ReviewSensors (Basel, Switzerland)2024
An In-Depth Study of Vibration Sensors for Condition Monitoring.
Review in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Effect of Aggregate Type on Noise Characteristics and Emissions During the Crushing Process.Materials (Basel, Switzerland) · 2026Article
- An Integrated IoT-Based Multi-Sensor Framework for Real-Time Indoor Environment and Safety Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Performance Analysis of Advanced Feature Extraction Methods for Manufacturing Defect Detection via Vibration Sensors in CNC Milling Machines.Sensors (Basel, Switzerland) · 2026Article
- Linearity Improvement of MEMS Electrochemical Vibration Sensors Based on Tapered-Hole Technology.Micromachines · 2026Article
- Low-Cost IoT-Based Predictive Maintenance Using Vibration.Sensors (Basel, Switzerland) · 2025Article
- Vibration Analysis of Aviation Electric Propulsion Test Stand with Active Main Rotor.Sensors (Basel, Switzerland) · 2025Article
- Micro-Vibrations Analysis in LEO CubeSats Using MEMS Accelerometers.Sensors (Basel, Switzerland) · 2025Article
- Accelerometer-based vibration analysis and oxygenator thrombosis in venovenous ECMO: an experimental porcine model.Intensive care medicine experimental · 2025Article
- Energy Harvesting Microelectromechanical System for Condition Monitoring Based on Piezoelectric Transducer Ring.Micromachines · 2025Article
- Fault Types and Diagnostic Methods of Manipulator Robots: A Review.Sensors (Basel, Switzerland) · 2025Review
- Ground-Target Recognition Method Based on Transfer Learning.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Heavy machinery allows for the efficient, precise, and safe management of large-scale operations that are beyond the abilities of humans. Heavy machinery breakdowns or failures lead to unexpected downtime, increasing maintenance costs, project delays, and leading to a negative impact on personnel safety. Predictive maintenance is a maintenance strategy that predicts possible breakdowns of equipment using data analysis, pattern recognition, and machine learning. In this paper, vibration-based condition monitoring studies are reviewed with a focus on the devices and methods used for data collection. For measuring vibrations, different accelerometers and their technologies were investigated and evaluated within data collection contexts. The studies collected information from a wide range of sources in the heavy machinery. Throughout our review, we came across some studies using simulations or existing datasets. We concluded in this review that due to the complexity of the situation, we need to use more advanced accelerometers that can measure vibration.
Indexed as
Identifiers
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.