Sensor-Integrated Clutches as a Data Source in the Powertrain

In highly dynamic mixing processes, torque often fluctuates between moderate continuous loads and extreme load peaks. A sensor-integrated coupling measures these loads directly in the power train in near real time, laying the foundation for data-driven design, condition monitoring, and predictive maintenance.

Industrial mixers are among the most mechanically demanding units in process plants. Highly dynamic mixing processes, in particular, require precise knowledge of the actual loads that occur. In practice, however, the actual torque in the drive train is often known only approximately. Design is based on empirical values, safety factors, or theoretical assumptions. How the torque actually evolves over time during the running process - especially during dynamic transition phases - often remains unclear.

Particularly when mixing a liquid medium with solids, the viscosity of the overall medium changes continuously. This rheological transition leads to a highly variable torque curve in the drive train. At the start of the mixing process, the resistance is usually moderate. As homogenization progresses, internal friction increases significantly. The mixing tool must transmit higher shear forces, causing the torque to rise significantly. In comparable applications, short-term peaks in the range of approximately 16,000 Nm can occur. Once the desired degree of homogeneity is achieved, the load decreases significantly again and typically stabilizes at a steady-state level of around 4,000 Nm.

This distinct load profile, featuring a temporary high-load phase, illustrates the highly dynamic nature of the process. Therefore, when designing a mixer drive train, it is not only the maximum value that is decisive, but above all its temporal progression and the ratio between peak loads and continuous load.

The Clutch as a Measurement Point in the Force Flow

Reliably capturing these dynamic load conditions poses a major challenge in practice. External torque sensors require additional installation space, necessitate design modifications, and increase system complexity. Furthermore, measurements taken outside the immediate force path can be distorted by additional influences.

The sensor-integrated iPK coupling developed by R+W Antriebselemente, in the flange version of the 15000 series, addresses this issue directly. It is positioned within the torque-transmitting train and measures the mechanical stress exactly where it actually occurs. The technological basis is an integrated deformation body that is inserted into a hollow cylindrical component using a press-fit process. The elastic deformations that occur under load are detected using high-precision strain gauges and subsequently processed by the integrated measurement amplifier and transmitted wirelessly in near real time. Power is supplied via a rechargeable battery or inductively, eliminating the need for external cabling. Depending on the model, in addition to torque, rotational speed and temperature can also be measured. The coupling thus functions as a compact, fully integrated sensor unit within the drivetrain.

Data-Driven Design and Development Validation

Continuous recording of the torque curve enables a realistic assessment of the entire mixing cycle. Short-term high-load phases can be analyzed in terms of their duration and frequency and clearly distinguished from the subsequent nominal operation. This provides significant added value for the design process. Service life calculations are based on actual load profiles rather than general assumptions. Safety margins can be defined in a targeted and data-driven manner. This reduces oversizing while simultaneously increasing operational safety.

The iPK also supports the validation of simulation models during the development of new mixing systems. Theoretical assumptions regarding viscosity profiles, mold geometries, or process parameters are compared with real operating data. Deviations are detected early on, allowing for the systematic identification of optimization potential.

Sensor Technology as the Basis for Condition Monitoring and Predictive Maintenance

During operation, the iPK continuously provides status data, thereby serving as the interface between mechanical drive technology and digital monitoring. The characteristic load curve of a mixing cycle serves as a reference. Changes in the torque rise, the intensity of high-load phases, or within the normal operating range may indicate process deviations. Fluctuations in material quality, increasing tool wear, or incipient damage to bearing and gear components are immediately reflected in the load behavior. Continuous data acquisition allows such developments to be identified at an early stage.

Beyond mere condition monitoring, sensor technology forms the basis for predictive maintenance concepts. While traditional maintenance strategies are based on fixed intervals, the analysis of real load profiles enables a condition-based assessment of actual stress levels. The systematic evaluation of load patterns supports a reliable estimation of remaining service life and allows for needs-based planning of maintenance measures. In conjunction with higher-level monitoring or analysis systems, trend analyses and threshold strategies can be implemented. Downtime is reduced, maintenance tasks become predictable, and overall plant effectiveness is sustainably increased.

Modular flange design for high torques

The 15000 Series is designed for high torque ranges and is particularly suitable for large-scale industrial mixers with shaft and/or flange connections. Within the R+W modular system, the sensor unit can be flexibly combined with various coupling types. The modular concept supports application-specific adaptation without requiring additional installation space and facilitates integration into existing drive systems.

In highly dynamic mixing processes, where peak and continuous loads differ significantly, the integrated sensor technology provides transparency regarding actual load conditions. The continuous availability of this data opens up new possibilities in design, operation, and maintenance. Mechanical components are no longer dimensioned exclusively based on specifications but are evaluated and optimized using data. As a result, the coupling is evolving into a strategic element of modern, networked drive systems.