Review and comparison of tacholess instantaneous speed estimation methods on experimental vibration data

Peeters, Cédric; Leclère, Quentin; Antoni, Jérôme; Lindahl, Peter; Donnal, John; Leeb, Steven B.; Helsen, Jan

doi:10.1016/j.ymssp.2019.02.031

Cited by 114 publications

(40 citation statements)

References 54 publications

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“…The only reason why it is possible to identify the gear damage at 135 degrees is because the measurements are aligned, which ensures that the position of the gear damage is the same between the different measurements. However, in applications where tacholess order tracking methods are used [37][38][39], it is not easy to align the different measurements and therefore the gear damage may be perceived as part of the random noise.…”

Section: Localised Gear Damage Investigationmentioning

confidence: 99%

A Simple Condition Monitoring Method for Gearboxes Operating in Impulsive Environments

Schmidt

Zimroz

Chaari

et al. 2020

Sensors

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Reliable condition indicators are necessary to perform effective diagnosis and prognosis. However, the vibration signals are often corrupted with non-Gaussian noise and rotating machines may operate under time-varying operating conditions. This impedes the application of conventional condition indicators. The synchronous average of the squared envelope is a relatively simple yet effective method to perform fault detection, fault identification and fault trending under constant and time-varying operating conditions. However, its performance is impeded by the presence of impulsive signal components attributed to impulsive noise or the presence of other damage modes in the machine. In this work, it is proposed that the synchronous median of the squared envelope should be used instead of the synchronous average of the squared envelope for gearbox fault diagnosis. It is shown on numerical and experimental datasets that the synchronous median is more robust to the presence of impulsive signal components and is therefore more reliable for estimating the condition of specific machine components.

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Section: Localised Gear Damage Investigationmentioning

confidence: 99%

A Simple Condition Monitoring Method for Gearboxes Operating in Impulsive Environments

Schmidt

Zimroz

Chaari

et al. 2020

Sensors

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“…The interest of the scientific diagnostics community then has recently moved to IAS estimation from the easily available accelerometric signals, fundamental for vibration monitoring, going "encoder-less" or "tacholess". In this regard, several different approaches are possible [7].…”

Section: Instantaneous Angular Speed (Ias) Reviewmentioning

confidence: 99%

“…The second method is based on phase demodulation via the Hilbert analytic signal of a fan speed-related harmonic [7,56]. In this particular case, it was noticed that the signal corresponding to the coordinates of the center of the outer hexagon (i.e., X c , Y c in Figure 7a) features a speed-related harmonic because of the not perfect alignment of the optical axis of the camera with the fan axis, leading to a circular movement of the tracked center point.…”

Section: Ias Estimationmentioning

confidence: 99%

“…The growing interest of the signal processing community in the IAS information is demonstrated by the increasing number of publications involving the estimation of the instantaneous frequency as well as the creation of a special issue on IAS processing in the Journal of Mechanical Systems & Signal Processing [6] and of a conference dedicated solely to condition monitoring in non-stationary operations [7]. In addition, at the international conferences Surveillance 8 (in 2015) [8] and SURVISHNO (in 2019), contests about IAS estimation were organized.…”

Section: Introductionmentioning

confidence: 99%

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GA-Adaptive Template Matching for Offline Shape Motion Tracking Based on Edge Detection: IAS Estimation from the SURVISHNO 2019 Challenge Video for Machine Diagnostics Purposes

Daga

Garibaldi

2020

Algorithms

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The estimation of the Instantaneous Angular Speed (IAS) has in recent years attracted a growing interest in the diagnostics of rotating machines. Measurement of the IAS can be used as a source of information of the machine condition per se, or for performing angular resampling through Computed Order Tracking, a practice which is essential to highlight the machine spectral signature in case of non-stationary operational conditions. In these regards, the SURVISHNO 2019 international conference held at INSA Lyon on 8–10 July 2019 proposed a challenge about the estimation of the instantaneous non-stationary speed of a fan from a video taken by a smartphone, a pocket, low-cost device which can nowadays be found in everyone’s pocket. This work originated by the author to produce an offline motion-tracking of the fan (actually, of the head of its locking-screw) and obtaining then a reliable estimate of the IAS. The here proposed algorithm is an update of the established Template Matching (TM) technique (i.e., in the Signal Processing community, a two-dimensional matched filter), which is here integrated into a Genetic Algorithm (GA) search. Using a template reconstructed from a simplified parametric mathematical model of the features of interest (i.e., the known geometry of the edges of the screw head), the GA can be used to adapt the template to match the search image, leading to a hybridization of template-based and feature-based approaches which allows to overcome the well-known issues of the traditional TM related to scaling and rotations of the search image with respect to the template. Furthermore, it is able to resolve the position of the center of the screw head at a resolution that goes beyond the limit of the pixel grid. By repeating the analysis frame after frame and focusing on the angular position of the screw head over time, the proposed algorithm can be used as an effective offline video-tachometer able to estimate the IAS from the video, avoiding the need for expensive high-resolution encoders or tachometers.

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“…In some cases, rotational speed measurement using a rotary encoder may not be practical when the rotor is very large or inaccessible [5,31]. In addition, the data acquisition system needs to be capable of acquiring and processing the encoder data stream and often requires dedicated measurement hardware [32]. For the imaging system, a free line of view (line of sight) between the camera and the zone to be monitored is required.…”

Section: ) Comparison Between the Czt And Piacmentioning

confidence: 99%

Instantaneous Rotational Speed Measurement Using Image Correlation and Periodicity Determination Algorithms

Wang

Yan²,

Wang³

et al. 2020

IEEE Trans. Instrum. Meas.

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Review and comparison of tacholess instantaneous speed estimation methods on experimental vibration data

Cited by 114 publications

References 54 publications

A Simple Condition Monitoring Method for Gearboxes Operating in Impulsive Environments

A Simple Condition Monitoring Method for Gearboxes Operating in Impulsive Environments

GA-Adaptive Template Matching for Offline Shape Motion Tracking Based on Edge Detection: IAS Estimation from the SURVISHNO 2019 Challenge Video for Machine Diagnostics Purposes

Instantaneous Rotational Speed Measurement Using Image Correlation and Periodicity Determination Algorithms

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