Development of an Intelligent Tool to allow real-time evaluation of harvesting practices as part of a framework for improved harvester payment systems : Final report 2016/951
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The project has resulted in the development of a cane loss indicator which can be a valuable tool to assist the harvester operator to optimise harvester performance as crop conditions change throughout the day. The system differs from previous attempts at cane loss monitors in that it does not attempt to identify individual billet loss, but rather looks at the energy dissipated in the processes of extracting cane and leaf and the effective dissociation of the billets as they are processed by the harvester extractor fans. The relationship between power consumption and actual cane loss utilises both keyboard inputs and parameters measured on the harvester. Data collection for the development of the algorithms and their calibration was undertaken in conjunction with field trials, where conventional cane loss measurement protocols were used to give the base data. Initially manual data collection strategies were utilised, followed by high accuracy data logging. The relationships observed between derived cane loss and measured cane loss in these trials allowed fine tuning of the algorithms, including the “weighting” of different measured inputs. Analysis of all datasets of electronically logged data indicates the repeatability of the cane loss values derived by SCHLOT under typical harvesting conditions to be high and, where variance was observed between the SCHLOT estimate and the field testing protocols, the SCHLOT number could be argued to give the more accurate determination of actual cane loss. In operation, the SCHLOT cane loss monitor gives highly useful feedback to the operator, and this drove significant changes in operating strategies by the harvester operator. The ability to remotely log cane loss in conjunction with other parameters such as harvester speed in near real time offers very significant benefits for the Industry with respect to the implementation of Best Practice Harvesting.