Evaluating machine learning algorithm for real-time heat exchanger optimization and automatic issue detection device: experimental analysis

The experimentation and analysis of a machine learning (ML) algorithm for automatic problem detection and real-time heat exchanger optimization (RTHEO) is presented in detail in this paper. Preparing datasets, optimizing heat exchanger parameters, identifying problems, self-training, and applying ma...

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Bibliographic Details
Published in:International journal on interactive design and manufacturing 2024-09, Vol.18 (7), p.4409-4420
Main Authors: Wankhede, Sagar, Lobo, Rayan, Pesode, Pralhad
Format: Article
Language:English
Subjects:
Algorithms
Anomalies
Artificial intelligence
Automation
CAE) and Design
Computer-Aided Engineering (CAD
Control algorithms
Cost control
Data acquisition systems
Electronics and Microelectronics
Energy consumption
Energy efficiency
Engineering
Engineering Design
Heat exchangers
Heat transfer
HVAC
Industrial Design
Instrumentation
Machine learning
Matlab
Mechanical Engineering
Nuclear energy
Nuclear power plants
Optimization
Optimization techniques
Original Article
Parameter identification
Polynomials
R&D
Real time
Research & development
Thermal energy
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Summary:The experimentation and analysis of a machine learning (ML) algorithm for automatic problem detection and real-time heat exchanger optimization (RTHEO) is presented in detail in this paper. Preparing datasets, optimizing heat exchanger parameters, identifying problems, self-training, and applying machine learning algorithms are the main areas of study. The suggested method utilizes MATLAB Simulink simulations that use polynomial regression to suggest parameters and a combination of algorithms to identify anomalies. The program continuously obtains real-time data, compares it with previous patterns, and notifies the user if any anomalies are detected. The algorithm adapts to observations through self-training, ensuring accurate and reliable predictions. The implementation is carried out using MATLAB, with robust error-handling mechanisms for real-world applications. The simulation procedure is discussed, and a future experimental setup is proposed to verify the program’s performance.
ISSN:1955-2513
1955-2505
DOI:10.1007/s12008-023-01709-7