Save 60% on maintenance costs – with predictive maintenance

Radar sensor solution for real-time wear control in the energy sector

 

Our IoT radar sensor solution monitors the wear of critical machine parts in combined heat and power plants in real time. Special algorithms enable an implementation of predictive maintenance. This reduces maintenance costs by up to 60 percent, reduces downtime and thus increases the productivity of the plant.

Combined heat and power plant (CHP). ©rostovdriver – Adobe Stock

The challenge

Time-consuming maintenance, long downtime

Combined heat and power plants (CHP) produce electricity and heat via cogeneration – for example in biogas plants or sewage treatment plants. Among other methods of production, large gasoline engines are used for energy generation in the CHP plants. These gas-powered internal combustion engines must be checked for wear in regular, complex maintenance cycles. If critical engine components fail, there is a risk of total damage to the internal combustion engine with lengthy repair costs in the six-digit range. In addition, energy production has to be suspended for several days or, in the worst case, weeks. Therefore, these components must be checked regularly for wear. Every three months, a maintenance specialist needs to come to the plant, open and inspect the internal combustion engine. This means around 4 to 8 days of annual downtime. The result is higher operating costs and lower income.

The solution

Reduced operating costs with real-time monitoring

OndoSense radar sensors can now check the CHP engines for wear in real time to reduce downtime. For this purpose, pencil-sized measuring heads of the OndoSense proxi radar sensor are installed in the motor and connected with one another. The sensor system measures the wear of critical components in very close range and during operation. The algorithms of the OndoNet sensor software can now monitor the condition of the motor components and the status of the system in real time. This enables a predictive planning of the maintenance cycles so that the operator only carries out maintenance when it is really necessary. The result of the predictive maintenance solution: maintenance costs are reduced by up to 60 percent and downtime as well as operating costs are reduced. At the same time, the plant's energy production increases significantly.

Predictive maintenance in the energy industry. ©Nicolas Herrbach – Adobe Stock
OndoSense radar sensor solutions

Products & solutions

OndoSense proxi – higly precise radar sensor for very close range

OndoNet software – cloud-based sensor control and networking, radar algorithms for predictive maintenance

Industry range

Energy industry (combined heat and power plants)

Agriculture (biogas plants)

Water management (CHPs in sewage plants) etc.

Your inquiry on our solution

Tell us about your application. Let us know how we may help you.

Are you interested in implementing our solution in your company? Do you have any questions about the application or our products? We will provide you with answers, advise you on the use of OndoSense radar sensors and work out a solution for your individual challenge together with you.