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Sensors and Signal Analysis for Dynamic Measurement in Industrial Process

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 August 2023) | Viewed by 18501

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Special Issue Editors

Prof. Dr. Manuchehr Soleimani

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Guest Editor

EEE Department, University of Bath, Bath BA1 8BE, UK
Interests: inverse problems; tomography; machine learning
Special Issues, Collections and Topics in MDPI journals

Dr. Yandan Jiang

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Guest Editor

State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
Interests: measurement techniques and automatic devices; process tomography; multiphase flow measurement techniques; signal processing and soft sensing; robot sensing techniques

Dr. Guanghui Liang

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Guest Editor

Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Interests: electrical/ultrasonic/multimodal tomography; dynamic imaging for multiphase flow processes; multi-source information fusion and multi-parameter joint inversion

Special Issue Information

Dear Colleagues,

Measurement is the front-end basis of information acquisition. Dynamic measurement is critical to the system design, optimal control, status or safety monitoring, energy conservation and emission reduction of industrial processes. Increasing attention is being paid to dynamic measurement techniques for its complexity, time-varying property, and intractable nature. This Special Issue focuses on the sensors and signal analysis for dynamic measurement in industrial processes, which aims to promote the theoretical development and technical advancement of process measurement in industry, including new sensing techniques and measurement methods, novel sensor design and system development, advanced signal analysis and processing, etc.

The Guest Editors invite contributions to this Special Issue of Sensors in relation to the following topics, which include, but are not limited to:

The novel design of industrial sensors or sensor systems.
Tomography and imaging sensors.
Multi-modality and smart/intelligent sensors.
Localization and object-tracking sensors.
Sensors in multiphase flow measurement.
Structural health-monitoring sensors.
Dynamic image reconstruction techniques.
Signal analysis and the modeling of industrial sensors.
Signal processing and data fusion for process measurement.
Machine/deep learning and artificial intelligence for process measurement.

Prof. Dr. Manuchehr Soleimani
Dr. Yandan Jiang
Dr. Guanghui Liang
Guest Editors

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Published Papers (11 papers)

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Editorial

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3 pages, 174 KiB

Open AccessEditorial

Editorial to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process

by Yandan Jiang, Manuchehr Soleimani and Guanghui Liang

Sensors 2023, 23(24), 9784; https://doi.org/10.3390/s23249784 - 12 Dec 2023

Viewed by 897

Abstract

Measurement is the front-end basis of information acquisition [...] Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

Research

Jump to: Editorial

14 pages, 3484 KiB

Open AccessArticle

Development of a Wideband Precision Electric Field Measuring Sensor

by Zhaozhi Long, Feng Zhou, Fuchang Lin, Jiawei Fan, Wenting Li, Yinglong Diao and Kangmin Hu

Sensors 2023, 23(23), 9409; https://doi.org/10.3390/s23239409 - 25 Nov 2023

Cited by 2 | Viewed by 1202

Abstract

High-voltage electric field measurement technology has certain applications in electric field measurement of power systems, but due to the limitation of its measurement accuracy and bandwidth, it cannot be used for the measurement of lightning-impulse voltage. In order to calibrate the nonlinearity of the MV-level lightning-impulse voltage measurement system, this paper proposes the design and implementation of a high-precision inductive wideband electric field measuring sensor (EFMS). The influence of the metal shell on the electric field distribution was simulated, and the influence of the electric field non-uniformity coefficient was studied. The characteristics of the EFMS were tested, and the results showed that the EFMS can accurately reproduce the waveform of lightning-impulse voltage and power-frequency voltage, with a proportionality coefficient of 0.05664 V/(kV/m). In mostly uniform and extremely non-uniform fields, the nonlinearity of the EFMS for impulse voltage is less than ±0.25%, and the nonlinearity of the EFMS for power-frequency voltage is less than 0.1%. It is shown that the EFMS can be used for the nonlinearity calibration of ultra-high voltage impulse measurement devices. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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14 pages, 11918 KiB

Open AccessArticle

Propellant Mass Gauging in a Spherical Tank under Micro-Gravity Conditions Using Capacitance Plate Arrays and Machine Learning

by Shah M. Chowdhury, Matthew A. Charleston, Qussai M. Marashdeh and Fernando L. Teixeira

Sensors 2023, 23(20), 8516; https://doi.org/10.3390/s23208516 - 17 Oct 2023

Cited by 4 | Viewed by 1351

Abstract

Propellant mass gauging under micro-gravity conditions is a challenging task due to the unpredictable position and shape of the fuel body inside the tank. Micro-gravity conditions are common for orbiting satellites and rockets that operate on limited fuel supplies. Capacitance sensors have been investigated for this task in recent years; however, the effect of various positions and shapes of the fuel body is not analyzed in detail. In this paper, we investigate this with various fill types, such as annular, core-annular, and stratified fills at different positions. We compare the performance among several curve-fitting-based approaches and a machine-learning-based approach, the latter of which offers superior performance in estimating the fuel content. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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20 pages, 15423 KiB

Open AccessArticle

Time–Frequency–Energy Characteristics Analysis of Vibration Signals in Digital Electronic Detonators and Nonel Detonators Exploders Based on the HHT Method

by Haojie Yin, Hui Chen, Yin Feng and Jingkun Zhao

Sensors 2023, 23(12), 5477; https://doi.org/10.3390/s23125477 - 10 Jun 2023

Cited by 4 | Viewed by 1698

Abstract

The China Society of Explosives and Blasting required a larger than 20% annual increase in the national use of digital electronic detonators since 2018. So, this article conducted a large number of on-site tests and then used the Hilbert–Huang Transform method to analyze and compare the vibration signals of digital electronic and nonel detonators during the excavation process of minor cross-sectional rock roadways from the perspective of time, frequency, and energy. Then, through vibration energy analysis, identification of actual delay time, and formula derivation, it was proved that the delay time error of the detonator can control vibration wave random interference and reduce vibration. The analysis results showed that when using a segmented simultaneous blasting network for excavation in small-sectioned rock tunnels, nonel detonators may provide more excellent protection to structures than digital electronic detonators. In the same segment, the timing error of nonel detonators produces a vibration wave with a random superposition damping effect, resulting in an average vibration reduction of 19.4% per segment compared to digital electronic detonators. However, digital electronic detonators are superior to nonel detonators for the fragmentation effect on rock. The research conducted in this paper has the potential to facilitate a more rational and comprehensive promotion of digital electronic detonators in China. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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25 pages, 8271 KiB

Open AccessArticle

A New Contactless Cross-Correlation Velocity Measurement System for Gas–Liquid Two-Phase Flow

by Bixia Sheng, Junchao Huang, Haifeng Ji and Zhiyao Huang

Sensors 2023, 23(10), 4886; https://doi.org/10.3390/s23104886 - 19 May 2023

Cited by 2 | Viewed by 1637

Abstract

Based on the principle of Contactless Conductivity Detection (CCD), a new contactless cross-correlation velocity measurement system with a three-electrode construction is developed in this work and applied to the contactless velocity measurement of gas–liquid two-phase flow in small channels. To achieve a compact design and to reduce the influence of the slug/bubble deformation and the relative position change on the velocity measurement, an electrode of the upstream sensor is reused as an electrode of the downstream sensor. Meanwhile, a switching unit is introduced to ensure the independence and consistency of the upstream sensor and the downstream sensor. To further improve the synchronization of the upstream sensor and the downstream sensor, fast switching and time compensation are also introduced. Finally, with the obtained upstream and downstream conductance signals, the velocity measurement is achieved by the principle of cross-correlation velocity measurement. To test the measurement performance of the developed system, experiments are carried out on a prototype with a small channel of 2.5 mm. The experimental results show that the compact design (three-electrode construction) is successful, and its measurement performance is satisfactory. The velocity range for the bubble flow is 0.312–0.816 m/s, and the maximum relative error of the flow rate measurement is 4.54%. The velocity range for the slug flow is 0.161 m/s–1.250 m/s, and the maximum relative error of the flow rate measurement is 3.70%. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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21 pages, 13700 KiB

Open AccessArticle

Dual-Modal Electrical Imaging of Two-Phase Flow—Experimental Evaluation of the State Estimation Approach

by M. Ziaul Arif, Aku Seppänen, Ville Kolehmainen and Marko Vauhkonen

Sensors 2023, 23(9), 4462; https://doi.org/10.3390/s23094462 - 3 May 2023

Cited by 5 | Viewed by 1610

Abstract

Accurate measurement of two-phase flow quantities is essential for managing production in many industries. However, the inherent complexity of two-phase flow often makes estimating these quantities difficult, necessitating the development of reliable techniques for quantifying two-phase flow. In this paper, we investigated the feasibility of using state estimation for dynamic image reconstruction in dual-modal tomography of two-phase oil–water flow. We utilized electromagnetic flow tomography (EMFT) to estimate velocity fields and electrical tomography (ET) to determine phase fraction distributions. In state estimation, the contribution of the velocity field to the temporal evolution of the phase fraction distribution was accounted for by approximating the process with a convection–diffusion model. The extended Kalman filter (EKF) and fixed-interval Kalman smoother (FIKS) were used to reconstruct the temporally evolving velocity and phase fraction distributions, which were further used to estimate the volumetric flow rates of the phases. Experimental results on a laboratory setup showed that the FIKS approach outperformed the conventional stationary reconstructions, with the average relative errors of the volumetric flow rates of oil and water being less than 4%. The FIKS approach also provided feasible uncertainty estimates for the velocity, phase fraction, and volumetric flow rate of the phases, enhancing the reliability of the state estimation approach. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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18 pages, 6474 KiB

Open AccessArticle

Dynamic Compensation of a Piezoelectric Accelerometer Obtained through a General Probabilistic Approach

by Francesco Crenna, Giovanni Battista Rossi and Marta Berardengo

Sensors 2023, 23(8), 3950; https://doi.org/10.3390/s23083950 - 13 Apr 2023

Cited by 1 | Viewed by 1677

Abstract

Dynamic compensation is the (partial) correction of the measurement signals for the effects due to bandwidth limitations of measurement systems and constitutes a research topic in dynamic measurement. The dynamic compensation of an accelerometer is here considered, as obtained by a method that directly comes from a general probabilistic model of the measurement process. Although the application of the method is simple, the analytical development of the corresponding compensation filter is quite complex and had been previously developed only for first-order systems, whilst here a second-order system is considered, thus moving from a scalar to a vector problem. The effectiveness of the method has been tested both through simulation and by a dedicated experiment. Both tests have shown the capability of the method of significantly improve the performance of the measurement system when dynamic effects are more prevalent than additive observation noise. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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14 pages, 6718 KiB

Open AccessArticle

Distributed Optical Measurement System for Plate Fin Heat Exchanger

by Huajun Li, Xiao Yang, Baoliang Wang and Haifeng Ji

Sensors 2023, 23(6), 3047; https://doi.org/10.3390/s23063047 - 11 Mar 2023

Cited by 2 | Viewed by 1529

Abstract

The acquirement of the flow information in plate-fin heat exchanger (PFHE) is limited by its metal structure and complex flow condition. This work develops a new distributed optical measurement system to obtain flow information and boiling intensity. The system utilizes numerous optical fibers installed at the surface of the PFHE to detect optical signals. The attenuation and fluctuation of the signals reflect the variation of the gas-liquid interfaces and can be further used to estimate the boiling intensity. Practical experiments of flow boiling in PFHE with different heating fluxes have been carried out. The results verify that the measurement system can obtain the flow condition. Meanwhile, according to the results, the boiling development in PFHE can be divided into four stages with the increase in the heating flux, including the unboiling stage, initiation stage, boiling developing stage, and fully developed stage. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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21 pages, 1444 KiB

Open AccessArticle

Correction of Dynamical Properties of Data Acquisition Systems

by Jarosław Figwer and Małgorzata I. Michalczyk

Sensors 2023, 23(3), 1676; https://doi.org/10.3390/s23031676 - 3 Feb 2023

Cited by 1 | Viewed by 2063

Abstract

Accurate and fast measurements are important in many areas of everyday engineering and research activities. This paper proposes a method that gives such measurements, additionally shortening the time in which they are obtained. To achieve this, a supplementary discrete-time filter, estimating values of delayed samples of the measured signal, is attached to the output of the data acquisition system. This filter is identified with the use of classical estimation methods, based on a dynamical model of the data acquisition system. The definition of the cost function minimised during filter identification depends on the nature of the environment in which measurements are acquired. The considerations presented in this paper are illustrated with four corresponding simulated case study examples. They show how, in a very simple way, dynamical properties of data acquisition systems may be corrected, and thus improved, using the corresponding supplementary discrete-time filters. The improvement, measured by the correction quality index introduced in the paper, was from a few times up to more than 100. The paper also raises the issue of obtaining models for tuning of the supplementary discrete-time filter. The considerations presented may be applied to formulate the artificial intelligence of data acquisition systems as well as sensors. Finally, the paper proposes to implement this intelligence as a knowledge base of the expert system. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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16 pages, 4207 KiB

Open AccessArticle

Application of Microwave Transmission Sensors for Water Cut Metering under Varying Salinity Conditions: Device, Algorithm and Uncertainty Analysis

by Kai Zuo, Yi Hong, Haitao Qi, Yi Li and Baolong Li

Sensors 2022, 22(24), 9746; https://doi.org/10.3390/s22249746 - 12 Dec 2022

Cited by 3 | Viewed by 1723

Abstract

The measurement of water cut in crude oil is an essential procedure in petroleum production and it is desirable to obtain these data through an automatic and real-time method. Microwave sensors can be used for the task, and they are safe, robust and can cover the whole water cut range. However, they are relatively susceptible to the water conductivity and temperature, and the algorithms for addressing these problems are still rare in the literature. In this paper, a microwave transmission sensor that can measure the water cut under varying salinity conditions is proposed, and the algorithm for solving the water cut and salinity simultaneously with the measured amplitude and phase is described in detail. Experiments under different water cut and salinity conditions are conducted, and the results are used to verify the model and algorithm. Finally, a simplified and fast method for uncertainty analysis is proposed and applied to the iteration algorithm under test conditions. It can be concluded that accuracy higher than 95% in the water cut measurements can be expected under the 0~100% water cut range, and an error of about 10% in the water conductivity is achievable under water-continuous flow conditions. The uncertainty analysis shows that the calculated water cut and salinity results are negatively correlated, and the water salinity uncertainty tends to be larger than the water cut uncertainty. When the water salinity is high, the water cut uncertainty tends to be high whereas the water salinity uncertainty tends to be low. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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16 pages, 4258 KiB

Open AccessCommunication

Response Characteristics of Contactless Impedance Detection (CID) Sensor on Slug Flow in Small Channels: The Investigation on Slug Separation Distance

by Chenxu Wang, Junchao Huang, Haifeng Ji and Zhiyao Huang

Sensors 2022, 22(22), 8987; https://doi.org/10.3390/s22228987 - 20 Nov 2022

Cited by 3 | Viewed by 1685

Abstract

In recent years, CID sensors have displayed great development potential in parameter measurement of gas–liquid two-phase flow in small channels. However, the fundamental/mechanism research on the response characteristics of CID sensors is relatively insufficient. This work focuses on the investigation of the influence of separation distance between slugs on the impedance (real part, imaginary part and amplitude) response characteristics of slug flow in small channels. Experiments were carried out with the CID sensors in four small channels with inner pipe diameters of 1.96 mm, 2.48 mm, 3.02 mm and 3.54 mm, respectively. The experimental results show that for a CID sensor, the slug separation distance has significant influence on the impedance response characteristics. There is a critical value of slug separation distance. When the slug separation distance is larger than the critical value, the impedance response characteristics of each slug can be considered independent of each other, i.e., there is no interaction between the slugs. When the slug separation distance is less than the critical value, the impedance response characteristics show obvious interaction between the slugs. It is indicated that the ratios of the critical values to the pipe inner diameters are approximate 100. Full article

(This article belongs to the Special Issue Sensors and Signal Analysis for Dynamic Measurement in Industrial Process)

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