CN114488949B - Method and device for realizing synchronization of numerical control machining state monitoring data and learning data - Google Patents
Method and device for realizing synchronization of numerical control machining state monitoring data and learning data Download PDFInfo
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- CN114488949B CN114488949B CN202210061630.4A CN202210061630A CN114488949B CN 114488949 B CN114488949 B CN 114488949B CN 202210061630 A CN202210061630 A CN 202210061630A CN 114488949 B CN114488949 B CN 114488949B
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 73
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/31—From computer integrated manufacturing till monitoring
- G05B2219/31434—Zone supervisor, collects error signals from, and diagnoses different zone
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Abstract
The invention relates to the technical field of processing monitoring data, in particular to a method for realizing synchronization of numerical control processing state monitoring data and learning data, which comprises the following steps of S1, segmenting an NC program and respectively setting segment identifiers; s2, learning the processing state of the product, acquiring learning data, and adding a segmentation identifier; s3, monitoring the processing state of the product, and obtaining monitoring data, wherein the monitoring data comprises actual state data of a processing cutter point, a sectional mark and coordinate values of the processing cutter point; s4, searching a corresponding learning data segment in the learning data according to the segment identification of the NC program segment where the machining tool position point is located, and searching two learning data points closest to the machining tool position point coordinate value in the learning data segment according to the machining tool position point coordinate value; s5, calculating theoretical machining state data of a machining tool site by using the learning data of the two points; s6, judging whether the machining process is abnormal or not according to the actual state data and the theoretical machining state data of the machining tool position points. The effectiveness of monitoring can be effectively improved.
Description
Technical Field
The invention relates to the technical field of processing monitoring data, in particular to a method and a device for synchronizing numerical control processing state monitoring data and learning data.
Background
Automated processing has become a future development trend in the machine-building industry. In an automated processing mode, processing state monitoring is a key means of ensuring product processing quality. At present, in order to monitor the state of the product processing process, a method for learning the processing state and monitoring the product processing process based on the learning result is generally adopted. In the state monitoring of the product processing process, the monitoring data and the learning data are required to be compared to find the abnormal state of the processing process. However, due to the fluctuation of data acquisition frequency, processing delay and other reasons, the coordinates/time of the monitored data point position and the coordinates/time corresponding to the learning data point position are misplaced, so that the monitoring is invalid or the false alarm is caused.
In order to realize synchronization of monitoring data and learning data, the patent 'a method for improving synchronization accuracy of a numerical control processing monitoring threshold and a signal' discloses a method for segmenting an NC program, comparing the monitoring threshold and the monitoring signal after each segment of processing, judging the advanced and the lagged states of the monitoring threshold, and carrying out corresponding error elimination. However, the method performs data synchronization after each segment of the NC program is processed, so that the synchronization of data in the segment processing cannot be ensured, and when data abnormality occurs in the segment, effective monitoring is difficult.
The germany art synchronizes the monitoring data and the learning data according to the processing time with the starting time of the processing program as a reference, but due to the processing delay or the fluctuation of the acquisition frequency, the time errors of the monitoring data and the learning data are transmitted and accumulated, and finally the monitoring is disabled.
Therefore, in order to better realize the state monitoring of the product processing process, a method for realizing the synchronization of the learning data and the monitoring data is urgently needed, so that the effective comparison of the monitoring data and the learning data is realized.
Disclosure of Invention
The invention aims to solve the problem that the synchronization of data in the segment processing cannot be ensured in the prior art, and when the data in the segment is abnormal, the data is difficult to effectively monitor, and provides a method and a device for realizing the synchronization of the numerical control processing state monitoring data and the learning data.
In order to achieve the above object, the present invention provides the following technical solutions:
a method for realizing synchronization of numerical control machining state monitoring data and learning data comprises the following steps:
s1, segmenting an NC program, wherein each NC program segment is provided with a segment identifier;
S2, learning a product processing state, acquiring learning data, and marking the segment identification of an NC program segment where a processing tool position point is located in the learning data to obtain a plurality of learning data segments;
s3, monitoring the processing state of the product, and obtaining monitoring data; the monitoring data comprise actual state data of a machining tool position point, a sectional identification of an NC program section where the machining tool position point is located and a coordinate value of the machining tool position point;
S4, searching a corresponding learning data segment in the learning data according to the segment identification of the NC program segment where the machining tool position is located, and searching two learning data points closest to the machining tool position coordinate value in the learning data segment according to the machining tool position coordinate value, namely a point A and a point B;
S5, calculating theoretical machining state data of the machining tool site by using learning data of the point A and the point B;
S6, comparing the actual state data of the machining tool position point with the theoretical machining state data, and judging whether the machining process is abnormal or not.
Further, in step S1, the specific method of segmenting the NC program is to segment according to the number of NC machining tool sites, where each NC program segment includes l tool sites, where l is a positive integer.
Further, the segment identification comprises a segment number, a segment start tool position point coordinate and a segment end tool position point coordinate.
Further, in step S2, learning the machining state of the product, and acquiring learning data, specifically, in the process of sampling learning data, starting from a start tool position of a certain NC program segment to an end tool position of the NC program segment, and recording coordinates of the machining tool position and machining state data in the process.
Preferably, the machining state data comprises machine tool spindle power and/or machine tool movement axis current.
Preferably, the machining tool bit point actual state data includes machine tool spindle power and/or machine tool movement axis current.
Further, step S5 specifically includes performing interpolation calculation between the point a and the point B according to the position relationship between the coordinate value of the machining tool point and the point a and the point B, and referring to the machining state data of the point a and the point B, to obtain theoretical machining state data of the machining tool point.
Further, in step S6, whether the machining process is abnormal is determined, and if the difference between the actual state data of the machining tool position and the theoretical machining state data exceeds a threshold, the machining tool position is considered to be abnormal.
Preferably, the threshold is set to ±5% of theoretical process state data.
Based on the same inventive concept, a device for synchronizing numerical control machining state monitoring data and learning data is provided, which comprises at least one processor and a memory in communication connection with the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform any one of the methods described above.
Compared with the prior art, the invention has the beneficial effects that:
According to the NC program section, different sectional identifications are set according to different program sections, firstly, standard product processing states are learned to obtain learning data for reference in a subsequent monitoring process, wherein the learning data comprise processing tool position coordinates, processing state data and sectional identifications, then in the actual processing monitoring process, actually measured monitoring data are obtained, wherein the monitoring data comprise processing tool position coordinate values, processing tool position actual state data and sectional identifications of NC program sections where the processing tool position points are located, according to the processing tool position coordinate values and the sectional identifications in the monitoring data, learning data sections corresponding to the sections and two learning data points closest to the processing tool position coordinate values are found, theoretical processing state data of the tool positions are calculated according to the processing tool position coordinates and the relative positions of the two learning data points, and whether the processing tool positions in the NC program section are abnormal or not is judged.
Drawings
FIG. 1 is a flow chart of a method for synchronizing numerical control process state monitoring data with learning data.
Fig. 2 is a diagram of an example of part processing.
FIG. 3 is a block diagram of NC program, learning data and monitoring data.
Fig. 4 is a schematic calculation diagram of theoretical machining state data of the machining tool positions corresponding to the monitoring data.
Detailed Description
The present invention will be described in further detail with reference to test examples and specific embodiments. It should not be construed that the scope of the above subject matter of the present invention is limited to the following embodiments, and all techniques realized based on the present invention are within the scope of the present invention.
Example 1
A method for synchronizing numerical control machining state monitoring data and learning data, as shown in fig. 1, includes:
s1, segmenting an NC program, wherein each NC program segment is provided with a segment identifier;
The invention segments according to the number of numerical control machining tool sites, each NC program segment comprises l tool sites, wherein l is a positive integer, thereby determining a data synchronization step length;
In the embodiment, 100 tool positions are used as data synchronization step length l, and the NC program processing process is divided into a plurality of sections;
in the example of machining a part as shown in fig. 2, the NC program contains 467 tool positions in total, and the NC program can be divided into 5 segments according to the data synchronization step, each segment identifier contains a segment number, a segment start tool position coordinate, and a segment end tool position coordinate, where the segment identifier of the first NC program segment is:
“N001,P0001:464.35,1981.26,121.04,P0100:490.794,1944.12,105.184”。
S2, learning a product processing state, acquiring learning data, and marking the segment identification of an NC program segment where a processing tool position point is located in the learning data to obtain a plurality of learning data segments;
As shown in fig. 3, during learning of the part processing state, the learning data is segmented according to the segmentation result of the NC program, the NC program is divided into 5 segments, and correspondingly, the part processing learning data is also divided into 5 segments, and the segment numbers in the segment identifiers of each segment are consistent with the segment numbers of the segment identifiers of the NC program segments, and are N001-N005;
The specific method for acquiring the learning data is that in the process of sampling the learning data, starting from a start tool position of a certain NC program section to the end of the end tool position of the section, the coordinates of the machining tool position and the machining state data in the process are recorded, the learning data of each machining tool position comprise the coordinates of the machining tool position and the corresponding machining state data, the machining state data comprise the power of a machine tool spindle and/or the current of a machine tool motion axis, and if the power of the machine tool spindle corresponding to the coordinates (481.739,1957.92,139.354) of the machining tool position is 5.2.
S3, monitoring the processing state of the product, and obtaining monitoring data; the monitoring data comprise actual state data of a machining tool position point, a sectional identification of an NC program section where the machining tool position point is located and a coordinate value of the machining tool position point;
the actual state data of the machining tool bit point comprises machine tool spindle power and/or machine tool motion axis current.
S4, searching a corresponding learning data segment in the learning data according to the segment identification of the NC program segment where the machining tool position is located, and searching two learning data points closest to the machining tool position coordinate value in the learning data segment according to the machining tool position coordinate value, namely a point A and a point B;
the step S4 mainly realizes the function of matching monitoring data and learning data in the process of monitoring the processing state of the product;
Specifically, firstly, a learning data segment with the same segment identification is found from learning data according to the segment identification corresponding to the monitoring data, if the NC program segment corresponding to the processing point position P (488.182,1954.845,131.741) is N003, the learning data of the N003 segment can be rapidly positioned according to the segment identification; and secondly, finding two learning data points A (481.739,1957.92,139.354) and B (494.518,1951.726,124.022) with coordinate values closest to the coordinate values of the monitoring data in the learning data segment.
S5, calculating theoretical machining state data of the machining tool site by using learning data of the point A and the point B;
The main function realized in the step S5 is to calculate theoretical machining state data of the machining position corresponding to the monitoring data;
As shown in fig. 4, points a and B are machining tool positions in the learning data, P is a machining tool position of the monitoring data, a ', B ' are machining state values of the learning data, and P ' is a theoretical machining state value at the machining point P of the monitoring data;
Specifically, the distance l A between the point P and the point a and the distance l B between the point P and the point B are calculated, and the theoretical machining state value P' of the point P is calculated according to the following formula according to the ratio of the distance l A to the distance l B:
for example, the machine tool spindle power learning data of the two learning data points a and B obtained in step S4 are 5.2 and 5.36 respectively, the distance between the point P and the point a is equal to the distance between the point P and the point B, and the theoretical machine tool spindle power value P' of the processing point P corresponding to the monitoring data is 5.28 according to the coordinate position relationship between the point P corresponding to the monitoring data and the learning data point A, B, by interpolating the processing state data of the reference point a and the point B by using the above formula between A, B points.
S6, comparing actual state data of the machining tool position points with theoretical machining state data, and judging whether an abnormality exists in the machining process;
The specific method is that if the difference value between the actual state data of the machining tool position and the theoretical machining state data exceeds a threshold value, the machining tool position is considered to be abnormal, and the threshold value is set to be +/-5% of the theoretical machining state data.
When machining the machining tool point P, the actual monitoring data of the machine tool spindle power is 5.41, the difference value is 0.13 compared with the theoretical machine tool spindle power value at the point of 5.28, and is 2.46% of the theoretical machine tool spindle power value of 5.28, and the monitoring threshold value is not exceeded by +/-5% of theoretical machining state data, so that the judgment result is that the machining process of the machining tool point P is not abnormal.
According to the NC program section, different sectional identifications are set according to different program sections, firstly, standard product processing states are learned to obtain learning data for reference in a subsequent monitoring process, wherein the learning data comprise processing tool position coordinates, processing state data and sectional identifications, then in the actual processing monitoring process, actually measured monitoring data are obtained, wherein the monitoring data comprise processing tool position coordinate values, processing tool position actual state data and sectional identifications of NC program sections where the processing tool position points are located, according to the processing tool position coordinate values and the sectional identifications in the monitoring data, learning data sections corresponding to the sections and two learning data points closest to the processing tool position coordinate values are found, theoretical processing state data of the tool positions are calculated according to the processing tool position coordinates and the relative positions of the two learning data points, and whether the processing tool positions in the NC program section are abnormal or not is judged.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (6)
1. A method for synchronizing numerical control machining state monitoring data with learning data, comprising:
S1, segmenting an NC program according to the number of numerical control machining tool sites, wherein each NC program segment comprises l tool sites, l is a positive integer, and each NC program segment is respectively provided with segment identifiers, wherein each segment identifier comprises a segment number, a segment start tool site coordinate and a segment end tool site coordinate;
s2, learning the processing state of the product, and acquiring learning data, wherein in the process of sampling learning data, coordinates of processing tool positions and processing state data in the process are recorded from a starting tool position of a certain NC program section to an ending tool position of the NC program section; marking the segment identification of the NC program segment where the machining tool position point is located in the learning data to obtain a plurality of learning data segments;
s3, monitoring the processing state of the product, and obtaining monitoring data; the monitoring data comprise actual state data of a machining tool position point, a sectional identification of an NC program section where the machining tool position point is located and a coordinate value of the machining tool position point;
S4, searching a learning data segment with the same segment identification in the learning data according to the segment identification of the NC program segment where the machining tool position point is located in the monitoring data, and finding two learning data points with the coordinate value closest to the coordinate value of the machining tool position point in the monitoring data in the learning data segment according to the coordinate value of the machining tool position point in the monitoring data, namely a point A and a point B;
S5, calculating theoretical machining state data of the machining tool site by using learning data of the point A and the point B, wherein the theoretical machining state data of the machining tool site is obtained by carrying out interpolation calculation between the point A and the point B according to the position relation between the coordinate value of the machining tool site and the point A and the point B and referring to the machining state data of the point A and the point B;
S6, comparing the actual state data of the machining tool position point with the theoretical machining state data, and judging whether the machining process is abnormal or not.
2. A method of synchronizing digitally controlled process state monitoring data with learning data according to claim 1, wherein the process state data comprises machine tool spindle power and/or machine tool movement axis current.
3. A method of synchronizing numerically controlled machining state monitoring data with learning data according to claim 1, wherein the machining tool point actual state data comprises machine tool spindle power and/or machine tool axis current.
4. The method for synchronizing numerical control machining state monitoring data with learning data according to claim 1, wherein in step S6, whether the machining process is abnormal is determined, specifically, if the difference between the actual machining state data of the machining tool position and the theoretical machining state data exceeds a threshold value, the machining tool position is considered to be abnormal.
5. The method of synchronizing digitally controlled process state monitoring data with learning data of claim 4, wherein the threshold is set to ± 5% of theoretical process state data.
6. The device for realizing synchronization of numerical control machining state monitoring data and learning data is characterized by comprising at least one processor and a memory in communication connection with the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
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