Journal bearing monitoring refers to the practice of assessing the condition & performance of journal bearings in rotating machinery, such as engines, turbines, and generators. Journal bearings are crucial components that support rotating shafts and ensure smooth operation by reducing friction and wear. Monitoring journal bearings is essential to prevent potential failures that can cause costly downtime and even catastrophic equipment damage.
Journal bearings are an essential component of many machines, and their failures can result in various negative consequences, including:
Vibration analysis : This technique involves using sensors to measure vibrations generated by the rotating machinery. Any changes in vibration patterns can indicate bearing wear, misalignment, or other issues.
Oil analysis : This method involves taking samples of lubricating oil used in the machinery and analyzing them for various parameters such as metal particles, viscosity, and acidity. Monitoring the lubricating oil can provide information on the presence of wear particles and other contaminants that can damage journal bearings.
Temperature monitoring : Journal bearings can overheat due to excessive friction caused by wear or lack of lubrication. Temperature sensors can detect abnormal heat buildup in the bearings and alert operators to potential issues.
Acoustic Emission Analysis : Acoustic emission analysis involves using sensors to measure the sound waves generated by the bearings during operation. By analyzing the acoustic emissions, maintenance teams can detect changes in the sound patterns that may indicate bearing wear, damage, or other issues.
Nanoprecise offers journal bearing monitoring services by facilitating bearing failure analysis to keep track of industrial assets. Our wireless plug & play sensors capture data on the condition & functionality of the machine's bearings, among other parts. They sense & track the information about the operational characteristics, including acoustic emissions, temperature, speed, vibration, humidity and magnetic flux. The data collected by the wireless industrial IoT sensors are delivered to the analytics platform over Wi-Fi or cellular networks.
The software analyses the bearing health data using AI & physics-based models to create a range-bound baseline for evaluating the equipment performance, and alerts the maintenance teams of any anomalies or impending faults. It then identifies any developing defects and makes recommendations for corrective actions. The real-time analytics dashboard also indicates the component's Remaining Useful Life.
To know more about Nanoprecise’s automated AI-driven Preventive maintenance solutions
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