Real-Time Acoustic Monitoring of Cutting Blade Sharpness in Agricultural Machinery

Cutting processes are among the most important crushing procedures in harvesting technology. Common practice attempts to identify the time for regrinding crop cutting blades do not often lead to the desired results. Continuous monitoring of the cutter bars in harvesting machines could provide the optimal regrinding time to maintain cutting performance and to achieve preferably long maintenance intervals. In this study, a method for real-time acoustic monitoring of the sharpness of crop cutting blades is shown based on an analytical simulation, acoustic measurements, and statistical analysis. These measurements were performed with piezoelectric accelerometers and signals were recorded at a sampling rate of 51 kHz. Structure-borne sound was measured on the counter blade, knife drum, and cabin of a self-propelled field chopper during harvesting. A good interrelation was found between the condition of the blades and the structure-borne sound. The statistical classification analysis with the support vector machine method allows an attribution of the blade sharpness (described by means of executed grinding cycles) with an accuracy of 0.76. Further development steps and the optimization potential of the design of system components are also discussed.