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arXiv · 2601.01616

Real Time NILM Based Power Monitoring of Identical Induction Motors Representing Cutting Machines in Textile Industry

Md Istiauk Hossain Rifat·Moin Khan·Zohara Kamal·Md Borhan Uddin Khan·Mohammad Zunaed
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Abstract

The textile industry in Bangladesh is one of the most energy-intensive sectors, yet its monitoring practices remain largely outdated, resulting in inefficient power usage and high operational costs. To address this, we propose a real-time Non-Intrusive Load Monitoring (NILM)-based framework tailored for industrial applications, with a focus on identical motor-driven loads representing textile cutting machines. A hardware setup comprising voltage and current sensors, Arduino Mega and ESP8266 was developed to capture aggregate and individual load data, which was stored and processed on cloud platforms. A new dataset was created from three identical induction motors and auxiliary loads, totaling over 180,000 samples, to evaluate the state-of-the-art MATNILM model under challenging industrial conditions. Results indicate that while aggregate energy estimation was reasonably accurate, per-appliance disaggregation faced difficulties, particularly when multiple identical machines operated simultaneously. Despite these challenges, the integrated system demonstrated practical real-time monitoring with remote accessibility through the Blynk application. This work highlights both the potential and limitations of NILM in industrial contexts, offering insights into future improvements such as higher-frequency data collection, larger-scale datasets and advanced deep learning approaches for handling identical loads.

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Md Istiauk Hossain Rifat, Moin Khan, Zohara Kamal, Md Borhan Uddin Khan, Mohammad Zunaed. 2026-01-04. Real Time NILM Based Power Monitoring of Identical Induction Motors Representing Cutting Machines in Textile Industry. https://arxiv.org/abs/2601.01616

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