JPS61252053A - Device for detecting abnormality of perforating tool - Google Patents

Abstract

PURPOSE:To improve accuracy in detecting abnormality in a perforating tool by replacing the width of dispersion of a load data with a standard deviation, based on load data in plural number of machinings. CONSTITUTION:A load applied to a drill is detected from the value of a current of main shaft of a drill driving motor by a load detecting means 1, and inputted into a microcomputer 3 via an A/D converter 2. A load data at the rear stage, particularly at the closing stage of machining of a workpiece in which dispersion occurs conspicuously, is inputted in this microcomputer 3, and a standard deviation is obtained from the load data of the defined number of times, and the abnormality, particularly the life, of a drill is detected based on a comparison between the obtained standard deviation and a reference standard deviation. Since the dispersion width sigmab of the loads of a drill with larger number of times of machining is greater than the dispersion width sigmaa of loads with smaller number of times of machining, the life of a drill can be accurately detected by comparing the dispersion widths with a standard deviation.

Description

DETAILED DESCRIPTION OF THE INVENTION (Industrial Application Field) The present invention relates to an abnormality detection device for a drilling tool for drilling a predetermined hole in a workpiece.

(Prior art) For machine tools that repeatedly drill into workpieces according to a predetermined program, it is necessary to accurately detect abnormalities in the drilling tool, especially the life of the drilling tool. .

Conventionally, this type of device was disclosed in Japanese Patent Application Laid-open No. 58-19695.
As seen in Publication No. 4, the load applied to the tool during workpiece processing is detected, and abnormalities in the processing tool are detected based on whether the maximum value of the load is greater than a set reference value. Ta.

(Problem to be solved by the invention) However, the load applied to the 5 processing tools varies greatly depending on the workpiece due to factors such as variations in workpiece hardness and bending of the machined hole, so tool abnormalities cannot be accurately determined. It was something I couldn't get.

In other words, since the data used to detect tool abnormalities itself includes variations, it is impossible to avoid the problem of misjudgment when comparing with a certain set standard value. There was a problem in that it was difficult to determine at what level the reference value should be set.

The present invention has been made in consideration of the above problems, and its technical problem is to provide an abnormality detection device for a drilling tool that improves the accuracy of abnormality detection in the drilling tool. It is in.

(Technical means for solving the problem) The present invention focuses on the fact that as the drilling process wears out, the variation in the load applied to the tool increases. It is designed to determine.

That is, a load detection means for detecting the load applied to drilling during workpiece processing, and a data storage means for receiving a load signal from the load detection means and storing representative load data for each drilling of the load signal. and a calculation means that calculates a standard deviation from representative load data for a predetermined past latest number of machining operations, and compares the standard deviation obtained by the calculation means with a reference standard deviation, and determines whether the standard deviation is larger than the reference standard deviation. At a certain time, a determination means for outputting an abnormality determination signal is provided, and the apparatus is configured to detect an abnormality in the processing tool by replacing the variation width of the load data with a standard deviation based on the load data obtained at a plurality of machining times. This is what I did.

(Example) The following is an example of the case where long holes such as sleeve holes (machined length is 1.5 times or more of the machining diameter) are repeatedly drilled in engine parts (castings) according to a predetermined program. Detailed description of the invention.

FIG. 1 shows an abnormality detection device according to an embodiment. The abnormality detection device includes means 1 for detecting a load applied to a drill (not shown), and A for converting a load signal from the load detection means l into a digital signal. /D converter 2 and a microcomputer 3 that determines whether there is an abnormality in the drill from the digitized load signal.
The load detection means 1 is configured to detect the load applied to the drill from the main shaft current value of the drill drive motor.

Further, a signal immediately before the end of machining is inputted to the microcomputer 3, and by this signal just before the end of machining, a load signal from the load detection means 1 just before the end of workpiece machining is taken into the microcomputer 3.
Based on this load data immediately before the end of machining, it is determined whether there is an abnormality in the drill.

To explain the drill abnormality determination performed by the microcomputer 3, the standard deviation is obtained from the load data of a predetermined number of times, and based on the comparison between the obtained standard deviation and the reference standard deviation, the drill abnormality, especially the life span, is detected. It will be done.

By the way, just before a drill breaks, it is generally worn out, and due to this drill wear,
There are many cases where the straightness of drilling a machined hole is lost and the drill enters the workpiece while being bent. For this reason, the load applied to the drill varies significantly during the latter stages of workpiece machining, especially at the final stage.

Therefore, in order to incorporate this characteristic phenomenon into concrete data, we decided to use the load immediately before the end of machining as the basic data for life determination, and to judge the life of the drill based on the variation range of this load data. It is. To explain this point in detail, in Fig. 2, the solid line A shows the load variation @ (σa) for drills with a small number of processing operations, and the broken line B shows the load variation width (σb) of a drill that has a large number of processing operations. It shows. As is clear from this figure, it is understood that as the number of machining operations (time of use) increases, in other words, as the drill wears, the variation width increases (σa + σb). By utilizing this phenomenon and comparing the variation width with the standard deviation, it becomes possible to accurately detect the drill life without being confused by variations in individual data.

Such life detection will be specifically explained based on the flowchart shown in FIG.

First, in step 10, the load applied to the drill, that is, the spindle current signal mentioned above, is captured. here,
In order to capture the spindle current signal immediately before the end of machining, a timer (not shown) causes the spindle current signal to be captured after a predetermined period of time has elapsed from the start of machining.

In step 20, representative load data χ is determined and stored from the spindle current value just before the machining path T taken in this way. The representative load data χ may be determined by the average of the spindle current values for each machining cycle described above, or the maximum value may be used as the representative load data χ.

Then, when the number of holes drilled by the drill reaches n times from the first time, the process proceeds to step 30, and in step 30, the standard deviation σ
1 is calculated. The standard deviation σ1 is calculated based on the following formula.

The reference standard deviation σ0 is set by multiplying the standard deviation σl obtained in this way by a coefficient k (step 40).
The coefficient here is a correction coefficient for compensating for individual differences in drills, and is obtained through experiments. Note that the standard deviation σ1 is calculated every time the drill is replaced.

For the base ξ standard deviation σ0 set in this way,
A comparison is made with the standard deviation σ2 (step 50) calculated based on the above formula from the representative load data (χ) of the past latest m-concave machining (step 60), and the standard deviation σ2 of the past latest m-concave machining is set. When it is larger than the reference standard deviation σ0, it is determined that the drill is at the end of its life, and a life warning signal is output (step 70). The reset shown in step 80 is provided to cancel the life warning signal.
Here it is said to be manual.

Of course, the representative data χ of the latest m-recess machining in the past is updated for each drilling process. From this, after machining m times after replacing the drill, if the load fluctuates significantly due to a sudden accident, the standard deviation obtained will inevitably become large, and this will also detect abnormalities such as drill breakage. It is possible.

Although one embodiment has been described above, it is also possible to set the reference standard deviation σ0 to an experimental value obtained through experiments in advance. Furthermore, if large load fluctuations occur in the early or middle stages of machining the workpiece due to the material of the workpiece, the load at that time can of course be detected and used as data for calculating the standard deviation. (Effects of the Invention) As is clear from the above description, according to the present invention, abnormalities in the drilling tool are detected based on load data from multiple machining operations, so there is a problem of misjudgment due to data fluctuations for each workpiece machining process. is eliminated, and since the determination is made based on the data variation range, that is, the standard deviation, the abnormality detection accuracy can be improved and the reference value can be easily set.

[Brief explanation of drawings]

FIG. 1 is an overall configuration diagram of the apparatus according to the embodiment, FIG. 2 is an explanatory diagram showing the range of variation in load data due to drill wear, and FIG. 3 is a flowchart for detecting drill life. l...Load detection means 3...Microcomputer step 20...Storage means step 50 Conflict/conflict calculation means

Claims (1)

[Claims] (1) Load detection means for detecting a load applied to a drilling tool; Data storage means for receiving a load signal from the load detection means and storing representative load data for each drilling process among the load signals; A calculation means for calculating a standard deviation from representative load data for the past latest number of machining times, and a comparison between the standard deviation obtained by the calculation means and a reference standard deviation, and when the standard deviation is larger than the reference standard deviation, An abnormality detection device for a drilling tool, comprising: an abnormality determination means for outputting an abnormality determination signal;