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Risk-based renewal planning for asset management of water distribution systems

asphaltfatigueann

about 疲劳寿命

asset-management-3

An Empirical Study on ML Asset Management

condition_based_maintenance

this repo use to simulate Joint optimization decision of condition-based maintenance and spare parts inventory

grid2op-1.1

Grid2Op a testbed platform to model sequential decision making in power systems.

gsp_bridge-paper6

Additional material for "Graph Signal Processing on Complex Networks for Structural Health Monitoring"

hidden-markov-models-4.1

kernelcpd_windscada

Code and supplementary material complementing the WES-publication: "Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour models""

lstms_for_predictive_maintenance

LSTMS for Predictive Maintenance

maintenance-optimization

Maintenance Optimization Problem. A mixed integer optimization model for maintenance operations to minimize the Total Cost and obtain the optimal value of decision variables.

maintenance-replacement-problem

maintenance-replacement optimization problem, where the goal is to optimize the decision of when to replace a machine based on its age and associated costs. This problem is relevant in many industries, where machines are critical for production and the decision of when to replace them can have a significant impact on costs and performance.

openoa

This library provides a framework for assessing wind plant performance using operational assessment (OA) methodologies that consume time series data from wind plants. The goal of the project is to provide an open source implementation of common data structures, analysis methods, and utility functions relevant to wind plant OA.

owf_repair_action_recommender

Deep Offshore Repair: A framework for Repair Action Recommendion using Alarm Sequences

pcrnn-wtg

about wind turbine predictive maintenance

platemo-paper5

Evolutionary multi-objective optimization platform

predictive-maintenance

Optimize maintenance schedule for gas turbine

predictive-maintenance-lstm

Predicting the Remaining Useful Life (RUL) of simulated turbofan data using Keras and LSTM.

predictive-maintenance-of-aircraft-engine

In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbofan engine.

predictive-maintenance-using-lstm

Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

predictive-maintenance2

A notebook tutorial series for performing predictive maintenance using machine learning

predictivemaintenance-1dcnn-azure

Predictive maintenance solution. 1D CNN model in TensorFlow 2.0 with Azure Machine Learning. Tf-Lite Model Optimization

predictivemaintenance-and-vibration-resources

Papers and datasets for Vibration Analysis

robust-reinforcement-4.2

scientometricreview-2

Data for our paper "Scientometric Review of Artificial Intelligence for Operations & Maintenance of Wind Turbines: The Past, Present and Future".

stn

maintenance strategy,涉及cost计算

tensorforce-1.2

Tensorforce: a TensorFlow library for applied reinforcement learning

vtnmpc-autonomous-wind-turbine-inspection

This repository contains the code and simulation files for the submitted paper titled "Autonomous Wind Turbine Inspection Framework Enabled by Visual Tracking Nonlinear Model Predictive Control (VT-NMPC)".

water_pump_maintenance_break_prediction

The Water Pump Maintenance Break Prediction project uses machine learning and sensor data to predict maintenance needs, improving pump efficiency and reducing downtime. It highlights the importance of predictive maintenance and data-driven decision-making in optimizing industrial operations and ensuring water supply management.

wind-maintenance

Supplementary data for utilising knowledge graph databases towards explainable decision support in wind turbines.

wind-turbines-level-a

The wind turbine failure dataset (SCADA – Supervisory Control and Data Acquisition) has measurements recorded every 10 seconds, from wind turbine sensors. The variable names are unknown, but they represent sensor measurements that correspond to various physical process properties.