Fault diagnosis without a priori model

2012 ◽  
Vol 61 (2) ◽  
pp. 316-321 ◽  
Author(s):  
Abdouramane Moussa Ali ◽  
Cédric Join ◽  
Frédéric Hamelin
Keyword(s):  
Fault Diagnosis ◽  
A Priori

scholarly journals Multipoint Optimal Minimum Entropy Deconvolution Adjusted for Automatic Fault Diagnosis of Hoist Bearing

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Tengyu Li ◽  
Ziming Kou ◽  
Juan Wu ◽  
Waled Yahya ◽  
Francesco Villecco
Keyword(s):  
Fault Diagnosis ◽  
Information Integration ◽  
Evaluation System ◽  
A Priori ◽  
Weight Coefficient ◽  
Engineering Practice ◽  
Minimum Entropy ◽  
Mode Function ◽  
Reconstructed Signal ◽  
Feature Frequency

Multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is a powerful method that can extract the periodic characteristics of signal effectively, but this method needs to evaluate the fault cycle a priori, and moreover, the results obtained in a complex environment are easily affected by noise. These drawbacks reduce the application of MOMEDA in engineering practice greatly. In order to avoid such problems, in this paper, we propose an adaptive fault diagnosis method composed of two parts: fault information integration and extracted feature evaluation. In the first part, a Teager energy spectrum amplitude factor (T-SAF) is proposed to select the intrinsic mode function (IMF) components decomposed by ensemble empirical mode decomposition (EEMD), and a combined mode function (CMF) is proposed to further reduce the mode mixing. In the second part, the particle swarm optimization (PSO) taking fractal dimension as the objective function is employed to choose the filter length of MOMEDA, and then the feature frequency is extracted by MOMEDA from the reconstructed signal. A cyclic recognition method is proposed to appraise the extracted feature frequency, and the evaluation system based on threshold and weight coefficient removes the wrong feature frequency. Finally, the feasibility of the method is verified by simulation data, experimental signals, and on-site signals. The results show that the proposed method can effectively identify the bearing state.

scholarly journals Model- vs. data-based approaches applied to fault diagnosis in potable water supply networks

2016 ◽  
Vol 18 (5) ◽  
pp. 831-850 ◽  
Author(s):  
M. À. Cugueró-Escofet ◽  
J. Quevedo ◽  
C. Alippi ◽  
M. Roveri ◽  
V. Puig ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Water Supply ◽  
Data Streams ◽  
Potable Water ◽  
A Priori ◽  
A Priori Information ◽  
Supply Networks ◽  
Water Supply Networks ◽  
Potable Water Supply ◽  
Priori Information

The problem of fault diagnosis in potable water supply networks is addressed in this paper. Two different fault diagnosis approaches are proposed to deal with this problem. The first one is based on a model-based approach exploiting a priori information regarding physical/temporal relations existing among the measured variables in the monitored system, providing fault detection and isolation capabilities by means of the residuals generated using these measured variables and their estimations. This a priori information is provided by the topology and the physical relations between the elements constituting the system. Alternatively, the second approach relies on a data-driven solution meant to exploit the spatial and temporal relationships present in the acquired data streams in order to detect and isolate faults. Relationships between data streams are modelled using sequences of linear dynamic time-invariant models, whose estimated coefficients are used to feed a hidden Markov model. Afterwards, a cognitive method based on a functional graph representation of the system isolates the fault when existing. Finally, a performance comparison between these two approaches is carried out using the Barcelona water supply network, showing successful and complementary results which suggest the integrated usage in order to improve the results achieved by each one separately.

Dissimilarity Measures for ICA-Based Source Number Estimation

2012 ◽  
Author(s):  
Wei Cheng ◽  
Seungchul Lee ◽  
Zhousuo Zhang ◽  
Zhengjia He
Keyword(s):  
Fault Diagnosis ◽  
Condition Monitoring ◽  
A Priori ◽  
Source Separation ◽  
Mechanical Vibration ◽  
Estimation Method ◽  
Dissimilarity Measures ◽  
Source Number Estimation ◽  
Machinery Condition Monitoring ◽  
Source Number

Most of blind source separation problems are carried out with a priori knowledge of the source numbers. However, for source separation-based machinery condition monitoring and fault diagnosis, it is a challenge work to determine the number of sources for a well source separation due to complex structures and nonlinear mixing mode. Therefore, source number estimation is a necessary and important procedure prior to source separation and further diagnosis work. In this paper, we focus on a novel source number estimation method based on independent component analysis (ICA) and clustering evaluation analysis, and investigate the performances of different dissimilarity measures of ICA-based source number estimations with typical mechanical vibration signals. Our work contributes to find an effective solution of source number estimation for source separation-based machinery condition monitoring and fault diagnosis.

Deep Domain Generalization Combining A Priori Diagnosis Knowledge Toward Cross-Domain Fault Diagnosis of Rolling Bearing

2021 ◽  
Vol 70 ◽  
pp. 1-11
Author(s):  
Huailiang Zheng ◽  
Yuantao Yang ◽  
Jiancheng Yin ◽  
Yuqing Li ◽  
Rixin Wang ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
A Priori ◽  
Rolling Bearing ◽  
Cross Domain

scholarly journals Takagi Sugeno fuzzy expert model based soft fault diagnosis for two tank interacting system

2014 ◽  
Vol 24 (3) ◽  
pp. 271-287 ◽  
Author(s):  
Pandiyan Manikandan ◽  
Mani Geetha
Keyword(s):  
Fuzzy Logic ◽  
Fault Diagnosis ◽  
Fault Detection ◽  
A Priori ◽  
Fault Detection And Diagnosis ◽  
Operator Experience ◽  
Reasoning System ◽  
Tank System ◽  
Detection And Diagnosis ◽  
Fuzzy Logic Theory

Abstract The inherent characteristics of fuzzy logic theory make it suitable for fault detection and diagnosis (FDI). Fault detection can benefit from nonlinear fuzzy modeling and fault diagnosis can profit from a transparent reasoning system, which can embed operator experience, but also learn from experimental and/or simulation data. Thus, fuzzy logic-based diagnostic is advantageous since it allows the incorporation of a-priori knowledge and lets the user understand the inference of the system. In this paper, the successful use of a fuzzy FDI based system, based on dynamic fuzzy models for fault detection and diagnosis of an industrial two tank system is presented. The plant data is used for the design and validation of the fuzzy FDI system. The validation results show the effectiveness of this approach.

Application of cross correlation to HREM images of surfaces

1987 ◽  
Vol 45 ◽  
pp. 754-755
Author(s):  
D. E. Luzzi ◽  
L. D. Marks ◽  
M. I. Buckett
Keyword(s):  
Cross Correlation ◽  
A Priori ◽  
Matrix Material ◽  
Correlation Method ◽  
Accurate Knowledge ◽  
Complex Image ◽  
Fourier Filtering ◽  
The Matrix ◽  
Low Pass ◽  
Data Reduction Technique

As the HREM becomes increasingly used for the study of dynamic localized phenomena, the development of techniques to recover the desired information from a real image is important. Often, the important features are not strongly scattering in comparison to the matrix material in addition to being masked by statistical and amorphous noise. The desired information will usually involve the accurate knowledge of the position and intensity of the contrast. In order to decipher the desired information from a complex image, cross-correlation (xcf) techniques can be utilized. Unlike other image processing methods which rely on data massaging (e.g. high/low pass filtering or Fourier filtering), the cross-correlation method is a rigorous data reduction technique with no a priori assumptions.We have examined basic cross-correlation procedures using images of discrete gaussian peaks and have developed an iterative procedure to greatly enhance the capabilities of these techniques when the contrast from the peaks overlap.

Towards 1-Ångstrom-resolution STEM

1993 ◽  
Vol 51 ◽  
pp. 996-997
Author(s):  
H.S. von Harrach ◽  
D.E. Jesson ◽  
S.J. Pennycook
Keyword(s):  
High Resolution ◽  
Field Emission ◽  
Phase Contrast ◽  
Spherical Aberration ◽  
A Priori ◽  
Dark Field ◽  
Image Resolution ◽  
Objective Lens ◽  
Annular Dark Field ◽  
First Results

Phase contrast TEM has been the leading technique for high resolution imaging of materials for many years, whilst STEM has been the principal method for high-resolution microanalysis. However, it was demonstrated many years ago that low angle dark-field STEM imaging is a priori capable of almost 50% higher point resolution than coherent bright-field imaging (i.e. phase contrast TEM or STEM). This advantage was not exploited until Pennycook developed the high-angle annular dark-field (ADF) technique which can provide an incoherent image showing both high image resolution and atomic number contrast.This paper describes the design and first results of a 300kV field-emission STEM (VG Microscopes HB603U) which has improved ADF STEM image resolution towards the 1 angstrom target. The instrument uses a cold field-emission gun, generating a 300 kV beam of up to 1 μA from an 11-stage accelerator. The beam is focussed on to the specimen by two condensers and a condenser-objective lens with a spherical aberration coefficient of 1.0 mm.

Treating Velopharyngeal Inadequacy Using Bilateral Buccal Flap Revision Palatoplasty

2019 ◽  
Vol 4 (5) ◽  
pp. 878-892
Author(s):  
Joseph A. Napoli ◽  
Linda D. Vallino
Keyword(s):  
Systematic Review ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Cleft Lip ◽  
Cleft Lip And Palate ◽  
A Priori ◽  
Sufficient Evidence ◽  
Obstructive Sleep ◽  
Before And After ◽  
Buccal Flap

Purpose The 2 most commonly used operations to treat velopharyngeal inadequacy (VPI) are superiorly based pharyngeal flap and sphincter pharyngoplasty, both of which may result in hyponasal speech and airway obstruction. The purpose of this article is to (a) describe the bilateral buccal flap revision palatoplasty (BBFRP) as an alternative technique to manage VPI while minimizing these risks and (b) conduct a systematic review of the evidence of BBFRP on speech and other clinical outcomes. A report comparing the speech of a child with hypernasality before and after BBFRP is presented. Method A review of databases was conducted for studies of buccal flaps to treat VPI. Using the principles of a systematic review, the articles were read, and data were abstracted for study characteristics that were developed a priori. With respect to the case report, speech and instrumental data from a child with repaired cleft lip and palate and hypernasal speech were collected and analyzed before and after surgery. Results Eight articles were included in the analysis. The results were positive, and the evidence is in favor of BBFRP in improving velopharyngeal function, while minimizing the risk of hyponasal speech and obstructive sleep apnea. Before surgery, the child's speech was characterized by moderate hypernasality, and after surgery, it was judged to be within normal limits. Conclusion Based on clinical experience and results from the systematic review, there is sufficient evidence that the buccal flap is effective in improving resonance and minimizing obstructive sleep apnea. We recommend BBFRP as another approach in selected patients to manage VPI. Supplemental Material https://doi.org/10.23641/asha.9919352

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