Provided is a monitoring device capable of easily ascertaining an abnormality. A monitoring device comprises: an acquisition unit which acquires actual operation data (53a) from a control device which controls an actual machine; a storage unit which stores reference operation data indicating reference operation of the actual machine, first related information and second related information; a timing chart generation unit which generates an actual operation timing chart and a reference operation timing chart, and displays the timing charts on a display device; and a simulation data generation unit which generates simulation data of a reference image and a real image.

A controller can switch a control system of a motor to a diagnostic operation mode in addition to a normal operation mode. Abnormality of the motor can be detected by taking advantage of the appearance of a clear difference between a feedback value detected when the motor is normal and a feedback value detected when the motor is abnormal if the control system is switched to the diagnostic mode.

An abnormality determining apparatus for a motor driven mechanism includes circuitry. The circuitry is configured to acquire time-series data with respect to an input to and an output from a motor which drives the motor driven mechanism, detect data abnormality in the time-series data, and determine, based on the data abnormality, whether mechanical abnormality in the motor driven mechanism occurs.

An abnormality detector includes a signal output unit for detecting a sign of an abnormality based on a physical quantity acquired from a manufacturing machine and outputting a signal; and a machine learning device including state observation unit for observing, as a state variable representing a present state of the environment, physical quantity data indicating the physical quantity related to an operation of the manufacturing machine from the manufacturing machine; a label data acquisition unit for acquiring, as label data, operation state data indicating an operation state of the manufacturing machine; a learning unit for learning the operation state of the manufacturing machine with respect to the physical quantity, using the state variable and the label data; and an estimation result output unit for estimating the operation state of the manufacturing machine using a learning result by the learning unit and outputting an estimation result.

An abnormality detection system, support device, and model generation method for generating a more highly accurate abnormality detection model before an actual operation are provided. A model generation part includes a section for generating feature values from state values provided from a state value storage part; a section for calculating importance levels respectively for the generated feature values based on plural methods, wherein the importance levels indicating a degree that is effective for abnormality detection; and a section for integrating the importance levels calculated based on the plural methods for each of the generated feature values and determining rankings of the importance levels of the generated feature values.

A controller can switch a control system of a motor to a diagnostic operation mode in addition to a normal operation mode. Abnormality of the motor can be detected by taking advantage of the appearance of a clear difference between a feedback value detected when the motor is normal and a feedback value detected when the motor is abnormal if the control system is switched to the diagnostic mode.

A numerical controller that detects occurrence of an abnormality according to a neighborhood method includes a sampling value acquisition unit configured to collect sampling values indicative of a state of a machine or environment, wherein the sampling values are collected during normal machining and during operation; a learning unit configured to generate a set of the sampling values during the normal machining; and an abnormality degree determination unit configured to compute an abnormality degree on the basis of a distance between the sampling value during the operation and the set of the sampling values during the normal machining.

A numerical controller having a machine abnormality history analysis support function includes drawing unit for generating a tool image based on CNC information in which operation state information of a machine tool at the time of detection of an abnormality by an abnormality detection unit is associated with information about the detected abnormality, and arranging and drawing the tool image in a coordinate space.

In a monitoring system for mutually monitoring first and second control devices, when the first and second control devices detect an abnormality in a counterpart control device respectively, the first and second control devices output, to a monitoring reset unit, a reset request signal that matches a reference reset request signal for the counterpart control device, and the monitoring reset unit resets the counterpart control device when the reset request signal for the counterpart control device from the first and second control devices matches the reference reset request signal.

Provided is a monitoring device capable of easily ascertaining an abnormality. A monitoring device comprises: an acquisition unit which acquires actual operation data (53a) from a control device which controls an actual machine; a storage unit which stores reference operation data indicating reference operation of the actual machine, first related information and second related information; a timing chart generation unit which generates an actual operation timing chart and a reference operation timing chart, and displays the timing charts on a display device; and a simulation data generation unit which generates simulation data of a reference image and a real image.