SKF seeks innovative solutions for detecting and classifying electrical currents in bearings to enable the offering of effective solutions to mitigate problems related to electric erosion for specific customers.
Opportunity overview
Electric drive systems consume 70% of the overall energy used in industrial applications. Bearings are critical components in electric motors across industries, including industrial motors, EVs, aerospace, and wind turbines. Advancements in motor technology, including higher voltages and fast-switching electronics have led to increasing issues with electric erosion in bearings.
Erosion caused by EDM (Electrical Discharge Machining) and high-frequency circulating currents is the leading cause of damage for bearings deployed in electric motors, resulting in significant negative impacts for overall motor performance and longevity. These types of currents lead to increased noise, vibration, and temperature, ultimately resulting in motor failure. While the currents are different and require different solutions to mitigate the risks caused by them, current diagnostic tools lack the capability to effectively assess whether a current is EDM or circulating current. Traditional solutions like filters can delay but do not eliminate damage, failing to solve the underlying issue.
To address this, SKF seeks innovative solutions for detecting and classifying electrical currents in bearings to enable the offering of effective mitigation solutions for specific customers. Developing sensors capable of accurate bearing discharge detection and classification can enable SKF to support OEMs with early risk identification, customized solutions, and continuous monitoring for maintenance optimization. This could reduce unplanned downtime, improve motor efficiency, and strengthen SKF’s value proposition as a partner in motor system performance.
Summary of the requested solution
The ideal solution involves sensors that can continuously monitor and detect electrical discharges inside the bearings, in various environments. While primarily being able to detect and measure discharge intensity and frequency (few KHz to MHz), the solution could also ideally specify the location of the discharge on the bearing raceway to help assess the risk of failure. The sensors should operate reliably in high temperatures (up to 150°C) while they may have to deal with oil or grease contamination, vibration, and humidity depending on the application or mounting location. The solution should be compact and compatible with bearings of varying sizes, ranging from diameters of 20 mm to several meters, as well as adaptable to different motor technologies (e.g., PMSM, induction). Optionally, some additional features such as voltage and temperature monitoring could be integrated to support further diagnostics. Depending on the technology, the sensors should be suitable for mounting directly on bearings or positioned in proximity to them. While we are open to different alternatives to solve the challenge, the solution should most importantly be able to detect and distinguish between different types of electrical discharges occurring inside the bearings.
Your opportunity with SKF
SKF is the world’s leading bearing manufacturer, with 17,000 distributors in 130 countries. Collaborating with SKF on the topic of bearing monitoring offers an opportunity to contribute to making industries reduce downtime, improving equipment longevity and making industrial operations more resource efficient. We want to work together and provide you with valuable learnings that enable your company further opportunities within the industry.
Examples we're looking for
Electrical current sensors
Sensors capable of continuous monitoring of electrical discharges in bearings will lay the foundation for comprehensive predictive maintenance and improved customer support. These sensors should be able to detect discharge signals and measure the intensity of the discharge occurring inside the bearings. Solutions that integrate easily with the existing infrastructure and offer real-time insights are preferred.
Condition monitoring software
Advanced software leveraging AI to analyze machine data for early identification of potential failures. The solution should support multi-sensor data integration and provide comprehensive intelligence such as discharge classification, voltage, current measurement (HFCC) and ideally even temperature and location of the discharge. All this should be continuous and integrable with SKFs models & internal infrastructure.
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