CN116461023B - Intelligent detection method and system for baking and curing of quartz crystal - Google Patents
Intelligent detection method and system for baking and curing of quartz crystal Download PDFInfo
- Publication number
- CN116461023B CN116461023B CN202310408931.4A CN202310408931A CN116461023B CN 116461023 B CN116461023 B CN 116461023B CN 202310408931 A CN202310408931 A CN 202310408931A CN 116461023 B CN116461023 B CN 116461023B
- Authority
- CN
- China
- Prior art keywords
- curing
- scoring
- frequency stability
- coordinate axis
- quartz crystal
- 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
Links
- 239000010453 quartz Substances 0.000 title claims abstract description 247
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 title claims abstract description 247
- 239000013078 crystal Substances 0.000 title claims abstract description 159
- 238000001514 detection method Methods 0.000 title claims abstract description 40
- 238000005457 optimization Methods 0.000 claims abstract description 44
- 238000000034 method Methods 0.000 claims abstract description 32
- 239000011347 resin Substances 0.000 claims abstract description 14
- 229920005989 resin Polymers 0.000 claims abstract description 14
- 239000000853 adhesive Substances 0.000 claims description 96
- 230000001070 adhesive effect Effects 0.000 claims description 96
- 238000006073 displacement reaction Methods 0.000 claims description 60
- 238000012545 processing Methods 0.000 claims description 41
- 238000011156 evaluation Methods 0.000 claims description 37
- 239000002904 solvent Substances 0.000 claims description 29
- 238000012549 training Methods 0.000 claims description 23
- 238000002360 preparation method Methods 0.000 claims description 21
- 230000002159 abnormal effect Effects 0.000 claims description 10
- 238000012937 correction Methods 0.000 claims description 10
- 238000013461 design Methods 0.000 claims description 8
- 238000007711 solidification Methods 0.000 claims description 8
- 230000008023 solidification Effects 0.000 claims description 8
- 238000013528 artificial neural network Methods 0.000 claims description 6
- 238000010276 construction Methods 0.000 claims description 6
- 230000001419 dependent effect Effects 0.000 claims description 6
- 238000013097 stability assessment Methods 0.000 claims description 2
- 238000001723 curing Methods 0.000 description 210
- 235000012431 wafers Nutrition 0.000 description 70
- 230000000694 effects Effects 0.000 description 9
- 238000012360 testing method Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000005684 electric field Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000013557 residual solvent Substances 0.000 description 1
- 230000000452 restraining effect Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C37/00—Component parts, details, accessories or auxiliary operations, not covered by group B29C33/00 or B29C35/00
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D18/00—Testing or calibrating apparatus or arrangements provided for in groups G01D1/00 - G01D15/00
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C37/00—Component parts, details, accessories or auxiliary operations, not covered by group B29C33/00 or B29C35/00
- B29C2037/90—Measuring, controlling or regulating
-
- 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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Piezo-Electric Or Mechanical Vibrators, Or Delay Or Filter Circuits (AREA)
Abstract
The invention provides a baking and curing intelligent detection method and system for quartz crystals, which relate to the technical field of intelligent detection, and the method comprises the following steps: and when the generated frequency stability score of the quartz crystal resonator does not meet the frequency stability score threshold value, conducting resin curing parameters are optimally designed, baking and curing real-time parameters are detected and corrected after conducting resin curing parameter optimization results are generated, so that the technical problem that the frequency stability of the prepared quartz crystal resonator is poor due to improper control parameters in the baking and curing process of the quartz crystal in the prior art is solved, the control parameters in the baking and curing process are detected and corrected, and the frequency stability of the quartz crystal resonator is improved.
Description
Technical Field
The invention relates to the technical field of intelligent detection, in particular to a baking and curing intelligent detection method and system for quartz crystals.
Background
Quartz crystals are commonly known as crystal, which is not only a good optical material, but also an important piezoelectric material. The main characteristic of the crystal is that its atoms or molecules are regularly arranged, reflecting the macroscopic symmetry of the appearance. The artificial crystal is crystallized under high temperature and high pressure. Under the action of the electric field, stress is generated in the crystal to deform, so that mechanical vibration is generated, and a specific frequency is obtained. We use this inverse piezoelectric effect characteristic to fabricate quartz crystal resonators.
In the development of continuous progress of modern technology, the application way of the quartz crystal is more and more wide, whether in the field of aviation military, the field of traffic astronomy, or the field of wireless communication and the like, the quartz crystal plays a vital role, the control parameters of the baking and curing process of the current quartz crystal are mainly determined based on past experience, and improper control parameters of the baking and curing process can lead to that stress between the quartz crystal and dispensing can not be eliminated, and residual solvents can exist in the conductive adhesive, so that the frequency stability of the prepared quartz crystal resonator is poor.
Disclosure of Invention
The application provides a baking and curing intelligent detection method and system for quartz crystals, which are used for solving the technical problem that the frequency stability of a prepared quartz crystal resonator is poor due to improper control parameters in the baking and curing process of quartz crystals in the prior art.
In view of the above problems, the application provides a baking solidification intelligent detection method and system for quartz crystals.
In a first aspect, the application provides a baking solidification intelligent detection method of quartz crystals, which comprises the following steps: obtaining preparation parameters of a quartz crystal resonator, wherein the preparation parameters of the quartz crystal resonator comprise conductive adhesive curing parameters; predicting the fixation stability of the quartz wafer according to the curing parameters of the conductive adhesive to generate a fixation stability score; predicting the frequency stability of the quartz crystal resonator according to the curing parameters of the conductive adhesive to generate a resonator frequency stability score; judging whether the fixed stability score meets a fixed stability score threshold; judging whether the frequency stability score of the resonator meets a frequency stability score threshold; when the fixed stability score does not meet the fixed stability score threshold value or/and the frequency stability score of the resonator does not meet the frequency stability score threshold value, optimally designing the conductive adhesive curing parameters to generate conductive adhesive curing parameter optimization results; and detecting and correcting the baking and curing real-time parameters according to the conducting resin curing parameter optimization result.
In a second aspect, the present application provides a baking solidification intelligent detection system for quartz crystals, the system comprising: the parameter acquisition module is used for acquiring preparation parameters of the quartz crystal resonator, wherein the preparation parameters of the quartz crystal resonator comprise conductive adhesive curing parameters; the fixed stability prediction module is used for predicting the fixed stability of the quartz wafer according to the curing parameters of the conductive adhesive and generating a fixed stability score; the frequency stability prediction module is used for predicting the frequency stability of the quartz crystal resonator according to the curing parameters of the conductive adhesive and generating a resonator frequency stability score; the first judging module is used for judging whether the fixed stability score meets a fixed stability score threshold value or not; the second judging module is used for judging whether the frequency stability score of the resonator meets a frequency stability score threshold value or not; the optimization design module is used for optimally designing the conductive adhesive curing parameters when the fixed stability score does not meet the fixed stability score threshold value or/and the frequency stability score of the resonator does not meet the frequency stability score threshold value, so as to generate a conductive adhesive curing parameter optimization result; and the detection and correction module is used for detecting and correcting the baking and curing real-time parameters according to the conducting resin curing parameter optimization result.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
the application provides a baking and curing intelligent detection method and system for quartz crystals, relates to the technical field of intelligent detection, solves the technical problem that the frequency stability of a prepared quartz crystal resonator is poor due to improper control parameters in the baking and curing process of the quartz crystals in the prior art, realizes detection and correction of the control parameters in the baking and curing process, and further improves the frequency stability of the quartz crystal resonator.
Drawings
FIG. 1 is a schematic flow chart of a baking solidification intelligent detection method for quartz crystals;
FIG. 2 is a schematic diagram showing a flow of obtaining a score for a fixed stability in an intelligent detection method for baking and curing quartz crystals;
FIG. 3 is a schematic diagram showing a flow chart of scoring the frequency stability of a generated resonator in an intelligent detection method for baking and curing quartz crystals;
FIG. 4 is a flow chart showing the result of optimizing the curing parameters of the conductive adhesive in the intelligent detection method for baking and curing the quartz crystal;
FIG. 5 is a schematic flow chart of generating an optimized abnormal signal and sending the optimized abnormal signal to a management terminal in the intelligent detection method for baking and curing quartz crystals;
Fig. 6 is a schematic structural diagram of a baking and curing intelligent detection system for quartz crystals.
Reference numerals illustrate: the system comprises a parameter acquisition module 1, a fixed stability prediction module 2, a frequency stability prediction module 3, a first judgment module 4, a second judgment module 5, an optimal design module 6 and a detection correction module 7.
Detailed Description
The application provides an intelligent detection method and system for baking and curing quartz crystals, which are used for solving the technical problem that the frequency stability of a prepared quartz crystal resonator is poor due to improper control parameters in the baking and curing process of quartz crystals in the prior art.
Example 1
As shown in fig. 1, an embodiment of the present application provides a method for intelligently detecting baking and curing of a quartz crystal, where the method is applied to a system for intelligently detecting baking and curing of a quartz crystal, and the method includes:
step S100: obtaining preparation parameters of a quartz crystal resonator, wherein the preparation parameters of the quartz crystal resonator comprise conductive adhesive curing parameters;
specifically, the intelligent detection method for baking and curing of the quartz crystal is applied to an intelligent detection system for baking and curing of the quartz crystal, in the system, in order to achieve the effect of detecting and correcting control parameters in the baking and curing process of the quartz crystal, the frequency of the quartz crystal is related to the cutting mode, the geometric shape and the size of the quartz crystal, all parameters of the quartz crystal resonator in the preparation process are required to be collected, and the collected preparation parameters of the quartz crystal resonator can comprise nominal frequency parameters, load frequency parameters, temperature characteristic parameters, assembly parameters of the quartz crystal resonator, curing parameters of conductive adhesive and the like, and according to the obtained parameters, detection, correction and curing of real-time parameters in later stages are realized as important reference bases.
Step S200: predicting the fixation stability of the quartz wafer according to the curing parameters of the conductive adhesive to generate a fixation stability score;
specifically, the method comprises the steps of extracting the conductive adhesive curing parameters contained in the preparation parameters of the obtained quartz crystal resonator, and predicting the stability of the quartz wafer according to the extracted conductive adhesive curing parameters, wherein the stability of the quartz wafer refers to the stable state of the quartz wafer at the fixed position when the quartz wafer is used after baking and curing, firstly, setting the conductive adhesive curing parameters contained in the preparation parameters of the quartz crystal resonator and the assembly parameters of the quartz crystal resonator as constraint conditions, collecting application record data of the quartz crystal resonator, and collecting the application record data, wherein the application record data contains the average displacement rate and the displacement amount of the quartz wafer in a preset service duration, and the vibration amplitude of the quartz wafer under the preset impact force, further, sequentially constructing a corresponding score according to the average displacement rate reciprocal of the quartz wafer in the preset service duration, and constructing a corresponding score coordinate axis according to the corresponding score according to the inverse of the average displacement rate, constructing a corresponding score according to the reciprocal of the quartz wafer amplitude parameter in the preset service duration, and simultaneously constructing a corresponding score according to the corresponding score of the quartz wafer coordinate axes, and the corresponding score of the quartz wafer in the quartz coordinate of the quartz coordinate in the preset service duration, and the corresponding score of the quartz wafer is lower, the displacement of the quartz wafer and the vibration amplitude of the quartz wafer are input into a scale generated quartz wafer fixed stability scoring coordinate system, a corresponding fixed stability score is output, and when the output fixed stability score is larger, the current fixed stability of the quartz wafer is considered to be higher, so that real-time parameters of baking and curing are detected, corrected and guaranteed.
Step S300: predicting the frequency stability of the quartz crystal resonator according to the curing parameters of the conductive adhesive to generate a resonator frequency stability score;
specifically, in order to monitor and correct the curing process of the quartz crystal better, the frequency stability of the quartz crystal resonator is also required to be predicted on the basis of the curing parameters of the conductive adhesive, that is, the frequency table stability of the current quartz crystal resonator can be evaluated according to the curing stability of the quartz crystal, firstly, the conductive adhesive curing parameters are required to be used as independent variables, the stress characteristic value and the solvent residual quantity contained in the frequency stability evaluation index are used as dependent variables, the data of the current quartz crystal during curing is acquired, the acquired data is input into the BP neural network for supervised training, so that the construction of the frequency stability evaluation index prediction layer is completed, a corresponding coordinate axis is respectively constructed on the basis of the inverse stress characteristic value contained in the frequency stability evaluation index in turn, the stress characteristic value is larger, the lower the corresponding stress characteristic value score is, a corresponding score coordinate axis is constructed based on the reciprocal of the solvent residual quantity contained in the frequency stability evaluation index, the higher the solvent residual quantity is, the lower the corresponding solvent residual quantity score is, the quartz crystal resonator frequency stability score coordinate system is generated according to the score coordinate axis corresponding to the stress characteristic value and the score coordinate axis corresponding to the solvent residual quantity, the output layer in the frequency stability evaluation index prediction layer and the quartz crystal resonator frequency stability score coordinate system input layer are combined in a hierarchical manner, the quartz crystal resonator frequency stability prediction model is correspondingly generated, the conductive adhesive curing parameter is finally input into the quartz crystal resonator frequency stability prediction model, the resonator frequency stability score is output at the same time, and the larger the output resonator frequency stability score is, the higher the frequency stability of the resonator of the current quartz wafer is, the basis for the detection, correction, baking and solidification real-time parameter tamping is realized for the follow-up.
Step S400: judging whether the fixed stability score meets a fixed stability score threshold;
specifically, a fixed stability score generated by predicting the fixed stability of the quartz wafer according to the curing parameters of the conductive adhesive is taken as a basis, whether the fixed stability score meets a fixed stability score threshold is judged, and the fixed stability score threshold can be correspondingly preset by related technicians according to the data quantity of the conductive curing parameters in big data. Further, the fixed stability score threshold is a basis for evaluating whether the quartz wafer needs to be optimized in the curing process, if the fixed stability score meets the fixed stability score threshold, that is, if the current fixed stability score is greater than or equal to the set fixed stability score threshold, the fixed stability score threshold is considered to be met, then the judgment is performed on whether the frequency stability score of the resonator meets the frequency stability score threshold, if the frequency stability score of the resonator does not meet the frequency stability score threshold, the corresponding optimization is performed on the frequency stability of the resonator, and the effect of limiting the detection, correction and curing real-time parameters is achieved.
Step S500: judging whether the frequency stability score of the resonator meets a frequency stability score threshold;
specifically, a frequency stability score of the quartz crystal resonator generated by predicting the frequency stability of the quartz crystal resonator according to the curing parameters of the conductive adhesive is taken as a basis, the frequency stability score threshold value can be correspondingly preset by related technicians according to the data volume of the conductive curing parameters in big data, and further, the frequency stability score threshold value is a basis for evaluating whether the vibration frequency of the quartz crystal resonator needs to be optimized in the curing process of the quartz crystal wafer, if the frequency stability score of the quartz crystal resonator meets the frequency stability score threshold value, that is, if the frequency stability score of the current resonator is larger than or equal to the set frequency stability score threshold value is considered to be met, the fixed stability score meets the fixed stability score threshold value, and if the fixed stability score does not meet the fixed stability score threshold value, the fixed stability is required to be correspondingly optimized, and the effect of restraining the detection, correction and curing real-time parameters is achieved.
Step S600: when the fixed stability score does not meet the fixed stability score threshold value or/and the frequency stability score of the resonator does not meet the frequency stability score threshold value, optimally designing the conductive adhesive curing parameters to generate conductive adhesive curing parameter optimization results;
Specifically, the conducting resin curing parameter optimization result refers to that if one of the three conditions that the fixed stability score does not meet the fixed stability score threshold, the resonator frequency stability score does not meet the frequency stability score threshold, the fixed stability score does not meet the fixed stability score threshold and the resonator frequency stability score does not meet the frequency stability score threshold exists, conducting resin curing parameters are subjected to intelligent optimization design to determine control parameters for guiding the baking curing process.
The preferred embodiment of the process for determining the optimized result of the curing parameters of the conductive adhesive as described above is as follows: setting a curing temperature constraint interval sequence and a curing placement position constraint space according to curing temperature time sequence information contained in a conductive adhesive curing parameter, acquiring baking and curing processing record data with preset data volume based on an industrial blockchain, and recording the baking and curing processing record data as a conductive adhesive curing parameter optimization result to be output when the baking and curing processing record data meets a fixed stability scoring threshold and the baking and curing processing record data meets a frequency stability scoring threshold after the baking and curing processing record data meets a fixed stability scoring threshold, wherein the baking and curing processing record data is used as a judging reference for detecting, correcting and curing real-time parameters in later period and is determined based on production big data statistical analysis of the industrial blockchain, so that the method has higher reliability and accuracy.
Step S700: and detecting and correcting the baking and curing real-time parameters according to the conducting resin curing parameter optimization result.
Specifically, the baking and curing real-time parameters are obtained by collecting conductive adhesive curing data in real time in the baking process, after judging whether a fixed stability score meets a fixed stability score threshold and whether a resonator frequency stability score meets a frequency stability score threshold, if the fixed stability score does not meet the fixed stability score threshold or/and the resonator frequency stability score does not meet the frequency stability score threshold, conducting adhesive curing parameters are optimally designed, so that a conducting adhesive curing parameter optimization result is obtained, and further, on the basis of the conducting adhesive curing parameter optimization result obtained after conducting adhesive curing parameters are optimally designed, a quartz crystal adhesive curing abnormal monitoring model is constructed according to an optimal curing temperature curve in the conducting adhesive curing parameter optimization result; and meanwhile, the real-time curing temperature of the quartz wafer is acquired, and the acquired curing temperature is input into the constructed quartz crystal dispensing curing anomaly monitoring model for anomaly detection and solving, so that the effect of detecting and correcting the baking curing real-time parameters is achieved, the control parameters of the baking curing process are detected and corrected, and the frequency stability of the quartz crystal resonator is improved.
Further, as shown in fig. 2, step S200 of the present application further includes:
step S210: the preparation parameters of the quartz crystal resonator also comprise assembly parameters of the quartz crystal resonator;
step S220: collecting first application record data of the quartz crystal resonator by taking the conductive adhesive curing parameters and the quartz crystal resonator assembly parameters as constraint conditions, wherein the first application record data of the quartz crystal resonator comprises quartz wafer average displacement rate and quartz wafer displacement in preset service time length and quartz wafer vibration amplitude under preset impact force;
step S230: constructing a first scoring coordinate axis based on the inverse of the average displacement rate, constructing a second scoring coordinate axis based on the inverse of the amplitude parameter, and constructing a third scoring coordinate axis based on the inverse of the displacement quantity;
step S240: generating a quartz wafer fixed stability scoring coordinate system according to the first scoring coordinate axis, the second scoring coordinate axis and the third scoring coordinate axis;
step S250: inputting the average displacement rate of the quartz wafer, the displacement amount of the quartz wafer and the vibration amplitude of the quartz wafer into the quartz wafer fixed stability scoring coordinate system to obtain the fixed stability score.
Specifically, since the fixing stability of the current quartz wafer needs to be predicted, the fixing stability needs to be scored based on the curing parameters of the conductive adhesive, and the obtained preparation parameters of the quartz crystal resonator include the assembly parameters of the quartz crystal resonator. The assembly parameters of the quartz crystal resonator are based on circuit elements contained in the quartz crystal resonator, all component structure parameters in the quartz crystal resonator are collected, and according to different assembly modes of all circuit elements, the assembly parameters of the quartz crystal resonator are correspondingly obtained, application record data of the quartz crystal resonator are collected, namely, the curing temperature time sequence information and the curing placement position time sequence information contained in the conductive adhesive curing parameters and the quartz crystal resonator assembly structure contained in the quartz crystal resonator assembly parameters are used as constraint parameters, the quartz crystal resonator is correspondingly constrained in the application process, and the data in the process are recorded and collected, so that the recorded and collected data are recorded as first application record data, the first application record data of the quartz crystal resonator comprise the average displacement rate and the quartz wafer displacement in a preset service period, the preset service period is the set period of the displacement parameters for counting the fixed stability degree of the quartz wafer, and the preferred determination process is as follows: the time period of the work of the set times is elapsed from the start of the service, wherein the set times are the shortest times which are considered to be possible to cause the quartz wafer to displace by an expert. The displacement of the quartz wafer is the total displacement distance within the preset service time length; and presetting the vibration amplitude of the quartz wafer under the impact force, wherein the preset impact force is the maximum impact force required to be born by the quartz wafer resonator set according to the working scene to be actually used. Meanwhile, a corresponding grading coordinate axis is built on the basis of the inverse of the average displacement rate of the quartz wafers in the preset service duration in sequence, namely, a first grading coordinate axis is built through the inverse of the average displacement rate of the quartz wafers, the corresponding average displacement rate grading is lower as the average displacement rate is larger, a corresponding grading coordinate axis is built on the basis of the inverse of the amplitude parameter of the quartz wafers in the preset service duration, namely, the first grading coordinate axis is built through the inverse of the amplitude parameter of the quartz wafers, the corresponding amplitude grading is lower as the amplitude of the quartz wafers is larger, a corresponding grading coordinate axis is built on the basis of the inverse of the displacement of the quartz wafers in the preset service duration, namely, the first grading coordinate axis is built through the inverse of the displacement of the quartz wafers, and the corresponding displacement grading is lower as the displacement of the quartz wafers is larger.
Meanwhile, the average displacement rate, the displacement amount and the vibration amplitude of the quartz wafer are input into a scale generated quartz wafer fixed stability scoring coordinate system, and the corresponding fixed stability score is output, so that the technical effect of providing important basis for later detection, correction, baking and curing real-time parameters is achieved.
Further, step S240 of the present application includes:
step S241: setting a first scoring weight for the average displacement velocity reciprocal, a second scoring weight for the amplitude parameter reciprocal, and a third scoring weight for the displacement reciprocal;
step S242: taking the first grading coordinate axis as a reference coordinate axis, and adjusting the second grading coordinate axis according to the ratio of the first grading weight to the second grading weight; and
step S243: and adjusting the third grading coordinate axis according to the ratio of the first grading weight to the third grading weight by taking the first grading coordinate axis as a reference coordinate axis, and generating the quartz wafer fixed stability grading coordinate system.
Specifically, since the average displacement rate, the amplitude parameter and the displacement amount of the quartz wafer have different degrees of influence on the stability of the quartz wafer, in order to show the difference of the influence weights in the scoring coordinate system of the stability of the quartz wafer, an expert group sets a first scoring weight for the reciprocal of the average displacement rate, a second scoring weight for the reciprocal of the amplitude parameter and a third scoring weight for the reciprocal of the displacement amount according to the difference of the degree of influence of the average displacement rate, the amplitude parameter and the displacement amount on the stability of the quartz wafer. Taking the first grading coordinate axis as a reference coordinate axis, and adjusting the second grading coordinate axis according to the ratio of the first grading weight to the second grading weight; and adjusting the third grading coordinate axis according to the ratio of the first grading weight to the third grading weight by taking the first grading coordinate axis as a reference coordinate axis, and generating the quartz wafer fixed stability grading coordinate system.
After the third scoring coordinate axis is adjusted according to the ratio of the first scoring weight to the third scoring weight, the quartz wafer fixed stability scoring coordinate system is generated as follows:
the original coordinate axis score is determined according to the average displacement rate, the amplitude parameter and the coordinate point of the displacement in the quartz wafer fixed stability score coordinate system, and the score of each coordinate axis of the quartz wafer fixed stability score coordinate system is increased along with the forward direction of the coordinate axis, so that when the weight is smaller, the input value of the coordinate axis is reduced, and when the weight is larger, the input value of the coordinate axis is increased, and the method is exemplified as follows: when the first scoring weight is 2 and the third scoring weight is 3, namely, the coordinate value in the third scoring coordinate axis is characterized in that the influence weight is larger in scoring, the ratio of the first scoring weight to the third scoring weight is 2/3, any input value of the third scoring coordinate axis is multiplied by 3/2 to increase, the final scoring is also influenced, and the degree difference that the average displacement rate, the amplitude parameter and the displacement amount influence the stability of the quartz wafer is considered, so that the final scoring accuracy is higher.
Further, as shown in fig. 3, step S300 of the present application further includes:
step S310: acquiring a frequency stability evaluation index, wherein the frequency stability evaluation index comprises a stress characteristic value and a solvent residual quantity;
step S320: taking the conductive adhesive curing parameters as independent variables, and taking the stress characteristic values and the solvent residual quantity as dependent variables to acquire curing processing data and obtain baking curing processing record data;
step S330: according to the baking and curing processing record data, performing supervised training based on a BP neural network, and constructing a frequency stability evaluation index prediction layer;
step S340: constructing a fourth scoring coordinate axis based on the inverse of the stress characteristic value, and constructing a fifth scoring coordinate axis based on the inverse of the solvent residual quantity;
step S350: generating a quartz crystal resonator frequency stability scoring coordinate system according to the fourth scoring coordinate axis and the fifth scoring coordinate axis;
step S360: combining an output layer of the frequency stability evaluation index prediction layer with an input layer of the frequency stability scoring coordinate system of the quartz crystal resonator to generate a frequency stability prediction model of the quartz crystal resonator;
step S370: inputting the curing parameters of the conductive adhesive into the quartz crystal resonator frequency stability prediction model to generate the resonator frequency stability score.
Specifically, since the frequency stability of the current quartz crystal resonator needs to be predicted, the frequency stability needs to be scored on the basis of the conductive adhesive curing parameters, firstly, a frequency stability evaluation index is set, the set frequency stability evaluation index comprises a stress characteristic value and a solvent residual quantity, further, the obtained adhesive curing parameters are set as independent variables, the stress characteristic value and the solvent residual quantity contained in the frequency stability evaluation index are set as dependent variables, the quartz crystal is subjected to data acquisition while being cured and is recorded as baking and curing processing record data, further, the obtained baking and curing processing record data is subjected to supervision and training through a BP neural network, on the basis, a frequency stability evaluation index prediction layer is constructed, and the frequency stability evaluation index prediction layer is obtained through training of a training data set and a supervision data set, wherein each group of training data in the training data set comprises the baking and curing processing record data; the supervision data set and the training data set are supervision data in one-to-one correspondence. And inputting each group of training data in the training data set into a frequency stability evaluation index prediction layer, performing output supervision adjustment of the frequency stability evaluation index prediction layer through supervision data corresponding to the group of training data, finishing the current group of training when the output result of the frequency stability evaluation index prediction layer is consistent with the supervision data, finishing all training data in the training data set, and finishing the training of the frequency stability evaluation index prediction layer. Meanwhile, in order to ensure the accuracy of the frequency stability evaluation index prediction layer, the test data set can be used for carrying out test processing on the frequency stability evaluation index prediction layer, namely the test accuracy can be set to 80%, and when the test accuracy of the test data set meets 80%, the frequency stability evaluation index prediction layer is constructed.
And constructing a corresponding grading coordinate axis based on the inverse stress characteristic value contained in the frequency stability evaluation index, namely a fourth grading coordinate axis, wherein the larger the stress characteristic value is, the lower the corresponding stress characteristic value grading is, constructing a corresponding grading coordinate axis based on the inverse solvent residual quantity contained in the frequency stability evaluation index, the lower the corresponding solvent residual quantity grading is, further, setting grading weights corresponding to the inverse stress characteristic value and the inverse solvent residual quantity, and adjusting the fifth grading coordinate axis according to the ratio of the fourth grading weight to the fifth grading weight by taking the fourth grading coordinate axis as a reference coordinate axis, thereby obtaining the frequency stability grading coordinate system of the quartz crystal resonator.
And connecting and combining the output layer in the constructed frequency stability evaluation index prediction layer with the input layer in the generated quartz crystal resonator frequency stability scoring coordinate system, namely directly inputting the data output by the frequency stability evaluation index prediction layer into the input layer in the quartz crystal resonator frequency stability scoring coordinate system after the baking and curing processing record data are input into the frequency stability evaluation index prediction layer, finishing the input of the data to the quartz crystal resonator frequency stability scoring coordinate system, wherein the process all occurs in a quartz crystal resonator frequency stability prediction model, namely the quartz crystal resonator frequency stability prediction model comprises the frequency stability evaluation index prediction layer and the quartz crystal resonator frequency stability scoring coordinate system, and finally achieving the technical effect of providing reference for detecting, correcting and curing real-time parameters according to the constructed quartz crystal resonator frequency stability prediction model.
Further, step S350 of the present application includes:
step S351: setting a fourth scoring weight for the inverse stress characteristic value and a fifth scoring weight for the inverse solvent residue;
step S352: and adjusting the fifth grading coordinate axis by taking the fourth grading coordinate axis as a reference coordinate axis according to the ratio of the fourth grading weight to the fifth grading weight, so as to generate the frequency stability grading coordinate system of the quartz crystal resonator.
Specifically, since the stress characteristic value and the solvent residual amount of the quartz wafer both affect the frequency stability, it is necessary to set a scoring weight corresponding to the inverse stress characteristic value and the inverse solvent residual amount of the quartz wafer, respectively, and in turn, a fourth scoring weight may be set according to the degree of influence thereof: the fifth scoring weight is 3:2, further, taking the fourth scoring coordinate axis constructed by the inverse stress characteristic value as a reference coordinate axis, and based on the ratio of the fourth scoring weight to the fifth scoring weight, namely the fourth scoring weight: the fifth scoring weight is 3: and 2, carrying out proportion adjustment on the solvent residual quantity on a fifth grading coordinate axis constructed by the reciprocal of the solvent residual quantity, thereby completing construction of a frequency stability grading coordinate system of the quartz crystal resonator so as to ensure stability when detecting and correcting baking solidification real-time parameters.
Further, as shown in fig. 4, step S600 of the present application further includes:
step S610: the conductive adhesive curing parameters comprise curing temperature time sequence information and curing placement position time sequence information;
step S620: setting a curing temperature constraint interval sequence and a curing placement position constraint space for the curing temperature time sequence information;
step S630: based on an industrial blockchain, taking the curing temperature constraint interval sequence and the curing placement position constraint space as constraint conditions, and collecting baking curing processing record data with preset data volume;
step S640: and setting the conductive adhesive curing parameter optimization result when the baking and curing processing record data meets the fixed stability scoring threshold value and the baking and curing processing record data meets the frequency stability scoring threshold value.
Specifically, in order to ensure better optimization design of the curing parameters of the conductive adhesive in the later period, the curing parameters of the conductive adhesive respectively comprise curing temperature time sequence information and curing placement position time sequence information, wherein the curing temperature time sequence information refers to different curing temperatures with time marks, the curing placement position time sequence information refers to positions of the curing process in a curing tunnel, the curing temperature time sequence information contained in the curing parameters of the conductive adhesive is correspondingly provided with a curing temperature constraint interval sequence and a curing placement position constraint space, the curing temperature constraint interval sequence can be set according to the range of the current curing temperature, and the curing placement position constraint space can be set according to the performance of the curing tunnel.
On the basis of an industrial blockchain, the industrial blockchain refers to an intelligent contract platform facing the industrial manufacturing field, a complete implementation of a bottom protocol, a supporting tool, an API interface set and the like are provided, a set curing temperature constraint interval sequence and a curing placement position constraint space are used as constraint conditions, a preset number of baking and curing processing record data are collected within the preset range, the preset number of baking and curing processing record data are correspondingly preset by related technicians according to the data amount of the baking and curing processing record in big data, when the fixed stability score meets the fixed stability score threshold or/and the frequency stability score of the resonator does not meet the frequency stability score threshold, the frequency stability of the current resonator is optimized, when the fixed stability score does not meet the fixed stability score threshold or/and the frequency stability score of the resonator does not meet the frequency stability score threshold, the conductive adhesive curing parameter is optimized, and iteration is conducted.
And (3) carrying out iterative judgment training on whether the fixed stability score meets a fixed stability score threshold value and whether the frequency stability score of the resonator meets a frequency stability score threshold value, limiting the number of times of iterative judgment training on whether the fixed stability score meets the fixed stability score threshold value and whether the frequency stability score of the resonator meets the frequency stability score threshold value when judging that the preset number of times meets the preset requirement, supposing that the number of iterations is limited to 10, carrying out iterative judgment training on whether the fixed stability score meets the fixed stability score threshold value and the frequency stability score of the resonator meets the frequency stability score threshold value to reach 10 times, if the baking and curing processing record data meets the fixed stability score threshold value and the baking and curing processing record data meets the frequency stability score threshold value, setting the current baking and curing record data as conducting resin curing parameter optimization results to be output, and finally achieving the technical effect of detecting, correcting and curing real-time parameters.
Further, as shown in fig. 5, step S800 of the present application further includes:
step S810: when the baking and curing processing record data does not meet the fixed stability scoring threshold value or/and does not meet the frequency stability scoring threshold value, randomly adjusting the curing temperature time sequence and the curing placing position time sequence information for N times to generate N groups of conductive adhesive curing parameter adjustment results;
Step S820: when any one of the N groups of conductive adhesive curing parameter adjustment results meets the fixed stability scoring threshold and the frequency stability scoring threshold is met, setting the result as the conductive adhesive curing parameter optimization result;
step S830: and when any one of the N groups of conductive adhesive curing parameter adjustment results does not meet the fixed stability scoring threshold value or/and does not meet the frequency stability scoring threshold value, generating an optimization abnormal signal and sending the optimization abnormal signal to a management terminal.
Specifically, when the baking and curing record data in the acquired preset data amount does not meet the fixed stability score threshold value or/and does not meet the frequency stability score threshold value, on the basis of a curing temperature constraint interval sequence or/and a curing placement position constraint space contained in the curing temperature time sequence information, the curing temperature time sequence information and the curing placement position time sequence information contained in the conductive curing parameters are randomly adjusted, and the random adjustment can be correspondingly set to N times, so that N groups of conductive adhesive curing parameter adjustment results are generated, and further, when any one of the N groups of conductive adhesive curing parameter adjustment results is selected, two conditions can occur, namely, when the current group of conductive adhesive curing parameter adjustment results meet the fixed stability score threshold value and simultaneously meet the frequency stability score threshold value, the current group of conductive adhesive curing parameter adjustment results are set as conductive adhesive curing parameter optimization results.
And when the current set of conductive adhesive curing parameter adjustment results do not meet the fixed stability scoring threshold value or/and do not meet the frequency stability scoring threshold value, generating a corresponding optimization abnormal signal, sending the corresponding optimization abnormal signal to the management terminal, and finally carrying out corresponding optimization adjustment on a curing temperature constraint interval and a curing placement position constraint interval by the management terminal.
Example two
Based on the same inventive concept as the baking and curing intelligent detection method of a quartz crystal in the foregoing embodiments, as shown in fig. 6, the present application provides a baking and curing intelligent detection system of a quartz crystal, the system comprising:
the parameter acquisition module 1 is used for acquiring preparation parameters of the quartz crystal resonator, wherein the preparation parameters of the quartz crystal resonator comprise conductive adhesive curing parameters;
the fixed stability prediction module 2 is used for predicting the fixed stability of the quartz wafer according to the curing parameters of the conductive adhesive, and generating a fixed stability score;
the frequency stability prediction module 3 is used for predicting the frequency stability of the quartz crystal resonator according to the curing parameters of the conductive adhesive, and generating a resonator frequency stability score;
A first judging module 4, where the first judging module 4 is configured to judge whether the fixed stability score meets a fixed stability score threshold;
a second judging module 5, where the second judging module 5 is configured to judge whether the frequency stability score of the resonator meets a frequency stability score threshold;
the optimization design module 6 is configured to perform an optimization design on the conductive adhesive curing parameter when the fixed stability score does not meet the fixed stability score threshold, or/and the resonator frequency stability score does not meet the frequency stability score threshold, so as to generate a conductive adhesive curing parameter optimization result;
the detection and correction module 7 is used for detecting and correcting the baking and curing real-time parameters according to the conducting resin curing parameter optimization result.
Further, the system further comprises:
the preparation parameter module is used for preparing parameters of the quartz crystal resonator and also comprises assembly parameters of the quartz crystal resonator;
the recording data module is used for collecting first application recording data of the quartz crystal resonator by taking the conductive adhesive curing parameters and the quartz crystal resonator assembly parameters as constraint conditions, wherein the first application recording data of the quartz crystal resonator comprises a quartz wafer average displacement rate and a quartz wafer displacement amount within a preset service duration and a quartz wafer vibration amplitude under a preset impact force;
The first coordinate axis construction module is used for constructing a first grading coordinate axis based on the inverse of the average displacement rate, constructing a second grading coordinate axis based on the inverse of the amplitude parameter and constructing a third grading coordinate axis based on the inverse of the displacement;
the first scoring coordinate system module is used for generating a quartz wafer fixed stability scoring coordinate system according to the first scoring coordinate axis, the second scoring coordinate axis and the third scoring coordinate axis;
and the score acquisition module is used for inputting the average displacement rate of the quartz wafer, the displacement amount of the quartz wafer and the vibration amplitude of the quartz wafer into the quartz wafer fixed stability score coordinate system to acquire the fixed stability score.
Further, the system further comprises:
the first weight setting module is used for setting a first scoring weight for the average displacement velocity reciprocal, setting a second scoring weight for the amplitude parameter reciprocal and setting a third scoring weight for the displacement reciprocal;
the first adjustment module is used for adjusting the second grading coordinate axis according to the ratio of the first grading weight to the second grading weight by taking the first grading coordinate axis as a reference coordinate axis; and
The second adjustment module is used for adjusting the third grading coordinate axis by taking the first grading coordinate axis as a reference coordinate axis according to the ratio of the first grading weight to the third grading weight, and then generating the quartz wafer fixed stability grading coordinate system.
Further, the system further comprises:
the index acquisition module is used for acquiring a frequency stability evaluation index, wherein the frequency stability evaluation index comprises a stress characteristic value and a solvent residual quantity;
the recording data acquisition module is used for acquiring curing processing data by taking the conductive adhesive curing parameters as independent variables and taking the stress characteristic values and the solvent residual quantity as dependent variables to acquire baking curing processing recording data;
the supervision and training module is used for performing supervision and training based on the BP neural network according to the baking, curing and processing record data to construct a frequency stability assessment index prediction layer;
the second coordinate axis construction module is used for constructing a fourth grading coordinate axis based on the inverse of the stress characteristic value and constructing a fifth grading coordinate axis based on the inverse of the solvent residual quantity;
The second scoring coordinate system module is used for generating a scoring coordinate system of the frequency stability of the quartz crystal resonator according to the fourth scoring coordinate axis and the fifth scoring coordinate axis;
the model generation module is used for combining the output layer of the frequency stability evaluation index prediction layer with the input layer of the frequency stability scoring coordinate system of the quartz crystal resonator to generate a frequency stability prediction model of the quartz crystal resonator;
and the resonator frequency stability score generation module is used for inputting the conductive adhesive curing parameters into the quartz crystal resonator frequency stability prediction model to generate the resonator frequency stability score.
Further, the system further comprises:
the second weight setting module is used for setting fourth scoring weight for the inverse stress characteristic value and setting fifth scoring weight for the inverse solvent residual quantity;
and the third grading coordinate system module is used for adjusting the fifth grading coordinate axis by taking the fourth grading coordinate axis as a reference coordinate axis according to the ratio of the fourth grading weight to the fifth grading weight to generate the frequency stability grading coordinate system of the quartz crystal resonator.
Further, the system further comprises:
the information acquisition module is used for acquiring curing parameters of the conductive adhesive, wherein the curing parameters comprise curing temperature time sequence information and curing placement position time sequence information;
the first constraint module is used for setting a curing temperature constraint interval sequence and a curing placement position constraint space for the curing temperature time sequence information;
the second constraint module is used for acquiring baking and curing processing record data of a preset data volume based on an industrial block chain by taking the curing temperature constraint interval sequence and the curing placement position constraint space as constraint conditions;
the first parameter optimization module is used for setting the conducting resin curing parameter optimization result when the baking and curing processing record data meet the fixed stability scoring threshold value and the baking and curing processing record data meet the frequency stability scoring threshold value.
Further, the system further comprises:
the random adjustment module is used for randomly adjusting the curing temperature time sequence and the curing position time sequence information for N times when the baking curing processing record data does not meet the fixed stability scoring threshold value or/and does not meet the frequency stability scoring threshold value, so as to generate N groups of conductive adhesive curing parameter adjustment results;
The first parameter optimization module is used for setting the curing parameter optimization result of the conductive adhesive when any one of the N groups of curing parameter adjustment results of the conductive adhesive meets the fixed stability scoring threshold and meets the frequency stability scoring threshold;
and the sending module is used for generating an optimized abnormal signal to be sent to the management terminal when any one of the N groups of conductive adhesive curing parameter adjustment results does not meet the fixed stability scoring threshold value or/and does not meet the frequency stability scoring threshold value.
The foregoing detailed description of a method for detecting baking and curing of a quartz crystal will be clear to those skilled in the art, and the device disclosed in this embodiment is relatively simple in description, and the relevant points refer to the description of the method section because it corresponds to the method disclosed in the embodiment.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. The intelligent detection method for baking and curing of the quartz crystal is characterized by comprising the following steps of:
obtaining preparation parameters of a quartz crystal resonator, wherein the preparation parameters of the quartz crystal resonator comprise conductive adhesive curing parameters;
predicting the fixation stability of the quartz wafer according to the curing parameters of the conductive adhesive to generate a fixation stability score;
predicting the frequency stability of the quartz crystal resonator according to the curing parameters of the conductive adhesive to generate a resonator frequency stability score;
judging whether the fixed stability score meets a fixed stability score threshold;
judging whether the frequency stability score of the resonator meets a frequency stability score threshold;
when the fixed stability score does not meet the fixed stability score threshold value or/and the frequency stability score of the resonator does not meet the frequency stability score threshold value, optimally designing the conductive adhesive curing parameters to generate conductive adhesive curing parameter optimization results;
detecting and correcting baking and curing real-time parameters according to the conducting resin curing parameter optimization result;
wherein, carry out quartz wafer fixed stability prediction according to the conducting resin curing parameter, generate fixed stability score, include:
The preparation parameters of the quartz crystal resonator also comprise assembly parameters of the quartz crystal resonator;
collecting first application record data of the quartz crystal resonator by taking the conductive adhesive curing parameters and the quartz crystal resonator assembly parameters as constraint conditions, wherein the first application record data of the quartz crystal resonator comprises quartz wafer average displacement rate and quartz wafer displacement in preset service time length and quartz wafer vibration amplitude under preset impact force;
constructing a first scoring coordinate axis based on the inverse of the average displacement rate, constructing a second scoring coordinate axis based on the inverse of the amplitude parameter, and constructing a third scoring coordinate axis based on the inverse of the displacement quantity;
generating a quartz wafer fixed stability scoring coordinate system according to the first scoring coordinate axis, the second scoring coordinate axis and the third scoring coordinate axis;
inputting the average displacement rate of the quartz wafer, the displacement amount of the quartz wafer and the vibration amplitude of the quartz wafer into a quartz wafer fixed stability scoring coordinate system to obtain the fixed stability score;
and predicting the frequency stability of the quartz crystal resonator according to the curing parameters of the conductive adhesive to generate a resonator frequency stability score, wherein the method comprises the following steps:
Acquiring a frequency stability evaluation index, wherein the frequency stability evaluation index comprises a stress characteristic value and a solvent residual quantity;
taking the conductive adhesive curing parameters as independent variables, and taking the stress characteristic values and the solvent residual quantity as dependent variables to acquire curing processing data and obtain baking curing processing record data;
according to the baking and curing processing record data, performing supervised training based on a BP neural network, and constructing a frequency stability evaluation index prediction layer;
constructing a fourth scoring coordinate axis based on the inverse of the stress characteristic value, and constructing a fifth scoring coordinate axis based on the inverse of the solvent residual quantity;
generating a quartz crystal resonator frequency stability scoring coordinate system according to the fourth scoring coordinate axis and the fifth scoring coordinate axis;
combining an output layer of the frequency stability evaluation index prediction layer with an input layer of the frequency stability scoring coordinate system of the quartz crystal resonator to generate a frequency stability prediction model of the quartz crystal resonator;
inputting the curing parameters of the conductive adhesive into the quartz crystal resonator frequency stability prediction model to generate the resonator frequency stability score.
2. The intelligent detection method for baking and curing quartz crystals according to claim 1, wherein generating a quartz wafer fixed stability scoring coordinate system according to the first scoring coordinate axis, the second scoring coordinate axis and the third scoring coordinate axis comprises:
Setting a first scoring weight for the average displacement velocity reciprocal, a second scoring weight for the amplitude parameter reciprocal, and a third scoring weight for the displacement reciprocal;
taking the first grading coordinate axis as a reference coordinate axis, and adjusting the second grading coordinate axis according to the ratio of the first grading weight to the second grading weight; and
and adjusting the third grading coordinate axis according to the ratio of the first grading weight to the third grading weight by taking the first grading coordinate axis as a reference coordinate axis, and generating the quartz wafer fixed stability grading coordinate system.
3. The intelligent detection method for baking solidification of quartz crystal according to claim 1, wherein generating a quartz crystal resonator frequency stability scoring coordinate system according to the fourth scoring coordinate axis and the fifth scoring coordinate axis comprises:
setting a fourth scoring weight for the inverse stress characteristic value and a fifth scoring weight for the inverse solvent residue;
and adjusting the fifth grading coordinate axis by taking the fourth grading coordinate axis as a reference coordinate axis according to the ratio of the fourth grading weight to the fifth grading weight, so as to generate the frequency stability grading coordinate system of the quartz crystal resonator.
4. The intelligent detection method for baking and curing quartz crystals according to claim 1, wherein when the fixed stability score does not meet the fixed stability score threshold, or/and the resonator frequency stability score does not meet the frequency stability score threshold, the optimization design is performed on the conductive adhesive curing parameters to generate a conductive adhesive curing parameter optimization result, which comprises the following steps:
the conductive adhesive curing parameters comprise curing temperature time sequence information and curing placement position time sequence information;
setting a curing temperature constraint interval sequence and a curing placement position constraint space for the curing temperature time sequence information;
based on an industrial blockchain, taking the curing temperature constraint interval sequence and the curing placement position constraint space as constraint conditions, and collecting baking curing processing record data with preset data volume;
and when the baking and curing processing record data meets the fixed stability scoring threshold value and the baking and curing processing record data meets the frequency stability scoring threshold value, setting the baking and curing processing record data as the conducting resin curing parameter optimization result.
5. The intelligent detection method for baking solidification of quartz crystal according to claim 4, further comprising:
When the baking and curing processing record data does not meet the fixed stability scoring threshold value or/and does not meet the frequency stability scoring threshold value, randomly adjusting the curing temperature time sequence and the curing placing position time sequence information for N times to generate N groups of conductive adhesive curing parameter adjustment results;
when any one of the N groups of conductive adhesive curing parameter adjustment results meets the fixed stability scoring threshold and the frequency stability scoring threshold is met, setting the result as the conductive adhesive curing parameter optimization result;
and when any one of the N groups of conductive adhesive curing parameter adjustment results does not meet the fixed stability scoring threshold value or/and does not meet the frequency stability scoring threshold value, generating an optimization abnormal signal and sending the optimization abnormal signal to a management terminal.
6. The intelligent detection system for baking and curing of quartz crystals is characterized by comprising:
the parameter acquisition module is used for acquiring preparation parameters of the quartz crystal resonator, wherein the preparation parameters of the quartz crystal resonator comprise conductive adhesive curing parameters;
The fixed stability prediction module is used for predicting the fixed stability of the quartz wafer according to the curing parameters of the conductive adhesive and generating a fixed stability score;
the frequency stability prediction module is used for predicting the frequency stability of the quartz crystal resonator according to the curing parameters of the conductive adhesive and generating a resonator frequency stability score;
the first judging module is used for judging whether the fixed stability score meets a fixed stability score threshold value or not;
the second judging module is used for judging whether the frequency stability score of the resonator meets a frequency stability score threshold value or not;
the optimization design module is used for optimally designing the conductive adhesive curing parameters when the fixed stability score does not meet the fixed stability score threshold value or/and the frequency stability score of the resonator does not meet the frequency stability score threshold value, so as to generate a conductive adhesive curing parameter optimization result;
the detection and correction module is used for detecting and correcting the baking and curing real-time parameters according to the conducting resin curing parameter optimization result;
The preparation parameter module is used for preparing parameters of the quartz crystal resonator and also comprises assembly parameters of the quartz crystal resonator;
the recording data module is used for collecting first application recording data of the quartz crystal resonator by taking the conductive adhesive curing parameters and the quartz crystal resonator assembly parameters as constraint conditions, wherein the first application recording data of the quartz crystal resonator comprises a quartz wafer average displacement rate and a quartz wafer displacement amount within a preset service duration and a quartz wafer vibration amplitude under a preset impact force;
the first coordinate axis construction module is used for constructing a first grading coordinate axis based on the inverse of the average displacement rate, constructing a second grading coordinate axis based on the inverse of the amplitude parameter and constructing a third grading coordinate axis based on the inverse of the displacement;
the first scoring coordinate system module is used for generating a quartz wafer fixed stability scoring coordinate system according to the first scoring coordinate axis, the second scoring coordinate axis and the third scoring coordinate axis;
the scoring acquisition module is used for inputting the average displacement rate of the quartz wafer, the displacement amount of the quartz wafer and the vibration amplitude of the quartz wafer into the quartz wafer fixed stability scoring coordinate system to acquire the fixed stability score;
The index acquisition module is used for acquiring a frequency stability evaluation index, wherein the frequency stability evaluation index comprises a stress characteristic value and a solvent residual quantity;
the recording data acquisition module is used for acquiring curing processing data by taking the conductive adhesive curing parameters as independent variables and taking the stress characteristic values and the solvent residual quantity as dependent variables to acquire baking curing processing recording data;
the supervision and training module is used for performing supervision and training based on the BP neural network according to the baking, curing and processing record data to construct a frequency stability assessment index prediction layer;
the second coordinate axis construction module is used for constructing a fourth grading coordinate axis based on the inverse of the stress characteristic value and constructing a fifth grading coordinate axis based on the inverse of the solvent residual quantity;
the second scoring coordinate system module is used for generating a scoring coordinate system of the frequency stability of the quartz crystal resonator according to the fourth scoring coordinate axis and the fifth scoring coordinate axis;
the model generation module is used for combining the output layer of the frequency stability evaluation index prediction layer with the input layer of the frequency stability scoring coordinate system of the quartz crystal resonator to generate a frequency stability prediction model of the quartz crystal resonator;
And the resonator frequency stability score generation module is used for inputting the conductive adhesive curing parameters into the quartz crystal resonator frequency stability prediction model to generate the resonator frequency stability score.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310408931.4A CN116461023B (en) | 2023-04-18 | 2023-04-18 | Intelligent detection method and system for baking and curing of quartz crystal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310408931.4A CN116461023B (en) | 2023-04-18 | 2023-04-18 | Intelligent detection method and system for baking and curing of quartz crystal |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116461023A CN116461023A (en) | 2023-07-21 |
| CN116461023B true CN116461023B (en) | 2023-10-13 |
Family
ID=87176576
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310408931.4A Active CN116461023B (en) | 2023-04-18 | 2023-04-18 | Intelligent detection method and system for baking and curing of quartz crystal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116461023B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US2376219A (en) * | 1944-01-28 | 1945-05-15 | Gen Electric | Fabrication of quartz resonators |
| SU720671A1 (en) * | 1974-09-26 | 1980-03-05 | Предприятие П/Я А-1001 | Quartz oscillator |
| JPH11326019A (en) * | 1998-05-19 | 1999-11-26 | Natl Res Inst For Metals | Determination method for quantity of sea salt grain |
| WO2009060100A2 (en) * | 2007-11-09 | 2009-05-14 | Universität Regensburg | Impedance-scanning quartz crystal microbalance |
| CN106487347A (en) * | 2015-08-31 | 2017-03-08 | 通用电气公司 | The system and method engaging for quartz wafer |
| CN113779927A (en) * | 2021-08-12 | 2021-12-10 | 华中科技大学 | Method and device for determining equivalent circuit parameters of quartz crystal resonator |
| CN113949359A (en) * | 2021-09-30 | 2022-01-18 | 铜陵嘉禾电子科技有限公司 | Frequency fine adjustment system and fine adjustment method of quartz crystal resonator |
| CN115186530A (en) * | 2022-06-10 | 2022-10-14 | 浙江工业大学 | Method for optimizing thermal stress of quartz crystal resonator through structural dimension parameters |
-
2023
- 2023-04-18 CN CN202310408931.4A patent/CN116461023B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US2376219A (en) * | 1944-01-28 | 1945-05-15 | Gen Electric | Fabrication of quartz resonators |
| SU720671A1 (en) * | 1974-09-26 | 1980-03-05 | Предприятие П/Я А-1001 | Quartz oscillator |
| JPH11326019A (en) * | 1998-05-19 | 1999-11-26 | Natl Res Inst For Metals | Determination method for quantity of sea salt grain |
| WO2009060100A2 (en) * | 2007-11-09 | 2009-05-14 | Universität Regensburg | Impedance-scanning quartz crystal microbalance |
| CN106487347A (en) * | 2015-08-31 | 2017-03-08 | 通用电气公司 | The system and method engaging for quartz wafer |
| CN113779927A (en) * | 2021-08-12 | 2021-12-10 | 华中科技大学 | Method and device for determining equivalent circuit parameters of quartz crystal resonator |
| CN113949359A (en) * | 2021-09-30 | 2022-01-18 | 铜陵嘉禾电子科技有限公司 | Frequency fine adjustment system and fine adjustment method of quartz crystal resonator |
| CN115186530A (en) * | 2022-06-10 | 2022-10-14 | 浙江工业大学 | Method for optimizing thermal stress of quartz crystal resonator through structural dimension parameters |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116461023A (en) | 2023-07-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110135079B (en) | Macroscopic elasticity evaluation method and system for offshore oil well control equipment | |
| CN107957562B (en) | Online prediction method for residual life of lithium ion battery | |
| US8190378B2 (en) | Crack growth evaluation apparatus, crack growth evaluation method, and recording medium recording crack growth evaluation program | |
| CN111125947B (en) | Modeling method and related device for crimping IGBT thermal network model | |
| CN111008502A (en) | Fault prediction method for complex equipment driven by digital twin | |
| CN111080477A (en) | Household power load prediction method and system | |
| CN113949359A (en) | Frequency fine adjustment system and fine adjustment method of quartz crystal resonator | |
| CN116461023B (en) | Intelligent detection method and system for baking and curing of quartz crystal | |
| CN114166318A (en) | Ultrasonic water meter flow data calibration method based on deep learning | |
| CN113435699A (en) | Intelligent quality control method and system | |
| CN102725644B (en) | Smoothed-current calculating device, smoothed-current calculating method, and battery monitoring module | |
| CN114130713B (en) | Battery echelon utilization screening method and device | |
| CN110927597B (en) | Method for determining battery discharge curve | |
| CN116990691A (en) | Method, device, equipment and medium for evaluating remaining full charge time of battery | |
| CN112532615A (en) | Smart grid worm detection method | |
| CN111238667B (en) | Temperature compensation method, printed circuit board, compressor and vehicle | |
| CN114328473A (en) | Battery data detection method and device | |
| CN113536489B (en) | Method for determining connection configuration and process parameters of component package | |
| CN110942019A (en) | Analysis method for finding longest adjoint path of two tracks | |
| CN111832169B (en) | Automatic correction method for battery cell life model | |
| CN114578249A (en) | Lithium battery health state estimation method based on stability characteristics and AS-TCN model | |
| CN115146525A (en) | System for estimating deterioration state of secondary battery, method for estimating deterioration state of secondary battery, and storage medium | |
| CN113393046A (en) | Photovoltaic power prediction method and application device thereof | |
| CN116566841B (en) | Flow trend prediction method based on network flow query | |
| CN114897091B (en) | Intelligent factory end data fusion method for high-end battery |
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 |