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Advanced Sensor Fusion in Industry 4.0

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 2147

Special Issue Editor


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Guest Editor
Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, Via P. Vivarelli 10, 41125 Modena, Italy
Interests: optical optic sensor; instrumentation and measurement methods; lidar; industrial smart measurements; IoT; front-end electronics, sensor fusion

Special Issue Information

Dear Colleagues,

The technological transformations fostered by Industry 4.0 (and the forthcoming Industry 5.0) paradigms deeply rely on a data-centric vision, where smart and advanced sensing technologies, together with innovative measurement paradigms, need to seamlessly cooperate to ensure reliability, accuracy, and timeliness.

A significant option nowadays is represented by the deployment of integrated and multiple sensors, whose outputs can be intelligently combined to provide meaningful, highly accurate, and more representative information about a physical process. This sensor fusion approach is becoming increasingly appealing in several fields and for many Industry 4.0 applications, such as additive manufacturing scenarios.

Moreover, the current technological advancement facilitates real-time data analysis and manipulation, potentially paving the way for the definition of novel approaches to sensor fusion based on Machine Learning and Artificial Intelligence approaches.

Potential topics include but are not limited to:

  • Hardware and software architectures for collaborative multi-sensor fusion;
  • Advance sensors and sensors systems for Industry 4.0;
  • Power management and energy harvesting in sensor systems;
  • Wired and wireless sensor networks;
  • Hardware and software IoT architectures;
  • Sensors for measurements, testbeds, calibration, and validation;
  • Data fusion algorithms for measurement processes;
  • Machine learning and artificial intelligence application in sensor fusion;
  • Cloud and edge computing for sensor data fusion.

Prof. Dr. Luigi Rovati
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

16 pages, 2907 KiB  
Article
Performance Evaluation Method for Intelligent Computing Components for Space Applications
by Man Xie, Lianguo Wang, Miao Ma and Pengfei Zhang
Sensors 2024, 24(1), 145; https://doi.org/10.3390/s24010145 - 27 Dec 2023
Viewed by 701
Abstract
The computational performance requirements of space payloads are constantly increasing, and the redevelopment of space-grade processors requires a significant amount of time and is costly. This study investigates performance evaluation benchmarks for processors designed for various application scenarios. It also constructs benchmark modules [...] Read more.
The computational performance requirements of space payloads are constantly increasing, and the redevelopment of space-grade processors requires a significant amount of time and is costly. This study investigates performance evaluation benchmarks for processors designed for various application scenarios. It also constructs benchmark modules and typical space application benchmarks specifically tailored for the space domain. Furthermore, the study systematically evaluates and analyzes the performance of NVIDIA Jetson AGX Xavier platform and Loongson platforms to identify processors that are suitable for space missions. The experimental results of the evaluation demonstrate that Jetson AGX Xavier performs exceptionally well and consumes less power during dense computations. The Loongson platform can achieve 80% of Xavier’s performance in certain parallel optimized computations, surpassing Xavier’s performance at the expense of higher power consumption. Full article
(This article belongs to the Special Issue Advanced Sensor Fusion in Industry 4.0)
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15 pages, 3175 KiB  
Article
Standalone Sensors System for Real-Time Monitoring of Cutting Emulsion Properties with Adaptive Integration in Machine Tool Operation
by Jozef Peterka, Frantisek Jurina, Marek Vozar, Boris Patoprsty, Tomas Vopat, Vladimir Simna and Pavol Bozek
Sensors 2023, 23(13), 5794; https://doi.org/10.3390/s23135794 - 21 Jun 2023
Viewed by 989
Abstract
This paper presents a novel cutting fluid monitoring sensor system and a description of an algorithm framework to monitor the state of the cutting emulsion in the machine tool sump. One of the most frequently used coolants in metal machining is cutting emulsion. [...] Read more.
This paper presents a novel cutting fluid monitoring sensor system and a description of an algorithm framework to monitor the state of the cutting emulsion in the machine tool sump. One of the most frequently used coolants in metal machining is cutting emulsion. Contamination and gradual degradation of the fluid is a common occurrence, and unless certain maintenance steps are undertaken, the fluid needs to be completely replaced, which is both un-economical and non-ecological. Increasing the effective service life of the cutting emulsion is therefore desired, which can be achieved by monitoring the parameters of the fluid and taking corrective measures to ensure the correct levels of selected parameters. For this purpose, a multi-sensor monitoring probe was developed and a prototype device was subsequently created by additive manufacturing. The sensor-carrying probe was then placed in the machine tool sump and tested in operation. The probe automatically takes measurements of the selected cutting emulsion properties (temperature, concentration, pH, level height) in set intervals and logs them in the system. During the trial run of the probe, sensor accuracy was tracked and compared to reference measurements, achieving sufficiently low deviations for the purpose of continuous operation. Full article
(This article belongs to the Special Issue Advanced Sensor Fusion in Industry 4.0)
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