Experimental Evaluation of MEMS Accelerometers Integrated into Smartphones: A Case Study of Bearing Condition Monitoring

2021 ◽  
pp. 1777-1786
Author(s):  
Abdelbaset Ait Ben Ahmed ◽  
Abdelhamid Touache ◽  
Abdelhadi El Hakimi ◽  
Abderrahim Chamat
Keyword(s):  
Condition Monitoring ◽  
Experimental Evaluation ◽  
Bearing Condition Monitoring ◽  
Mems Accelerometers

Application Research of Kalman Filter and SVM Applied to Condition Monitoring and Fault Diagnosis

2011 ◽  
Vol 121-126 ◽  
pp. 268-272 ◽  
Author(s):  
Ke Li ◽  
Yue Lei Zhang ◽  
Zhi Xiong Li
Keyword(s):  
Kalman Filter ◽  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Rolling Bearing ◽  
Support Vector ◽  
Measured Signal ◽  
Fault Features ◽  
Bearing Condition Monitoring ◽  
Filtering Technique

In the condition monitoring and fault diagnosis, useful information about the incipient fault features in the measured signal is always corrupted by noise. Fortunately, the Kalman filtering technique can filter the noise effectively, and the impending system fault can be revealed to prevent the system from malfunction. This paper has discussed recent progress of the Kalman filters for the condition monitoring and fault diagnosis. A case study on the rolling bearing condition monitoring and fault diagnosis using Kalman filter and support vector machine (SVM) has been presented. The analysis result showed that the integration of the Kalman filter and SVM was feasible and reliable for the rolling bearing condition monitoring and fault diagnosis and the fault detection rate was over 96.5%.

scholarly journals Simplification and Detection of Outlying Trajectories from Batch and Streaming Data Recorded in Harsh Environments

2019 ◽  
Vol 8 (6) ◽  
pp. 272 ◽  
Author(s):  
Iq Reviessay Pulshashi ◽  
Hyerim Bae ◽  
Hyunsuk Choi ◽  
Seunghwan Mun ◽  
Riska Asriana Sutrisnowati
Keyword(s):  
South Korea ◽  
Real World ◽  
Experimental Evaluation ◽  
Streaming Data ◽  
Harsh Environments ◽  
Noise Filtering ◽  
New Approach ◽  
Detection Algorithms ◽  
Outlying Point

Analysis of trajectory such as detection of an outlying trajectory can produce inaccurate results due to the existence of noise, an outlying point-locations that can change statistical properties of the trajectory. Some trajectories with noise are repairable by noise filtering or by trajectory-simplification. We herein propose the application of a trajectory-simplification approach in both batch and streaming environments, followed by benchmarking of various outlier-detection algorithms for detection of outlying trajectories from among simplified trajectories. Experimental evaluation in a case study using real-world trajectories from a shipyard in South Korea shows the benefit of the new approach.

The SMART SRP Well – Application of Edge Analytics for Automated Well Performance Control and Condition Monitoring in a Mature Brownfield Environment – A Case Study from Austria

2021 ◽  
Author(s):  
Christian Windisch
Keyword(s):  
Condition Monitoring ◽  
Data Communication ◽  
Holistic Approach ◽  
Well Performance ◽  
Measuring Device ◽  
Technology Transfers ◽  
Failure Conditions ◽  
Diverse Data ◽  
Bottomhole Pressure

Abstract This paper presents a holistic approach to modern oilfield and well surveillance through the inclusion of state-of-the-art edge computing applications in combination with a novel type of data transmission technology and algorithms developed in-house for automatic condition monitoring of SRP systems. The objective is to enable the responsible specialist staff to focus on the most important decisions regarding oilfield management, rather than wasting time with data collection and preparation. An own operated data communication system, based on LPWAN-technology transfers the dyno-cards, generated by an electric load cell, into the in-house developed production assistance software platform. Suitable programmed AI-algorithms enable automatic condition detection of the incoming dyno cards, including conversion and analysis of the corresponding subsurface dynamograms. A smart alarming system informs about occurring failure conditions and specifies whether an incident of rod rupture, pump-off condition, gas lock or paraffin precipitation occurred in the well. A surface mounted measuring device delivers liquid level and bottomhole pressure information automatically into the software. Based on these diverse data, the operations team plans the subsequent activities. The holistic application approach is illustrated using the case study of an SPR-operated well in an Austrian brownfield.

scholarly journals Prototyping and Validation of MEMS Accelerometers for Structural Health Monitoring—The Case Study of the Pietratagliata Cable-Stayed Bridge

2018 ◽  
Vol 7 (3) ◽  
pp. 30 ◽  
Author(s):  
Chiara Bedon ◽  
Enrico Bergamo ◽  
Matteo Izzi ◽  
Salvatore Noè
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Full Scale ◽  
Shaking Table ◽  
Efficient Design ◽  
Dynamic Identification ◽  
Structural Health ◽  
Cable Stayed Bridge ◽  
Mems Accelerometers

In recent years, thanks to the simple and yet efficient design, Micro Electro-Mechanical Systems (MEMS) accelerometers have proven to offer a suitable solution for Structural Health Monitoring (SHM) in civil engineering applications. Such devices are typically characterised by high portability and durability, as well as limited cost, hence resulting in ideal tools for applications in buildings and infrastructure. In this paper, original self-made MEMS sensor prototypes are presented and validated on the basis of preliminary laboratory tests (shaking table experiments and noise level measurements). Based on the well promising preliminary outcomes, their possible application for the dynamic identification of existing, full-scale structural assemblies is then discussed, giving evidence of their potential via comparative calculations towards past literature results, inclusive of both on-site, Experimental Modal Analysis (EMA) and Finite Element Analytical estimations (FEA). The full-scale experimental validation of MEMS accelerometers, in particular, is performed using, as a case study, the cable-stayed bridge in Pietratagliata (Italy). Dynamic results summarised in the paper demonstrate the high capability of MEMS accelerometers, with evidence of rather stable and reliable predictions, and suggest their feasibility and potential for SHM purposes.

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