CN116929277A - Quality detection method and monitoring mechanism for bonding copper wire processing - Google Patents
Quality detection method and monitoring mechanism for bonding copper wire processing Download PDFInfo
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- CN116929277A CN116929277A CN202310785311.2A CN202310785311A CN116929277A CN 116929277 A CN116929277 A CN 116929277A CN 202310785311 A CN202310785311 A CN 202310785311A CN 116929277 A CN116929277 A CN 116929277A
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- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 title claims abstract description 54
- 238000012544 monitoring process Methods 0.000 title claims abstract description 24
- 238000012545 processing Methods 0.000 title claims abstract description 19
- 230000007246 mechanism Effects 0.000 title claims abstract description 16
- 238000001514 detection method Methods 0.000 title claims abstract description 14
- 238000000034 method Methods 0.000 claims abstract description 41
- 230000008569 process Effects 0.000 claims abstract description 26
- 230000008859 change Effects 0.000 claims abstract description 15
- 238000013135 deep learning Methods 0.000 claims abstract description 8
- 230000005540 biological transmission Effects 0.000 claims description 11
- 230000006870 function Effects 0.000 claims description 9
- 238000012549 training Methods 0.000 claims description 9
- 229910052802 copper Inorganic materials 0.000 claims description 7
- 239000010949 copper Substances 0.000 claims description 7
- 238000013528 artificial neural network Methods 0.000 claims description 6
- 238000007689 inspection Methods 0.000 claims description 4
- 230000002159 abnormal effect Effects 0.000 claims description 3
- 230000004913 activation Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 3
- 238000003062 neural network model Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 claims description 2
- 238000003754 machining Methods 0.000 claims 1
- 238000004519 manufacturing process Methods 0.000 abstract description 6
- 238000012360 testing method Methods 0.000 abstract description 5
- 230000007935 neutral effect Effects 0.000 abstract description 3
- 238000012423 maintenance Methods 0.000 abstract description 2
- 230000005389 magnetism Effects 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 3
- 238000009434 installation Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 239000011532 electronic conductor Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000005389 semiconductor device fabrication Methods 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/10—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring diameters
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/02—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring length, width, or thickness
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/32—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring the deformation in a solid
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N3/40—Investigating hardness or rebound hardness
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R27/00—Arrangements for measuring resistance, reactance, impedance, or electric characteristics derived therefrom
- G01R27/02—Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/048—Activation functions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0499—Feedforward networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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Abstract
The invention relates to the technical field of bonding copper wire processing, in particular to a quality detection method and a monitoring mechanism for bonding copper wire processing, comprising the following steps: obtaining initial parameters of the bonding copper wire, including the diameter, length, hardness and color of the copper wire; in the bonding process, the resistance change, deformation and color change of the copper wire are monitored in real time and compared with a preset threshold value; if the data monitored in real time exceeds the threshold value, judging the data to be a quality problem, stopping the bonding process, and generating an error report at the same time; if the data monitored in real time does not exceed the threshold value, judging that the quality is qualified, and continuing the bonding process; wherein the threshold is derived by a deep learning algorithm based on a large amount of historical data. According to the invention, real-time quality detection can be performed in the copper wire bonding process, instead of waiting for the test after bonding, the production efficiency is greatly improved, and the monitoring neutral gear is avoided when the calliper is in fault replacement and maintenance.
Description
Technical Field
The invention relates to the technical field of bonding copper wire processing, in particular to a quality detection method and a monitoring mechanism for bonding copper wire processing.
Background
Copper wire bonding techniques are commonly used in the field of electronic device, semiconductor device fabrication, and the like. Copper wire bonding is a connection technology, and has the advantages of good conductivity, thermal conductivity and corrosion resistance, however, the production quality of the copper wire and the parameter control in the bonding process directly affect the bonding effect, thereby affecting the performance of electronic or semiconductor equipment.
The existing copper wire bonding technology is mostly dependent on the later product test to judge the bonding quality, such as the connection stability, the contact resistance and other indexes on the test equipment, but the mode has the problems of low efficiency, material waste and the like, and once the problem is found, the bonding process can be needed to be carried out again, even the operation of the whole production line is influenced, so that the production cost is increased.
In addition, these test methods have a certain limitation, and some potential quality problems, such as small deformation, color change, etc., may not be detected accurately, so as the requirements of production on precision and efficiency are higher and higher, how to effectively detect and control the quality problems in the copper wire bonding process in real time, and reduce the later test work have become the problems to be solved in the industry.
Furthermore, diameter monitoring of copper wires is one of important parameters, diameter measurement is mostly carried out by adopting a diameter measuring instrument, the existing diameter measuring instrument is generally arranged singly, the existing diameter measuring instrument is easy to damage after long-time use or is inaccurate in data, and a monitoring neutral gear exists during replacement, so that the quality of products is not beneficial to handle control.
Disclosure of Invention
Based on the above purpose, the invention provides a quality detection method and a monitoring mechanism for bonding copper wire processing.
A quality detection method for bonding copper wire processing comprises the following steps:
step one: obtaining initial parameters of the bonding copper wire, including the diameter, length, hardness and color of the copper wire;
step two: in the bonding process, the resistance change, deformation and color change of the copper wire are monitored in real time and compared with a preset threshold value;
step three: if the data monitored in real time exceeds the threshold value, judging the data to be a quality problem, stopping the bonding process, and generating an error report at the same time;
step four: if the data monitored in real time does not exceed the threshold value, judging that the quality is qualified, and continuing the bonding process;
wherein the threshold is derived by a deep learning algorithm based on a large amount of historical data.
Further, in the second step, the method further includes monitoring the temperature change of the copper wire in real time, and if there is an abnormal temperature change, the method is regarded as a quality problem.
Further, the error report includes relevant parameters of the bonding copper wire, error time, error stage and recommended treatment.
Further, the treatment measures include changing bonding parameters, replacing copper wires, or replacing equipment.
Further, the fourth step further includes generating and updating a quality detection report in real time.
Further, the deep learning algorithm predicts bonding quality based on a deep neural network model, specifically: the model inputs various parameters of the copper wire, wherein the parameters comprise resistance, deformation and color of the copper wire, the model outputs a predicted result of bonding quality, and the model is trained through a training data set to learn a mapping relation between the parameters of the copper wire and the bonding quality, and in the training process, the model automatically adjusts the parameters so as to minimize a prediction error;
assuming a single hidden layer feedforward neural network, the calculation process is expressed as the following two steps:
calculating the output of the hidden layer:
h＝σ(W1x+b1)
output of the computing network:
y＝σ(W2h+b2)
where x is the input of the network, y is the output of the network, h is the output of the hidden layer, W1, W2 are the weights of the network, b1, b2 are bias terms, σ is an activation function, such as a ReLU function or a Sigmoid function;
the process of training the neural network is to adjust the weights W and the bias b of the network by a back propagation (Backpropagation) algorithm and a Gradient Descent (Gradient Descent) method, so that the predicted output y of the network is as close to the actual tag value as possible.
The utility model provides a monitoring mechanism of bonding copper wire processing, includes mounting bracket, two callipers, mounting bracket upper portion is fixed with the support cover, and the support is sheathe in and is equipped with two lantern rings, the lantern ring all rotates through between bearing and the support cover and is connected, and two lantern ring one sides all are fixed with the side bearer, and two callipers are installed respectively in two side bearer one ends, and all are equipped with the direction lifting assembly between calliper and the side bearer, the coaxial transmission shaft that is equipped with in the support cover, the stepper motor that is used for driving the transmission shaft rotation is installed to the mounting bracket bottom, transmission shaft one side is fixed with T shape pole, it has the arc mouth to open support cover one side, and T shape pole passes the arc mouth and at its internal movement, and T shape pole both ends all are fixed with the push rod, and two push rods are used for promoting two side bearer respectively, be equipped with the magnetism on the mounting bracket and inhale the subassembly, magnetism and inhale the subassembly and be used for fixing a position two side bearer in turn.
Further, the direction lifting assembly is including being fixed in the support column of calliper bottom, the support column runs through the side bearer and rather than sliding connection, and the gyro wheel is all installed to the support column lower extreme, the mounting bracket both ends all are fixed with trapezoidal guide block, and two gyro wheels correspond the setting with two trapezoidal guide blocks respectively, calliper bottom both sides all are fixed with the guide arm, the guide arm all runs through the side bearer and rather than sliding connection.
Further, the magnetism is inhaled the subassembly and is including being fixed in two installation poles on mounting bracket upper portion, and two installation poles set up in mounting bracket upper portion both sides, and install first electro-magnet, second electro-magnet on two installation poles respectively, and two side bearer one sides all are fixed with the magnetism and inhale the piece, and two magnetism inhale the piece and first electro-magnet, second electro-magnet correspond the setting.
Further, the first light touch switch and the second light touch switch are fixed on the upper portion of the mounting frame and are used for controlling the first electromagnet and the second electromagnet to be powered on and off respectively, the first light touch switch and the second light touch switch are distributed in ninety degrees around the supporting sleeve, the T-shaped rod rotates within the ninety degrees range, the trigger rod is fixed on the bottom of the T-shaped rod, and the trigger rod alternately triggers the first light touch switch and the second light touch switch.
The invention has the beneficial effects that:
the invention can carry out real-time quality detection in the copper wire bonding process instead of waiting for the test after bonding, greatly improves the production efficiency and the product quality, and in addition, the invention adopts a deep learning algorithm, can automatically learn and adjust the threshold value according to a large amount of historical data, so that the quality judgment is more accurate, and can generate detailed error report when detecting the quality problem, thereby being beneficial to timely finding and solving the problem.
According to the invention, when the device is used, the two calipers are arranged on the supporting sleeve, one of the calipers is in a working state, the other calipers is in a standby state, when the calipers in the working state are out of order or are required to be periodically switched, the calipers in the working state are separated from the working position, rotate to a non-working area, and are detached for maintenance or in the standby state, and the other calipers are in the working state.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only of the invention and that other drawings can be obtained from them without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a quality inspection method according to an embodiment of the invention
FIG. 2 is a schematic perspective view of a monitoring mechanism according to an embodiment of the present invention;
FIG. 3 is a schematic perspective view of the other side of the monitoring mechanism according to the embodiment of the present invention;
FIG. 4 is a perspective view of a calliper for a monitoring mechanism according to an embodiment of the present invention;
FIG. 5 is a perspective view of a mounting bracket of a monitoring mechanism according to an embodiment of the present invention;
fig. 6 is a schematic top view of a monitoring mechanism according to an embodiment of the invention.
Marked in the figure as:
1. a calliper; 2. copper wires; 3. a mounting frame; 4. a support sleeve; 6. a collar; 7. a side frame; 8. a trapezoidal guide block; 9. a mounting rod; 10. a stepping motor; 11. a first tact switch; 12. a second light touch switch; 13. a first electromagnet; 14. a second electromagnet; 15. an arc-shaped opening; 16. a transmission shaft; 17. a T-bar; 18. a push rod; 19. a trigger pin; 20. a support column; 21. a roller; 22. a magnetic suction block; 23. and a guide rod.
Detailed Description
The present invention will be further described in detail with reference to specific embodiments in order to make the objects, technical solutions and advantages of the present invention more apparent.
It is to be noted that unless otherwise defined, technical or scientific terms used herein should be taken in a general sense as understood by one of ordinary skill in the art to which the present invention belongs. The terms "first," "second," and the like, as used herein, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", etc. are used merely to indicate relative positional relationships, which may also be changed when the absolute position of the object to be described is changed.
As shown in fig. 1, a quality detection method for bonding copper wire processing includes the following steps:
step one: obtaining initial parameters of the bonding copper wire, including the diameter, length, hardness and color of the copper wire;
step two: in the bonding process, the resistance change, deformation and color change of the copper wire are monitored in real time and compared with a preset threshold value;
step three: if the data monitored in real time exceeds the threshold value, judging the data to be a quality problem, stopping the bonding process, and generating an error report at the same time;
step four: if the data monitored in real time does not exceed the threshold value, judging that the quality is qualified, and continuing the bonding process;
wherein the threshold is derived by a deep learning algorithm based on a large amount of historical data.
In the second step, the method also comprises the step of monitoring the temperature change of the copper wire in real time, and if abnormal temperature change exists, the method is also regarded as a quality problem.
The error report includes the relevant parameters of the bonding wire, the error time, the error phase and the recommended treatment.
The treatment measures include changing bonding parameters, replacing copper wires or replacing equipment.
And step four, generating and updating a quality detection report in real time.
The deep learning algorithm predicts bonding quality based on a deep neural network model, and specifically comprises the following steps: the model inputs various parameters of the copper wire, wherein the parameters comprise resistance, deformation and color of the copper wire, the model outputs a predicted result of bonding quality, and the model is trained through a training data set to learn a mapping relation between the parameters of the copper wire and the bonding quality, and in the training process, the model automatically adjusts the parameters so as to minimize a prediction error;
assuming a single hidden layer feedforward neural network, the calculation process is expressed as the following two steps:
calculating the output of the hidden layer:
h＝σ(W1x+b1)
output of the computing network:
y＝σ(W2h+b2)
where x is the input of the network, y is the output of the network, h is the output of the hidden layer, W1, W2 are the weights of the network, b1, b2 are bias terms, σ is an activation function, such as a ReLU function or a Sigmoid function;
the process of training the neural network is to adjust the weights W and the bias b of the network by a back propagation (Backpropagation) algorithm and a Gradient Descent (Gradient Descent) method, so that the predicted output y of the network is as close to the actual tag value as possible.
As shown in fig. 2-6, a monitoring mechanism for processing bonding copper wires comprises a mounting frame 3 and two callipers 1, wherein a supporting sleeve 4 is fixed on the upper portion of the mounting frame 3, two lantern rings 6 are sleeved on the supporting sleeve 4, the lantern rings 6 are rotationally connected with the supporting sleeve 4 through bearings, side frames 7 are fixed on one sides of the two lantern rings 6, the two callipers 1 are respectively installed at one ends of the two side frames 7, guiding lifting components are respectively arranged between the callipers 1 and the side frames 7, a transmission shaft 16 is coaxially arranged in the supporting sleeve 4, a stepping motor 10 for driving the transmission shaft 16 to rotate is installed at the bottom of the mounting frame 3, a T-shaped rod 17 is fixed on one side of the transmission shaft 16, an arc-shaped opening 15 is formed in one side of the supporting sleeve 4, the T-shaped rod 17 penetrates through the arc-shaped opening 15 and moves inside the arc-shaped opening, push rods 18 are respectively fixed at two ends of the T-shaped rod 17, the two push rods 18 are respectively used for pushing the two side frames 7, a magnetic component is arranged on the mounting frame 3, and the magnetic component is used for alternately positioning the two side frames 7.
The guide lifting assembly comprises a support column 20 fixed at the bottom of the diameter measuring instrument 1, the support column 20 penetrates through the side frame 7 and is in sliding connection with the side frame, rollers 21 are all installed at the lower end of the support column 20, trapezoidal guide blocks 8 are all fixed at two ends of the mounting frame 3, two rollers 21 are respectively and correspondingly arranged with the two trapezoidal guide blocks 8, guide rods 23 are all fixed at two sides of the bottom of the diameter measuring instrument 1, the guide rods 23 penetrate through the side frame 7 and are in sliding connection with the side frame, one push rod 18 is driven to push the diameter measuring instrument 1 in a standby state to move towards a working position while the T-shaped rod 17 rotates, and when the position is close to the position, the rollers 21 are in contact with the corresponding trapezoidal guide blocks 8, the diameter measuring instrument 1 is jacked up upwards, and copper wires 2 enter a detection port of the diameter measuring instrument 1.
The magnetic assembly comprises two mounting rods 9 fixed on the upper portion of the mounting frame 3, the two mounting rods 9 are arranged on two sides of the upper portion of the mounting frame 3, a first electromagnet 13 and a second electromagnet 14 are respectively arranged on the two mounting rods 9, magnetic blocks 22 are fixed on one sides of the two side frames 7, and the two magnetic blocks 22 are arranged corresponding to the first electromagnet 13 and the second electromagnet 14, so that alternate absorption and positioning of the two callipers 1 are realized.
The upper portion of the mounting frame 3 is fixedly provided with a first tact switch 11 and a second tact switch 12, the first tact switch 11 and the second tact switch 12 are respectively used for controlling the first electromagnet 13 and the second electromagnet 14 to be powered on and off, the first tact switch 11 and the second tact switch 12 are distributed in ninety degrees around the supporting sleeve 4, the T-shaped rod 17 rotates within the ninety degrees range, the bottom of the T-shaped rod 17 is fixedly provided with a trigger pin 19, the trigger pin 19 alternately triggers the first tact switch 11 and the second tact switch 12, when the T-shaped rod 17 rotates, the first tact switch 11 (the second tact switch 12) controls the first electromagnet 13 (the second electromagnet 14) to be powered on or powered off, so that the side frame 7 corresponding to the calliper 1 entering the working position is sucked and positioned by the first electromagnet 13 (the second electromagnet 14), and the side frame 7 corresponding to the calliper 1 leaving the working position is separated from the second electromagnet 14 (the first electromagnet 13), thereby seamless connection is realized, and the monitoring neutral gear is avoided.
Working principle: when the caliper 1 is in use, two calipers 1 are arranged on the supporting sleeve 4, a copper wire 2 passes through one of the calipers 1, the other calipers 1 is in a normal monitoring state, the other calipers 1 is rotated to a non-working position to be in a standby state, when the calipers 1 in the working state are in fault or are required to be periodically switched, the stepping motor 10 is started to drive the transmission shaft 16 to rotate, so that the T-shaped rod 17 rotates, the trigger pin 19 at the bottom of the T-shaped rod 17 is separated from the first tact switch 11, the first electromagnet 13 is electrified, the T-shaped rod 17 rotates and drives one push rod 18 to push the standby state calipers 1 to move to the working position, when approaching the position, the roller 21 is in contact with the corresponding trapezoid guide block 8, the calipers 1 are jacked up upwards, the copper wire 2 enters a detection port of the calipers 1, at the moment, the calipers 1 start to work, meanwhile, the corresponding side frame 7 of the calipers 1 are sucked and positioned with the first electromagnet 13 through the magnetic suction block 22, and after the calipers 1 are in place, the trigger pin 19 is contacted with the second tact switch 12, so that the second tact switch 12 is in contact with the trigger pin 14, the second side frame 14 is lost, the other calipers are alternately to be disconnected from the other calipers 1 to the working position, and the other calipers 1 are detached from the working position or are detached from the other calipers 1.
Those of ordinary skill in the art will appreciate that: the discussion of any of the embodiments above is merely exemplary and is not intended to suggest that the scope of the invention is limited to these examples; the technical features of the above embodiments or in the different embodiments may also be combined within the idea of the invention, the steps may be implemented in any order and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.
The present invention is intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the present invention should be included in the scope of the present invention.
Claims (10)
1. The quality detection method for processing the bonding copper wire is characterized by comprising the following steps of:
step one: obtaining initial parameters of the bonding copper wire, including the diameter, length, hardness and color of the copper wire;
step two: in the bonding process, the resistance change, deformation and color change of the copper wire are monitored in real time and compared with a preset threshold value;
step three: if the data monitored in real time exceeds the threshold value, judging the data to be a quality problem, stopping the bonding process, and generating an error report at the same time;
step four: if the data monitored in real time does not exceed the threshold value, judging that the quality is qualified, and continuing the bonding process;
wherein the threshold is derived by a deep learning algorithm based on a large amount of historical data.
2. The method according to claim 1, wherein the second step further comprises monitoring the temperature change of the copper wire in real time, and if there is an abnormal temperature change, the method is regarded as a quality problem.
3. A quality inspection method for bonding copper wire processing according to claim 1, characterized in that the error report comprises related parameters of the bonding copper wire, error time, error phase and recommended treatment measures.
4. A quality inspection method for bonded copper wire processing according to claim 1, wherein the processing means comprises changing bonding parameters, replacing copper wires or replacing equipment.
5. The method according to claim 1, wherein the fourth step further comprises generating and updating a quality inspection report in real time.
6. The method for detecting the quality of bonding copper wire processing according to claim 1, wherein the deep learning algorithm predicts the bonding quality based on a deep neural network model, specifically: the model inputs various parameters of the copper wire, wherein the parameters comprise resistance, deformation and color of the copper wire, the model outputs a predicted result of bonding quality, and the model is trained through a training data set to learn a mapping relation between the parameters of the copper wire and the bonding quality, and in the training process, the model automatically adjusts the parameters so as to minimize a prediction error;
assuming a single hidden layer feedforward neural network, the calculation process is expressed as the following two steps:
calculating the output of the hidden layer:
h＝σ(W1x+b1)
output of the computing network:
y＝σ(W2h+b2)
where x is the input of the network, y is the output of the network, h is the output of the hidden layer, W1, W2 are the weights of the network, b1, b2 are bias terms, σ is an activation function, such as a ReLU function or a Sigmoid function;
the process of training the neural network is to adjust the weights W and the bias b of the network by a back propagation (Backpropagation) algorithm and a Gradient Descent (Gradient Descent) method, so that the predicted output y of the network is as close to the actual tag value as possible.
7. The utility model provides a monitoring mechanism of bonding copper wire processing, includes mounting bracket (3), two calliper (1), its characterized in that, mounting bracket (3) upper portion is fixed with support sleeve (4), and the cover is equipped with two lantern rings (6) on support sleeve (4), lantern ring (6) all rotate through between bearing and support sleeve (4) and are connected, two lantern ring (6) one side all are fixed with side bearer (7), two calliper (1) are installed respectively in two side bearer (7) one end, and all are equipped with direction lifting assembly between calliper (1) and side bearer (7), coaxial being equipped with transmission shaft (16) in support sleeve (4), mounting bracket (3) bottom is installed and is used for driving step motor (10) that transmission shaft (16) are rotatory, transmission shaft (16) one side is fixed with T shape pole (17), open on one side of support sleeve (4) has arc mouth (15), T shape pole (17) pass arc mouth (15) and at its inside activity, T shape pole (17) both ends all are fixed with push rod (18), two push rod (18) are used for two side bearer (7) are equipped with two in the side bearer (7) magnet assembly magnet attraction in turn.
8. The monitoring mechanism for processing the bonding copper wire according to claim 7, wherein the guiding lifting assembly comprises a supporting column (20) fixed at the bottom of the caliper (1), the supporting column (20) penetrates through the side frame (7) and is in sliding connection with the side frame, rollers (21) are mounted at the lower end of the supporting column (20), trapezoidal guide blocks (8) are fixed at two ends of the mounting frame (3), two rollers (21) are respectively arranged corresponding to the two trapezoidal guide blocks (8), guide rods (23) are fixed at two sides of the bottom of the caliper (1), and the guide rods (23) penetrate through the side frame (7) and are in sliding connection with the side frame.
9. The monitoring mechanism for processing the bonding copper wire according to claim 8, wherein the magnetic attraction assembly comprises two mounting rods (9) fixed on the upper portion of the mounting frame (3), the two mounting rods (9) are arranged on two sides of the upper portion of the mounting frame (3), the first electromagnet (13) and the second electromagnet (14) are respectively arranged on the two mounting rods (9), the magnetic attraction blocks (22) are fixed on one side of each of the two side frames (7), and the two magnetic attraction blocks (22) are arranged corresponding to the first electromagnet (13) and the second electromagnet (14).
10. The monitoring mechanism for bonding copper wire machining according to claim 9, wherein a first tact switch (11) and a second tact switch (12) are fixed on the upper portion of the mounting frame (3), the first tact switch (11) and the second tact switch (12) are respectively used for controlling the first electromagnet (13) and the second electromagnet (14) to be powered on and powered off, the first tact switch (11) and the second tact switch (12) are distributed in ninety degrees around the supporting sleeve (4), the T-shaped rod (17) rotates within the ninety degrees range, a trigger rod (19) is fixed on the bottom of the T-shaped rod (17), and the trigger rod (19) alternately triggers the first tact switch (11) and the second tact switch (12).
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002343825A (en) * | 2002-04-30 | 2002-11-29 | Miyagi Oki Electric Co Ltd | Wire bonding method |
| US20190094842A1 (en) * | 2017-09-27 | 2019-03-28 | International Business Machines Corporation | Orchestration of learning and execution of model predictive control tool for manufacturing processes |
| CN211206042U (en) * | 2019-12-20 | 2020-08-07 | 泰州新星金属材料有限公司 | Intensity detection device of tinned copper wire |
| CN113111570A (en) * | 2021-03-09 | 2021-07-13 | 武汉大学 | Lead bonding quality prediction control method based on machine learning |
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2023
- 2023-06-29 CN CN202310785311.2A patent/CN116929277B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002343825A (en) * | 2002-04-30 | 2002-11-29 | Miyagi Oki Electric Co Ltd | Wire bonding method |
| US20190094842A1 (en) * | 2017-09-27 | 2019-03-28 | International Business Machines Corporation | Orchestration of learning and execution of model predictive control tool for manufacturing processes |
| CN211206042U (en) * | 2019-12-20 | 2020-08-07 | 泰州新星金属材料有限公司 | Intensity detection device of tinned copper wire |
| CN113111570A (en) * | 2021-03-09 | 2021-07-13 | 武汉大学 | Lead bonding quality prediction control method based on machine learning |
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| Title |
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| 张彩珍等: "基于神经网络的引线键合质量预测模型研究", 兰州交通大学学报, vol. 30, no. 1, 15 February 2011 (2011-02-15), pages 47 - 50 * |
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