Tractor accelerated test on test rig

The experimental tests performed to validate a tractor prototype before its production, need a substantial financial and time commitment. The tests could be reduced using accelerated tests able to reproduce on the structural part of the tractor, the same damage produced on the tractor during real life in a reduced time. These tests were usually performed reproducing a particular harsh condition a defined number of times, as for example using a bumpy road on track to carry out the test in any weather condition. Using these procedures the loads applied on the tractor structure are different with respect to those obtained during the real use, with the risk to apply loads hard to find in reality. Recently it has been demonstrated how, using the methodologies designed for cars, it is possible to also expedite the structural tests for tractors. In particular, automotive proving grounds were recently successfully used with tractors to perform accelerated structural tests able to reproduce the real use of the machine with an acceleration factor higher than that obtained with the traditional methods. However, the acceleration factor obtained with a tractor on proving grounds is in any case reduced due to the reduced speed of the tractors with respect to cars. In this context, the goal of the paper is to show the development of a methodology to perform an accelerated structural test on a medium power tractor using a 4 post test rig. In particular, several proving ground testing conditions have been performed to measure the loads on the tractor. The loads obtained were then edited to remove the not damaging portion of signals, and finally the loads obtained were reproduced in a 4 post test rig. The methodology proposed could be a valid alternative to the use of a proving ground to reproduce accelerated structural tests on tractors

A Computational Tool for Three-Point Hitch Geometry Optimisation Based on Weight-Transfer Minimisation

The weight-transfer effect, consisting of the change in dynamic load distribution between the front and the rear tractor axles, is one of the most impairing phenomena for the performance, comfort, and safety of agricultural operations. Excessive weight transfer from the front to the rear tractor axle can occur during operation or manoeuvring of implements connected to the tractor through the three-point hitch (TPH). In this respect, an optimal design of the TPH can ensure better dynamic load distribution and ultimately improve operational performance, comfort, and safety. In this study, a computational tool (the Optimiser) for the determination of a TPH geometry which minimises the weight-transfer effect is developed. The Optimiser is based on a constrained minimisation algorithm. The objective function to be minimized is related to the tractor front-to-rear axle load transfer during a simulated reference manoeuvre performed with a reference implement on a reference soil. Simulations are based on a dynamic model of the tractor-TPH-implement aggregate. The geometry determined by the Optimiser complies with the ISO-730 Standard functional requirements and other design requirements. The interaction between the soil and the implement during the simulated reference manoeuvre was successfully validated against experimental data. The simulation results show that the adopted reference manoeuvre is effective in triggering the weight-transfer effect, with the front axle load exhibiting a peak-to-peak value of 27.1 kN during the manoeuvre. A benchmark test was conducted starting from the geometry of a commercially available TPH; the test showed that the Optimiser, after 36 iterations, was able to find an optimised TPH geometry which allows to reduce the weight-transfer effect by 14.9%

Monitoring of the tractor working parameters from the Can-Bus.

The analysis of the tractor mission profile is one of the main objectives for tractor manufacturers. The mission profile has usually been estimated through the use of questionnaires submitted to consumers. This procedure is time-consuming and not totally reliable due to the trustworthiness in the questionnaire compilation. In all the high power tractors numerous transducers are fitted to monitor some parameters to optimise the operation of the machines. All of these transducers are connected to an electronic central unit or with the tractor CAN-Bus. In this context, a system able to monitor the working parameters of the machines capitalising the existing transducers could represent the optimal solution for monitoring tractors distributed in different regions. The high number of signals are in any case difficult to memorise without a high quantity of memory. The goal of the paper is to define a methodology to memorise the operation parameters useful to define the mission profile of a tractor using a small memory. A tractor of a nominal power of 230 kW was selected and a system able to measure the signals acquired by the transducers fitted on the tractor was connected to the CAN Bus of the tractor. After a detailed analysis of the parameters measured on the tractor, the useful parameters were defined and acquired in different working conditions. The analysis of the parameters stored in the memory has allowed a detailed analysis of the operational parameters of the tractor in different applications. These parameters could be used by engineers to design tractors with a higher quality and reliability and also to define predictive maintenance criteria and reduce unexpected tractor failures

User Driven Model Adjustment via Boolean Rule Explanations

AI solutions are heavily dependant on the quality and accuracy of the input training data, however the training data may not always fully reflect the most up-to-date policy landscape or may be missing business logic. The advances in explainability have opened the possibility of allowing users to interact with interpretable explanations of ML predictions in order to inject modifications or constraints that more accurately reflect current realities of the system. In this paper, we present a solution which leverages the predictive power of ML models while allowing the user to specify modifications to decision boundaries. Our interactive overlay approach achieves this goal without requiring model retraining, making it appropriate for systems that need to apply instant changes to their decision making. We demonstrate that user feedback rules can be layered with the ML predictions to provide immediate changes which in turn supports learning with less data

Outlining the mission profile of agricultural tractors through CAN-BUS data analytics

Tractor manufacturers need to know how farmers use their agricultural tractors for an optimal machine design. Tractor usage is not easy to assess due to the large variability of field operations. However, modern tractors embed sensors integrated into the CAN-BUS network and their data is accessible through the ISO 11,783 protocol. Even though this technology has been available for a long time, the use of CAN-BUS data for outlining the tractor usage is still limited, because a proper post-processing method is lacking. This study aimed to present a novel classification scheme of CAN-BUS data which permits to outline the tractor usage. On a tractor, a CAN-BUS data logger and a GNSS receiver were installed, and real-world data were recorded for 579 h. Thus, data was obtained in the most realistic condition. Tractor positions were classified using GIS layers while operating conditions were classified depending on the usage of the tractor's subsystems. The method highlights that showed to be able to detect the 97% of the logged data and that the tractor operated on the field in working, on idle, and moving duties for 65%, 18% and 16% of the time, respectively. The method allows a far more precise outline of tractor usage opening opportunities to obtain large benefits from massively collected CAN-BUS data

Tractor accelerated test on test rig.

The experimental tests performed to validate a tractor prototype before its production, need a substantial financial and time commitment. The tests could be reduced using accelerated tests able to reproduce on the structural part of the tractor, the same damage produced on the tractor during real life in a reduced time. These tests were usually performed reproducing a particular harsh condition a defined number of times, as for example using a bumpy road on track to carry out the test in any weather condition. Using these procedures the loads applied on the tractor structure are different with respect to those obtained during the real use, with the risk to apply loads hard to find in reality. Recently it has been demonstrated how, using the methodologies designed for cars, it is possible to also expedite the structural tests for tractors. In particular, automotive proving grounds were recently successfully used with tractors to perform accelerated structural tests able to reproduce the real use of the machine with an acceleration factor higher than that obtained with the traditional methods. However, the acceleration factor obtained with a tractor on proving grounds is in any case reduced due to the reduced speed of the tractors with respect to cars. In this context, the goal of the paper is to show the development of a methodology to perform an accelerated structural test on a medium power tractor using a 4 post test rig. In particular, several proving ground testing conditions have been performed to measure the loads on the tractor. The loads obtained were then edited to remove the not damaging portion of signals, and finally the loads obtained were reproduced in a 4 post test rig. The methodology proposed could be a valid alternative to the use of a proving ground to reproduce accelerated structural tests on tractors