Digital signal processing techniques for accurate ultrasonic sensor measurement

Andria, G.; Attivissimo, Filippo; Giaquinto, Nicola

doi:10.1016/s0263-2241(00)00059-2

Cited by 71 publications

(29 citation statements)

References 10 publications

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“…Normally the time-of-flight (TOF) is used for the ultrasonic sensor distance measurement [25]. The distance can be calculated by using the ultrasonic speed of the medium and the time difference between transmitted and received signal.…”

Section: Target Distance Measurementmentioning

confidence: 99%

Design and implementation of an automated monitoring system

2016

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One of the main limitations of existing monitoring systems is their dependency on the continuous recording of video data. As a result, the system consumes huge power and needs large memory to store this data. The aim of this paper is to present an automated monitoring system that can save memory, as well as measure the target distance precisely based on the motion sensors and ultrasonic sensor. The target is detected by motion sensors and then an ultrasonic sensor is used to measure the target distance. The cross-correlation technique is used to calculate the distance of targets using ultrasonic signal. To obtain high measuring accuracy, noise reduction technique and temperature effect on velocity have been adopted. A series of real-world experiments are conducted with different targets and target positions. The experimental results show that using a noise reduction technique and temperature compensation improve the accuracy of the designed system.

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Section: Target Distance Measurementmentioning

confidence: 99%

Design and implementation of an automated monitoring system

2016

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“…Investigations on error in TOF measurement of signals due to random noise have been reported for threshold crossing 25 , cross correlation 24,26 and some other TOF measurement methods. In this paper the noise modeled as an additive zero mean Gaussian random noise with 0.01standard deviation approximated in the laboratory by means of acquiring several signals in 5 cm distance with several pencil lead breaks as AE sources and normalizing the standard deviation of noise to the average of maximum signal envelopes.…”

Section: Tof Error Of Noisy Datamentioning

confidence: 99%

Acoustic emission (AE) source localization using extended Kalman filter (EKF)

2012

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This paper presents a method for Acoustic Emission (AE) source localization in isotropic plate-like structures based on the Extended Kalman Filter (EKF). The accuracy of the traditional triangulation methods depends on the time of flight (TOF) measurements and on the group velocity assumption so uncertainties in both should be taken into account and filtered out. An algorithm based on the Extended Kalman Filter (EKF), capable of filtering out these uncertainties, has been developed for the estimation: 1) the AE source location and 2) the wave velocity. Experimental tests have been carried out on an aluminum plate to show accuracy and robustness of the proposed approach.

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“…Of previously proposed Digital Signal Processing techniques for TOF estimation, detecting the peak of the crosscorrelation between the transmitted and received signals is, in general, more accurate than other techniques such as thresholddetection, curve fitting, and sliding-window [20], [21], [22]. However the best resolution that, can be achieved using crosscorrelation is half the sampling period meaning that to obtain higher resolution, a higher sampling frequency must be used.…”

Section: Related Workmentioning

confidence: 99%