AI-BASED SYSTEM FOR PREDICTIVE MAINTENANCE IN ELECTRICAL GRIDS

Abstract

The present invention provides an AI-based predictive maintenance system for electrical grid infrastructure, designed to monitor, analyze, and predict the operational health of critical grid components, including transformers, circuit breakers, and substations. The system incorporates a data collection unit equipped with sensors to gather real-time data on parameters such as temperature, current, vibration, and environmental conditions. A data processing module normalizes and prepares the data, which is then analyzed by an AI-driven module utilizing machine learning algorithms. These algorithms detect anomalies and trends that may indicate early signs of equipment degradation, enabling the system to predict potential failures before they occur.

Specification

Description:The embodiments of the present invention generally relates to predictive maintenance technology for electrical grid systems, employing artificial intelligence (AI) to monitor, analyze, and predict potential faults or degradation in critical electrical grid infrastructure. Specifically, this invention integrates real-time and historical data acquisition with machine learning algorithms to anticipate equipment failures, thereby enabling proactive maintenance, optimizing operational efficiency, and reducing unexpected downtimes in complex grid networks.
BACKGROUND OF THE INVENTION
The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.

Predi , Claims:1. An AI-based system for predictive maintenance in an electrical grid, comprising:
a data collection unit configured to monitor operational parameters of electrical grid components;
a data processing module configured to process collected data and extract features relevant to component health;
an AI algorithm module configured to analyze processed data and predict potential failures of electrical grid components;
an alert and notification system configured to generate predictive alerts based on analysis from the AI algorithm module;
a user interface configured to display alerts, maintenance schedules, and equipment health data, wherein the AI-based system facilitates proactive maintenance actions to prevent component failure.

2. The system of claim 1, wherein the data collection unit includes sensors measuring voltage, current, temperature, vibration, and environmental conditions.

3. The system of claim 1, wherein the AI algorithm module utilizes a neural network model to analyze temporal patterns in colle

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