List: Predictive maintenance | Curated by Michael Kingston

Feb 12, 2024
46 stories
Predictive maintenancecollection of articles related to predictive maintenance and machine learning
In
TDS Archive
by
Brent Larzalere
LSTM Autoencoder for Anomaly DetectionCreate an AI deep learning anomaly detection model using Python, Keras and TensorFlow
Sep 25, 2019
14
Sep 25, 2019
14
Sabtain Ahmad
Condition Monitoring through Diagnosis of Anomalies — LSTM-based Unsupervised ML ApproachLSMT-autoencoder based method for condition monitoring and anomaly detection for rotating machines.
Jan 17, 2021
1
Jan 17, 2021
1
Amir Khademi
An Introduction to Vibration AnalysisIn this story, I’m going to talk about vibration analysis fundamentals. The idea of this story is to take a quick look at all the primary…
Apr 11, 2018
Apr 11, 2018
In
TDS Archive
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Koen Peters
Time series analysis for predictive maintenance of turbofan enginesUsing distributed lag models to predict remaining useful life
Oct 4, 2020
3
Oct 4, 2020
3
Amir Khademi
A Summary on “Vibration analysis for bearing fault detection and classification using an…In this story, I’m going to summarize a paper on using machine learning techniques in fault detection for bearings. Paper’s title is…
Mar 27, 2018
Mar 27, 2018
In
Intuz
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Pratik K Rupareliya
How to implement predictive maintenance and asset optimization with IIOTIIoT helps collect and analyze real-time data from machines and equipment in an organization. Understanding this data helps organizations…
Jul 3, 2023
Jul 3, 2023
Jacob Ferus
An Introduction To Data-Driven Strategies For Predictive Maintenance And Related FieldsMonitoring the state of systems, predicting their remaining useful life and managing their maintenance using condition-based scheduling is…
Oct 2, 2022
1
Oct 2, 2022
1
Mathieu
Implementing Predictive Maintenance with t6 IoT Platform and Temperature SensorsIn today’s fast-paced industrial landscape, maximizing equipment reliability while minimizing downtime is crucial for businesses to…
Jul 9, 2023
Jul 9, 2023
In
TDS Archive
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Marco Cerliani
Predictive Maintenance: detect Faults from Sensors with CRNN and SpectrogramsApply Deep Learning and Spectrogram transformations to prevent Failures
Jan 21, 2020
1
Jan 21, 2020
1
Growthbotics
Predictive Maintenance using Python andThere has been a lot of talks about how python can replace all of the existing programming languages out there. Python has been the…
Nov 7, 2020
Nov 7, 2020
In
Low Code for Data Science
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Pierpaolo Vergati
Cognitive Digital Twin: Advanced Building and Energy Management in a Multitenant BuildingCreate powerful low-code AI solutions with KNIME to support smart decision-making
May 31, 2023
May 31, 2023
In
Vademecum of Practical Data Science
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Gianmario Spacagna
Deep Time-to-Failure: Predictive maintenance and survival analysis using RNNs and Weibull…A tutorial on how to implement an algorithm for predictive maintenance using survival analysis theory and gated RNNs in Keras
Feb 6, 2018
Feb 6, 2018
In
The Startup
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Shad Griffin
Converting a Probability to Fail Into a Time to Failure MetricGetting the most out of your Probability to Fail Models
Aug 4, 2020
Aug 4, 2020
In
TDS Archive
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Koen Peters
The importance of problem framing for supervised predictive maintenance solutionsRevisiting our assumption of Remaining Useful Life & Support Vector Regression
Sep 20, 2020
4
Sep 20, 2020
4
Expleo
Introduction to Bayesian Networks and Predictive Maintenance — Part 1Mohamed Benzerga (Data Scientist, PhD)
Apr 9, 2021
Apr 9, 2021
Pranav B
Predictive Maintenance of the Process equipment using PythonRemaining useful life (RUL) prediction using machine learning can significantly aid in the efficient scheduling of maintenance activities…
May 25, 2023
May 25, 2023
Anubhav Chaturvedi
Anomaly Detection for Predictive maintenance- Building autoregressive modelAn auto-regressive model predicts time series values by a linear combination of its past values. It assumes that the time series shows…
Apr 12, 2023
Apr 12, 2023
In
Eni digiTALKS
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Annagiulia Tiozzo
Detecting anomalies in industrial equipment: an explainable predictive approach to maintenance.Three steps to understand how data and machine learning algorithms can explain when and why an industrial equipment is going to fail.
Apr 4, 2022
Apr 4, 2022
Software Engineers Blog (TheGeneralAICo.)
Using Rust for IoT Devices: Tracking Jet Engine FatigueUsing Rust for IoT Devices: Tracking Jet Engine Fatigue
Sep 19, 2023
Sep 19, 2023
In
TDS Archive
by
Koen Peters
LSTM for predictive maintenance of turbofan enginesExplaining sequence generation, padding and hyperparameter tuning for FD004
Dec 13, 2020
1
Dec 13, 2020
1