Argon leakage detection and degradation analysis method for curtain wall hollow glass unit

Abstract

The invention provides an argon leakage detection and degradation analysis method for a curtain wall hollow glass unit, and relates to the technical field of hollow glass unit evaluation. The method comprises the following steps: putting a qualified hollow glass unit into a water tank for a water sinking experiment, and detecting whether dew is formed in a cavity of the hollow glass unit; the argon content is measured for the hollow glass unit without condensation, and data are recorded; obtaining argon content data of a plurality of groups of hollow glass units; modeling the argon content degradation data by using a Wiener process model, and finding out all deterministic parameters influencing the argon content degradation; and iteratively solving the value of a deterministic parameter, substituting the value into a degradation increment distribution formula of the argon content in the hollow glass unit, fitting argon degradation data, calculating the reliability of the hollow glass unit, and analyzing the degradation process of the hollow glass unit. The method has a certain guiding significance for maintaining the heat insulation performance of the hollow glass unit in engineering practice.

Description

Technical Field

[0001] The invention relates to the technical field of insulating glass unit evaluation, and in particular to an argon gas leakage detection and degradation analysis method for a curtain wall insulating glass unit. Background Art

[0002] Insulating Glass Unit (IGU) is a common structural component in curtain walls, which uses argon gas in its cavity to reduce heat exchange between indoor and outdoor thermal environments, thereby improving energy efficiency. Argon leakage can seriously affect the thermal performance of glass curtain walls and mean that its sealing system fails. This failure may lead to water ingress, mold growth, and even structural failure of the entire curtain wall unit. Therefore, it is crucial to understand the degradation process of argon content in insulating glass units under actual engineering conditions.

[0003] In order to evaluate the degradation of the thermal insulation performance of the curtain wall insulating glass unit during long-term service, it is necessary to analyze the degradation process of the argon content in the unit. After obtaining the argon content degradation data, the sealing performance can be further evaluated and the long-term reliability can be predicted.

[0004] In recent years, many scholars have studied the degradation of the thermal insulation performance of insulating glass units, focusing on the role of sealants, partition design, spacing materials and environmental factors. Existing studies have demonstrated the importance of the sealing performance of insulating glass units from different perspectives, and have conducted quantitative and qualitative analysis of the factors that lead to the failure of its thermal insulation performance, laying the foundation for the degradation of the thermal insulation performance of insulating glass units and the performance monitoring of curtain walls. Its basic principles have been quite mature.

[0005] However, these studies did not consider the impact of various random factors on the failure of the insulation performance of the insulating glass unit, and lacked quantitative analysis of the key issue of argon leakage. In addition, these studies did not provide specific results for predicting the reliability of the insulating glass unit, making it difficult to provide maintenance recommendations after installation. Therefore, the above studies have certain limitations. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide an argon leakage detection and degradation analysis method for a curtain wall hollow glass unit in view of the deficiencies of the above-mentioned prior art, analyze the degradation process of the argon content in the unit, and further evaluate the sealing performance and predict the long-term reliability after obtaining the argon content degradation data.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for detecting argon leakage and degradation analysis of a curtain wall insulating glass unit, comprising: Step S1: collecting the initial argon content of insulating glass units of different models to determine whether the quality of the insulating glass units is qualified; Step S2: placing the insulating glass unit of qualified quality into a water tank for a submersion test; Step S3: Wipe clean the surface of the insulating glass unit after the submersion test, detect whether condensation occurs in the cavity of the insulating glass unit, and apply a layer of 95% ethanol at the detection position; Step S4: Observe whether condensation occurs at the measured position of the insulating glass unit. If no condensation occurs, measure the argon content and record the data. Step S5: repeating steps S2 to S4 to obtain multiple groups of argon content data of insulating glass units; and processing the argon content degradation data of the insulating glass units to increase the argon content data; Step S6: Modeling the argon content degradation data using the Wiener process model to find all deterministic parameters that affect the argon content degradation; Modeling the argon content degradation data of insulating glass units using Indicates the insulating glass unit at time t Based on the argon content degradation data, the degradation process of the argon content in the insulating glass unit is modeled using the Wiener process model shown in formula (1): (1) In this model, the argon content degradation data is represented as a Wiener process with drift, where the drift term Corresponding to the average leakage rate, is a random variable representing the initial degradation level; the parameter and are simulated as independent Gaussian random variables, i.e. ,in, N () is the normal distribution function, They are The mean and standard deviation of They are The mean and standard deviation of represents random fluctuations due to changes in conditions; in addition, represents standard Brownian motion; represents the diffusion coefficient; In the j In this test, the incremental degradation of the argon content of the insulating glass unit is expressed as , Respectively represent j Second and j -Degradation of the argon content of the insulating glass unit during 1 test, j =1,2... n , n Indicates the total number of argon content measurements; Respectively represent the argon content of the insulating glass unit j Second and j - 1 test time; The degradation increment distribution formula of argon content in insulating glass units is as follows: (2) (3) in, represents the time increment; Then we get the deterministic parameter matrix ; Step S7: using the EM algorithm to iteratively obtain the value of the deterministic parameter, substituting it into the degradation increment distribution formula of the argon content in the insulating glass unit, fitting the argon degradation data, calculating the reliability of the insulating glass unit, and further analyzing its degradation process; For degraded data , the EM algorithm is used to iteratively find the value of the deterministic parameter, which includes two steps: 1) E-step: Calculate the deterministic parameter matrix The likelihood function Q of: (4) In the formula, is the random parameter matrix; is the probability density function of the argon content degradation increment estimation under the condition of known prior information of random parameters and deterministic parameters, according to the probability density function of the argon content degradation increment under the condition of known prior information of random parameters Sure; is the probability density function of the random parameter matrix under the condition of known deterministic parameters. The joint probability density function of Determine; E represents conditional expectation; In the jth test, the probability density function of the degradation increment of argon content under the condition of known random parameter prior information is It is expressed as: (5) in, Indicates a time interval; Random parameter matrix The joint probability density function of It is expressed as: (6) Substituting formula (5)-(6) into formula (4), we can further derive the expression of likelihood function Q: (7) Parameters involved in formula (7) The conditional expected value of is shown in the following formula (8), and the value of the unknown parameter in the conditional expected value is shown in the following formula (9); (8) (9) in, For the n The time of the measurement; 2) M-step: through the function To update , q represents the number of iterations; make , then we get the estimation formula (10) of the deterministic parameters in the q+1 step: (10) Repeat the M-step until the difference between the likelihood function Q values ​​of two consecutive times is less than , that is , at this time, the values ​​of each deterministic parameter converge; obtain the deterministic parameter matrix The value of Find the deterministic parameter matrix Afterwards, the fitting results of the argon degradation data were obtained; Calculating the reliability of insulating glass units using Monte Carlo simulation algorithm , determine the thermal insulation performance of the insulating glass unit; (11) In the formula, , and is the sampling index, and is a parameter and The sampling size of the sampling, D is the failure threshold.

[0008] The beneficial effects of the above technical solution are as follows: the present invention provides a method for detecting argon leakage and degradation analysis of the insulating glass unit of the curtain wall, designs a submerged test for the cold-bent IGU, and measures its argon content data set; innovatively adopts the Wiener process model to simulate the argon content degradation data of the IGU. After the model parameters are determined using the EM algorithm, the degradation process is fitted and the reliability of the IGU is calculated. Finally, the reliability calculation results of the IGU are analyzed and discussed, which has certain guiding significance for the maintenance of the thermal insulation performance of the insulating glass unit in actual engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1A flow chart of a method for detecting argon leakage and analyzing degradation of a curtain wall insulating glass unit provided by an embodiment of the present invention; Figure 2 A schematic diagram of the structure of a hollow glass provided by an embodiment of the present invention; Figure 3 A graph showing degradation data of argon content in an insulating glass unit provided by an embodiment of the present invention; Figure 4 The deterministic parameter iteration result diagram of the insulating glass unit 0383 provided in the embodiment of the present invention, wherein (a) is the parameter The iterative result of (b) is the parameter The iterative result, (c) is the parameter The iterative result, (d) is the parameter The iterative result, (e) is the parameter The iteration result of Figure 5 A fitting result diagram of the degradation data of the insulating glass unit 0383 provided in an embodiment of the present invention; Figure 6 This is a diagram showing the reliability analysis results of the insulating glass unit 0383 provided in an embodiment of the present invention.

[0010] In the figure: 1. first laminated glass; 2. second laminated glass; 3. argon gas; 4. super spacer; 5. structural adhesive; 6. silicone sealant; 7. butyl adhesive. DETAILED DESCRIPTION

[0011] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0012] In this embodiment, a method for detecting argon leakage and analyzing degradation of a curtain wall insulating glass unit is provided. Figure 1 As shown, including: Step S1: Put different types of insulating glass on the assembly frame, put on the buckle plate to get the insulating glass unit, then put the obtained insulating glass unit on the iron frame, measure the initial argon content of the insulating glass unit with an argon detector, and seal the pinhole with silicone sealant.

[0013] The argon leakage detection and degradation analysis method of the curtain wall insulating glass unit of this embodiment can be applied to various insulating glass units. The structural diagram of the insulating glass unit used in this embodiment is as follows: Figure 2 As shown, the first laminated glass 1 and the second laminated glass 2 form a cavity structure, the cavity is filled with argon gas 3, and the bottom of the cavity is provided with a super spacer 4, structural adhesive 5 and silicone sealant 6; butyl adhesive 7 is provided on both sides of the super spacer 4.

[0014] First, put different types of insulating glass on the assembly frame, install the gusset plates to achieve the cold bending amount required in actual engineering, form a complete insulating glass unit, and then place it on the iron frame.

[0015] Then use an argon detector to measure the initial argon content of the insulating glass unit. In this embodiment, during measurement, first insert a needle into the hollow glass cavity to open the airway, and then insert the needle on the top of the argon detector. After the reading of the argon detector stabilizes, read the argon content monitoring data. After reading the data, unplug the needle and plug the needle eye with silicone sealant. Record the average of the three test values ​​as the initial argon content of the insulating glass unit. If the initial argon content of the insulating glass unit is greater than 90%, it means that the quality of the insulating glass unit is qualified and the experiment can continue. If the argon content does not meet the standard, the insulating glass unit needs to be returned to the factory for inspection and no subsequent experiments will be carried out.

[0016] Step S2: After the sealant is air-dried, the insulating glass unit is placed in a water tank, and water is added to the water tank until the water covers the glass unit. The submersion experiment begins, and the insulating glass unit is taken out of the water after 5 days.

[0017] After the sealant used to seal the pinholes was air-dried, the insulating glass unit in this embodiment and the glass frame were placed into a large water tank using a crane. Water was poured into the water tank until the water covered the insulating glass unit. The submersion experiment began and the insulating glass unit was fished out of the water after 5 days.

[0018] Step S3: Wipe the surface of the insulating glass unit clean, use a portable dew point meter to detect whether there is condensation in the cavity of the insulating glass unit, and apply a layer of 95% ethanol on the detection position.

[0019] After soaking in water for 5 days, wipe the surface of the insulating glass unit clean and apply a layer of 95% ethanol solution on the measured area. Use a portable dew point meter to detect whether there is condensation inside the cavity of the insulating glass unit. When testing, first add 25ml of 95% ethanol solution in the measuring cylinder and pour it into the measuring cylinder of the dew point meter. Then add a small amount of dry ice to the measuring cylinder and insert the thermometer of the dew point meter to ensure that the temperature in the measuring cylinder is lower than -60℃. If the temperature is higher than -60℃, it is necessary to re-pour the ethanol solution and dry ice. After reaching the temperature condition, place the measuring cylinder on the surface of the glass to be tested for 10 minutes.

[0020] Step S4: Observe whether condensation occurs at the measured position of the insulating glass unit. If no condensation occurs, measure the argon content and record the data. After the measurement is completed, seal the pinhole.

[0021] If there is no condensation inside the tested insulating glass unit, it means that no water or water vapor enters the unit during the submersion test, and the water tightness of the insulating glass unit is good, and further test its argon content. If condensation occurs, it means that the sealing structure of the insulating glass unit fails, and the degradation test for the insulating glass unit is stopped.

[0022] Step S5: Repeat steps S2 to S4 until the 151st day of the experiment, and obtain 31 sets of argon content data of insulating glass units.

[0023] Repeat steps S2 to S4 until the 151st day, when the submersion test has been carried out for 30 cycles, and the initial argon content test data of the insulating glass unit is added, and a total of 31 tests are carried out. In this embodiment, at the end of the experiment, five insulating glass units did not fail in watertightness or airtightness, and the models were 4894, 3542, 3319-1, 0383, and 3319-2. In order to facilitate the subsequent modeling and further analysis of the argon content degradation data of the insulating glass unit, the experimental data obtained is subtracted from 100% to increase the argon content data. The results are as follows Figure 3 shown.

[0024] Step S6: Modeling the argon content degradation data using the Wiener process model to find all deterministic parameters that affect the argon content degradation; In this embodiment, the argon content degradation data of the insulating glass unit is modeled. Indicates the insulating glass unit at time t Based on the argon content degradation data, the degradation process of the argon content in the insulating glass unit is modeled using the Wiener process model shown in formula (1): (1) In this model, the argon content degradation data is represented as a Wiener process with drift, where the drift term Corresponding to the average leakage rate, is a random variable representing the initial degradation level; the parameter and are simulated as independent Gaussian random variables, i.e. ,in, N () is the normal distribution function, They are The mean and standard deviation of They are The mean and standard deviation of represents random fluctuations due to changes in conditions; in addition, represents standard Brownian motion; represents the diffusion coefficient; In thej In this test, the incremental degradation of the argon content of the insulating glass unit is expressed as , Respectively represent j Second and j -Degradation of the argon content of the insulating glass unit during 1 test, j =1,2... n , n Indicates the total number of argon content measurements; Respectively represent the argon content of the insulating glass unit j Second and j - 1 test time; The degradation increment distribution formula of argon content in insulating glass units is as follows: (2) (3) in, represents the time increment; Then we get the deterministic parameter matrix ; Step S7: Use the EM algorithm (Expectation Maximization Algorithm) to iteratively obtain the value of the deterministic parameter, substitute it into the degradation increment distribution formula (2)-(3) of the argon content in the insulating glass unit, fit the argon degradation data, calculate the reliability of the insulating glass unit, and further analyze its degradation process; For degraded data , the EM algorithm is used to iteratively find the value of the deterministic parameter, which includes two steps: 1) E-step: Calculate the deterministic parameter matrix The likelihood function Q of: (4) In the formula, is the random parameter matrix; is the probability density function of the argon content degradation increment estimation under the condition of known prior information of random parameters and deterministic parameters, according to the probability density function of the argon content degradation increment under the condition of known prior information of random parameters Sure; is the probability density function of the random parameter matrix under the condition of known deterministic parameters. The joint probability density function of Determine; E represents conditional expectation; In the jth test, the probability density function of the degradation increment of argon content under the condition of known random parameter prior information is It is expressed as: (5) in, Indicates a time interval; Random parameter matrix The joint probability density function of It is expressed as: (6) Substituting formula (5)-(6) into formula (4), we can further derive the expression of likelihood function Q: (7) Parameters involved in formula (7) The conditional expected value of is shown in the following formula (8), and the value of the unknown parameter in the conditional expected value is shown in the following formula (9); (8) (9) in, For the n The time of the measurement; 2) M-step: through the function To update , q represents the number of iterations; arg max is a function that finds the set of parameters for a function. When there is another function If there is a result , it means that when the function Pick When you get The maximum value in the range; if there are multiple points such that To obtain the same maximum value, The result is a point set; make , then we get the estimation formula (10) of the deterministic parameters in the q+1 step: (10) Repeat the M-step until the difference between the likelihood function Q values ​​of two consecutive times is less than , that is , at this time, the values ​​of each deterministic parameter converge; then the deterministic parameter matrix is ​​obtained by formula (10) The value of From the Wiener process model established in step S6, it can be seen that the deterministic parameter matrix Afterwards, the fitting results of the argon degradation data can be obtained.

[0025] In order to obtain the values ​​of the deterministic parameters, the EM algorithm is used to iteratively calculate the deterministic parameters. In this embodiment, the insulating glass unit with model 0383 is taken as an example. The iterative process of the five parameters is as follows: Figure 4 As shown, the arrow points to the final iterative result.

[0026] After obtaining the deterministic parameter estimation results, the argon content degradation data is fitted according to formulas (2)-(3). The results are as follows: Figure 5 As shown in the figure, it can be seen that the data obtained by fitting the Wiener process model is always within 10% of the actual data, indicating that the fitting effect is very good.

[0027] Then the Monte Carlo simulation algorithm is used to calculate the reliability of the insulating glass unit according to formula (11): , determine the thermal insulation performance of the insulating glass unit; (11) In the formula, , and is the sampling index, and is a parameter and The sampling size of the sampling, D is the failure threshold.

[0028] In this embodiment, the failure threshold is given D =30, which means that when the argon gas leakage exceeds 30%, the insulating glass unit fails and the thermal insulation performance is basically lost.

[0029] For the Monte Carlo simulation in this embodiment, and Set to 5000. If you want to obtain higher calculation accuracy, the sampling size can also be larger, but this will make the calculation time longer. The size of the sample selected in this embodiment is selected after considering various factors.

[0030] In this embodiment, the reliability calculation result of the insulating glass unit 0383 is as follows: Figure 6 As shown, it is predicted that when the submerged test is carried out to the 992th day, the reliability calculation result is 0.6. At this time, it is considered that the sealing system of the insulating glass unit 0383 has been damaged, the thermal insulation performance has been lost a lot, causing a large amount of heat loss, and timely maintenance is required.

[0031] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. A method for detecting argon leakage and analyzing degradation of a curtain wall insulating glass unit, characterized in that: include: Step S1: collecting the initial argon content of insulating glass units of different models to determine whether the quality of the insulating glass units is qualified; Step S2: placing the insulating glass unit of qualified quality into a water tank for a submersion test; Step S3: Wipe clean the surface of the insulating glass unit after the submersion test and detect whether condensation occurs in the cavity of the insulating glass unit; Step S4: Observe whether condensation occurs at the measured position of the insulating glass unit. If no condensation occurs, start measuring the argon content and record the data. Step S5: repeating steps S2 to S4 to obtain multiple groups of argon content data of insulating glass units; and processing the argon content degradation data of the insulating glass units to increase the argon content data; Step S6: Modeling the argon content degradation data using the Wiener process model to find all deterministic parameters that affect the argon content degradation; Modeling the argon content degradation data of insulating glass units using Indicates the insulating glass unit at time t Based on the argon content degradation data, the degradation process of the argon content in the insulating glass unit is modeled using the Wiener process model shown in formula (1): （1） In this model, the argon content degradation data is represented as a Wiener process with drift, where the drift term Corresponding to the average leakage rate, is a random variable representing the initial degradation level; the parameter and are simulated as independent Gaussian random variables, i.e. ,in, N () is the normal distribution function, They are The mean and standard deviation of They are The mean and standard deviation of represents random fluctuations due to changes in conditions; in addition, represents standard Brownian motion; represents the diffusion coefficient; In the j In this test, the incremental degradation of the argon content of the insulating glass unit is expressed as , Respectively represent j Second and j -Degradation of the argon content of the insulating glass unit during 1 test, j =1,2... n , n Indicates the total number of argon content measurements; Respectively represent the argon content of the insulating glass unit j Second and j - 1 test time; The degradation increment distribution formula of argon content in insulating glass units is as follows: （2） （3） in, represents the time increment; Then we get the deterministic parameter matrix ; Step S7: iteratively obtain the value of the deterministic parameter, substitute it into the degradation increment distribution formula of the argon content in the insulating glass unit, fit the argon degradation data, calculate the reliability of the insulating glass unit, and further analyze its degradation process; For degraded data , the EM algorithm is used to iteratively find the value of the deterministic parameter; Find the deterministic parameter matrix Afterwards, the fitting results of the argon degradation data were obtained; Calculating the reliability of insulating glass units using Monte Carlo simulation algorithm , to judge the thermal insulation performance of the insulating glass unit.

2. The method for detecting argon leakage and analyzing degradation of a curtain wall insulating glass unit according to claim 1, characterized in that: The step S7 is for degradation data , the values ​​of deterministic parameters iteratively obtained using the EM algorithm include: 1) E-step: Calculate the deterministic parameter matrix The likelihood function Q of 2) M-step: through the function To update , q represents the number of iterations; Repeat the M-step until the difference between two consecutive likelihood function Q values ​​is less than , that is , at this time, the values ​​of each deterministic parameter converge; obtain the deterministic parameter matrix The value of .

3. The method for detecting argon leakage and analyzing degradation of a curtain wall insulating glass unit according to claim 2, characterized in that: The deterministic parameter matrix The likelihood function Q of is shown in the following formula: （4） In the formula, is the random parameter matrix; is the probability density function of the argon content degradation increment estimation under the condition of known prior information of random parameters and deterministic parameters, according to the probability density function of the argon content degradation increment under the condition of known prior information of random parameters Sure; is the probability density function of the random parameter matrix under the condition of known deterministic parameters. The joint probability density function of Determine; E represents conditional expectation.

4. The method for detecting argon leakage and analyzing degradation of a curtain wall insulating glass unit according to claim 3, characterized in that: In the jth test, the probability density function of the degradation increment of argon content under the condition of known random parameter prior information is It is expressed as: （5） in, Indicates a time interval; Random parameter matrix The joint probability density function of It is expressed as: （6） The expression of the likelihood function Q is further derived: （7） Parameters involved in formula (7) The conditional expected value of is shown in the following formula (8), and the value of the unknown parameter in the conditional expected value is shown in the following formula (9); （8） （9） in, For the n The time of the measurement.

5. The method for detecting argon leakage and analyzing degradation of a curtain wall insulating glass unit according to claim 4, characterized in that: The M-step includes: make , then we get the estimation formula (10) of the deterministic parameters in the q+1 step: （10）。 6. The method for detecting argon leakage and analyzing degradation of a curtain wall insulating glass unit according to claim 5, characterized in that: The Monte Carlo simulation algorithm is used to calculate the reliability of the insulating glass unit. As shown in the following formula: （11） In the formula, , and is the sampling index, and is a parameter and The sampling size of the sampling, D is the failure threshold.

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