Abstract: The present invention improves accuracy in machine learning and reduce running costs by updating to a new learning model generated by selecting data, etc. The data collector collects data to perform machine learning. The data storage stores the collected data. The data selector selects data for updating existing learning models used for machine learning from the data stored in the data storage. The learning model generator generates a new learning model by machine learning based on the selected data, and the updater updates at least the existing learning model to the new learning model generated in the learning model generator.

Abstract: A fluid leakage detection system has a detection space to which working oil leaked out through a rod seal is guided; the rod seal being configured to seal an annular gap between a piston rod and a cylinder head; a sensor unit configured to detect pressure in the detection space; and a controller configured to acquire detected result from the sensor unit, wherein the controller has: a calculation unit configured to calculate a pressure parameter representing a pressure fluctuation in the detection space; a determination unit configured to determine occurrence of leakage of the working oil based on the pressure parameter; and the pressure parameter includes an upper limit value and a lower limit value of the pressure fluctuation obtained from the detected result detected by the sensor unit within a predetermined detection period.

Abstract: A fluid leakage detection system includes: a measurement unit configured to detect leakage of working oil in a hydraulic cylinder; and a controller configured to acquire a measurement result from the measurement unit, wherein the controller diagnoses that a battery depletion has been caused in a battery in a case in which it is determined that a data from the measurement unit has not been acquired and it is determined that the battery of the measurement unit has been in a low-remaining-battery-level state, and the controller diagnoses that a communication abnormality has been caused in a first communication part of the measurement unit in a case in which it is determined that the data from the measurement unit has not been acquired and it is determined that the battery has not been in the low-remaining-battery-level state.

Abstract: A fluid leakage detection system has a detection space to which working oil leaked out through a rod seal is guided; the rod seal being configured to seal an annular gap between a piston rod and a cylinder head; a sensor unit configured to detect pressure in the detection space; and a controller configured to acquire detected result from the sensor unit, wherein the controller has: a calculation unit configured to calculate a pressure parameter representing a pressure fluctuation in the detection space; a determination unit configured to determine occurrence of leakage of the working oil based on the pressure parameter; and the pressure parameter includes an upper limit value and a lower limit value of the pressure fluctuation obtained from the detected result detected by the sensor unit within a predetermined detection period.

Abstract: A fluid leakage detection system includes: a measurement unit configured to detect leakage of working oil in a hydraulic cylinder; and a controller configured to acquire a measurement result from the measurement unit, wherein the controller diagnoses that a battery depletion has been caused in a battery in a case in which it is determined that a data from the measurement unit has not been acquired and it is determined that the battery of the measurement unit has been in a low-remaining-battery-level state, and the controller diagnoses that a communication abnormality has been caused in a first communication part of the measurement unit in a case in which it is determined that the data from the measurement unit has not been acquired and it is determined that the battery has not been in the low-remaining-battery-level state.

Abstract: In this road surface displacement detection device, for each frame of an image obtained by a stereo camera that images a road surface in a movement direction of an object such as a vehicle, for example, an arithmetic processing circuit detects heights of the road surface at a plurality of points for detection at different distances from the stereo camera, and superimposes information about the heights at the plurality of points for detection, which are detected for a plurality of frames, on each other while considering a movement distance of the object between the plurality of frames.