Hydraulic design method, device and equipment for mobile drip irrigation system are provided. Different distances between drip-lines, a depth of a bottom boundary, a flux of infiltration boundary and soil hydraulic parameters are input into a simulation model, and output parameters of the model including a soil water content at each observation point and an amount of deep percolation loss under the different distances at the same irrigation depth are acquired. An optimal distance between drip-lines is obtained according to an installation cost function, the soil water content at each observation point and the amount of deep percolation loss, and lengths of drip-lines matched with the optimal distance are obtained. Structural parameters of the irrigation system and a designed irrigation depth are obtained to determine working parameters. The irrigation system with the optimal distance and the matched lengths of drip-lines is controlled to irrigate crops based on the working parameters.

An irrigation system having a pipeline supported by one or more towers includes an improved truss connection system having a means for readily adjusting a crown height of the pipeline. A pair of cooperating members define a joint which selectively couples headed ends of adjacent truss rods together to form a truss rail of a truss system that supports the pipeline. A single fastener may fasten the cooperating members, a strut, and a cross-member together at the joint. A length of the truss rail may be decreased by holding the truss rods closer together. In an aspect, the headed ends of the adjacent truss rods are held closer together by inserting a shim in one of the joints. Decreasing the length of the truss rail increases the deflection of the pipeline and raises the crown height.

The present invention provides a system and method which includes a machine learning module which analyzes data collected from one or more sources such as UAVs, satellites, span mounted crop sensors, direct soil sensors and climate sensors. According to a further preferred embodiment, the machine learning module preferably creates sets of field objects from within a given field and uses the received data to create a predictive model for each defined field object based on detected characteristics from each field object within the field.

A direct pivot smart tower box communication system is disclosed. The direct pivot smart tower box communication system includes a plurality of wheel sensor modules, a plurality of tower box modules, and a pivot center module. The plurality of wheel sensor modules are coupled to respective wheel hubs of respective towers of a direct pivot irrigation system. The plurality of tower box modules are coupled to the respective towers of the direct pivot irrigation system, wherein a tower box module includes a tower box module controller and is in communication with a wheel sensor module at a same tower as the tower box module. The pivot center module is coupled to the pivot center, wherein the pivot center module includes a pivot center module controller and is in communication with the plurality of tower box modules.

The present invention provides a system and method for analyzing drive tower current and voltage levels to determine drive wheel status. In accordance with a first preferred embodiment, the system of the present invention includes a machine analysis module which analyzes data from electrical sensing systems, GPS sensors, and gyroscopic sensors. According to a further preferred embodiment, the machine analysis module applies a current/voltage sensing algorithm which analyzes the status of the first and second drive wheels based on detected operating currents/voltages of selected motors.

The present invention teaches an irrigation motor and gearset which include an enveloping worm drive gearbox for use with a mechanized irrigation machine. According to a preferred embodiment, the system of the present invention may include a gearbox which includes a worm drive and a reduction assembly. According to a preferred embodiment, the worm drive preferably includes a worm shaft, a worm, a first gear wheel, and a first wheel shaft. Preferably, the worm shaft and the first wheel shaft are oriented orthogonally to each other. According to a further preferred embodiment, the worm drive of the present invention is preferably a double enveloping worm drive with the worm and the first gear wheel each being throated, mated and fully enveloped gears.

A system and method for calibrating an irrigation system to account for variations in flow rates, motor operating parameters, and other parameters caused by field elevation changes, pipe friction losses, water emitter nozzle wear, pressure-regulator inaccuracies, and other factors. A calibration map is created to account for the flow rate variations or other parameters and then consulted to control operation of the irrigation system.

Systems, methods and apparatuses for irrigating soils and crops are described. The irrigation system may include a center pivot irrigation system and at least one irrigation apparatus. The irrigation apparatus may include at least one side frame, at least one back frame, at least one boom assembly, at least one means for enabling the apparatus to move, and at least one means for configuring the apparatus to the center pivot irrigation system. The disclosure may reduce and/or eliminate rut formation.

Some embodiments of a gearbox for an irrigation system can comprise a housing, a worm gear within the housing, a bull gear within the housing and configured to be engaged with the worm gear, a diaphragm, and a vent. The diaphragm can define a chamber configured for expansion and contraction and configured to be positioned inside the housing to relieve pressure build-up within the housing. The vent can be configured to allow air to flow between the atmosphere and the chamber.

The present invention provides an irrigation system that includes a control system for determining whether to apply an applicant to an agricultural field. In an implementation, the control system includes memory operable to store one or more modules and a processor coupled to the memory. The processor is operable to execute the one or more modules to cause the processor to receive one or more signals representing a microbe characteristic from a soil sensor. The processor is also operable to determine whether to apply an applicant (i.e., water having a concentration of a biological or a microbe therein) to a soil based upon the microbe characteristics and to initiate operation of the irrigation assembly to apply the applicant to the soil in response when the soil requires the applicant.