A system may comprise a device. The device may be configured to receive, from one or more sensor devices of the machine, sensor data associated with wear of one or more components of an undercarriage of the machine; and predict, using a machine learning model and the sensor data, an amount wear of the one or more components based on a wear rate of the one or more components. The machine learning model is trained, using training data, to predict the wear rate of the one or more components. The training data includes two or more of: historical sensor data, historical inspection data, or simulation data, of a simulation model, from one or more third devices. The device may perform an action based on the amount of wear.

Movement data of a plurality of positions on an observation object performing a predetermined movement action is acquired, feature data is generated by performing frequency analysis on the movement data, a transition sequence of a primitive action is extracted by segmenting the feature data, and based on the transition sequence and an action model obtained by learning a transition sequence of a primitive action obtained by segmenting a movement state of a training object performing a movement action, an occurrence rate of the primitive action in the predetermined movement action is analyzed to extract a pattern of the primitive action, thereby predicting an end timing of the predetermined movement action.

A construction machine is provided with a control device having an operating panel with operating elements, which can assume numerous switching states/positions, a control and monitoring unit for controlling machine components via control signals signalling the switching state/position of associated operating elements, and a display/signal unit interacting with the control and monitoring unit. The control device provides first and second signal transmission paths for transmitting a first control signal signalling the switching state/position of a first operating element and a second control signal signalling the switching state/position of a second operating element, respectively. The control signals are checked for the existence of a plausibility criterion. If the plausibility criterion is not met, signal transmission over one or the other signal transmission path is deactivated, wherein the functionality of the relevant component is checked. Switching to emergency operation is only possible after confirmation of the functionality of the relevant component.

In an overturning-risk presentation device according to the present invention, a reception unit is configured to receive posture data of a work machine of a time when the work machine detects an overturning risk. A generation unit is configured to generate an inclination posture image representing a posture of the work machine based on the posture data. An output unit is configured to output the generated inclination posture image.

Disclosed herein are an anti-stall control method and system for a tracked vehicle. The system includes a control module that includes a processor and a storage medium for storing computer programming code. The computer programming code defines a set of behaviour states including: a start state, a tramming state, and at least one corrective state. Each behaviour state has an associated set of behaviour controls for governing control of tracks of the vehicle. The computer programming code, executed on the processor, performs the method steps of: assigning an initial start state, wherein the tracks of the tracked vehicle are stationary; changing to the tramming state, on receipt of instructions to move the tracked vehicle, wherein tramming behaviour controls control the tracks of the tracked vehicle to operate in the same direction; and changing to a corrective states when corrective state conditions associated with that corrective state are satisfied.

A system includes a first industrial machine and a second industrial machine. The system also includes a power distribution system configured to provide power to the first industrial machine and the second industrial machine. The first industrial machine includes a first power control system configured to monitor power usage of the first industrial machine, and transmit power usage information of the first industrial machine to the second industrial machine. The second industrial machine includes a second power control system configured to monitor power usage of the second industrial machine, receive the power usage information from the first industrial machine, and control power usage of the second industrial machine based on the power usage information received from the first industrial machine.

A work vehicle includes an arm. An arm cylinder drives the arm. A direction control valve operates the arm cylinder by allowing supply of a hydraulic oil to the arm cylinder as a spool moves. An oil path is connected to the direction control valve. A pilot oil for moving the spool flows through the oil path. A proportional solenoid valve for arm excavation is provided in the oil path. An arm control member is provided for an operator to operate drive of the arm. An amount of operation of the arm control member is equal to or smaller than a prescribed value in a first operation state and greater than the prescribed value in a second operation state. A command current instructing an opening of the proportional solenoid valve for arm excavation is set to a constant value in the first operation state.

A system for determining a priority of monitoring a machine is provided. The system includes a data acquisition module disposed in communication with a sensor. The data acquisition module is configured to generate data based on at least an operational parameter associated with the machine. The system further includes a server configured to determine a first factor indicative of a rate of usage of the machine, a second factor indicative of a number of exceptions of the machine at corresponding severities, a third factor indicative of a risk of unscheduled downtime of the machine, a fourth factor indicative of a distance from a preventive maintenance of the machine, a fifth factor indicative of an importance of a sub-system of the machine, and the priority of monitoring the machine based on at least the first factor, the second factor, the third factor, the fourth factor and the fifth factor.

A shovel includes a hardware processor configured to collect diagnostic data from a condition detecting sensor and to detect an abnormality based on the collected diagnostic data. The hardware processor is configured to continue to collect the diagnostic data, after detection of the abnormality during collection of the diagnostic data.

Based on operation trajectory data an operation analysis device identifies all open points indicating positions at which the crusher is opened during the operation period and all close points indicating positions at which a crusher is closed during an operation period, calculates, as a shortest distance, a distance between each open point of the all open points and a close point nearest to the each open point, and identifies, as a sorting destination open point, an open point at which the shortest distance exceeds a first threshold value, identifies data until the crusher grasping the dismantling part moves to the sorting destination and returns to the dismantling target again from among the operation trajectory data as movement data of the crusher having moved in the dismantling operation, and identifies data in which the movement data has been removed from the operation trajectory data as grasping operation data.