Theoretical model construction and structure optimization of electromagnetic flow transducer based on neural network

Li, Yingwei; Yang, Yuntong; Ma, Shaoqing; Li, Lei; Wang, Yanjun; Liu, Xingbin; Xie, Ronghua

doi:10.3233/jifs-179153

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…established a prediction model between different excitation structure parameters and performance evaluation indexes based on the neural network to improve the accuracy of the electromagnetic flowmeter. However, the stable part of the signal had to be maintained for a sufficient period of time to extract effective data by excitation, which easily caused a large power consumption of the EMF and was not conducive to eliminating the slurry interference [13]. Webilor, R.O.…”

Section: Introductionmentioning

confidence: 99%

Study on a New Electromagnetic Flow Measurement Technology Based on Differential Correlation Detection

Chen

Tian

et al. 2020

Sensors

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Under the conditions of low flow rate and strong noise, the current electromagnetic flowmeter (EMF) cannot satisfy the requirement for measurement or separate the actual flow signal and interference signal accurately. Correlation detection technology can reduce the bandwidth and suppress noise effectively using the periodic transmission of signal and noise randomness. As for the problem that the current anti-interference technology cannot suppress noise effectively, the noise and interference of the electromagnetic flowmeter were analyzed in this paper, and a design of the electromagnetic flowmeter based on differential correlation detection was proposed. Then, in order to verify the feasibility of the electromagnetic flow measurement system based on differential correlation, an experimental platform for the comparison between standard flow and measured flow was established and a verification experiment was carried out under special conditions and with flow calibration measurements. Finally, the data obtained in the experiment were analyzed. The research result showed that an electromagnetic flowmeter based on differential correlation detection satisfies the need for measurement completely. The lower limit of the flow rate of the electromagnetic flowmeter based on the differential correlation principle could reach 0.084 m/s. Under strong external interferences, the electromagnetic flowmeter based on differential correlation had a fluctuation range in output value of only 10 mV. This shows that the electromagnetic flowmeter based on the differential correlation principle has unique advantages in measurements taken under the conditions of strong noise, slurry flow, and low flow rate.

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Section: Introductionmentioning

confidence: 99%

Study on a New Electromagnetic Flow Measurement Technology Based on Differential Correlation Detection

Chen

Tian

et al. 2020

Sensors

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“…Article [43] investigates the impacts that salary variation caused by insufficient information, then evaluates the condition of information holding between the employee and the employer. Article [44] designed an measurement model and simulation model of electromagnetic flow transducer (EFT) with saddle excitation structure and then analyzed the distribution characteristics of magnetic flux density of different excitation structures. Article [45] focused on the study of constructing efficient two-dimensional wavelet synopses with maximum error bound.…”

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confidence: 99%

Big data analysis techniques for intelligent systems

Farouk

Dou

2019

IFS

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Recently, Internet of Things (IoT), Cloud, Big Data and AI gained a great attention as the most research topics. They cover not only information and communication technology, but also all kinds of intelligent systems in our society, including business, finance, industry, manufacture, management, and environment. As a result of the extensive use of these new technologies, a huge volume of data in different formats are generated much faster than before. Big data, characterized by high volume, variety and velocity, increasingly drives decision making and is changing the landscape of intelligent systems, from governments, organizations, communities to individual decision making. Cognitive big data analytics that discovers insights from pieces of evidence has a high demand for computing efficiency, knowledge discovery, problem-solving, and event prediction/prescription. It also poses great challenges in terms of data, process, analytical modelling and management for organizations to turn big data into big insight. Due to the increase in data size, complexity, and formats, it is no longer practical to anticipate and model all possible interactions and data processing in big data-based intelligent systems using the

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Recent advancements in volumetric flow meter for industrial application

Mohindru

2023

Heat Mass Transfer

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Theoretical model construction and structure optimization of electromagnetic flow transducer based on neural network

Cited by 5 publications

References 12 publications

Study on a New Electromagnetic Flow Measurement Technology Based on Differential Correlation Detection

Study on a New Electromagnetic Flow Measurement Technology Based on Differential Correlation Detection

Big data analysis techniques for intelligent systems

Recent advancements in volumetric flow meter for industrial application

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