ArticleSensors (Basel, Switzerland)2021
Sensors Data Analysis in Supervisory Control and Data Acquisition (SCADA) Systems to Foresee Failures with an Undetermined Origin.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Literature Review on Visual Analytics of Predictive Maintenance in the Manufacturing Industry.Sensors (Basel, Switzerland) · 2022Pooled it
- Survival Models for Predictive Maintenance and Remaining Useful Life in Sensor-Enabled Smart Energy Networks: A Review.Sensors (Basel, Switzerland) · 2026Review
- Design of Fire Risk Estimation Method Based on Facility Data for Thermal Power Plants.Sensors (Basel, Switzerland) · 2023Article
- A Compact IIoT System for Remote Monitoring and Control of a Micro Hydropower Plant.Sensors (Basel, Switzerland) · 2023Article
- A Configurable Monitoring, Testing, and Diagnosis System for Electric Power Plants.Sensors (Basel, Switzerland) · 2022Article
- Clustering at the Disposal of Industry 4.0: Automatic Extraction of Plant Behaviors.Sensors (Basel, Switzerland) · 2022Article
- Analyzing Particularities of Sensor Datasets for Supporting Data Understanding and Preparation.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents the design and implementation of a supervisory control and data acquisition (SCADA) system for automatic fault detection. The proposed system offers advantages in three areas: the prognostic capacity for preventive and predictive maintenance, improvement in the quality of the machined product and a reduction in breakdown times. The complementary technologies, the Industrial Internet of Things (IIoT) and various machine learning (ML) techniques, are employed with SCADA systems to obtain the objectives. The analysis of different data sources and the replacement of specific digital sensors with analog sensors improve the prognostic capacity for the detection of faults with an undetermined origin. Also presented is an anomaly detection algorithm to foresee failures and to recognize their occurrence even when they do not register as alarms or events. The improvement in machine availability after the implementation of the novel system guarantees the accomplishment of the proposed objectives.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.