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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.


Instrumentation system PCB. (a) Top view. (b) Bottom view.
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f10-sensors-09-03767: Instrumentation system PCB. (a) Top view. (b) Bottom view.

Mentions: The proposed methodology for jerk estimation can be applied to any accelerometer. In our case a 3-axis LIS3L02AS4 accelerometer from STMicroelectronics [17] was used. The accelerometer has a user-selectable full scale of ± 2g/ ± 6g (g = 9.81 m/s2); a 5×10-4g resolution over a 100 Hz bandwidth; and a bandwidth of 1.5 kHz for all axes. The accelerometer is mounted in a PCB with the signal conditioning and anti-alias filtering, as recommended by the manufacturer. This PCB also contains a 4-channel, 12-bit sampling ADC from Texas Instruments ADS7841 [18], with a 200 kHz maximum sampling rate for each channel. The communication between the instrumentation system and the FPGA signal processing unit is done with a MAX3243 transceiver. Figure 10 shows the top and bottom views of the instrumentation system PCB.


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)

Instrumentation system PCB. (a) Top view. (b) Bottom view.
© Copyright Policy
Related In: Results  -  Collection

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

f10-sensors-09-03767: Instrumentation system PCB. (a) Top view. (b) Bottom view.
Mentions: The proposed methodology for jerk estimation can be applied to any accelerometer. In our case a 3-axis LIS3L02AS4 accelerometer from STMicroelectronics [17] was used. The accelerometer has a user-selectable full scale of ± 2g/ ± 6g (g = 9.81 m/s2); a 5×10-4g resolution over a 100 Hz bandwidth; and a bandwidth of 1.5 kHz for all axes. The accelerometer is mounted in a PCB with the signal conditioning and anti-alias filtering, as recommended by the manufacturer. This PCB also contains a 4-channel, 12-bit sampling ADC from Texas Instruments ADS7841 [18], with a 200 kHz maximum sampling rate for each channel. The communication between the instrumentation system and the FPGA signal processing unit is done with a MAX3243 transceiver. Figure 10 shows the top and bottom views of the instrumentation system PCB.

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.