Tata Consulting Engineers presents DigitalPoint, an AI platform that monitors transformer health in real time. Transformers fail after 25 years due to insulation degradation and overloading, but conventional inspections miss hotspots and oil overheating. DigitalPoint predicts failures, schedules maintenance, and estimates remaining useful life to cut outages and costs.
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Tata Consulting engineers with decades of domain expertise in transmission and distribution system has leveraged artificial intelligence, machine learning, and data analytics to develop a digital point solution for transformer performance monitoring and diagnosis. This digital point solution can be used in various sectors such as power, transmission and distribution, oil and gas, chemical, and steel. It will help the operator to better understand the asset health and performance and predict failures. It can be used in both greenfield and brownfield projects to improve the availability of transformers while minimizing the risk of outage. Now let us look into the significance of a transformer. Transformer is one of the critical equipment in electrical network system. The average life of a transformer is approximately 25 years. However, failure rate is on a higher side. Any fault in the transformer may reduce power system efficiency and would lead to complete failure of electric network. The major causes of transformer failure are are deterioration of winding insulation resistance, unbalanced loading, single phasing, overloading, less maintenance, and low transformer oil level, etc. As transformers are critical equipment in power transmission and distribution, it is essential to monitor the health of transformer in real time to avoid frequent failure. The monitoring of the energy consumption will help to detect power theft and overloading. Now let's understand the conventional management of a transformer. Currently, the operator periodically visits the transformers for visual inspection, monitoring of key parameters, and performing any maintenance activity. This traditional approach may not provide detailed information about occasional overloads overheating of transformer oil, rise in winding temperature, and local hotspots. These factors may lead to unexpected outages, unavailability of the transformer, and reduction in transformer life. Overloading of the transformer should be detected in the incipient stage to prevent unexpected tripping and outages. The shortcomings of the conventional approach are: absence of real-time transformer health status, increased downtime due to unexpected failures, higher maintenance costs, increased probability of health and safety hazards. All these shortcomings can be addressed using a holistic predictive maintenance approach. TCE has developed a digital point solution for transformer performance monitoring and diagnosis. Let us look at TCE's DigitalPoint solution. This DigitalPoint solution aids the operator in real-time monitoring of overall health scores of transformers, providing alerts and recommending remedial measures for any vital deviation, optimizing maintenance schedules, estimating remaining useful life, Centralized monitoring of various transformers. The Digital Point solution offers many benefits such as reduction in outages, downtime, and maintenance cost, improvement in reliability and availability, reduction in health and safety risk, optimal utilization of resources, ultimately improving plant profitability. Tadic Consulting Engineers, your trusted partner for digital solutions. Stay tuned to this space to know more about our upcoming digital point solutions.
