The present invention belongs to the field of automation equipment predictive maintenance, and relates to a method for diagnosing health of a CNC machine tool. Parameters such as vibration and temperature are detected by Zigbee nodes adopted in the present invention and uploaded to a Zigbee gateway. The detected data is transmitted by the Zigbee gateway to a cloud server for digital signal processing, data mining and analysis processing. After a training test of the above data is carried out by the cloud server, a health degree model is obtained. The health degree model is transmitted by the cloud server to the Zigbee gateway. A clock circuit can be used for synchronizing system time and recording time as data is recorded. For the on-line predictive maintenance of a CNC machine tool, the most rapid and accurate predictive maintenance information is provided.

Provided is a tool state detection system capable of improving usability. A tool state detection system that detects a state of a tool attached to a machining device includes: a detection device which is formed separately from a tool holder that holds the tool and is detachably attached to the tool holder, the detection device being configured to detect the state of the tool and output measurement data; and a data analysis device which provided to be communicable with the detection device, the data analysis device being configured to analyze the measurement data from the detection device. As a result, usability for a user is improved since the detection device can be formed separately from the tool holder and be detachably attached to the tool holder.

The invention provides a machining system (201) comprising: a machining apparatus (202), notably an abrasive waterjet cutting system (203), said machining apparatus being adapted for machining a workpiece (204); a monitoring device (228) adapted for monitoring machining conditions of the machining apparatus (202) and/or of the workpiece, the monitoring device comprising a plurality of sensors, said plurality of sensors comprising a first sensor (237) at a first location and a second sensor (239) at a second location which is distant from the first location. The plurality of sensors comprises a fourth sensor (243) which is formed by an array of microphones (254) arranged on a grid. The plurality of sensors comprises accelerometers, strain gauges and microphones. The invention also provides a monitoring method of a machining system (201) wherein a specific benchmark signature is chosen from a library.

A method and system of a predictive maintenance IoT system comprises receiving a plurality of sensor data over a communications network and determining one or more clusters from the sensor data based on a pre-determined rule set. Further, the sensor data is classified through a machine learning engine and the sensor data is further base-lined through a combination of database architecture, data training architecture, and a base-lining algorithm. Intensity or degree of fault state is mapped to a fuel gauge to be depicted on a user interface and a predictive maintenance state is predicted through a regression model and appropriate alarm is raised for user action.

A method and a system for estimating state of wear of a cutting tool mounted on a machine tool. The system includes an acquisition module configured to acquire at least one operating signal specific to the cutting tool during at least one interaction of introduction or of extraction between the cutting tool and the material to be machined, and a microprocessor configured to generate from the at least one operating signal a wear signature of the cutting tool and to determine the state of wear of the cutting tool as a function of the signature.

An intelligent tungsten carbide cutter may include a shank, at least a cutting portion, and a sensor. The shank made of tungsten steel comprises a first end, a second end, and at least a first connecting portion, and the first connecting portion is located adjacent to the second end of the shank. The shank and the cutting portion are thermally connected through high frequency oscillation heating method, and the cutting portion is secured on the first connecting portion of the shank. An accommodating channel axially penetrates through a center portion of the first end of the shank and extends toward the second end, and the sensor is installed in the accommodating channel so as to be positioned close to the cutting portion, thereby achieving the direct and accurate sensing.

Tool bodies, tools and machines for operating the tool include electronic circuits for providing data, collecting data, analyzing data and for controlling machines based on such data. Tool bodies and tools may include electronic circuits having data collecting sensors, which may be embedded in a housing with the electronic circuit and/or positioned outside of such a housing. Sensors include temperature sensors, motion sensors, strain sensors, moisture sensors, electrical resistance sensors, position sensors, antennas, and other components.

A method for automated condition monitoring whereby techniques of automated vibration analysis and signal processing are combined with deep learning/machine learning techniques for an enhanced system of automated anomaly detection, problem classification, and problem regression. The method may be implemented in software, firmware or hardware to run autonomously. Machines monitored and analyzed according to the disclosed method are typically found in industrial plants or commercial applications, but the disclosed invention may be applied to any rotating equipment such as motors, fans, pumps, compressors, and etc., in any environment where they are functioning.

A tool-mounting-state estimation system includes: a measuring tool including a body section having a tapered external surface common with a tapered external surface of a tool and a vibrating source that is mounted on the body section and that generates vibration; a sensor that is provided on a spindle for drawing the measuring tool thereinto so that the tapered external surface of the measuring tool comes into close contact with a tapered internal surface of the spindle and that detects the vibration generated by the vibrating source when the vibration propagates towards the spindle via the tapered external surface and the tapered internal surface; and an estimation unit for estimating a mounting state of the tool on the basis of the vibration detected by sensor.

A motor control device includes an acceleration detecting section configured to detect an acceleration of a control object, and an acceleration control section configured to control an acceleration of a motor driving the control object based on the detected acceleration, in which the acceleration control section includes a vibration component extraction filter configured to extract a vibration component generated between the motor and the control object, and the vibration component extraction filter changes a filter characteristic frequency according to at least one of a position and a mass of the control object.