Two-dimensional time series sample entropy algorithm: Applications to rotor axis orbit feature identification

Wu, Huachun; Zhou, Jian; Chunhu, Xie; Zhang, Jiyang; Huang, Yue

doi:10.1016/j.ymssp.2020.107123

Cited by 29 publications

(14 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As described above, the developed ORS could sense the acceleration in three directions and rotate with the rotor system such that it could draw the spindle rotor trajectory easily compared with the wired acceleration sensor. Furthermore, an axis orbit can directly reflect the operating conditions of a rotor system and is widely used to monitor rotor conditions and faulty diagnoses 26 . The orbit of the spindle rotor system was calculated based on this phenomenon, as shown in Fig.…”

Section: Experimental Evaluation and Discussionmentioning

confidence: 99%

Assessment of a three-axis on-rotor sensing performance for machining process monitoring: a case study

Zou

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Online monitoring of cutting conditions is essential in intelligent manufacturing, and vibrations are one of the most effective signals in monitoring machining conditions. Generally, traditional wired accelerometers should be installed on a motionless or stable platform, such as a tool holder or lathe bed, to sense vibrations. Such installation methods would cause the signals to suffer more serious noise interferences and a low signal-to-noise ratio, resulting in less sensitivity to valuable information. Therefore, this study developed a novel three-axis wireless on-rotor sensing (ORS) system for monitoring the turning process. The Micro Electromechanical System (MEMS) accelerometer sensor node can be mounted on a rotating workpiece or spindle rotor and is more sensitive in detecting the vibrations of the entire rotor system without any modification of the lathe system and interference in the cutting procedure. The processor, data acquisition, and Bluetooth Low Energy (BLE) 5.0+ modules were developed and debugged to cooperate with a piezoelectric triaxial accelerometer, with a vibration amplitude not larger than ± 16 g. A series of turning tests were conducted and the results were compared with those from the commercial wired accelerometers, which proved that the ORS system can measure the vibration signal of the rotor system more effectively and sensitively than wired accelerometers, thus demonstrating the accurate monitoring of machining parameters.

show abstract

Section: Experimental Evaluation and Discussionmentioning

confidence: 99%

Assessment of a three-axis on-rotor sensing performance for machining process monitoring: a case study

Zou

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Additionally, orbits can also react to certain failures in bearings or supporting springs [ 59 ]. This parameter is used in the diagnostics of many rotating machines [ 60 , 61 , 62 , 63 , 64 ]. Reconstructing the shaft orbit using Instantaneous Angular Speed (IAS) measurement to detect bearing faults is proposed in [ 65 ].…”

Section: State Of the Artmentioning

confidence: 99%

Condition Monitoring of Horizontal Sieving Screens—A Case Study of Inertial Vibrator Bearing Failure in Calcium Carbonate Production Plant

et al. 2023

View full text Add to dashboard Cite

Predictive maintenance is increasingly popular in many branches, as well as in the mining industry; however, there is a lack of spectacular examples of its practice efficiency. Close collaboration between Omya Group and Wroclaw University of Science and Technology allowed investigation of the failure of the inertial vibrator’s bearing. The signals of vibration are captured from the sieving screen just before bearing failure and right after repair, when it was visually inspected after replacement. The additional complication was introduced by the loss of stable attachment of the vibrator’s shield, which produced great periodical excitation in each place of measurement on the machine. Such anomalies in the signals, in addition to falling pieces of material, made impossible the diagnostics by standard methods. However, the implementation of advanced signal processing techniques such as time–frequency diagrams, envelope spectrum, cyclic spectral coherence, orbits analysis, and phase space plots allowed to undermine defects (pitting on the inner ring). After repair, the amplitudes of vibration from the damaged bearing side were reduced by five times, while sound pressure was only two times lower. The quantitative parameters of vibrations showed significant changes: time series RMS (−68%) median energy of spectrograms (89%), frequencies ratio of cyclic spectral coherence (−85%), and average amplitude of harmonics in envelope spectrum (−80%). The orbits demonstrated changes in inclination angle (16%) and sizes (−48 ... −96%), as well as phase space plots sizes (−28 ... −67%). Directions of further research are considered.

show abstract

“…On the other hand, due to the popularity of SampEn in the analysis of temporary signals, the SampEn2D extension has had some visibility for the analysis of irregularity in images (details in References [24,[30][31][32][33]); some new methods have incorporated into their algorithm the calculation of SampEn2D, generating interesting alternatives, such as multiscale entropy (MSE2D) and its variant ModMSE2D [34]. However, expanding the SampEn1D method into the world of 2D data analysis or imaging should mean additional considerations, such as the number of m points taken as a pattern for comparison in SampEn1D; typically, m = 2 or m = 3 is less than the number of points (pixels) taken as a pattern in the case of SampEn2D.…”

Section: Espinosa Entropy Proposal (Espen) For 2dmentioning

confidence: 99%

Two-Dimensional EspEn: A New Approach to Analyze Image Texture by Irregularity

Espinosa

Bailón

Laguna

2021

Entropy

View full text Add to dashboard Cite

Image processing has played a relevant role in various industries, where the main challenge is to extract specific features from images. Specifically, texture characterizes the phenomenon of the occurrence of a pattern along the spatial distribution, taking into account the intensities of the pixels for which it has been applied in classification and segmentation tasks. Therefore, several feature extraction methods have been proposed in recent decades, but few of them rely on entropy, which is a measure of uncertainty. Moreover, entropy algorithms have been little explored in bidimensional data. Nevertheless, there is a growing interest in developing algorithms to solve current limits, since Shannon Entropy does not consider spatial information, and SampEn2D generates unreliable values in small sizes. We introduce a proposed algorithm, EspEn (Espinosa Entropy), to measure the irregularity present in two-dimensional data, where the calculation requires setting the parameters as follows: m (length of square window), r (tolerance threshold), and ρ (percentage of similarity). Three experiments were performed; the first two were on simulated images contaminated with different noise levels. The last experiment was with grayscale images from the Normalized Brodatz Texture database (NBT). First, we compared the performance of EspEn against the entropy of Shannon and SampEn2D. Second, we evaluated the dependence of EspEn on variations of the values of the parameters m, r, and ρ. Third, we evaluated the EspEn algorithm on NBT images. The results revealed that EspEn could discriminate images with different size and degrees of noise. Finally, EspEn provides an alternative algorithm to quantify the irregularity in 2D data; the recommended parameters for better performance are m = 3, r = 20, and ρ = 0.7.

show abstract

Two-dimensional time series sample entropy algorithm: Applications to rotor axis orbit feature identification

Cited by 29 publications

References 18 publications

Assessment of a three-axis on-rotor sensing performance for machining process monitoring: a case study

Assessment of a three-axis on-rotor sensing performance for machining process monitoring: a case study

Condition Monitoring of Horizontal Sieving Screens—A Case Study of Inertial Vibrator Bearing Failure in Calcium Carbonate Production Plant

Two-Dimensional EspEn: A New Approach to Analyze Image Texture by Irregularity

Contact Info

Product

Resources

About