Abnormality detection apparatus for working tools

1. An abnormality detection apparatus for working tools configured to be used in a machining process performed by a machine tool, the abnormality detection apparatus comprising:

a storage portion which previously stores correlations between features of a plurality of operating portions relation to the machining process performed by the machine tool, and a tool condition of each of a plurality of working tool types; and

a tool condition determining portion which generates a determination model for each of the plurality of working tool types, based on measurement data of the features of the operating portions, and determines the tool condition of the working tools based on the determination model.

2. The abnormality detection apparatus for working tools according to claim 1 ,

wherein the tool condition is abrasion of an edge of a working tool of the working tools.

3. The abnormality detection apparatus for working tools according to claim 1 ,

wherein the tool condition is chipping of an edge a working tool of the working tools.

4. The abnormality detection apparatus for working tools according to claim 1 ,

wherein the abnormality detection apparatus further comprises a sensor selecting portion which selects a predetermined sensor from a plurality of sensors for measuring the features of the operating portions, based on the features which are effective in determination of the tool condition of the working tools, and

wherein the tool condition determining portion is configured to determine the tool condition of the working tools, based on the measurement data of the features measured by the selected sensors.

5. The abnormality detection apparatus for working tools according to claim 4 ,

wherein the plurality of sensors include a torque sensor, a vibration sensor, and a position sensor.

6. The abnormality detection apparatus for working tools according to claim 1 ,

wherein the tool condition determining portion defines a normal area indexing that the working tools are normal, based on the determination model, and, when the measurement data of the features are outside the normal area, determines that the working tools are abnormal.

7. The abnormality detection apparatus for working tools according to claim 1 ,

wherein the tool condition determining portion defines a normal area indexing that the working tools are normal, based on the determination model, and determines a level of abrasion of an edge of the working tools, based on positions of the measurement data of the features in the normal area.

8. The abnormality detection apparatus for working tools according to claim 1 ,

wherein the determination model is stored in a determination model storage portion of the machine tool.

9. The abnormality detection apparatus for working tools according to claim 1 ,

wherein the abnormality detection apparatus further comprises a measurement data analyzing portion configured to analyze the measurement data and store analysis data to in the storage portion, each time when measurement data of the features are collected, and

wherein the tool condition determining portion is configured to generate the determination model by performing machine learning on a stored analysis data of the features.

10. The abnormality detection apparatus for working tools according to claim 9 ,

wherein the tool condition determining portion is configured to generate the determination model by re-learning data relation to the machining process obtained during the machining process performed by the machine tool.

11. The abnormality detection apparatus for working tools according to claim 1 ,

wherein the plurality of tool types include a drill and a skiving.