Q3 provided an IoT based transformer monitoring system for checking health parameters in real-time and alert the concerned people through e-mail/SMS.
The client is one of the biggest Indian conglomerate with businesses across India engaged in healthcare, petrochemicals, textiles, retail, and energy and telecommunications sector.
For energy and power companies’ transformers are one of the most important equipment distributed over a wide area in a power electric system. Transformers have a long life if they are monitored and are going through maintenance cycles at frequent intervals. Most of the maintenance part is done manually, capturing all the important parameters in intervals and maintenance person gets to know the machine health only when it stops performing/working.
The client wanted a solution where they can have predictive maintenance of the machines and monitor them with real-time data for any issues. The client was using manual method of monitoring where the maintenance person was visiting at scheduled interval and checking the voltage, current, oil level, oil temperature of the transformers. There were failure scenarios between the visits, where the client had no visibility about the machine’s performance. They wanted a real-time monitoring system to check all these health parameters and decrease the response time during a failure event.
Q3 provided an IoT based transformer monitoring system for checking health parameters in real-time and alert the concerned people through e-mail/SMS. Microprocessors and embedded module at the transformer site were used for capturing different parameters of temperature, oil level, current etc. These sensor values were transmitted to the IoT cloud platform through a WiFi network.
Providing end-to-end solution, Q3 provided the client with integration and registration of all the sensors on IoT cloud platform and a web application with specific user group access, dashboard, and notification/alert dashboards. MQTT protocol & Adafruit library was used for communication between sensors and IoT Cloud platform.
Q3 developed system of monitoring data in real-time and alert users to take quick action. Analytics dashboard showing historical data, real-time data and time-bound data presented users an overall view of the transformer location, health of transformer machines and any discrepancies. Predictive analytics based on historical data to help with predictive maintenance and increase in machine life.