CNC) machines. Several works highlight the necessity of measuring jerk in a reliable way for improving production processes. Nowadays, the computation of jerk is done by finite differences of the acceleration signal, computed at the Nyquist rate, which leads to low signal-to-quantization noise ratio (SQNR) during the estimation. The novelty of this work is the development of a smart sensor for jerk monitoring from a standard accelerometer, which has improved SQNR. The proposal is based on oversampling techniques that give a better estimation of jerk than that produced by a Nyquist-rate differentiator. Simulations and experimental results are presented to show the overall methodology performance.

No MeSH data available.