DESIGN AND IMPLEMENTATION OF ERROR ISOLATION IN TECHNO METER

From heavy machinery to air conditioning, everything is getting automated and mechanized. Sensors facilitate automation. Sensors are utilized by industries and farms to collect data. Not only do agriculture and industry rely on data collecting and analysis; many other fields do as well. Sensors determine data accuracy. Typically, sensors fail at risk. Early sensor detection diminishes damage. This study discusses contemporary ways of fault-finding for researchers and professionals. This study uses the Kalman filter because it minimizes mean-squared error when estimating the state of the process. Even if the system being model is obscure, the filter can estimate past, present, and future states. Use a discrete Kalman filter. The discrete and extended Kalman filters are covered in this introduction. In addition, we will analyze a simple physical example using actual numbers.

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Publication Details

Journal
Kashf Journal of Multidisciplinary Research
Published
2024-12-10
DOI
https://doi.org/10.71146/kjmr150
Citations
4
Primary Topic
Industrial Automation and Control Systems
Type
article
Field-Weighted Citation Impact
1.31
Controls
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article

DESIGN AND IMPLEMENTATION OF ERROR ISOLATION IN TECHNO METER

Abdalla A. Latif, Mohd Ashraf, Salahuddin Salahuddin, Arslan Jalil et al.
4 citations
Kashf Journal of Multidisciplinary Research
Industrial Automation and Control Systems
1.31
article

DESIGN AND IMPLEMENTATION OF ERROR ISOLATION IN TECHNO METER

Abdalla A. Latif, Mohd Ashraf, Salahuddin Salahuddin, Arslan Jalil, Furqan Jamil
article en
4 citations

Abstract

From heavy machinery to air conditioning, everything is getting automated and mechanized. Sensors facilitate automation. Sensors are utilized by industries and farms to collect data. Not only do agriculture and industry rely on data collecting and analysis; many other fields do as well. Sensors determine data accuracy. Typically, sensors fail at risk. Early sensor detection diminishes damage. This study discusses contemporary ways of fault-finding for researchers and professionals. This study uses the Kalman filter because it minimizes mean-squared error when estimating the state of the process. Even if the system being model is obscure, the filter can estimate past, present, and future states. Use a discrete Kalman filter. The discrete and extended Kalman filters are covered in this introduction. In addition, we will analyze a simple physical example using actual numbers.

Kashf Journal of Multidisciplinary ResearchVol. 1(12)
North China University of Water Resources and Electric Power (CN), Muhammad Nawaz Sharif University of Engineering & Technology (PK), Khawaja Farid Social Security Hospital (PK), National College of Business Administration and Economics (PK), Government College of Science (PK)
Openalex Percentile: Top 18%
Industrial Automation and Control Systems
1.31
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