Granted Patent B2

US 12,481,265 · App. 18/961,676 · Granted Nov 25, 2025

Inventor: Hanshu Shao (Chengdu, CN)

Assignee: CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD.

G05B19/406G05B2219/33099

Abstract

Claims (80)

1 . A method for intelligent monitoring of a computerized numerical control (CNC) machine tool based on Industrial Internet of Things (IIoT), wherein the CNC machine tool refers to a tool employed by a CNC machine, and the method is performed by an IIoT management platform of a system for intelligent monitoring of the CNC machine tool based on the IIoT;

the IIoT management platform is configured in a processor and communicates with a sensing control platform via a sensor network platform;

the sensor network platform is configured on a communication device;

the sensing control platform is configured in a host computer of the CNC machine and configured to control an operation of a camera and an operation of a machine monitoring device;

the method comprises:

obtaining appearance information of the CNC machine tool based on a tool image, and storing the appearance information in a data center of the IIoT management platform, the tool image being acquired by the camera at a preset acquisition time, the preset acquisition time including a time when the CNC machine tool is in a stop state;

in response to the CNC machine tool being in an operational state, obtaining operational state information of the CNC machine tool and the CNC machine based on the machine monitoring device, and sending the operational state information to the data center of the IIoT management platform via the communication device, wherein the obtaining operational state information of the CNC machine tool and the CNC machine includes:

collecting cutting fluid change information via the camera and a first monitoring component configured in a cutting fluid storage tank; and

collecting a cutting force data sequence of the CNC machine tool via a second monitoring component;

issuing an image acquisition instruction to the sensing control platform to control the camera to acquire a workpiece image of a workpiece at a preset frequency, and determining workpiece information based on the workpiece image;

processing the workpiece information to generate machining quality information, and storing the machining quality information in the data center of the IIoT management platform;

retrieving the appearance information, the operational state information, and the machining quality information from the data center, and generating tool wear information, including:

evaluating a degree of wear of the CNC machine tool during at least one time period based on the appearance information, the operational state information, and the machining quality information, the operational state information including at least one of the cutting fluid change information and the cutting force data sequence; and

generating the tool wear information based on the degree of wear of the CNC machine tool during the at least one time period;

issuing, based on the tool wear information, an alert via at least one of a machine warning device and an interactive screen to indicate a wear condition of the CNC machine tool;

determining the CNC machine will be replaced based on the tool wear information, and controlling a tool replacement assembly to clip a spare tool from a spare tool box;

issuing a rotational speed adjustment instruction and a frequency adjustment instruction based on the tool wear information;

controlling, using the issued rotational speed adjustment instruction, a rotational speed of a tool holder group that adjusts a machining intensity of the CNC machine tool that will be replaced; and

adjusting, using the issued frequency adjustment instruction, an acquisition frequency of the camera.

2 . The method of claim 1 , wherein the processing of the workpiece information to generate machining quality information includes:

retrieving a tool trajectory corresponding to the workpiece information; and

generating the machining quality information based on workpiece material information, the tool trajectory, and the workpiece information.

3 . The method of claim 1 , wherein the determining the CNC machine tool will be replaced based on the tool wear information includes:

determining a remaining life sequence of the CNC machine tool based on historical machining data and the tool wear information of the CNC machine tool;

determining a replacement priority of the CNC machine tool based on the remaining life sequence; and

determining the CNC machine tool will be replaced based on the replacement priority.

4 . The method of claim 3 , wherein the remaining life sequence of the CNC machine tool is correlated with the degree of wear of the CNC machine tool during the at least one time period.

5 . A system for intelligent monitoring of a computerized numerical control (CNC) machine tool based on Industrial Internet of Things (IIoT), wherein the CNC machine tool refers to a tool employed by a CNC machine, and the system comprises an IIoT management platform, a sensor network platform, and a sensing control platform;

the IIoT management platform is configured in a processor and communicates with the sensing control platform via the sensor network platform;

the sensor network platform is configured on a communication device;

the sensing control platform is configured in a host computer of the CNC machine and configured to control an operation of a camera and an operation of a machine monitoring device;

the IIoT management platform is configured to:

obtain appearance information of the CNC machine based on a tool image, and store the appearance information in a data center of the IIoT management platform, the tool image being acquired by the camera at a preset acquisition time, the preset acquisition time including a time when the CNC machine tool is in a stop state;

in response to the CNC machine tool being in an operational state, obtain operational state information of the CNC machine tool and the CNC machine based on the machine monitoring device, and send the operational state information to the data center of the IIoT management platform via the communication device, wherein to obtain the operational state information of the CNC machine tool and the CNC machine, the IIoT management platform is further configured to:

collect cutting fluid change information via the camera and a first monitoring component configured in a cutting fluid storage tank; and

collect a cutting force data sequence of the CNC machine tool via a second monitoring component;

issue an image acquisition instruction to the sensing control platform to control the camera to acquire a workpiece image of a workpiece at a preset frequency, and determine workpiece information based on the workpiece image;

process the workpiece information to generate machining quality information, and store the machining quality information in the data center of the IIoT management platform;

retrieve the appearance information, the operational state information, and the machining quality information from the data center, and generate tool wear information, wherein to generate the tool wear information, the IIoT management platform is further configured to:

evaluate a degree of wear of the CNC machine tool during at least one time period based on the appearance information, the operational state information, and the machining quality information, the operational state information including at least one of the cutting fluid change information and the cutting force data sequence; and

generate the tool wear information based on the degree of wear of the CNC machine tool during the at least one time period;

issue, based on the tool wear information, an alert via at least one of a machine warning device and an interactive screen to indicate a wear condition of the CNC machine tool;

determine the CNC machine tool will be replaced based on the tool wear information, and control a tool replacement assembly to clip a spare tool from a spare tool box;

issue a rotational speed adjustment instruction and a frequency adjustment instruction based on the tool wear information;

control, using the issued rotational speed adjustment instruction, a rotational speed of a tool holder group that adjusts a machining intensity of the CNC machine tool that will be replaced; and

adjust, using the issued frequency adjustment instruction, an acquisition frequency of the camera.

6 . The system of claim 5 , wherein the IIoT management platform includes a production process management sub-platform, the data center, and a device management sub-platform.

7 . The system of claim 5 , wherein the IIoT management platform is further configured to:

retrieve a tool trajectory corresponding to the workpiece information;

generate the machining quality information based on workpiece material information, the tool trajectory, and the workpiece information.

8 . The system of claim 5 , wherein the IIoT management platform is further configured to:

determine a remaining life sequence of the CNC machine tool based on historical machining data and the tool wear information of the CNC machine tool;

determine a replacement priority of the CNC machine tool based on the remaining life sequence; and

determine the CNC machine tool will be replaced based on the replacement priority.

9 . The method of claim 1 , wherein the evaluating of a degree of wear of the CNC machine tool during at least one time period based on the appearance information, the operational state information, and the machining quality information includes:

determining, based on the appearance information, the operational state information, and the machining quality information, the degree of wear of the CNC machine tool during the at least one time period via a wear assessment model; wherein

the wear assessment model is a machine learning model, and the wear assessment model is obtained by training an initial wear assessment model.

10 . The method of claim 9 , further comprising:

determining, based on historical data, a plurality of training samples for training the initial wear assessment model and historical wear data corresponding to each of the plurality of training samples;

for each of the plurality of training samples, determining a historical degree of wear based on the historical wear data corresponding to the training sample, and determining the historical degree of wear as a label corresponding to the training sample;

dividing the plurality of training samples into a plurality of training datasets based on the historical wear data;

performing at least one round of training on the initial wear assessment model based on at least one of the plurality of training datasets, and determining an initial training effect;

determining an adjusted learning rate based on the initial training effect; and

obtaining the wear assessment model by continuing to train the initial wear assessment model based on the adjusted learning rate and one or more unused datasets from the plurality of training datasets until an end-of-training condition is met.

11 . The method of claim 3 , further comprising:

collecting dust information based on an environmental sensor; and

adjusting the replacement priority based on workpiece material information and the dust information.

12 . The system of claim 5 , wherein the IIoT management platform is further configured to:

determine, based on the appearance information, the operational state information, and the machining quality information, the degree of wear of the CNC machine tool during the at least one time period via a wear assessment model; wherein

the wear assessment model is a machine learning model, and the wear assessment model is obtained by training an initial wear assessment model.

13 . The system of claim 12 , wherein the IIoT management platform is further configured to:

determine, based on historical data, a plurality of training samples for training the initial wear assessment model and historical wear data corresponding to each of the plurality of training samples;

for each of the plurality of training samples, determine a historical degree of wear based on the historical wear data corresponding to the training sample, and determine the historical degree of wear as a label corresponding to the training sample;

divide the plurality of training samples into a plurality of training datasets based on the historical wear data;

perform at least one round of training on the initial wear assessment model based on at least one of the plurality of training datasets, and determine an initial training effect;

determine an adjusted learning rate based on the initial training effect; and

obtain the wear assessment model by continuing to train the initial wear assessment model based on one or more unused datasets from the plurality of training datasets and the adjusted learning rate until an end-of-training condition is met.

14 . The system of claim 8 , wherein the IIoT management platform is further configured to:

collect dust information based on an environmental sensor; and

adjust the replacement priority based on workpiece material information and the dust information.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (27)