CN111266926B - Method and system for accurately monitoring cutting power of machine tool spindle - Google Patents

Method and system for accurately monitoring cutting power of machine tool spindle Download PDF

Info

Publication number
CN111266926B
CN111266926B CN202010200206.4A CN202010200206A CN111266926B CN 111266926 B CN111266926 B CN 111266926B CN 202010200206 A CN202010200206 A CN 202010200206A CN 111266926 B CN111266926 B CN 111266926B
Authority
CN
China
Prior art keywords
power
machine tool
data
cutting
spindle
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010200206.4A
Other languages
Chinese (zh)
Other versions
CN111266926A (en
Inventor
胡勇
田广军
郭晓磊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Bosheng Prewi Shanghai Tools Co ltd
Original Assignee
Bosheng Prewi Shanghai Tools Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Bosheng Prewi Shanghai Tools Co ltd filed Critical Bosheng Prewi Shanghai Tools Co ltd
Priority to CN202010200206.4A priority Critical patent/CN111266926B/en
Publication of CN111266926A publication Critical patent/CN111266926A/en
Application granted granted Critical
Publication of CN111266926B publication Critical patent/CN111266926B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/09—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool
    • B23Q17/0952—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool during machining
    • B23Q17/0961—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool during machining by measuring power, current or torque of a motor
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/09—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool
    • B23Q17/0952—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool during machining
    • B23Q17/0966—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool during machining by measuring a force on parts of the machine other than a motor

Landscapes

  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Numerical Control (AREA)

Abstract

The invention discloses a method and a system for accurately monitoring cutting power of a machine tool spindle, and belongs to the technical field of machine manufacturing. The monitoring method of the invention firstly identifies the type of the machine tool and the composition structure of the main transmission system to formulate a proper dynamic load loss coefficient alpha calculation method, and secondly identifies the no-load power P of the machine tool at different rotating speedsiAnd input power PtThe method comprises the steps of collecting and filtering, selecting a matched dynamic load loss coefficient alpha calculation formula according to the type of the machine tool and the composition structure of a main transmission system, obtaining the dynamic load loss coefficient alpha of the machine tool based on a least square method, and finally calculating to obtain the cutting power of a main shaft of the machine tool at different rotating speeds, so that the error of a power original signal can be eliminated, the accuracy of data obtained through monitoring and calculation is ensured, and the average error rate of the obtained monitoring result is lower than 1.5%. The monitoring system for the cutting power of the machine tool spindle is simple in structure and convenient to operate, and the obtained monitoring result is accurate.

Description

Method and system for accurately monitoring cutting power of machine tool spindle
Technical Field
The invention relates to the technical field of machine manufacturing, in particular to a method and a system for accurately monitoring cutting power of a machine tool spindle.
Background
In recent years, with the introduction of slogans such as green manufacturing, the improvement of the energy efficiency of a machining system becomes an important content of energy conservation, emission reduction and green manufacturing research. The key for evaluating the energy efficiency of the machine tool is to acquire the energy consumption and cutting power P for cutting of the machine tool in real timecIs the power consumed when the main shaft of the machine tool drives the cutter to cut the workpiece material, so the cutting power PcIs an important parameter for measuring the cutting energy consumption, and has great significance for obtaining accurate cutting power.
At present, the cutting power monitoring method is mainly to directly monitor or indirectly monitor the cutting power from a machine tool control box through a power sensor. Wherein the direct monitoring is based on Pt＝Pi+Pu+PcAccording to the formula, the input power of the main shaft of the machine tool is separated, but interference is easily introduced in the acquisition process of the input power, and the monitoring accuracy is reduced. Wherein, PtFor power input to machine tool spindle，PiAt no load power, PuPower is lost for the additional load.
Indirectly monitored cutting power PcBy means of a cut power PcAfter the coefficient in the empirical formula is subjected to data fitting calculation, substituting the coefficient into the empirical formula and then measuring the input power P of the machine tool spindletCalculating the cutting power Pc. For example, a china journal document entitled method for estimating cutting power of a numerically controlled machine tool online ("machine tool and hydraulic pressure", 1 month 2014, vol 42, 1 st), discloses a method for indirectly estimating cutting power online through input power of a spindle motor without measuring cutting force. According to the scheme, an additional load loss power characteristic function of a main transmission system of a machine tool to be measured is obtained through an experimental method, and then cutting power is calculated by measuring the input power of a spindle motor in real time and combining the additional load loss characteristic of the spindle system.
Also as the invention and creation name is the Chinese patent document of the machine tool working step energy consumption monitoring method (application number is 2016102747776) based on the least square iterative algorithm. The monitoring method of the application comprises the following steps: firstly, the method comprises the following steps: collecting input power of a main transmission system of the machine tool, and filtering an input power signal; II, secondly: judging the online running state of the machine tool through the analysis of the input power data of the main transmission system of the machine tool; thirdly, the method comprises the following steps: the cutting power is estimated by measuring the real-time power of a main shaft of the machine tool and combining a power balance equation of a main transmission system of the machine tool and the loss characteristic of an additional load, and a reasonable cutting energy consumption model is established to achieve the on-line estimation of the cutting power of the machine tool; fourthly, the method comprises the following steps: and solving the cutting power parameter of the machine tool by using an off-line identification algorithm of the additional loss function coefficient of the machine tool based on a least square iterative algorithm.
However, in practice, it has been found that the cutting power P is obtained by the above-mentioned methodcIn the indirect detection, the dynamic load loss coefficient is determined without considering the type of the machine tool and the composition structure of the main transmission system
Figure GDA0003263425470000011
Substitution into Pt＝Pi+Pu+PcThen indirectly measureCalculate PcThe method has the disadvantages of complicated steps, complicated calculation, unsuitability for machine tools with different types of machine tools and different main transmission system composition structures, and limitation, so the monitored cutting power PcThe error is large.
Disclosure of Invention
1. Technical problem to be solved by the invention
The invention aims to overcome the defect that the monitoring of the cutting power of the machine tool spindle in the prior art cannot be adjusted along with the change of the type of the machine tool and the composition structure of a main transmission system, so that the monitoring result has larger error, and provides a method for accurately monitoring the cutting power of the machine tool spindle. The scheme identifies the type of the machine tool and the composition structure of the main transmission system, and calculates the loss power P of the additional load by adopting a least square methoduAnd cutting power PCAccording to the dynamic load loss coefficient alpha of the ratio
Figure GDA0003263425470000021
Calculating the cutting power PcThereby improving the accuracy of the results obtained by monitoring.
The invention also aims to provide a system for monitoring the cutting power of the spindle of the machine tool, which has the advantages of simple structure, convenient operation and accurate obtained monitoring result.
2. Technical scheme
In order to achieve the purpose, the technical scheme provided by the invention is as follows:
the invention discloses a method for accurately monitoring cutting power of a machine tool spindle, which comprises the following steps:
step one, identifying the type of a machine tool and a main transmission system composition structure;
secondly, connecting one end of a power sensor into a main shaft circuit of a machine tool control box, and connecting the other end of the power sensor into a data processing computer; starting the machine tool, and setting the rotating speed of a main shaft of the machine tool as a preset value;
step three, acquiring the no-load power original signal P of the main shaft by using the power sensori' and filtering the obtained data to obtain the original signal P with no-load poweri' corresponding no-load power Pi；
Step four, acquiring an input power original signal P of the machine tool during cutting at the corresponding rotating speed in the step three by using a power sensort' and filtering the obtained data to obtain the original signal P of input powert' corresponding input Power Pt；
Step five, adjusting the rotating speed of the machine tool spindle, and repeating the step three and the step four to obtain the no-load power P of the spindle at different rotating speedsiAnd input power Pt，
Wherein, if the machine tool has an auxiliary system working during cutting, the auxiliary power P is measuredf；
Step six, according to the machine tool type and the main transmission system composition structure identified in the step one, selecting a matched dynamic load loss coefficient alpha calculation formula, calculating the dynamic load loss coefficient alpha by using a least square method,
wherein, when the machine tool is a common machine tool, the calculation formula is
Figure GDA0003263425470000022
When the machine tool is a numerically controlled machine tool,
Figure GDA0003263425470000023
wherein, PuLoss of power for additional load, PcC, alpha, as cutting power1And alpha0Are all constants;
step seven, obtaining the no-load power P according to the step fiveiAnd input power PtAnd calculating the cutting power P of the spindle of the machine tool at different rotating speeds according to the dynamic load loss coefficient alpha obtained in the step sixc；
Wherein, for a common machine tool:
Figure GDA0003263425470000031
for a common machine tool with an auxiliary system
Figure GDA0003263425470000032
For a numerically controlled machine tool:
Figure GDA0003263425470000033
for a numerically controlled machine tool with an auxiliary system:
Figure GDA0003263425470000034
further, in the third step, the original signal P of the idle load power is filtered by adopting the anti-pulse interference sliding average based on the wavelet packeti' carrying out filtering processing and obtaining the corresponding no-load power P at the rotating speedi(ii) a The filtering process specifically includes the steps of:
s21, collecting a main shaft no-load power original signal P containing noise interference through a power sensor at the same rotating speed at intervalsiAcquiring a first set consisting of a plurality of data, selecting a proper wavelet and determining the number of wavelet packet decomposition layers, and performing wavelet packet decomposition on the data in the first set;
s22, calculating an optimal tree, selecting a proper threshold value to carry out threshold value quantization on the wavelet packet decomposition coefficient, reconstructing data in the first set according to the decomposition coefficient, and obtaining a second set consisting of a plurality of data;
s23, putting the first n data of the second set into a queue memory M [ n ];
s24, placing the n +1+ i data of the second set at the tail of a queue memory M [ n ], and discarding 1 data at the head of the queue, wherein i is the number of times that S24 has been executed;
s25, discarding the data with the maximum value and the data with the minimum value in the queue memory M [ n ], and calculating the average value of the rest n-2 data;
S26、judging whether the data in the second set are completely processed, if not, returning to the step S24; if the processing is finished, outputting the average value obtained in the step S25 as the no-load power P corresponding to the rotating speed in the step S21i。
Further, in the step S23, the value range of n is 3-14.
Furthermore, in the fourth step, the original signal P of the input power is filtered by adopting a wavelet packet-based anti-pulse interference moving average filtering methodt' carry out filtering process and obtain the corresponding input power Pt(ii) a The filtering process specifically includes the steps of:
s31, collecting an input power original signal P containing noise interference through a power sensor at the same rotating speed at intervalstAcquiring a third set consisting of a plurality of data, selecting a proper wavelet and determining the number of wavelet packet decomposition layers, and performing wavelet packet decomposition on the data in the third set;
s32, calculating an optimal tree, selecting a proper threshold value to carry out threshold value quantization on the wavelet packet decomposition coefficient, reconstructing data in the third set according to the decomposition coefficient, and obtaining a fourth set consisting of a plurality of data;
s33, putting the first M data of the fourth set into a queue memory M [ M ];
s34, placing the (M +1+ j) th data of the fourth set at the tail of a queue memory M [ M ], and discarding the 1 data at the head of the queue, wherein j is the number of times that S34 has been executed;
s35, discarding the data with the largest value and the data with the smallest value in the queue memory M [ M ], and calculating the average value of the rest M-2 data;
s36, judging whether the data in the fourth set are completely processed, if not, returning to the step S34; if the processing is finished, the average value obtained in the step S35 is the input power P corresponding to the rotating speed in the step S31t。
Further, in the step S33, the value range of m is 3-14.
Further, in the sixth step,carrying out a plurality of tests, and carrying out no-load power P for each testiAnd input power PtMultiple acquisition is carried out, and corresponding cutting power P is simultaneously obtainedcReal-time acquisition is carried out, and then the dynamic load loss coefficient alpha is calculated according to the following process:
xnβ＝yn n∈{ni,i＝1,2,3,4...,k}
β＝(xn Txn)-1xn Tyn n∈{ni,i＝1,2,3,4...,k}
wherein:
for a common machine tool:
xn＝[Pc1 Pc2 ... PcL]T，yn＝[Pt1-Pi Pt2-Pi ... PtL-Pi]T，β＝[1+α]
for a common machine tool with an auxiliary system:
xn＝[Pc1 Pc2 ... PcL]T，yn＝[Pt1-Pi-Pf Pt2-Pi-Pf ... PtL-Pi-Pf]T，β＝[1+α]
for a numerically controlled machine tool:
Figure GDA0003263425470000041
for a numerically controlled machine tool with an auxiliary system:
Figure GDA0003263425470000042
wherein:
n-number of test groups;
l is the data acquisition times of each group of tests;
PcL-the L-th acquired real-time measurement of cutting power;
PtL-the input power acquisition value of the lth acquisition;
Pi-no-load power acquisition value;
Pf-secondary power acquisition values.
Further, in the fifth step, when the rotating speed of the main shaft is changed, after the main shaft rotates for 15-30 seconds, the third step and the fourth step are repeated.
Further, the second step further comprises a process of operating the machine tool for 15-30 min after the machine tool is started so that the current of the main shaft of the machine tool is constant.
Further, the auxiliary power PfAccording to the input power PtOr no load power PiAnd performing filtering processing by using the consistent filtering processing method.
The invention discloses a system for accurately monitoring the cutting power of a machine tool spindle, which is used for the monitoring method and is characterized in that: the machine tool comprises a machine tool, a control box, a power sensor, a torque sensor and a data processing device, wherein a main shaft of the machine tool is driven by a driving motor, the driving motor is electrically connected with the control box, the control box is electrically connected with the power sensor, the torque sensor is fixedly arranged below a workpiece, and the power sensor and the torque sensor are electrically connected with the data processing device;
the monitoring system is configured to: the power sensor generates a power signal according to current in the control box, the torque sensor is used for collecting a cutting power real-time signal of the main shaft, and the data processing device carries out filtering processing and calculation evaluation on the power signal and the cutting power real-time signal.
3. Advantageous effects
Compared with the prior art, the technical scheme provided by the invention has the following beneficial effects:
(1) the invention relates to a method for monitoring the cutting power of a machine tool spindle, which comprises the steps of firstly identifying the type of a machine tool and the composition structure of a main transmission system to formulate a proper dynamic load loss coefficient alpha calculation formula, and secondly identifying the no-load power P of the machine tool at different rotating speedsiAnd input power PtPerforming collection andfiltering, selecting a matched dynamic load loss coefficient alpha calculation formula according to the type of the machine tool and the composition structure of the main transmission system, obtaining the dynamic load loss coefficient alpha of the machine tool based on a least square method, and finally obtaining the dynamic load loss coefficient alpha of the machine tool according to the formula
Figure GDA0003263425470000051
And calculating to obtain the cutting power of the machine tool spindle at different rotating speeds. Therefore, the invention sets a proper dynamic load loss coefficient alpha calculation formula according to the type of the machine tool and the composition structure of the main transmission system, and inputs power P through filtering processingtSeparating layer by layer, monitoring and optimizing the power signal layer by layer, eliminating the error of the power original signal to the maximum extent, ensuring the accuracy of each data obtained by monitoring and calculating, and finally obtaining the data according to a formula
Figure GDA0003263425470000052
Directly obtaining cutting power PcThe method is simple, the efficiency is high, the average error rate of the obtained monitoring result is lower than 1.5%, and the accuracy is high.
(2) In the invention, the original signal P of the empty-load power is filtered by adopting the anti-pulse interference sliding average based on the wavelet packeti' sum input power original signal Pt' carrying out filtering processing and obtaining the corresponding no-load power P at the rotating speediAnd input power PtSubstantially eliminating the no-load power original signal Pi' sum input power original signal PtThe periodic impulse interference and random non-stationary noise in the' well-preserved no-load power original signal Pi' sum input power original signal PtUseful information in. Therefore, the anti-pulse interference sliding average filtering based on the wavelet packet can effectively process the empty-load power original signal Pi' sum input power original signal Pt' noise reduction and error processing are performed to increase the no-load power PiAnd input power PtThe accuracy of (2).
(3) In the invention, the specific value of the dynamic load loss coefficient alpha is obtained by using a least square method, and the least square method can search the additional load loss by minimizing the sum of squares of errorsPower PuAnd cutting power PcThe ratio dynamic load loss coefficient alpha is the most accurate matching value, the least square method is simple to operate and quick and simple to calculate, and the sum of squares of errors between the calculated data and actual data is minimized, so that the calculated cutting power P can be ensuredcAnd (4) precision.
(4) The monitoring system comprises a machine tool, a control box, a power sensor, a torque sensor and a data processing device, wherein a main shaft of the machine tool is driven by a driving motor, and the driving motor, the control box, the power sensor and the data processing device are electrically connected; the power sensor generates a power signal according to the current in the control box and transmits the power signal to the data processing device, and the data processing device carries out filtering processing and calculation evaluation on the power signal and obtains the cutting power of the machine tool spindle.
Drawings
FIG. 1 is a flow chart of a method for monitoring the cutting power of a spindle of a machine tool according to the present invention;
FIG. 2 is a flow chart of a processing method of the wavelet packet anti-pulse interference sliding average filtering method of the present invention;
fig. 3 is a schematic structural diagram of the monitoring system of the present invention.
The reference numerals in the schematic drawings illustrate: 1. a main shaft; 2. a control box; 3. a power sensor; 4. a torque sensor; 5. a data processing device; 6. and (5) a workpiece.
Detailed Description
For a further understanding of the invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings and examples.
The structure, proportion, size and the like shown in the drawings are only used for matching with the content disclosed in the specification, so that the person skilled in the art can understand and read the description, and the description is not used for limiting the limit condition of the implementation of the invention, so the method has no technical essence, and any structural modification, proportion relation change or size adjustment still falls within the scope of the technical content disclosed by the invention without affecting the effect and the achievable purpose of the invention. In addition, the terms "upper", "lower", "left", "right" and "middle" used in the present specification are for clarity of description, and are not intended to limit the scope of the present invention, and the relative relationship between the terms and the relative positions may be changed or adjusted without substantial technical changes.
Input power P of machine tool spindle for cutting machining in related arttNo load power PiParasitic load loss power PuAuxiliary power PfAnd cutting power PcSatisfies the following conditions:
Pt＝Pi+Pu+Pf+Pc (1)
wherein the parasitic load loses power PuIs complicated to form and mainly comprises additional electric loss and mechanical consumption generated by the motor and the mechanical transmission part in a cutting state, so that additional load loses power PuIt cannot be measured directly. In the related field, for a main transmission system of a common machine tool (the operating power frequency of a motor is 50Hz), the additional load loss coefficient alpha is approximately constant (Liufei, the energy characteristic of a mechanical processing system and the application thereof [ M [)]Beijing mechanical industry press, 1995) and is only concerned with the performance of the machine tool itself; for numerically controlled machine tool, additional load loses power PuCan be approximately expressed as cutting power PcThe relationship of the quadratic function of (Hu S, Liu F, He Y, et al. characteristics of additive Load loads of Spindle System of Machine Tools [ J].Journal of Advanced Mechanical Design,Systems,and Manufacturing,2010,4(7):1221-1233.)。
Therefore, for a normal machine tool, the dynamic load loss coefficient α is:
Figure GDA0003263425470000071
for a numerically controlled machine tool, the dynamic load loss coefficient α is:
Figure GDA0003263425470000072
substituting equations (2) and (3) into equation (1) respectively, there are:
for a common machine tool:
Figure GDA0003263425470000073
for a common machine tool with an auxiliary system
Figure GDA0003263425470000074
For a numerically controlled machine tool:
Figure GDA0003263425470000075
for a numerically controlled machine tool with an auxiliary system:
Figure GDA0003263425470000076
for equations (4), (5), (6) and (7), the no-load power PiAuxiliary power PfAnd input power PtCan be directly obtained by measurement, so that the cutting power P can be indirectly calculated according to the formulas (4), (5), (6) and (7) by only obtaining the value of the dynamic load loss coefficient alphac. For the value of the dynamic load loss coefficient α, the present embodiment uses the least square method to calculate, and the least square method can search the most accurate matching value of the load loss coefficient α by minimizing the sum of squares of errors, so that the sum of squares of errors between these obtained data and actual data is minimized, thereby ensuring that the cutting power P calculated according to the formulas (4), (5), (6) and (7) is the minimumcAnd (4) precision.
For no load power PiAuxiliary power PfAnd input power PtCollecting and processing machine toolUnder complex working conditions, noise interference is often introduced, so that the detection data is not accurate enough, and therefore, the embodiment firstly collects the no-load power original signal Pi', auxiliary power Pf' sum input power original signal Pt' performing a filtering process to remove noise interference, thereby further increasing the calculated cutting power PcAnd (4) precision.
As a possible implementation mode, the filtering processing can adopt a filtering processing method of pulse interference prevention moving average based on a wavelet packet, so as to remove the no-load power original signal Pi' sum input power original signal PtThe periodic impulse disturbances and random non-stationary noise in' are present.
Therefore, referring to fig. 1, the method for accurately monitoring the cutting power of the spindle of the machine tool in the embodiment specifically includes the following steps:
firstly, identifying the type of a machine tool and a main transmission system composition structure, and formulating a proper dynamic load loss coefficient alpha calculation formula
Wherein, the dynamic load loss coefficient of the common machine tool during cutting
Figure GDA0003263425470000081
Wherein c is a constant; dynamic load loss coefficient of numerical control machine tool during cutting
Figure GDA0003263425470000082
Wherein a is1And a0Is a constant;
secondly, one end of a power sensor is connected into a spindle circuit in a control box, and the other end of the power sensor is connected into a data processing device; and starting the machine tool, and setting the rotating speed of the main shaft of the machine tool as a preset value.
Wherein, after the machine tool is started, the no-load power P is collectediAnd input power PtBefore, the machine tool needs to run for 15-30 min, such as 18min, 20min, 22min and 25min, so that the current of the main shaft of the machine tool is constant. Meanwhile, all parts of the machine tool can be fully lubricated, the local temperature of the circuit board is increased along with the increase of the temperature, the work of electronic devices tends to be stable, and the screw rod and the guide railThe constant temperature is achieved, so that the precision of the power signal during collection can be ensured.
Step three, acquiring the no-load power original signal P of the main shaft by using the power sensori' and filtering the obtained data to obtain the original signal P with no-load poweri' corresponding no-load power Pi。
Wherein, the original signal P of the empty-load power is processed by adopting the anti-pulse interference sliding average filtering based on the wavelet packeti' carrying out filtering processing and obtaining the corresponding no-load power P at the rotating speedi. Referring to fig. 2, the filtering process specifically includes the steps of:
s21, collecting a main shaft no-load power original signal P containing noise interference through a power sensor at the same rotating speed at intervalsiObtaining a first set of a plurality of data, selecting a proper wavelet and determining the number of wavelet packet decomposition layers, and carrying out wavelet packet decomposition on the data in the first set.
S22, calculating an optimal tree, selecting a proper threshold value to carry out threshold value quantization on the wavelet packet decomposition coefficient, reconstructing data in the first set according to the decomposition coefficient, and obtaining a second set consisting of a plurality of data.
S23, the first n data of the second set are put into a queue memory M [ n ]. In the step, the value of n is 3-14, when the value of n is equal to 2, a new data is added, the maximum value and the minimum value are removed, only one median value is left, and the median value actually obtained by adopting the wavelet packet-based anti-pulse interference sliding average filtering processing is the median value of a plurality of data in the second set. When the value of n is less than 2, the wavelet packet-based anti-pulse interference moving average filtering processing method is not applicable. When the value of n is greater than 14, the amount of the acquired data needs to be increased in order to achieve a better filtering processing effect, which is inconvenient.
S24, placing the (n +1+ i) th data of the second set at the tail of the queue memory M [ n ], and discarding the 1 data at the head of the queue, wherein i is the number of times S24 has been executed.
S25, discarding the data with the largest value and the data with the smallest value in the queue memory M [ n ], and calculating the average value of the rest n-2 data.
S26, judging whether the data in the second set are processed completely, if not, returning to the step S24. If the processing is finished, the average value obtained in the step S25 is the no-load power P corresponding to the rotating speed in the step S21i。
Step four, acquiring an input power original signal P of the machine tool during cutting at the corresponding rotating speed in the step three by using a power sensort' and filtering the obtained data to obtain the original signal P of input powert' corresponding input Power Pt。
Wherein, the input power original signal P is subjected to the anti-pulse interference sliding average filtering method based on the wavelet packett' carry out filtering process and obtain the corresponding input power Pt. The filtering process specifically includes the steps of:
s31, collecting an input power original signal P containing noise interference through a power sensor at the same rotating speed at intervalst' obtaining a third set consisting of a plurality of data, selecting a proper wavelet and determining the number of wavelet packet decomposition layers, and carrying out wavelet packet decomposition on the data in the third set.
And S32, calculating an optimal tree, selecting a proper threshold value to carry out threshold value quantization on the wavelet packet decomposition coefficients, reconstructing data in the third set according to the decomposition coefficients, and obtaining a fourth set consisting of a plurality of data.
S33, the first M data of the fourth set are put into a queue memory M [ M ]. The value of m is 3-14.
S34, placing the (M +1+ j) th data of the fourth set at the tail of the queue memory M [ M ], and discarding the 1 data at the head of the queue, wherein j is the number of times that S34 has been executed.
S35, discarding the data with the largest value and the data with the smallest value in the queue memory M [ M ], and calculating the average value of the rest M-2 data.
S36, judging whether the data in the fourth set are processed completely, if not, returning to the step S34. If the treatment is finished, thenOutputting the average value obtained in the step S35 as the input power P corresponding to the rotation speed in the step S31t。
Step five, adjusting the rotating speed of the machine tool spindle, and repeating the step three and the step four to obtain the no-load power P of the spindle at different rotating speedsiAnd input power PtIf the machine tool has an auxiliary system working during cutting, the auxiliary power P is also measuredf。
And when the rotating speed of the main shaft is changed, waiting for 15-30 s of rotation of the main shaft, such as 17s, 21s, 25s and 29s, and repeating the third step and the fourth step after the machine tool is stabilized, so that errors and interference are eliminated to the maximum extent.
If the main transmission system of the numerical control machine tool needs an auxiliary system such as a hydraulic system or a cutter cooling system to assist cutting during cutting, the auxiliary power P of the auxiliary system for filtering processing needs to be measured separatelyfWhen the auxiliary system works, the auxiliary power is constant and only needs to be measured once, and the auxiliary power P is constantfMeasurement filtering processing method and input power PtAnd no load power PiThe measurement filtering processing methods are consistent.
In the third step and the fourth step, the empty load power P is subjected to the anti-pulse interference sliding average filtering method based on the wavelet packetiAuxiliary power PfAnd input power PtAnd filtering the original signal. The anti-pulse interference moving average filtering method can effectively inhibit periodic pulse interference in the signal, and the wavelet packet denoising is suitable for removing random non-stationary noise in the signal. Therefore, the noise and the interference in the power signal of the numerical control machine tool can be thoroughly eliminated by using the two signal processing methods in a combined way, namely the pulse interference prevention moving average filtering method based on the wavelet packet. After being processed by a wavelet packet-based pulse interference prevention sliding average filtering method, the no-load power original signal Pi', auxiliary power Pf' sum input power original signal PtThe periodic impulse interference and random non-stationary noise in the' are substantially eliminated, and the no-load power original signal Pi', auxiliary power Pf' sum input power original signal PtThe useful information in' is well preserved. Due to the fact thatThe wavelet packet-based anti-pulse interference sliding average filtering can effectively process the empty-load power original signal Pi', auxiliary power Pf' sum input power original signal Pt' noise reduction and error processing are performed, increasing the collected no-load power PiAuxiliary power PfAnd input power PtAnd (4) precision.
And step six, selecting a matched dynamic load loss coefficient alpha calculation formula according to the type of the machine tool and the composition structure of the main transmission system, calculating the dynamic load loss coefficient alpha by using a least square method, and calculating the dynamic load loss coefficient alpha by using the least square method. Wherein, for a common machine tool, the calculation formula is
Figure GDA0003263425470000101
For a numerical control machine tool, the calculation formula is
Figure GDA0003263425470000102
Wherein P isuLoss of power for additional load, PcIs the cutting power.
The specific calculation process is as follows:
carrying out a plurality of tests, and carrying out no-load power P for each testiAuxiliary power PfAnd input power PtMultiple acquisition is carried out, and corresponding cutting power P is simultaneously obtainedcUsing a torque sensor to carry out actual measurement, and then calculating the dynamic load loss coefficient alpha according to the following process:
xnβ＝yn n∈{ni,i＝1,2,3,4...,k} (8)
β＝(xn Txn)-1xn Tyn n∈{ni,i＝1,2,3,4...,k} (9)
in equations (8) and (9):
for a common machine tool:
xn＝[Pc1 Pc2 ... PcL]T (10)
yn＝[Pt1-Pi Pt2-Pi ... PtL-Pi]T (11)
β＝[1+α] (12)
for a common machine tool with an auxiliary system:
xn＝[Pc1 Pc2 ... PcL]T (13)
yn＝[Pt1-Pi-Pf Pt2-Pi-Pf ... PtL-Pi-Pf]T (14)
β＝[1+α] (15)
for a numerically controlled machine tool:
xn＝[Pc1 Pc2 ... PcL]T (16)
yn＝[Pt1-Pi Pt2-Pi ... PtL-Pi]T (17)
Figure GDA0003263425470000111
for a numerically controlled machine tool with an auxiliary system:
xn＝[Pc1 Pc2 ... PcL]T (19)
yn＝[Pt1-Pi-Pf Pt2-Pi-Pf ... PtL-Pi-Pf]T (20)
Figure GDA0003263425470000112
wherein:
n-number of test groups;
l is the data acquisition times of each group of tests;
PcLreal-time measurement of the cutting power acquired in the L < th > timeA value;
PtL-the input power acquisition value of the lth acquisition;
Pi-no-load power acquisition value;
Pf-an auxiliary power acquisition value;
step seven, obtaining the no-load power P according to the step fiveiAuxiliary power PfAnd input power PtAnd calculating the cutting power P of the spindle of the machine tool at different rotating speeds according to the dynamic load loss coefficient alpha obtained in the step sixc(ii) a Wherein the cutting power PcIs calculated by the formula
Figure GDA0003263425470000113
If the auxiliary system of the machine tool is working during cutting, the cutting power PcIs calculated by the formula
Figure GDA0003263425470000114
For a common machine tool:
Figure GDA0003263425470000115
for a common machine tool with an auxiliary system
Figure GDA0003263425470000116
For a numerically controlled machine tool:
Figure GDA0003263425470000121
for a numerically controlled machine tool with an auxiliary system:
Figure GDA0003263425470000122
according to the prior theoretical research, when a machine tool main shaft beltWhen the movable cutter cuts the workpiece, the power signal measured by the sensor is not the cutting power PCInstead, the machine spindle input power Pt. If the cutting power P is to be accurately acquiredcThe no-load power P must be adjustediAuxiliary power PfWith additional load loss of power PuAnd (5) measuring. No load power PiThe power consumed when the machine tool spindle stably runs at a specified rotating speed and does not cut workpiece materials can be directly measured by a power sensor; auxiliary power PfThe power consumed by the working of a machine tool hydraulic system and a cutter cooling system when a machine tool spindle cuts a workpiece; while the additional load loses power PuThe loss power added by the load when the machine tool main shaft cuts the processed material, namely the current and mechanical energy loss added by the driving motor and the mechanical transmission, exists only during cutting, can not be directly measured by a power sensor, but can be measured by the additional load loss power PuAnd cutting power PcIndirectly calculating the cutting power Pc. Inputting power P to the main shaft of the machine tooltSeparating layer by layer, acquiring and processing power signals layer by layer, eliminating the error of each layer of power signal to the maximum extent, ensuring the correctness of each acquired and calculated data, and finally obtaining the accurate cutting power Pc。
In order to prove the accuracy of the monitoring method of the embodiment, a verification test is performed in a numerical control machining center of a certain wood factory, wherein the monitored object is a numerical control machine. A wood-plastic composite (WPC) is milled by using a shank milling cutter with the diameter of 12mm, a machine tool does not have an auxiliary system to work during cutting, the rotating speed of a main shaft of the machine tool is changed under the milling conditions that the feeding speed of the machine tool is 600mm/r, the cutting depth is 2mm, and the cutting width is 10mm, the power of each layer is monitored by using a power sensor WT500, the sampling period is 25ms, and the obtained data are shown in Table 1.
Table 1 test cutting parameters
Figure GDA0003263425470000123
Dynamic load loss factor α is calculated using the power data in Table 1Evaluating the rows to obtain alpha finally1＝0.1175,α215.571. Subsequently, the spindle rotation speed was measured at 500 to 6000r/min using a torque sensor, and the measured cutting power value and the error rate between the measured value and the monitored value obtained by the method are shown in table 2.
TABLE 2 cutting test results
Figure GDA0003263425470000124
Figure GDA0003263425470000131
As is clear from table 2, the average error rate of monitoring by monitoring the cutting power of the machine tool spindle according to the present embodiment is 1.4%. In addition, after a plurality of tests are continuously carried out on different types of machine tools, the fact that the average error rate of monitoring obtained by monitoring the cutting power of the machine tool spindle by adopting the method is always lower than 1.5 percent is found, and therefore the method for monitoring the machine tool spindle has high precision.
The embodiment also provides a system for monitoring the cutting power of the spindle of the machine tool, and the system is used for implementing the monitoring method of the embodiment. Referring to fig. 3, it may specifically include a machine tool, a control box 2, a power sensor 3, a torque sensor 4, and a data processing system 5. The machine tool is a machine tool that can be used for cutting machining, and specifically may be a cutting machine tool commonly used in the related art, such as a CNC machine. The main shaft 1 of the machine tool is driven by a drive motor of the machine tool, so that a cutter is driven to cut on a workpiece 6. The driving motor, the control box 2, the power sensor 3 and the data processing system 5 are electrically connected. When the machine tool spindle 1 drives a cutter to cut a workpiece 6, current flows into the power sensor 3 through the control box 2 and generates a power signal, the power sensor 3 transmits the power signal into the data processing system 5, and the data processing system 5 carries out filtering processing and calculation evaluation on the power signal according to the monitoring method of the embodiment, so that a monitoring result of the cutting power of the machine tool spindle 1 can be obtained. The torque sensor 4 is used for measuring the cutting power in real time, calculating the dynamic load loss coefficient alpha and verifying the precision of the method.
The present invention and its embodiments have been described above schematically, without limitation, and what is shown in the drawings is only one of the embodiments of the present invention, and the actual structure is not limited thereto. Therefore, if the person skilled in the art receives the teaching, without departing from the spirit of the invention, the person skilled in the art shall not inventively design the similar structural modes and embodiments to the technical solution, but shall fall within the scope of the invention.

Claims (8)

1. A method for accurately monitoring the cutting power of a main shaft of a machine tool is characterized in that: which comprises the following steps:
step one, identifying the type of a machine tool and a main transmission system composition structure;
secondly, connecting one end of a power sensor into a main shaft circuit of a machine tool control box, and connecting the other end of the power sensor into a data processing computer; starting the machine tool, and setting the rotating speed of a main shaft of the machine tool as a preset value;
step three, acquiring the no-load power original signal P of the main shaft by using the power sensori' adopting a wavelet packet-based pulse interference prevention moving average filtering method to carry out zero power original signal Pi' performing filtering processing to obtain the original signal P with no-load poweri' corresponding no-load power Pi；
Step four, acquiring an input power original signal P of the machine tool during cutting at the corresponding rotating speed in the step three by using a power sensort' the original signal P of input power is filtered by the anti-pulse interference sliding average filtering method based on the wavelet packett' performing filtering processing to obtain the original signal P corresponding to the input powert' corresponding input Power Pt；
Step five, adjusting the rotating speed of the machine tool spindle, and repeating the step three and the step four to obtain the no-load power P of the spindle at different rotating speedsiAnd input power Pt，
Wherein if the machine toolWhen the auxiliary system works during cutting, the auxiliary power P is measuredf；
Step six, according to the machine tool type and the main transmission system composition structure identified in the step one, selecting a matched dynamic load loss coefficient alpha calculation formula, calculating the dynamic load loss coefficient alpha by using a least square method,
wherein, when the machine tool is a common machine tool, the calculation formula is
Figure FDA0003269259820000011
When the machine tool is a numerically controlled machine tool,
Figure FDA0003269259820000012
step seven, obtaining the no-load power P according to the step fiveiAnd input power PtAnd calculating the cutting power P of the spindle of the machine tool at different rotating speeds according to the dynamic load loss coefficient alpha obtained in the step sixc；
Wherein, for a common machine tool:
Figure FDA0003269259820000013
for a common machine tool with an auxiliary system:
Figure FDA0003269259820000014
for a numerically controlled machine tool:
Figure FDA0003269259820000015
for a numerically controlled machine tool with an auxiliary system:
Figure FDA0003269259820000016
wherein, PuLoss of power for additional load, PcC, alpha, as cutting power1And alpha0Are all constants;
in the third step, the empty load power original signal P is processedi' performing the filtering process specifically includes the steps of:
s21, collecting a main shaft no-load power original signal P containing noise interference through a power sensor at the same rotating speed at intervalsiAcquiring a first set consisting of a plurality of data, selecting a proper wavelet and determining the number of wavelet packet decomposition layers, and performing wavelet packet decomposition on the data in the first set;
s22, calculating an optimal tree, selecting a proper threshold value to carry out threshold value quantization on the wavelet packet decomposition coefficient, reconstructing data in the first set according to the decomposition coefficient, and obtaining a second set consisting of a plurality of data;
s23, putting the first n data of the second set into a queue memory M [ n ];
s24, placing the n +1+ i data of the second set at the tail of a queue memory M [ n ], and discarding 1 data at the head of the queue, wherein i is the number of times that S24 has been executed;
s25, discarding the data with the maximum value and the data with the minimum value in the queue memory M [ n ], and calculating the average value of the rest n-2 data;
s26, judging whether the data in the second set are completely processed, if not, returning to the step S24; if the processing is finished, outputting the average value obtained in the step S25 as the no-load power P corresponding to the rotating speed in the step S21i；
In the fourth step, the input power original signal P is processedt' performing the filtering process specifically includes the steps of:
s31, collecting an input power original signal P containing noise interference through a power sensor at the same rotating speed at intervalst' obtaining a third set of a plurality of data, selecting a suitable wavelet and determining the number of wavelet packet decomposition layers, and for the data in the third setCarrying out wavelet packet decomposition;
s32, calculating an optimal tree, selecting a proper threshold value to carry out threshold value quantization on the wavelet packet decomposition coefficient, reconstructing data in the third set according to the decomposition coefficient, and obtaining a fourth set consisting of a plurality of data;
s33, putting the first M data of the fourth set into a queue memory M [ M ];
s34, placing the (M +1+ j) th data of the fourth set at the tail of a queue memory M [ M ], and discarding the 1 data at the head of the queue, wherein j is the number of times that S34 has been executed;
s35, discarding the data with the largest value and the data with the smallest value in the queue memory M [ M ], and calculating the average value of the rest M-2 data;
s36, judging whether the data in the fourth set are completely processed, if not, returning to the step S34; if the processing is finished, the average value obtained in the step S35 is the input power P corresponding to the rotating speed in the step S31t。
2. A method of accurately monitoring the cutting power of a spindle of a machine tool according to claim 1, wherein: in S23, n ranges from 3 to 14.
3. A method of accurately monitoring the cutting power of a spindle of a machine tool according to claim 1, wherein: in the step S33, the value range of m is 3-14.
4. A method of accurately monitoring the cutting power of a spindle of a machine tool according to claim 1, wherein: in the sixth step, a plurality of groups of tests are carried out, and the no-load power P of each group of testsiAnd input power PtMultiple acquisition is carried out, and corresponding cutting power P is simultaneously obtainedcReal-time acquisition is carried out, and then the dynamic load loss coefficient alpha is calculated according to the following process:
xnβ＝yn n∈{ni,i＝1,2,3,4...,k}
β＝(xn Txn)-1xn Tyn n∈{ni,i＝1,2,3,4...,k}
wherein:
for a common machine tool:
xn＝[Pc1 Pc2...PcL]T，yn＝[Pt1-Pi Pt2-Pi...PtL-Pi]T，β＝[1+α]
for a common machine tool with an auxiliary system:
xn＝[Pc1 Pc2...PcL]T，yn＝[Pt1-Pi-Pf Pt2-Pi-Pf...PtL-Pi-Pf]T，β＝[1+α]
for a numerically controlled machine tool:
xn＝[Pc1 Pc2...PcL]T，yn＝[Pt1-Pi Pt2-Pi...PtL-Pi]T，
Figure FDA0003269259820000031
for a numerically controlled machine tool with an auxiliary system:
xn＝[Pc1 Pc2...PcL]T，yn＝[Pt1-Pi-Pf Pt2-Pi-Pf...PtL-Pi-Pf]T，
Figure FDA0003269259820000032
wherein:
n-number of test groups;
l is the data acquisition times of each group of tests;
PcL-the L-th acquired real-time measurement of cutting power;
PtL-the input power acquisition value of the lth acquisition;
Pi-no-load power acquisition value;
Pf-secondary power acquisition values.
5. A method of accurately monitoring the cutting power of a spindle of a machine tool according to claim 1, wherein: and in the fifth step, when the rotating speed of the main shaft is changed, after the main shaft rotates for 15-30 s, repeating the third step and the fourth step.
6. A method of accurately monitoring the cutting power of a spindle of a machine tool according to claim 1, wherein: and in the second step, the process of operating the machine tool for 15-30 min after the machine tool is started so as to enable the current of the main shaft of the machine tool to be constant is also included.
7. A method of accurately monitoring the cutting power of a spindle of a machine tool according to claim 1, wherein: the auxiliary power PfAccording to the input power PtOr no load power PiAnd performing filtering processing by using the consistent filtering processing method.
8. A precise monitoring system of cutting power of a machine tool spindle, which is used for implementing the monitoring method of any one of claims 1-7, and is characterized in that: the machine tool comprises a machine tool, a control box, a power sensor, a torque sensor and a data processing device, wherein a main shaft of the machine tool is driven by a driving motor, the driving motor is electrically connected with the control box, the control box is electrically connected with the power sensor, the torque sensor is fixedly arranged below a workpiece, and the power sensor and the torque sensor are electrically connected with the data processing device;
the monitoring system is configured to: the power sensor generates a power signal according to current in the control box, the torque sensor is used for collecting a cutting power real-time signal of the main shaft, and the data processing device carries out filtering processing and calculation evaluation on the power signal and the cutting power real-time signal.
CN202010200206.4A 2020-03-20 2020-03-20 Method and system for accurately monitoring cutting power of machine tool spindle Active CN111266926B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010200206.4A CN111266926B (en) 2020-03-20 2020-03-20 Method and system for accurately monitoring cutting power of machine tool spindle

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010200206.4A CN111266926B (en) 2020-03-20 2020-03-20 Method and system for accurately monitoring cutting power of machine tool spindle

Publications (2)

Publication Number Publication Date
CN111266926A CN111266926A (en) 2020-06-12
CN111266926B true CN111266926B (en) 2021-10-29

Family

ID=70994526

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010200206.4A Active CN111266926B (en) 2020-03-20 2020-03-20 Method and system for accurately monitoring cutting power of machine tool spindle

Country Status (1)

Country Link
CN (1) CN111266926B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112571151B (en) * 2020-10-21 2022-01-28 重庆工程职业技术学院 Device for measuring additional load loss coefficient of milling machine without cutting
CN113805533B (en) * 2021-09-14 2024-03-26 南京林业大学 Processing method and device for spindle power signal of numerical control machine tool and electronic equipment

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105955198A (en) * 2016-04-28 2016-09-21 江南大学 Machine tool working step energy consumption monitoring method based on least square iterative algorithm

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5199990B2 (en) * 2009-12-17 2013-05-15 日精樹脂工業株式会社 Molding machine hydraulic oil temperature raising method
CN103105820B (en) * 2012-05-22 2014-10-29 华中科技大学 Machining cutter abrasion state identification method of numerical control machine tool
CN104669057B (en) * 2015-01-31 2017-02-22 重庆大学 Additional load loss coefficient acquiring method of machining system of machine tool
CN109725599A (en) * 2017-10-31 2019-05-07 于铃 A kind of numerically-controlled machine tool efficiency on-line monitoring method
CN108133091B (en) * 2017-12-13 2020-05-22 西安交通大学 Method for establishing machine tool carbon emission optimization model based on cutter state
CN109333155A (en) * 2018-10-25 2019-02-15 山东理工大学 Energy efficiency online test method in water ring vacuum pump armature spindle numerical control workshop

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105955198A (en) * 2016-04-28 2016-09-21 江南大学 Machine tool working step energy consumption monitoring method based on least square iterative algorithm

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
基于IMPACT2002+的机械加工过程绿色评价与优化模型研究;潘媛;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20181115(第11期);第29-31页 *
深孔加工过程油压监测信号消噪技术研究;郑建明等;《西安理工大学学报》;20080630;第24卷(第2期);第162-165页 *

Also Published As

Publication number Publication date
CN111266926A (en) 2020-06-12

Similar Documents

Publication Publication Date Title
CN111266926B (en) Method and system for accurately monitoring cutting power of machine tool spindle
CN106181579B (en) A kind of Tool Wear Monitoring method based on multisensor current signal
CN105312965B (en) Breakage monitoring method for milling tool
CN102091972B (en) Numerical control machine tool wear monitoring method
CN102621932B (en) Energy consumption prediction method for use in service process of numerically-controlled machine tool
CN101870076B (en) Method for predicting service life of guide pair of numerical control machine on basis of performance degradation model
CN106842922B (en) Numerical control machining error optimization method
CN111694320B (en) Machine tool self-adaptive control method considering flutter suppression
CN111660141B (en) Milling cutter wear state identification method based on spindle driving current and irrelevant to working conditions
CN110263474A (en) A kind of cutter life real-time predicting method of numerically-controlled machine tool
CN106970593B (en) A method of realizing that processing flutter inhibits online by speed of mainshaft intelligent control
CN112192319A (en) Tool wear monitoring method and system of unsupervised model
Xu et al. A tool breakage monitoring method for end milling based on the indirect electric data of CNC system
CN113126564B (en) Digital twin driven numerical control milling cutter abrasion on-line monitoring method
CN108629864B (en) Vibration-based electric spindle radial precision characterization method and system
CN106141815A (en) A kind of high-speed milling tremor on-line identification method based on AR model
Ammouri et al. Current rise criterion: A process-independent method for tool-condition monitoring and prognostics
CN110346130B (en) Boring flutter detection method based on empirical mode decomposition and time-frequency multi-feature
CN114326593B (en) Cutter life prediction system and method
DE102019122772A1 (en) Machining environment measuring device
CN108363822A (en) Cutter rigid predictions are used to inhibit the device and method of cutting-vibration
CN112819646B (en) Fault diagnosis system for flexible production line of customized wood furniture
CN112475410A (en) Correlation analysis system and method for milling temperature and multivariate influence factors
CN114357851A (en) Numerical control milling surface roughness prediction method based on DAE-RNN
CN109407614B (en) Gear hobbing processing technological parameter optimization method for numerical control gear hobbing machine

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant