CN116954158A - Quick denture cutting speed control method based on data analysis - Google Patents
Quick denture cutting speed control method based on data analysis Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 76
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- G—PHYSICS
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- 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
- G05B19/416—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 control of velocity, acceleration or deceleration
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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
- G05B2219/32—Operator till task planning
- G05B2219/32063—Adapt speed of tool as function of deviation from target rate of workpieces
Abstract
The invention relates to the technical field of digital data processing, and provides a rapid denture cutting speed control method based on data analysis, which comprises the following steps: acquiring a processing speed matrix; obtaining a jitter effect index of each local speed extremum data point of each machine tool shaft corresponding to the processing moment and a motion load overweight degree of each machine tool shaft corresponding to the processing moment according to the phenomenon that the machine tool shaft is easy to generate jitter phenomenon and motion load overweight due to overlarge processing speed and overlarge change; acquiring the overweight degree of the combined load at each corresponding processing moment by adopting a data fusion and data prediction method; marking the processing time when the combined load overweight degree is higher than the preset parameter, and regulating and controlling the cutting processing speed according to the marked denture processing time. The invention effectively avoids the phenomenon of machine tool shaft shaking and overweight motion load of the machine tool, and reduces the influence on the rapid denture cutting precision.
Description
Technical Field
The invention relates to the technical field of digital data processing, in particular to a rapid denture cutting speed control method based on data analysis.
Background
Aiming at quick processing of false teeth, five-axis numerical control double rotary tables are mostly selected for processing the false teeth. In the cutting process of the target denture, the post-treatment of the denture needs to take different speeds at different processing positions, and meanwhile, the severe shaking of the machine tool during processing is avoided, otherwise, the denture is damaged, and meanwhile, the machine tool is damaged. Therefore, it is necessary to ensure smooth running of the speeds of the respective axes of the machine tool.
At present, the speed of the machine tool shaft is mainly adjusted to avoid exceeding the maximum allowable speed through the speed of the machine tool shaft in actual movement, the speed of the machine tool shaft is adjusted through a data processing mode, the stable operation of the speed of each machine tool shaft is ensured, and meanwhile, the stable operation of the numerical control machine tool is ensured. The detection and adjustment of the machine tool shaft speed at the present stage mainly comprises an abnormal data detection LOF algorithm, a CURE clustering algorithm and the like. However, it is difficult for the abnormal data detection LOF algorithm to define the minimum neighborhood, the accuracy of the result of the abnormal detection is low, and the selection of the representative point in the CURE clustering algorithm is difficult.
Disclosure of Invention
The invention provides a rapid denture cutting speed control method based on data analysis, which aims to solve the problem of lower denture processing precision caused by unstable operation of a numerical control machine tool, and adopts the following specific technical scheme:
one embodiment of the present invention provides a rapid denture cutting rate control method based on data analysis, the method comprising the steps of:
acquiring processing speed data, and acquiring a processing speed matrix by using the processing speed data;
acquiring local speed extremum data points in a processing speed sequence of each machine tool shaft according to the processing speed matrix; obtaining a jitter effect index of the local speed extremum data point of each machine tool shaft corresponding to the processing time according to the local speed extremum data point of the processing speed sequence of each machine tool shaft; acquiring a speed differential sequence of each machine tool shaft according to the processing speed change of adjacent processing time in the processing speed sequence of each machine tool shaft, and acquiring a distance characteristic sequence of each element in the speed differential sequence of each machine tool shaft according to the speed differential sequence of each machine tool shaft; acquiring the overweight degree of the motion load of each element in the speed differential sequence of each machine tool shaft according to the similarity between the distance characteristic sequences of adjacent elements in the speed differential sequence of each machine tool shaft;
acquiring a motion load overweight degree sequence of each machine tool shaft according to the motion load overweight degree of each data point in the speed differential sequence of each machine tool shaft; acquiring updated motion load overweight degree of each machine tool shaft at each machining moment according to the motion load overweight degree sequence of each machine tool shaft; acquiring the combined load overweight degree of each corresponding processing moment according to the updated motion load overweight degree of each processing moment of each machine tool shaft;
marking the processing time when the combined load overweight degree is higher than the preset parameter, and regulating and controlling the cutting processing speed according to the marked denture processing time.
Preferably, the method for acquiring the local speed extremum data point in the processing speed sequence of each machine tool shaft according to the processing speed matrix comprises the following steps:
acquiring a processing speed sequence of each machine tool shaft according to the processing speed matrix; acquiring a processing speed function corresponding to a processing speed sequence of each machine tool shaft by using a nonlinear fitting algorithm; the maximum point in the processing speed function is taken as a local speed extremum data point in the processing speed sequence of each machine tool shaft.
Preferably, the method for obtaining the jitter effect index of each local speed extremum data point of each machine axis corresponding to the machining time according to each local speed extremum data point of the machining speed sequence of each machine axis comprises the following steps:
acquiring overspeed effect indexes of each local speed extremum data point of each machine tool shaft according to the processing speed of each local speed extremum data point of each machine tool shaft;
setting a sequence window with a preset size by taking each local speed extremum data point of the processing speed sequence of each machine tool shaft as a center according to the obtained processing speed sequence of each machine tool shaft;
acquiring the change degree of each target data point in the sequence window of each local speed extremum data point in each machine tool axis according to the processing speed in the sequence window of each local speed extremum data point of each machine tool axis;
taking the number of target data points in a sequence window of each local speed extremum data point in each machine tool axis as denominator, taking the accumulation of the change degree on the sequence window as numerator, and taking the ratio of the numerator to the denominator as the average change degree of each local speed extremum data point in each machine tool axis;
and taking the normalization result of the product of the overspeed effect index of each local speed extremum data point in each machine tool axis and the average change degree of each local speed extremum data point in each machine tool axis as the jitter effect index of each local speed extremum data point of each machine tool axis corresponding to the processing time.
Preferably, the method for obtaining the overspeed effect index of each machine axis local speed extremum data point according to the processing speed of each machine axis local speed extremum data point comprises the following steps:
in the method, in the process of the invention,overspeed effect index, ++f, representing the jth local speed extremum data point of the ith machine axis>Processing speed of the jth local speed extremum data point representing the ith machine axis, +.>Indicating the maximum allowable speed of the ith machine axis.
Preferably, the method for obtaining the variation degree of each target data point in the sequence window of each local speed extremum data point in each machine axis according to the processing speed in the sequence window of each local speed extremum data point in each machine axis comprises the following steps:
in the method, in the process of the invention,degree of change of the s-th target data point in the sequence window of the j-th local speed extremum data point representing the i-th machine axis,/->And->The processing speeds of the (s-1) th target data point and the (s-1) th target data point in the sequence window of the jth local speed extremum data point of the ith machine tool shaft are respectively expressed.
Preferably, the method for obtaining the speed differential sequence of each machine axis according to the processing speed variation of the adjacent processing time in the processing speed sequence of each machine axis and obtaining the distance feature sequence at each speed differential position in the speed differential sequence of each machine axis according to the speed differential sequence of each machine axis comprises the following steps:
for the processing speed sequence of each machine tool shaft, taking a sequence formed by the difference value of the processing speed at the next moment and the processing speed at the previous moment in the processing speed sequence as a speed difference sequence of each machine tool shaft;
according to the speed differential sequence of each machine tool shaft, detecting a mutation point to obtain a mutation speed differential sequence of the corresponding machine tool shaft;
and acquiring a distance characteristic sequence at each speed differential position in the speed differential sequence of each machine tool shaft based on the Euclidean distance between the data point at each speed differential position in the speed differential sequence of each machine tool shaft and each data point in the abrupt speed differential sequence of each machine tool shaft according to the acquired speed differential sequence of each machine tool shaft and the abrupt speed differential sequence of each machine tool shaft.
Preferably, the method for obtaining the overweight degree of the motion load of each data point in the speed differential sequence of each machine axis according to the similarity between the distance characteristic sequences at the adjacent speed differential positions in the speed differential sequence of each machine axis comprises the following steps:
taking the DTW distance between the distance characteristic sequence of each data point in the speed differential sequence of each machine tool axis and the distance characteristic sequence of each adjacent data point as the variation degree of each data point in the speed differential sequence of each machine tool axis and each adjacent data point;
acquiring average absolute differences between the distance characteristic sequences of each data point in the speed differential sequence of each machine tool axis and the distance characteristic sequences of each adjacent data point according to each distance characteristic value in the distance characteristic sequences of each data point in the speed differential sequence of each machine tool axis and each adjacent data point;
and accumulating the adjacent data points of each data point in the speed differential sequence of each machine tool axis by using the product of the variation degree of each data point and the average absolute difference of each adjacent data point as a numerator, using the number of the adjacent data points of the data points as a denominator, and using the normalized value of the ratio of the numerator to the denominator as the overweight degree of the motion load of each data point in the speed differential sequence of each machine tool axis.
Preferably, the method for obtaining the average absolute difference between the distance characteristic sequence of each data point in the speed differential sequence of each machine axis and the distance characteristic sequence of each adjacent data point according to each distance characteristic value in the distance characteristic sequence of each data point in the speed differential sequence of each machine axis and each adjacent data point comprises the following steps:
in the method, in the process of the invention,indicating the (th) in the speed differential sequence of the ith machine axis>Average absolute difference between distance signature of data point and distance signature of its q-th adjacent data point,/v>Representing the length of the distance characteristic sequence in the speed differential sequence of the ith machine axis, +.>Indicating the (th) in the speed differential sequence of the ith machine axis>H distance feature value in distance feature sequence of data points +.>Indicating the (th) in the speed differential sequence of the ith machine axis>The h-th distance feature value in the distance feature sequence of the q-th adjacent data point of the data points.
Preferably, the method for obtaining the updated motion load overweight degree of each corresponding processing time of each machine axis according to the motion load overweight degree sequence of each machine axis comprises the following steps:
taking the overweight degree of the motion load at a plurality of continuous preset moments as the input of a prediction model, and taking the output of the prediction model as the overweight degree of the motion load at the predicted moments;
and acquiring an average value of the overweight degree of the motion load and the jitter effect index at the processing time corresponding to the local speed extremum data point, and updating the overweight degree of the motion load by using the average value as the updated overweight degree of the motion load, thereby acquiring the updated overweight degree of the motion load at each corresponding processing time of each machine tool axis.
Preferably, the method for obtaining the combined load overweight degree of each corresponding processing moment according to the updated motion load overweight degree of each corresponding processing moment of each machine tool shaft comprises the following steps:
respectively obtaining the overweight degree of the updated motion load of each corresponding machining moment of each machine tool shaft;
and taking the sum of the updated motion load overweight degrees of each corresponding processing moment of the machine tool shaft as an input of a downward rounding function, and taking the output of the downward rounding function as the combined load overweight degree of each corresponding processing moment.
The beneficial effects of the invention are as follows: according to the data characteristics of overlarge machining speed and overlarge machining speed change of the machine tool shaft, the machine tool shaft is easy to generate a shaking phenomenon and a phenomenon of movement load of the machine tool shaft, and a shaking effect index and an overweight degree of the movement load are obtained according to the characteristics. And combining the jitter effect index and the overweight degree of the moving load, acquiring the overweight degree of the moving load at the processing time corresponding to each processing speed by adopting a data fusion and data prediction method, further acquiring the overweight degree of the combined load at the processing time corresponding to each processing speed of the processing machine tool, setting preset parameters, screening the processing time corresponding to a larger value of the overweight degree index of the combined load, further carrying out processing speed regulation and control when the same false tooth is processed next time, and assisting the rapid cutting processing of the false tooth. The method has the beneficial effects that the machining time of the selection regulation is more accurate, the overweight phenomenon of the moving load and the shaking phenomenon of the machine tool shaft of the machine tool are effectively avoided, and further the influence of the overweight phenomenon of the moving load and the shaking phenomenon of the machine tool shaft on the rapid denture cutting machining precision is effectively avoided.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a flowchart of a method for controlling a rapid denture cutting speed based on data analysis according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a flowchart of a method for controlling a rapid denture cutting speed based on data analysis according to an embodiment of the present invention is shown, the method comprises the following steps:
in step S001, the actual processing speed is acquired using the sensor device, and a speed matrix is constructed.
In the post-processing of the denture processing, the actual processing speed of the denture processing is obtained by a speed sensor, and the five axes are marked as an X axis, a Y axis, a Z axis, an L axis and an M axis. The time interval for collecting the actual processing speed is t, the collection times are n, the empirical value of t is 5s, and the empirical value of n is 500. Thereby, a processing speed sequence of the 5 machine axes is obtained. In order to avoid the influence of environmental noise on subsequent prediction, data cleaning is performed on the obtained processing speed sequence, a speed matrix is constructed, and the data cleaning is a known technology and is not redundant.
The velocity matrix is:
in the method, in the process of the invention,for said velocity matrix +.>The nth acquisition data representing the mth machine axis. It should be noted that, each collected data corresponds to a processing time of the denture by a machine axis.
Thus far, a velocity matrix is obtained。
Step S002, obtaining the jitter effect index of the local speed extremum data point of each machine axis corresponding to the processing time, obtaining the distance characteristic sequence at each speed difference position in the speed difference sequence of each machine axis by obtaining the speed difference sequence, and further calculating the overweight degree of the motion load.
According to the obtained speed matrix, the processing speed of each machine axis is firstly carried out due to the need of ensuring the stability of the speed of the machine axis in the processing of false teethLine analysis, obtaining the processing speed sequence of the ith machine tool shaft, and recording as：
In the method, in the process of the invention,for the processing speed sequence of the ith machine axis, < > for the processing speed sequence of the ith machine axis>And->The machining speeds at the 1 st and nth machining times of the i-th machine tool axis are shown.
Since the severe shaking of the machine tool spindle needs to be avoided, i.e. the machining speed cannot be too high, while the speed variation needs to be avoided.
Specifically, according to the processing speed sequence of the ith machine tool shaft, a nonlinear fitting algorithm is used to obtain a processing speed function, and the nonlinear fitting algorithm is a known technology and is not redundant. And obtaining a maximum point in the processing speed function by making the first order derivative of the processing speed function be 0 and the second order derivative of the processing speed function be greater than zero according to the obtained processing speed function. Thus, local speed extremum data points in the process speed sequence are obtained. In addition, the phenomenon of intense shaking of the machine axis is generally caused by excessive speed and excessive speed change, and in order to obtain the processing speed which is likely to generate the phenomenon of shaking of the machine axis, the magnitude is set to be that of each local speed extremum data point as the center according to the obtained processing speed sequenceThe practitioner can select an appropriate window size according to the actual situation.
Calculating jitter effect index of jth local speed extremum data point of ith machine tool axis corresponding to machining time：
In the method, in the process of the invention,overspeed effect index, ++f, representing the jth local speed extremum data point of the ith machine axis>Processing speed of the jth local speed extremum data point representing the ith machine axis, +.>Indicating the maximum allowable speed of the ith machine axis,/->Degree of change of the s-th target data point in the sequence window of the j-th local speed extremum data point representing the i-th machine axis,/->And->Processing speed of the (s-1) th target data point in the sequence window of the (s-1) th local speed extremum data point respectively representing the (i) th machine tool axis, (-)>Jitter effect index corresponding to processing time for the jth local speed extremum data point of the ith machine tool axis，/>Number of data points in the sequence window of jth local speed extremum data points for the ith machine axis, +.>Is a normalization function.
Processing speed of the jth local speed extremum data point of the ith machine tool axisThe greater the difference between the maximum allowable speed and the processing speed of the local speed extremum data point +.>The smaller this indicates that the more likely the machine axis is to exceed the limits of motion, the jitter effect index +.>The larger. At the same time, the average degree of variation +.>The larger the processing speed change of the jth local speed extremum data point of the ith machine tool axis is, the more the processing speed change is more severe, the more the possibility of generating the shaking of the machine tool axis is, the shaking effect index is +.>The larger.
Since the time interval between adjacent processing time points is short from the angle of the speed variation of the adjacent processing time points, when the speed variation is large, the motion load of the machine tool suddenly increases, and the machine tool shaft is easy to shake. Therefore, the exercise load needs to be kept at a relatively stable level, and the phenomenon of abrupt increase of the exercise load should be avoided.
Specifically, in order to analyze the phenomenon of overweight of the motion load, the processing speeds of two adjacent processing moments are processed according to the processing speed sequence of the obtained ith machine tool shaftThe difference, i.e. the processing speed at the next moment minus the processing speed at the previous moment, is used to obtain a speed differential sequence：
In the method, in the process of the invention,representing the speed differential sequence of the ith machine axis,/->The (n-1) th speed differential value in the speed differential sequence of the ith machine tool axis is represented, and (n-1) is the number of speed differentials in the speed differential sequence.
The speed difference in the speed difference sequence can represent the speed variation amount at the corresponding position to a certain extent through the speed difference sequence. In order to measure the overweight degree of the motion load of the machine tool shaft through the speed differential sequence, the mutation speed differential in the speed differential sequence is obtained by utilizing a BG segmentation algorithm according to the obtained speed differential sequence, so that the mutation speed differential sequence is obtained, and the BG segmentation algorithm is a known technology and is not redundant.
The mutation speed differential sequence：
In the method, in the process of the invention,for the mutation speed differential sequence of the ith machine tool axis, < > for>The difference of the ith mutation speed in the mutation speed difference sequence of the ith machine tool shaft is r, and r is the mutation of the ith machine tool shaftThe number of abrupt speed differences in the sequence of speed differences.
According to the obtained speed differential sequence of the ith machine tool shaft and the mutation speed differential sequence of the ith machine tool shaft, constructing a distance characteristic sequence at the g speed differential position in the speed differential sequence of the ith machine tool shaftI.e.
In the method, in the process of the invention,a h distance feature value in a feature sequence representing a g-th speed differential position in a speed differential sequence of an i-th machine axis,/a>Is a Euclidean distance function, ">Representing the g-th speed differential value in the speed differential sequence of the i-th machine axis,/th speed differential value>Indicating the h th mutation speed differential value in the mutation speed differential sequence of the ith machine axis,/for the mutation speed differential sequence of the ith machine axis>A distance characteristic sequence representing the g-th speed differential position in the speed differential sequence of the i-th machine tool shaft.
Specifically, a distance characteristic sequence at each speed difference position in the speed difference sequence is obtained, and the distance characteristic sequences of adjacent speed differences are passed. Calculating the ith machine axis speed differential sequenceDegree of overweight of the exercise load in the data point position +.>：
In the method, in the process of the invention,indicating the (th) in the speed differential sequence of the ith machine axis>Degree of variability of a data point from its q-th neighbor, +.>Representing the calculation of two distance feature sequences +.>Distance (L)>Indicating the (th) in the speed differential sequence of the ith machine axis>Distance feature sequence of data points, +.>Indicating the (th) in the speed differential sequence of the ith machine axis>The q-th of data pointsDistance feature sequence of adjacent data points, +.>Indicating the (th) in the speed differential sequence of the ith machine axis>Average absolute difference between distance signature of data point and distance signature of its q-th adjacent data point,/v>Representing the length of the distance characteristic sequence in the speed differential sequence of the ith machine axis, +.>Indicating the (th) in the speed differential sequence of the ith machine axis>H distance feature value in distance feature sequence of data points +.>Indicating the (th) in the speed differential sequence of the ith machine axis>H distance feature value in the distance feature sequence of the q-th adjacent data point of the data points,/>Indicating the (th) in the speed differential sequence of the ith machine axis>The degree of overweight of the exercise load of the data points,indicating the (th) in the speed differential sequence of the ith machine axis>Number of adjacent data points of data points, +.>Is a normalization function. Note that +/in the speed differential sequence of the ith machine axis>The q-th adjacent data point of the data points, wherein the adjacent data points are defined according to the sequence of the data in the speed differential sequence, for example, the adjacent data point of the 1 st data point of the speed differential sequence is the 2 nd data point, and there is only one adjacent data point; the 20 th data point is adjacent to the 19 th data point and the 20 th data point, and only two data points exist, namely, other data points except the 1 st data point and the last data point in the speed differential sequence only have one adjacent data point, and the other data points have two adjacent data points.
The lower the similarity between adjacent data points from the feature sequence, i.eThe greater the distance, the greater the fluctuation of speed at the processing time of the data point, the more serious the motion load of the machine tool shaft is likely to be, the overweight degree of the motion load isThe larger. Average absolute difference between adjacent data point distance characteristic sequences +.>The larger the movement load of the machine tool spindle is, the more the movement load of the machine tool spindle is possibly serious, the more overweight degree of the movement load is +.>The larger.
Step S003, a motion load overweight degree sequence of each machine tool axis and a jitter effect index of a local speed extremum data point corresponding to a processing time are obtained according to the motion load overweight degree, the motion load overweight degree of each machine tool axis at each corresponding processing time is obtained, and then the combined overweight degree of each corresponding processing time is obtained.
Thus, the degree of overweight of the motion load of each data point in the speed differential sequence of the ith machine axis is obtained. Because the length of the speed differential sequence is 1 less than the length of the process speed sequence, it is not sufficient to characterize the motion load of each data point in the process speed sequence. In order to represent the motion load characteristics of each processing time point in the processing speed sequence, a motion load overweight degree sequence with the length of (n-1) is constructed according to the motion load overweight degree of each data point in the obtained speed differential sequence of the ith machine tool axis：
In the method, in the process of the invention,representing the sequence of the degree of overweight of the motion load of the ith machine axis,>and->The degree of overweight of the motion load of the 1 st and (n-1) th data points in the speed differential sequence of the ith machine tool axis is respectively shown.
In order to enable the overweight degree of the motion load to represent the motion load characteristic of each processing time data point in the processing speed sequence, the overweight degree of the motion load sequence is taken as a set of time sequence data, and the overweight degree of the motion load at the nth time is predicted by using a neural network according to the overweight degree of the motion load at the (n-1) time in the overweight degree of the motion load sequence. The neural network is an LSTM neural network, a cross entropy function is used as a loss function, an Adam algorithm is used as an optimization algorithm, the input of the neural network is the overweight degree of the moving load at (n-1) moment in the overweight degree sequence of the moving load of the ith machine tool shaft, and the output of the neural network is the overweight degree of the moving load of the ith machine tool shaftThe overweight degree of the exercise load at the nth moment in the degree sequence is recorded as the acquired overweight degree of the exercise load at the nth momentThe training of the neural network is a well-known technique, and the specific process is not described in detail.
In particular, a sequence of the degree of overweight of the motion load with a sequence length of n is obtained, which corresponds one-to-one to the sequence of the processing speeds of the machine axes of the ith machine axis, i.eA1 st machining speed of the machining speed sequence representing the ith machine axis corresponds to the degree of overweight of the moving load at the machining moment, +.>The 2 nd machining speed of the machining speed sequence representing the ith machine axis corresponds to the degree of overweight of the moving load at the machining moment …, +.>The nth processing speed of the processing speed sequence of the machine tool shaft of the ith machine tool shaft corresponds to the overweight degree of the motion load at the processing time.
Thus, the overweight degree of the motion load of each machining speed of each machine tool shaft corresponding to the machining time and the jitter effect index of each local speed extremum data point corresponding to the machining time are obtained. Because the local speed extremum data point is determined by the extremum points in the processing speed sequence, the processing time corresponding to the local speed extremum data point can be obtained by traversing the position of the local speed extremum data point in the processing speed sequence, and meanwhile, the overweight degree of the motion load and the jitter effect index corresponding to the processing time can be obtained. The overweight degree of the moving load and the jitter effect index can reflect abnormal information of a machine tool shaft to a certain extent, and the greater the jitter effect is, the greater the moving load degree is, and the overweight degree of the moving load at the corresponding processing time is updated by adding and averaging the overweight degree of the moving load at the processing time corresponding to the local speed extremum data point and the jitter effect index.
The method comprises the steps of obtaining the overweight degree of the updated motion load of each processing speed corresponding to the processing time in the processing speed sequence of each machine axis, and recording the overweight degree of the updated motion load of the processing time corresponding to the x-th processing speed in the processing speed sequence of the i-th machine axis as the overweight degree of the updated motion load of the processing time corresponding to the x-th processing speed. Since the machine axis should be as heavy as possible while being loaded in the denture cutting process, there is a high possibility that this will cause damage to the machine.
Here, the combined load overweight degree of the xth processing speed in the processing speed sequence corresponding to the processing time is calculated：
In the method, in the process of the invention,indicating the degree of combined load overweight at the processing time corresponding to the xth processing speed in the processing speed sequence,/->To round down the function ++>The update motion load overweight degree of the x-th machining speed corresponding to the machining moment in the machining speed sequences of the 1 st, 2 nd, 3 rd, 4 th and 5 th machine tool axes is respectively shown.
And S004, marking the processing time when the combined load is overweight, and slowly adjusting the processing speed to finish the control of the rapid denture cutting speed.
The greater the degree of combined load overweight, the more likely damage to the machine tool will occur. And setting a judging threshold value for the overweight degree of the combined load, wherein the experience value of the judging threshold value is 3, marking the time when the overweight degree of the combined load is higher than 3 at the corresponding processing time, and reducing the processing speed of the false tooth at the marked processing time when the same false tooth is produced next time, so as to realize the control of the processing speed of a machine tool in the false tooth processing.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. The above description is only of the preferred embodiments of the present invention and is not intended to limit the invention, but any modifications, equivalent substitutions, improvements, etc. within the principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. The rapid denture cutting speed control method based on data analysis is characterized by comprising the following steps of:
acquiring processing speed data, and acquiring a processing speed matrix by using the processing speed data;
acquiring local speed extremum data points in a processing speed sequence of each machine tool shaft according to the processing speed matrix; obtaining a jitter effect index of the local speed extremum data point of each machine tool shaft corresponding to the processing time according to the local speed extremum data point of the processing speed sequence of each machine tool shaft; acquiring a speed differential sequence of each machine tool shaft according to the processing speed change of adjacent processing time in the processing speed sequence of each machine tool shaft, and acquiring a distance characteristic sequence of each element in the speed differential sequence of each machine tool shaft according to the speed differential sequence of each machine tool shaft; acquiring the overweight degree of the motion load of each element in the speed differential sequence of each machine tool shaft according to the similarity between the distance characteristic sequences of adjacent elements in the speed differential sequence of each machine tool shaft;
acquiring a motion load overweight degree sequence of each machine tool shaft according to the motion load overweight degree of each data point in the speed differential sequence of each machine tool shaft; acquiring updated motion load overweight degree of each machine tool shaft at each machining moment according to the motion load overweight degree sequence of each machine tool shaft; acquiring the combined load overweight degree of each corresponding processing moment according to the updated motion load overweight degree of each processing moment of each machine tool shaft;
marking the processing time when the combined load overweight degree is higher than the preset parameter, and regulating and controlling the cutting processing speed according to the marked denture processing time.
2. The rapid denture cutting speed control method based on data analysis according to claim 1, wherein the method for acquiring the local speed extremum data points in the processing speed sequence of each machine axis according to the processing speed matrix is as follows:
acquiring a processing speed sequence of each machine tool shaft according to the processing speed matrix; acquiring a processing speed function corresponding to a processing speed sequence of each machine tool shaft by using a nonlinear fitting algorithm; the maximum point in the processing speed function is taken as a local speed extremum data point in the processing speed sequence of each machine tool shaft.
3. The rapid denture cutting speed control method based on data analysis according to claim 1, wherein the method for acquiring the jitter effect index of each local speed extremum data point of each machine axis corresponding to the machining time according to each local speed extremum data point in the machining speed sequence of each machine axis is as follows:
acquiring overspeed effect indexes of each local speed extremum data point of each machine tool shaft according to the processing speed of each local speed extremum data point of each machine tool shaft;
setting a sequence window with a preset size by taking each local speed extremum data point of the processing speed sequence of each machine tool shaft as a center according to the obtained processing speed sequence of each machine tool shaft;
acquiring the change degree of each target data point in the sequence window of each local speed extremum data point in each machine tool axis according to the processing speed in the sequence window of each local speed extremum data point of each machine tool axis;
taking the number of target data points in a sequence window of each local speed extremum data point in each machine tool axis as denominator, taking the accumulation of the change degree on the sequence window as numerator, and taking the ratio of the numerator to the denominator as the average change degree of each local speed extremum data point in each machine tool axis;
and taking the normalization result of the product of the overspeed effect index of each local speed extremum data point in each machine tool axis and the average change degree of each local speed extremum data point in each machine tool axis as the jitter effect index of each local speed extremum data point of each machine tool axis corresponding to the processing time.
4. The rapid denture cutting speed control method based on data analysis according to claim 3, wherein the method for obtaining the overspeed effect index of each machine axis local speed extremum data point according to the processing speed of each machine axis local speed extremum data point is as follows:
in the method, in the process of the invention,overspeed effect index, ++f, representing the jth local speed extremum data point of the ith machine axis>Processing speed of the jth local speed extremum data point representing the ith machine axis, +.>Indicating the maximum allowable speed of the ith machine axis.
5. A rapid denture cutting speed control method according to claim 3 wherein said means for obtaining the degree of change of each target data point within the sequence of each local speed extremum data point in each machine axis from the processing speed within the sequence of each local speed extremum data point for each machine axis is:
in the method, in the process of the invention,degree of change of the s-th target data point in the sequence window of the j-th local speed extremum data point representing the i-th machine axis,/->And->The processing speeds of the (s-1) th target data point and the (s-1) th target data point in the sequence window of the jth local speed extremum data point of the ith machine tool shaft are respectively expressed.
6. The rapid denture cutting speed control method based on data analysis according to claim 1, wherein the method for obtaining a speed differential sequence of each machine axis according to the processing speed variation of the adjacent processing time in the processing speed sequence of each machine axis, and obtaining a distance characteristic sequence at each speed differential position in the speed differential sequence of each machine axis according to the speed differential sequence of each machine axis comprises the following steps:
for the processing speed sequence of each machine tool shaft, taking a sequence formed by the difference value of the processing speed at the next moment and the processing speed at the previous moment in the processing speed sequence as a speed difference sequence of each machine tool shaft;
according to the speed differential sequence of each machine tool shaft, detecting a mutation point to obtain a mutation speed differential sequence of the corresponding machine tool shaft;
and acquiring a distance characteristic sequence at each speed differential position in the speed differential sequence of each machine tool shaft based on the Euclidean distance between the data point at each speed differential position in the speed differential sequence of each machine tool shaft and each data point in the abrupt speed differential sequence of each machine tool shaft according to the acquired speed differential sequence of each machine tool shaft and the abrupt speed differential sequence of each machine tool shaft.
7. The rapid denture cutting speed control method based on data analysis according to claim 1, wherein the method for obtaining the overweight degree of the motion load of each data point in the speed differential sequence of each machine axis according to the similarity between the distance characteristic sequences at the adjacent speed differential positions in the speed differential sequence of each machine axis is as follows:
taking the DTW distance between the distance characteristic sequence of each data point in the speed differential sequence of each machine tool axis and the distance characteristic sequence of each adjacent data point as the variation degree of each data point in the speed differential sequence of each machine tool axis and each adjacent data point;
acquiring average absolute differences between the distance characteristic sequences of each data point in the speed differential sequence of each machine tool axis and the distance characteristic sequences of each adjacent data point according to each distance characteristic value in the distance characteristic sequences of each data point in the speed differential sequence of each machine tool axis and each adjacent data point;
and accumulating the adjacent data points of each data point in the speed differential sequence of each machine tool axis by using the product of the variation degree of each data point and the average absolute difference of each adjacent data point as a numerator, using the number of the adjacent data points of the data points as a denominator, and using the normalized value of the ratio of the numerator to the denominator as the overweight degree of the motion load of each data point in the speed differential sequence of each machine tool axis.
8. The method for controlling a rapid denture cutting speed based on data analysis according to claim 7, wherein the method for obtaining the average absolute difference between the distance characteristic sequence of each data point in the speed differential sequence of each machine axis and the distance characteristic sequence of each adjacent data point according to the distance characteristic value of each data point in the speed differential sequence of each machine axis and the distance characteristic sequence of each adjacent data point is as follows:
in the method, in the process of the invention,indicating the (th) in the speed differential sequence of the ith machine axis>Average absolute difference between distance signature of data point and distance signature of its q-th adjacent data point,/v>Representing the length of the distance characteristic sequence in the speed differential sequence of the ith machine axis, +.>Indicating the (th) in the speed differential sequence of the ith machine axis>H distance feature value in distance feature sequence of data points +.>Indicating the (th) in the speed differential sequence of the ith machine axis>The h-th distance feature value in the distance feature sequence of the q-th adjacent data point of the data points.
9. The rapid denture cutting speed control method based on data analysis according to claim 1, wherein the method for obtaining the updated motion load overweight degree of each corresponding processing time of each machine axis according to the motion load overweight degree sequence of each machine axis is as follows:
taking the overweight degree of the motion load at a plurality of continuous preset moments as the input of a prediction model, and taking the output of the prediction model as the overweight degree of the motion load at the predicted moments;
and acquiring an average value of the overweight degree of the motion load and the jitter effect index at the processing time corresponding to the local speed extremum data point, and updating the overweight degree of the motion load by using the average value as the updated overweight degree of the motion load, thereby acquiring the updated overweight degree of the motion load at each corresponding processing time of each machine tool axis.
10. The rapid denture cutting speed control method based on data analysis according to claim 1, wherein the method for obtaining the combined load overweight degree of each corresponding processing time according to the updated motion load overweight degree of each corresponding processing time of each machine axis is as follows:
respectively obtaining the overweight degree of the updated motion load of each corresponding machining moment of each machine tool shaft;
and taking the sum of the updated motion load overweight degrees of each corresponding processing moment of the machine tool shaft as an input of a downward rounding function, and taking the output of the downward rounding function as the combined load overweight degree of each corresponding processing moment.
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