Weighing scales – Structural installation – Vehicle
Reexamination Certificate
1999-08-04
2003-02-25
Gibson, Randy W. (Department: 2841)
Weighing scales
Structural installation
Vehicle
C177S025190, C701S050000, C702S174000
Reexamination Certificate
active
06525276
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to a crop yield monitoring system and method for use during harvesting of a crop.
BACKGROUND OF THE INVENTION
Load cells, such as strain gage load cells, have been used in development of yield monitors for harvesting grains, forage, potato, and sugar beet. For example, Birrell et al. in “Comparison of sensors and techniques for crop yield mapping”, Computers and Electronics in Agriculture, 14:215-33, 1996, used a catch bin situated in a clean grain tank to provide a comparison to the grain yield indicated by commercial monitors. Wagner and Schrock in “Yield Determination Using Pivoted Auger Flow Sensor”, Transactions of the ASAE, 32(2): 409-13, 1989, replaced an existing clean grain elevator with a triangular auger system to provide a horizontal section of flowing grain. This horizontal section was supported on one end by a pin connection and on the other end by a load cell. The load cell provided instantaneous weight measurements which were used to derive material flow rate.
Rawlins et al. in “Yield Mapping of Potato”, In-Site-specific Management for Agricultural Systems, 59-68, Madison, Wis., ASA-CSSA-SSSA 1995, and Campbell et al. in “Monitoring Methods for Potato Yield Mapping”, ASAE paper #94-1584, St. Joseph, Mich., 1994, developed a system in which a section of a conveyor on a potato harvester was supported by load cells integrated into idler wheel mounts. In this system, instantaneous conveyor section weights and conveyor speed measurements were used to obtain mass flow rate of potato which was referenced to position data simultaneously collected with a global position system receiver. This yield monitor, now commercially available as the HarvestMaster monitor from HarvestMaster, Inc. Logan, Utah, is used for sugar beet and potato yield monitoring.
Yield monitoring of forage was attempted and described by Wild et al. in “Automatic Data Acquistion on Round Balers”, ASAE Paper #94-1582, St. Joseph, Mich. 1994. A round baler was equipped with load cells that monitored the weight of the entire machine as the forage was collected. Preliminary results showed that individual bale weights could be accurately determined under static conditions, but excessive noise severely limited real time yield measurements. The tractor and baler also were instrumented with accelerometers to monitor vibration. Acceleration thresholds were used to screen data for real-time measurement, but the signal noise remained a severe limitation to forage yield monitoring.
Machine vibration is an unfortunate but real characteristic of all harvesting equipment. Rotating shafts and other undulating parts drive the cutting, threshing and transport operations within both self-propelled and tractor-driven combines. Any sensor installed within a combine must be able to endure vibration, and the data acquisition system or subsequent analysis must likewise be able to produce usable data from the sensor output. Strain-gage based sensors are particularly sensitive to vibration.
Spectral analysis provides a useful method for evaluating machine vibrations. These techniques were used by Wagner and Schock in aforementioned “Yield Determination Using Pivoted Auger Flow Sensor”, Transactions of the ASAE, by Pringle et al. in “Yield Variation in Grain Crops”, ASAE paper #93-1505, St. Joseph, Mich. 1993, and by Elliot et al. in “Evaluation of Dynamic Noise Sources in a Real-Time Soil Sensor”, ASAE paper 394-1579, St. Joseph, Mich., 1994, to determine the needed sampling rate and the characteristics of the filters to be used.
Analog filtering techniques to remove vibration and other electrical noise in yield monitoring systems are presented by DeBaerdemaeker et al. in “Monitoring the Grain Flow on Combines”, Agri-Mation 1. ASAE, 329-338, 1985, by Vansichen et al. in “A Measurement Technique for Yield Mapping of Corn Silage”, Journal of Agricultural Engineering Research, 55:1-10, 1993, by Pringle et al, in aforementioned “Yield Variation in Grain Crops”, ASAE paper #93-1505, by Vansichen et al. in “Continuous Wheat Yield Measurement on a Combine”, Automated Agriculture for the 21st Century, ASAE, 346-355 1991, and by Schrock et al. in “Sensing Grain Yield with a Triangular Elevator”, Site-Specific Management for Agriculture Systems, ASA-CSSA-SSSA, 1995.
Digital filtering techniques were used in yield monitoring research by Wagner and Schock in aforementioned “Yield Determination Using Pivoted Auger Flow Sensor”, Transactions of the ASAE, by Vansichen et al. in aforementioned “Continuous Wheat Yield Measurement on a Combine”, Automated Agriculture for the 21st Century, ASAE, by Birrell et al. in aforementioned “Comparison of sensors and techniques for crop yield mapping”, Computers and Electronics in Agriculture, by Pringle in aforementioned “Yield Variation in Grain Crops”, ASAE paper #93-1505, by Vansichen et al. in aforementioned in “A Measurement Technique for Yield Mapping of Corn Silage”, Journal of Agricultural Engineering Research, and by Murphy in “Yield Mapping-A Guide to Improved Techniques and Strategies”, Site-Specific Management for Agricultural Systems, 33-47, ASA-CSSA-SSSA, 1995.
Yield monitoring studies have recognized a problem of delay, or lag, between the moment that the crop enters the combine and the moment that it is sensed. If no compensation technique is used to correct or minimize this problem, the spatial representation of the yield data will be misleading. Lamb et al. report in “Perils of Yield Monitoring on the Go” in Proceedings of the Second International Conference on Site Specific Management for Agricultural Systems, Madison Wis.: ASA-CSSA-SSSA, 1995, that a time lag of 15 seconds with the average harvest speed of 5.1 km/h (3.2 mi/hr) will displace true yield data by as much as 20.1 meters (66 feet). Searcy et al. in “Mapping of Spatially variable Yield During Grain Combining” in Transactions of the ASAE, 32 (3):826-9, 1989, proposed mathematical models to reconstruct the actual yield data from the measured yield data. They used a first order transfer function model and considered the combine as a lumped parameter system. Also see Vansichen and De Baerdemaeker article entitled “A Measurement Technique for Yield Mapping of Corn Silage” in Journal of Agricultural Engineering Research, 55:1-0, 1991. Birrell and Borgelt in “Crop Yield Mapping: Comparison of Yield Monitors and Mapping Techniques” in Site-Specific Management for Agricultural Systems, 15-31, Madison, Wis. ASA-CSSA-SSSA, 1995, experimented with both simple delay and the transfer function model. Their results showed that the transfer function was a better model for describing the “step” input of crop at the beginning of a row; however, the noise amplification involved in inverting the transfer function data from the frequency domain to the time domain reduced the usefulness of this method. Depending on the desired yield resolution (harvested crop per unit area), the added complexity of the transfer function may be counterproductive to the yield monitor design.
Yield monitoring systems have been developed for grain harvesting in order to promote precision farming operations. However, a yield monitoring system for harvesting peanuts is not available today in part due to the functionally different nature of peanut harvesting and peanut combines.
In particular, peanut plants are mechanically dug, the fruit (pods) and vines are shaken free of soil, and the whole plant inverted before being laid back on the soil surface. The peanut plants remain on the surface to cure (dry) to a moisture content suitable for harvest (e.g. less than 12-18%) and pod removal. With the dried peanut plants arranged in windrows, a peanut combine uses a pickup reel to harvest the windrows. The pickup reel feeds the cured plants onto a throat elevator where they are drawn through a series of rotating cylinders and sieves to separate the pods from the vines. The pods fall through the sieve into a collecting hopper where either a mechanical lateral floor auger or a fan moves them across the bot
Durrence Jeffrey S.
Hamrita Takoi K.
Hill Rodney W.
Perry Calvin D.
Thomas Daniel L.
Gibson Randy W.
The University of Georgia Research Foundation Inc.
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