CN106271036A - Ultrasonic metal welding method for evaluating quality, device and ultrasonic metal bonding machine - Google Patents
Ultrasonic metal welding method for evaluating quality, device and ultrasonic metal bonding machine Download PDFInfo
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- CN106271036A CN106271036A CN201610662302.4A CN201610662302A CN106271036A CN 106271036 A CN106271036 A CN 106271036A CN 201610662302 A CN201610662302 A CN 201610662302A CN 106271036 A CN106271036 A CN 106271036A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K20/00—Non-electric welding by applying impact or other pressure, with or without the application of heat, e.g. cladding or plating
- B23K20/26—Auxiliary equipment
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K20/00—Non-electric welding by applying impact or other pressure, with or without the application of heat, e.g. cladding or plating
- B23K20/10—Non-electric welding by applying impact or other pressure, with or without the application of heat, e.g. cladding or plating making use of vibrations, e.g. ultrasonic welding
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Abstract
The present invention relates to a kind of ultrasonic metal welding method for evaluating quality, device and ultrasonic metal bonding machine.Described method includes step: metal to be welded carries out ultrasonic metal welding, obtains the welding process information in actual production process；The characteristic parameter of the welding process information in extraction actual production process；Characteristic parameter in actual production process is inputted the ultrasonic bonding Evaluation Model on Quality that described metal to be welded is corresponding；Described Evaluation Model on Quality is with the characteristic parameter of welding process information for input, and welding quality assessed value is output；The welding quality assessed value of this ultrasonic metal welding is calculated by described ultrasonic bonding Evaluation Model on Quality.The present invention can predict welding quality assessed value, it is achieved that the real non-destructive assessment of welding quality, substantially increases the stability of product quality, and the manpower and materials reducing monitoring put into, and improve production efficiency.
Description
Technical field
The present invention relates to ultrasonic metal welding technical field, particularly relate to a kind of ultrasonic metal welding quality evaluation
Method, ultrasonic metal welding quality assessment device and ultrasonic metal bonding machine.
Background technology
Ultrasonic metal welding is a kind of Solid-phase welding technology.In welding process, soldering appliance head is executed to metal to be welded
Plus-pressure and high frequency ultrasound vibration, make metal interface produce severe friction and plastic deformation and then promote interface to be formed well to connect
Connect.Ultrasonic metal welding technology has become welding method main in lithium battery manufacture process at present, but due to this welding side
Method is the most sensitive to welding condition, and many extraneous factors can have undesirable effect by welding quality, causes lithium battery quality
Concordance is poor.
Along with ultrasonic welding technique in sector applications such as battery manufactures more and more extensively, people's welding quality is reliable
Property and conforming requirement more and more higher, but at present in actual production process use solder joint off-line quality determining methods pair more
Welding quality is estimated, and the method workload is big, inefficiency, there is certain error, is not suitable for extensive chemical industry automatically
Industry production line application.
Summary of the invention
Based on this, it is necessary to for the problems referred to above, it is provided that a kind of ultrasonic metal welding method for evaluating quality, device and super
Sound wave metal welding machine, it is possible to realize accurate, quick and lossless welding quality assessment.
In order to achieve the above object, the technical scheme that the present invention takes is as follows:
A kind of ultrasonic metal welding method for evaluating quality, including step:
Metal to be welded is carried out ultrasonic metal welding, obtains the welding process information in actual production process；
The characteristic parameter of the welding process information in extraction actual production process；
Characteristic parameter in actual production process is inputted the ultrasonic bonding quality evaluation mould that described metal to be welded is corresponding
Type；Described Evaluation Model on Quality is with the characteristic parameter of welding process information for input, and welding quality assessed value is output；
The welding quality assessed value of this ultrasonic metal welding is calculated by described ultrasonic bonding Evaluation Model on Quality.
A kind of ultrasonic metal welding quality assessment device, including:
First welding process information acquisition module, for metal to be welded carries out ultrasonic metal welding, obtains reality raw
Welding process information during product；
Fisrt feature parameter extraction module, for extracting the characteristic parameter of the welding process information in actual production process；
Characteristic parameter input module is corresponding for the characteristic parameter in actual production process is inputted described metal to be welded
Ultrasonic bonding Evaluation Model on Quality；Described Evaluation Model on Quality, with the characteristic parameter of welding process information for input, welds matter
Amount assessed value is output；
Hot strength obtains module, for being calculated this ultrasonic wave metal by described ultrasonic bonding Evaluation Model on Quality
The welding quality assessed value of welding.
A kind of ultrasonic metal bonding machine, including described ultrasonic metal welding quality assessment device.
Ultrasonic metal welding method for evaluating quality of the present invention, device and ultrasonic metal bonding machine, weld for each
Object, carries out the soldering test of large sample amount, analyses in depth the welding process information obtained, extracts and welding quality
The information characteristics of close relation also sets up the ultrasonic bonding Evaluation Model on Quality that each welding object is corresponding, in actual production
In, obtain the welding process information of metal to be welded and extract characteristic parameter, by supersonic welding corresponding for the input of this feature parameter
Connect Evaluation Model on Quality, i.e. can obtain welding quality assessed value, it is achieved that the real non-destructive assessment of welding quality, be greatly improved
The stability of product quality, the manpower and materials reducing monitoring put into, and improve production efficiency.Through checking, the present invention predicts
Welding quality assessed value in rational range of error, so present invention achieves the accurate evaluation of welding quality.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of ultrasonic metal welding method for evaluating quality embodiment of the present invention；
Fig. 2 is the structural representation of ultrasonic metal welding procedural information acquisition analysis system embodiment of the present invention；
Fig. 3 is the schematic diagram of the neural network model embodiment that the present invention sets up；
Fig. 4 is the schematic diagram of neural metwork training variance of the present invention；
Fig. 5 is the contrast schematic diagram of neural network prediction value of the present invention and actual value；
Fig. 6 is the linear fit result schematic diagram of neural network prediction value of the present invention and actual value；
Fig. 7 is the structural representation of ultrasonic metal welding quality assessment device embodiment of the present invention.
Detailed description of the invention
By further illustrating the technological means and the effect of acquirement that the present invention taked, below in conjunction with the accompanying drawings and the most real
Execute example, to technical scheme, carry out clear and complete description.
As it is shown in figure 1, a kind of ultrasonic metal welding method for evaluating quality, including step:
S110, metal to be welded is carried out ultrasonic metal welding, obtain the welding process information in actual production process；
S120, the characteristic parameter of the welding process information extracted in actual production process；
S130, the ultrasonic bonding quality that the characteristic parameter in actual production process is inputted described metal to be welded corresponding are commented
Estimate model；Described Evaluation Model on Quality is with the characteristic parameter of welding process information for input, and welding quality assessed value is output；
S140, the welding quality being calculated this ultrasonic metal welding by described ultrasonic bonding Evaluation Model on Quality are commented
Valuation.
The inventive method can realize according to corresponding program or chip, and program or chip operate in ultrasonic metal welding
In machine, it is achieved the accurate real-time assessment of welding quality.In order to be more fully understood that the present invention, below each step of the present invention is entered
Row is discussed in detail.
In step s 110, metal to be welded can be the metals such as copper, and such as, metal to be welded is C1100 fine copper plate, fine copper plate
Materials behavior be half-hard state, dimensions is 50mm (millimeter) × 25mm × 0.6mm etc..In actual production process, according to
Conventional welding method carries out ultrasonic metal welding to metal to be welded, obtains welding process information, wherein welding process information
Including ultrasound wave current signal and ultrasound wave voltage signal etc., welding process information can use corresponding sensor to obtain.
As in figure 2 it is shown, be the structural representation of ultrasonic metal welding procedural information acquisition analysis system.Sample is (to be welded
Metal) welding before be made without any surface process, sample is positioned on chopping block and welds, welding point for overlap joint shape
Formula, the lap of splice can be 25mm etc., chopping block is additionally provided with limited block, prevents in welding process due to the vibrations of tool heads
And making sample produce bigger skew, it is ensured that solder joint is positioned at overlapping regions center.In welding process, current transformer is selected to measure
Ultrasound wave current signal, electric resistance partial pressure is measured ultrasound wave voltage signal, is pressed displacement to believe under laser displacement sensor survey tool head
Number.The signal that each sensor obtains, after signal conditioning circuit processes, is converted into the voltage signal input number of 0～10V (volt)
According to capture card, then voltage signal carries out data convert, and (being reduced under current signal, voltage signal and tool heads presses displacement to believe
Number etc.), data analysis system carries out data analysis, it is thus achieved that the predictive value of the hot strength of welding point.
It should be noted that the present invention is not restricted to the device shown in Fig. 2 gathers welding process information, user is all right
Selecting other device to obtain welding process information as required, the process processing the welding process information data gathered does not limits
Being formed on above-mentioned processing procedure, user can also carry out other to the procedural information gathered as required and process.
In the step s 120, the welding process information got is analysed in depth, extract the spy of welding process information
Levying parameter group, in one embodiment, the step of the characteristic parameter extracting the welding process information in actual production process includes
Following any one or more:
S1201, the ultrasound wave current signal of transducer obtained and ultrasound wave voltage signal are carried out Hilbert respectively
(Hilbert) converts, it is thus achieved that the electric current analytic signal of described ultrasound wave current signal and the voltage of described ultrasound wave voltage signal
Analytic signal, obtains, according to described electric current analytic signal and described voltage analytic signal, the gross energy consumed in welding process；
In Fig. 2, the ultrasound wave current signal of sensor acquisition and ultrasound wave voltage signal are the ultrasound wave electric current of transducer
Signal and ultrasound wave voltage signal.In one embodiment, obtain according to described electric current analytic signal and described voltage analytic signal
The step obtaining the gross energy consumed in welding process may include that
The amplitude envelope line of current signal, voltage letter is obtained according to described electric current analytic signal and described voltage analytic signal
Number amplitude envelope line and current signal and voltage signal between phase contrast；
Amplitude envelope line, the amplitude envelope line of voltage signal and described phase contrast according to current signal, it is thus achieved that welding
During active-power P (n)；Active power can be obtained according to existing method in prior art；
Described active-power P (n) is integrated, it is thus achieved that the gross energy E1 consumed in welding process.
S1202, ultrasonic power maximum P according to welding processmaxAverage value P with the virtual value of ultrasonic signalm
Difference, it is thus achieved that power difference Δ P；That is:
Δ P=Pmax-Pm (1)
Ultrasonic power maximum PmaxAverage value P with the virtual value of ultrasonic signalmCan set according to the needs of user
Put.
S1203, according to obtain tool heads press down displacement signal obtain welding start in rear Preset Time tool heads under
The average speed V of pressurem；
In one embodiment, press down displacement signal to obtain welding according to the tool heads obtained to start in rear Preset Time
The step of the average speed that tool heads is pressed down may include that
Press down displacement signal to obtain under the tool heads in each t time period according to tool heads and press average speed V (i), t time
Section for starting the sub-time period of rear Preset Time segmentation to welding；Such as, Preset Time is 100ms (millisecond), is divided by 100ms
Being 50 sections, each time period t is 2ms；
Calculate the tool heads in all t time periods and press down the meansigma methods of average speed, it is thus achieved that welding starts rear Preset Time
The average speed V that interior tool heads is pressed downm。
In order to be more fully understood that VmAcquisition process, to press average speed V under 100ms tool heads before calculating after welding startsm
As a example by illustrate.
Calculate in every 2ms first with formula (2) and press average speed under tool heads, it is thus achieved that rate curve V (i).Then basis
Formula (3) calculates the meansigma methods of V (i), it is thus achieved that press average speed V under front 100ms tool headsm。
Wherein, D (i) is the displacement signal that tool heads is pressed down.Further, since the sample frequency of displacement signal D (i) is
1Mhz, thus the 2ms correspondence 2000 in formula (2), when the sample frequency of displacement signal D (i) is other numerical value, formula (2)
In 2000 change accordingly.
S1204, the ultrasound wave current signal of transducer obtained is carried out WAVELET PACKET DECOMPOSITION and signal reconstruction successively, it is thus achieved that
Each reconstruction signal, calculates signal energy and the signal gross energy of all frequency ranges of each frequency range according to each reconstruction signal,
Signal energy according to each frequency range and described signal gross energy obtain the signal energy ratio of each frequency range.
WAVELET PACKET DECOMPOSITION and signal reconstruction can pass through MATLAB (Matrix Laboratory, matrix labotstory) software
Realize.The number of plies of WAVELET PACKET DECOMPOSITION and carry out the frequency range of signal reconstruction and can determine according to practical situation.Such as, at a tool
In body embodiment, use MATLAB software that with db10 small echo, ultrasound wave current signal is carried out 5 layers of WAVELET PACKET DECOMPOSITION, ultrasound wave electricity
In stream signal, the waveform of different frequency composition is broken down into 32 different frequency ranges, then selects front 8 frequency ranges to carry out signal reconstruction,
Obtain reconstruction signal x50, x51, x52, x53, x54, x55, x56, x57.
After obtaining reconstruction signal, determine signal energy { Ej} and the signal total energy of each frequency range according to formula (4) and formula (5)
Amount E2:
Wherein, the n in formula (4) represents signal continuing force, and N represents that signal continues total length.
Signal energy according to each frequency range Ej} and signal gross energy E2, it is thus achieved that each frequency band signals energy proportion to
Amount w=[w50, w51, w52, w53, w54, w55, w56, w57], wherein w5jDetermine according to formula (6):
w5j=Ej/ E2 (j=0,1 ... 7) (6)
It should be noted that in order to ensure welding point hot strength assess accuracy, be preferably extract three kinds or
The characteristic parameter of more than three kinds.
In step s 130, the present invention is built with in advance based on RBF (Radial basis function, radially base letter
Number) ultrasonic bonding Evaluation Model on Quality that each metal to be welded of neutral net is corresponding.When carrying out quality evaluation, according to treating
The type of weldering metal chooses the ultrasonic bonding Evaluation Model on Quality of correspondence, and the characteristic parameter of extraction inputs the ultrasound wave chosen
Welding quality assessment models.
In order to realize the assessment real-time of welding quality, typically before actual production, just enter for each welding object
The soldering test of row large sample amount, sets up the ultrasonic bonding Evaluation Model on Quality that each welding object is corresponding.So, at one
In embodiment, before metal to be welded is carried out ultrasonic metal welding, it is also possible to include step:
S070, metal to be welded is carried out ultrasonic metal welding test, obtain the welding process letter under the conditions of different tests
Breath；
Different tests condition can be in the factors such as the welding pressure in welding process, weld interval and weld interface state
One or more are different.Under certain experimental condition, obtain welding process information, then change experimental condition, obtain experimental condition
Welding process information after change, repetitive operation, until obtaining enough sample datas.
The characteristic parameter of the welding process information under the conditions of S080, extraction different tests；
Extract the characteristic parameter of welding process information and the welding process letter extracted in actual production process under experimental condition
The method of the characteristic parameter of breath is identical.The most in one embodiment, the spy of the welding process information under the conditions of extraction different tests
Levy the step of parameter and include following any one or more:
S0801, the ultrasound wave current signal of transducer obtained and ultrasound wave voltage signal are carried out Hilbert change respectively
Change, it is thus achieved that the electric current analytic signal of described ultrasound wave current signal and the voltage analytic signal of described ultrasound wave voltage signal, root
The gross energy consumed in welding process is obtained according to described electric current analytic signal and described voltage analytic signal；
S0802, according to the ultrasonic power maximum of welding process and the difference of the meansigma methods of the virtual value of ultrasonic signal
Value, it is thus achieved that power difference；
S0803, according to obtain tool heads press down displacement signal obtain welding start in rear Preset Time tool heads under
The average speed of pressure；
S0804, the ultrasound wave current signal of transducer obtained is carried out WAVELET PACKET DECOMPOSITION and signal reconstruction successively, it is thus achieved that
Each reconstruction signal, calculates signal energy and the signal gross energy of all frequency ranges of each frequency range according to each reconstruction signal,
Signal energy according to each frequency range and described signal gross energy obtain the signal energy ratio of each frequency range.
In order to ensure the accuracy that the hot strength of welding point is assessed, it is preferably the feature extracting three kinds or more
Parameter.
The ultimate tensile strength of the welding point under the conditions of S090, acquisition different tests；
When obtaining the ultimate tensile strength of welding point, it is possible to use universal tensile experimental machine Welded Joints draws
Stretch experiment.Using the ultimate tensile strength of welding point as welding quality evaluating, set up under the conditions of different tests each
(gross energy E1, power difference, tool heads press down appointing in the characteristic parameter such as average speed and energy proportion vector to characteristic parameter group
Meaning three kinds or more) with the corresponding relation of the ultimate tensile strength of welding point.
S100, using the characteristic parameter under the conditions of different tests as the input of neutral net, the maximum of described welding point
Hot strength, as the output of described neutral net, builds the ultrasonic bonding Evaluation Model on Quality of described metal to be welded.
The characteristic parameter group under each experimental condition obtained is used to input as neutral net, corresponding welding point
Ultimate tensile strength as neutral net export, utilize large sample amount data to carry out model training, inspection, set up neutral net
Model, i.e. ultrasonic bonding Evaluation Model on Quality.As it is shown on figure 3, be the neural network model set up according to four characteristic parameters,
Wherein, the E1 in Fig. 3, Δ P, VmAnd w5jFor the characteristic parameter of input, φ (x, ck) it is neuron, ωikFor corresponding neuron
Weights, F is the ultimate tensile strength of welding point.
The newrb () function that can use MATLAB Neural Network Toolbox builds RBF neural, and network was creating
Journey completes training, i.e. from the beginning of 0 neuron, constantly adds neuron to hidden layer according to specification error, until output knot
The mean square error of fruit reaches the quantity of design requirement or hidden layer neuron node and reaches deconditioning after setting value, therefore institute's structure
Building RBF neural has Adaptation of structure should determine that, exports the feature unrelated with initial weight.
The newrb () function using MATLAB Neural Network Toolbox builds RBF neural concrete operations: net=
Newrb (P, T, goal, spread, mn), wherein, net is newly-established neural network model；P is input vector, i.e. each examination
Characteristic parameter group under the conditions of testing；T is target group vector, i.e. the ultimate tensile strength of welding point；Goal is mean square error；
Spread is expansion rate；Mn is maximum neuron number.First the initiation parameter of neutral net is set, such as,
Mean square error goal is set as 0.005, and the expansion rate spread initial set value of RBF is 0.8, subsequently according to reality
Border situation is adjusted.Set expansion rate spread and be gradually increased 0.1 by initial value 0.8, when spread be 0.8,
0.9,1,1.1 time, it was predicted that the mean error of result is respectively 10.1%, 9.8%, 7.7%, 9.6%.The net when spread is 1
The error of network is minimum, and therefore spread=1 is the expansion rate of applicable RBF.Fig. 4 is the training of RBF neural
Process, wherein the dotted line in Fig. 4 represents that trained values, solid line represent desired value.Can be seen that network is trained through 24 steps according to Fig. 4
After reach default mean square error requirement.
In step S140, described welding quality assessed value can be the ultimate tensile strength of welding point.By selected
Procedural information feature as RBF neural input layer, output contact 1, RBF neural export one 0 to 1 it
Between numerical value, this numerical value represents the intensity of welding point, and output valve is obtained welding point after renormalization processes
The predictive value of big hot strength.
180 groups of data samples after normalized are used as the training of RBF neural and to test data, its
In 150 groups as network training data, remaining the 30 groups performances testing set up network as checking data.It is used for training
150 data sample packages of neutral net include normal quality joint 60, and the too low joint of welding pressure 45, interface has impurity to weld
Point 15, the input too low solder joint of energy 15, the input excessive solder joint of energy 15.
Use data above that the neutral net trained is tested.As it is shown in figure 5, predicting the outcome for neutral net
Comparing result with measured result, it can be seen that the predictive value of neutral net is basically identical with the trend of measured value.Such as Fig. 6 institute
Show that predicting the outcome and the linear fit result of measured result, both correlation coefficient r=0.92 for neutral net illustrates pre-
Survey result and have preferable dependency with actual measurement.Neural network prediction result is 16.4% with the maximum error of actual measured value,
Little error is 0.36%, and mean error is 7.7%.Test result shows that the present invention is set up in rational range of error
The hot strength of welding point can be preferably predicted after neutral net is trained.
Based on same inventive concept, the present invention also provides for a kind of ultrasonic metal welding quality assessment device, below in conjunction with
The detailed description of the invention of apparatus of the present invention is described in detail by accompanying drawing.
As it is shown in fig. 7, a kind of ultrasonic metal welding quality assessment device, including:
First welding process information acquisition module 110, for metal to be welded carries out ultrasonic metal welding, obtains reality
Welding process information in production process；
Fisrt feature parameter extraction module 120, for extracting the feature ginseng of the welding process information in actual production process
Number；
Characteristic parameter input module 130, for inputting described metal pair to be welded by the characteristic parameter in actual production process
The ultrasonic bonding Evaluation Model on Quality answered；Described Evaluation Model on Quality, with the characteristic parameter of welding process information for input, welds
Connect quality assessment value for output；
Hot strength obtains module 140, for being calculated this ultrasound wave by described ultrasonic bonding Evaluation Model on Quality
The welding quality assessed value of metal solder.Described welding quality assessed value can be the ultimate tensile strength of welding point.
In one embodiment, apparatus of the present invention can also include:
Second welding process information acquisition module 070, for metal to be welded is carried out ultrasonic metal welding test, obtains
Welding process information under the conditions of different tests；
Second feature parameter extraction module 080, the feature ginseng of the welding process information under the conditions of extracting different tests
Number；
Ultimate tensile strength acquisition module 090, the maximum tension of the welding point under the conditions of obtaining different tests is strong
Degree；
Assessment models builds module 100, for the input using the characteristic parameter under the conditions of different tests as neutral net,
The ultimate tensile strength of described welding point, as the output of described neutral net, builds the ultrasonic bonding of described metal to be welded
Evaluation Model on Quality.
In one embodiment, described fisrt feature parameter extraction module 120 includes following any one unit or many
Individual unit:
Gross energy obtains unit, for ultrasound wave current signal and the ultrasound wave voltage signal difference of the transducer to acquisition
Carry out Hilbert conversion, it is thus achieved that the electric current analytic signal of described ultrasound wave current signal and the electricity of described ultrasound wave voltage signal
Pressure analytic signal, obtains, according to described electric current analytic signal and described voltage analytic signal, the gross energy consumed in welding process；
Power difference obtains unit, effective for according to the ultrasonic power maximum of welding process and ultrasonic signal
The difference of the meansigma methods of value, it is thus achieved that power difference；
Average speed obtains unit, for according to when pressing displacement signal acquisition welding to preset after starting under the tool heads obtained
The average speed that interior tool heads is pressed down；
Signal energy ratio obtains unit, for the ultrasound wave current signal of the transducer obtained is carried out wavelet packet successively
Decompose and signal reconstruction, it is thus achieved that each reconstruction signal, calculate signal energy and the institute of each frequency range according to each reconstruction signal
There is the signal gross energy of frequency range, obtain the signal of each frequency range according to the signal energy of each frequency range and described signal gross energy
Energy proportion.
In one embodiment, described second feature parameter extraction module 080 includes following any one unit or many
Individual unit:
Gross energy obtains unit, for ultrasound wave current signal and the ultrasound wave voltage signal difference of the transducer to acquisition
Carry out Hilbert conversion, it is thus achieved that the electric current analytic signal of described ultrasound wave current signal and the electricity of described ultrasound wave voltage signal
Pressure analytic signal, obtains, according to described electric current analytic signal and described voltage analytic signal, the gross energy consumed in welding process；
Power difference obtains unit, effective for according to the ultrasonic power maximum of welding process and ultrasonic signal
The difference of the meansigma methods of value, it is thus achieved that power difference；
Average speed obtains unit, for according to when pressing displacement signal acquisition welding to preset after starting under the tool heads obtained
The average speed that interior tool heads is pressed down；
Signal energy ratio obtains unit, for the ultrasound wave current signal of the transducer obtained is carried out wavelet packet successively
Decompose and signal reconstruction, it is thus achieved that each reconstruction signal, calculate signal energy and the institute of each frequency range according to each reconstruction signal
There is the signal gross energy of frequency range, obtain the signal of each frequency range according to the signal energy of each frequency range and described signal gross energy
Energy proportion.
In one embodiment, described gross energy acquisition unit includes:
Amplitude envelope line and phase contrast obtain subelement, for resolving letter according to described electric current analytic signal and described voltage
Number obtain the amplitude envelope line of current signal, voltage signal amplitude envelope line and current signal with voltage signal between phase
Potential difference；
Active power obtains subelement, for the amplitude envelope line according to current signal, the amplitude envelope line of voltage signal
And described phase contrast, it is thus achieved that the active power in welding process；
Gross energy obtains subelement, for being integrated described active power, it is thus achieved that the total energy consumed in welding process
Amount.
In one embodiment, described average speed acquisition unit includes:
First average speed obtains subelement, for pressing down displacement signal to obtain in each t time period according to tool heads
Pressing average speed, t time period under tool heads is the sub-time period that welding starts the segmentation of rear Preset Time；
Second average speed obtains subelement, presses down the flat of average speed for calculating the tool heads in all t time periods
Average, it is thus achieved that welding starts the average speed that the tool heads in rear Preset Time is pressed down.
Other technical characteristic of apparatus of the present invention is identical with the inventive method, does not repeats them here.
The present invention also provides for a kind of ultrasonic metal bonding machine, and described ultrasonic metal bonding machine includes above-mentioned ultrasound wave
Metal solder quality assessment device.
The welding process information obtained is analysed in depth by the present invention, extracts and the information of welding quality close relation
Feature also sets up the hot strength of neural network prediction welding point, it is achieved the automatic on-line monitoring and evaluation of welding quality,
Thus can effectively identify second-rate welding point in process of production, so will be greatly improved stablizing of product quality
Property, the manpower and materials reducing monitoring put into, and improve production efficiency.
Each technical characteristic of embodiment described above can combine arbitrarily, for making description succinct, not to above-mentioned reality
The all possible combination of each technical characteristic executed in example is all described, but, as long as the combination of these technical characteristics is not deposited
In contradiction, all it is considered to be the scope that this specification is recorded.
Embodiment described above only have expressed the several embodiments of the present invention, and it describes more concrete and detailed, but also
Can not therefore be construed as limiting the scope of the patent.It should be pointed out that, come for those of ordinary skill in the art
Saying, without departing from the inventive concept of the premise, it is also possible to make some deformation and improvement, these broadly fall into the protection of the present invention
Scope.Therefore, the protection domain of patent of the present invention should be as the criterion with claims.
Claims (10)
1. a ultrasonic metal welding method for evaluating quality, it is characterised in that include step:
Metal to be welded is carried out ultrasonic metal welding, obtains the welding process information in actual production process；
The characteristic parameter of the welding process information in extraction actual production process；
Characteristic parameter in actual production process is inputted the ultrasonic bonding Evaluation Model on Quality that described metal to be welded is corresponding；Institute
Stating Evaluation Model on Quality with the characteristic parameter of welding process information for input, welding quality assessed value is output；
The welding quality assessed value of this ultrasonic metal welding is calculated by described ultrasonic bonding Evaluation Model on Quality.
Ultrasonic metal welding method for evaluating quality the most according to claim 1, it is characterised in that described welding quality is commented
Valuation is the ultimate tensile strength of welding point.
Ultrasonic metal welding method for evaluating quality the most according to claim 2, it is characterised in that metal to be welded is carried out
Before ultrasonic metal welding, further comprise the steps of:
Metal to be welded is carried out ultrasonic metal welding test, obtains the welding process information under the conditions of different tests；
The characteristic parameter of the welding process information under the conditions of extraction different tests；
The ultimate tensile strength of the welding point under the conditions of acquisition different tests；
Using the characteristic parameter under the conditions of different tests as the input of neutral net, the ultimate tensile strength of described welding point is made
For the output of described neutral net, build the ultrasonic bonding Evaluation Model on Quality of described metal to be welded.
Ultrasonic metal welding method for evaluating quality the most according to claim 3, it is characterised in that extract actual production
The step of the characteristic parameter of the welding process information in journey and/or under the conditions of different tests includes following any one or many
Kind:
Ultrasound wave current signal and ultrasound wave voltage signal to the transducer obtained carry out Hilbert conversion respectively, it is thus achieved that institute
State electric current analytic signal and the voltage analytic signal of described ultrasound wave voltage signal of ultrasound wave current signal, according to described electric current
Analytic signal and described voltage analytic signal obtain the gross energy consumed in welding process；
Ultrasonic power maximum according to welding process and the difference of the meansigma methods of the virtual value of ultrasonic signal, it is thus achieved that power
Difference；
Press down displacement signal to obtain according to the tool heads obtained and weld the average speed that the tool heads starting in rear Preset Time is pressed down
Degree；
The ultrasound wave current signal of the transducer obtained is carried out WAVELET PACKET DECOMPOSITION and signal reconstruction successively, it is thus achieved that each reconstructs letter
Number, calculate signal energy and the signal gross energy of all frequency ranges of each frequency range according to each reconstruction signal, according to each frequency
The signal energy of section and described signal gross energy obtain the signal energy ratio of each frequency range.
Ultrasonic metal welding method for evaluating quality the most according to claim 4, it is characterised in that
The step bag of the gross energy consumed in welding process is obtained according to described electric current analytic signal and described voltage analytic signal
Include: obtain the amplitude envelope line of current signal, voltage signal according to described electric current analytic signal and described voltage analytic signal
Phase contrast between amplitude envelope line and current signal and voltage signal；Amplitude envelope line according to current signal, voltage letter
Number amplitude envelope line and described phase contrast, it is thus achieved that the active power in welding process；Described active power is integrated,
Obtain the gross energy consumed in welding process；
Press down displacement signal to obtain according to the tool heads obtained and weld the average speed that the tool heads starting in rear Preset Time is pressed down
The step of degree includes: presses down displacement signal to obtain under the tool heads in each t time period according to tool heads and presses average speed, during t
Between section be to welding start rear Preset Time segmentation the sub-time period；Calculate pressing average rate under the tool heads in all t time periods
The meansigma methods of degree, it is thus achieved that welding starts the average speed that the tool heads in rear Preset Time is pressed down.
6. a ultrasonic metal welding quality assessment device, it is characterised in that including:
First welding process information acquisition module, for metal to be welded carries out ultrasonic metal welding, obtains actual production
Welding process information in journey；
Fisrt feature parameter extraction module, for extracting the characteristic parameter of the welding process information in actual production process；
Characteristic parameter input module, for inputting corresponding ultrasonic of described metal to be welded by the characteristic parameter in actual production process
Wave soldering connects Evaluation Model on Quality；Described Evaluation Model on Quality is with the characteristic parameter of welding process information for input, and welding quality is commented
Valuation is output；
Hot strength obtains module, for being calculated this ultrasonic metal welding by described ultrasonic bonding Evaluation Model on Quality
Welding quality assessed value.
Ultrasonic metal welding quality assessment device the most according to claim 6, it is characterised in that described welding quality is commented
Valuation is the ultimate tensile strength of welding point；Described ultrasonic metal welding quality assessment device also includes:
Second welding process information acquisition module, for metal to be welded carries out ultrasonic metal welding test, obtains difference examination
Welding process information under the conditions of testing；
Second feature parameter extraction module, the characteristic parameter of the welding process information under the conditions of extracting different tests；
Ultimate tensile strength acquisition module, the ultimate tensile strength of the welding point under the conditions of obtaining different tests；
Assessment models builds module, for the input using the characteristic parameter under the conditions of different tests as neutral net, described weldering
The ultimate tensile strength of joint is commented as the output of described neutral net, the ultrasonic bonding quality building described metal to be welded
Estimate model.
Ultrasonic metal welding quality assessment device the most according to claim 7, it is characterised in that described fisrt feature is joined
Number extraction modules and/or described second feature parameter extraction module include any one following unit or multiple unit:
Gross energy obtains unit, for carrying out the ultrasound wave current signal of the transducer obtained and ultrasound wave voltage signal respectively
Hilbert converts, it is thus achieved that the electric current analytic signal of described ultrasound wave current signal and the voltage solution of described ultrasound wave voltage signal
Analysis signal, obtains, according to described electric current analytic signal and described voltage analytic signal, the gross energy consumed in welding process；
Power difference obtains unit, is used for the virtual value of the ultrasonic power maximum according to welding process and ultrasonic signal
The difference of meansigma methods, it is thus achieved that power difference；
Average speed obtains unit, for according to pressing displacement signal acquisition welding to start in rear Preset Time under the tool heads obtained
The average speed pressed down of tool heads；
Signal energy ratio obtains unit, for the ultrasound wave current signal of the transducer obtained is carried out WAVELET PACKET DECOMPOSITION successively
And signal reconstruction, it is thus achieved that each reconstruction signal, calculate the signal energy of each frequency range and all frequencies according to each reconstruction signal
The signal gross energy of section, obtains the signal energy of each frequency range according to the signal energy of each frequency range and described signal gross energy
Ratio.
Ultrasonic metal welding quality assessment device the most according to claim 8, it is characterised in that
Described gross energy obtains unit and includes: amplitude envelope line and phase contrast obtain subelement, for resolving according to described electric current
Signal and described voltage analytic signal obtain the amplitude envelope line of current signal, the amplitude envelope line of voltage signal and electric current letter
Number and voltage signal between phase contrast；Active power obtains subelement, for the amplitude envelope line according to current signal, voltage
The amplitude envelope line of signal and described phase contrast, it is thus achieved that the active power in welding process；Gross energy obtains subelement, is used for
Described active power is integrated, it is thus achieved that the gross energy consumed in welding process；
Described average speed obtains unit and includes: the first average speed obtains subelement, for according to pressing displacement to believe under tool heads
Number obtaining and pressing average speed, t time period under the tool heads in each t time period is the son that welding starts the segmentation of rear Preset Time
Time period；Second average speed obtains subelement, presses down the average of average speed for calculating the tool heads in all t time periods
Value, it is thus achieved that welding starts the average speed that the tool heads in rear Preset Time is pressed down.
10. a ultrasonic metal bonding machine, it is characterised in that include the ultrasound wave gold described in claim 6 to 9 any one
Belong to welding quality apparatus for evaluating.
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