An intelligent performance detection method for environmentally friendly gypsum mortar

Abstract

The present invention relates to the field of data processing technology, and in particular to an intelligent performance detection method for an environmentally friendly gypsum mortar, comprising: obtaining a number of gypsum mortar solidification samples to be detected; obtaining the significance of the reflection intensity change of each sample position according to the difference in reflection intensity before and after immersion at each sample position; obtaining the immersion influence of each sample position according to the significance of the reflection intensity change; obtaining the confidence of the immersion influence of each sample position on the target gypsum mortar solidification sample to be detected according to the immersion influence; screening according to the confidence of the immersion influence to obtain all the areas to be detected on the target gypsum mortar solidification sample to be detected; and using the areas to be detected to perform water retention performance detection on the target gypsum mortar solidification sample to be detected. The present invention improves the accuracy of the performance detection results of the gypsum mortar.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, and in particular to an intelligent performance detection method for environmentally friendly gypsum mortar. Background Art

[0002] Gypsum mortar is a green and environmentally friendly building material, suitable for decorative coating and has good decorative effect; water retention is one of the important properties of gypsum mortar. Currently, the common method to improve the water retention of gypsum mortar is to add a certain amount of cellulose ether with high viscosity, but cellulose ether will increase the product cost and affect the product construction performance; therefore, it is necessary to accurately test the water retention performance of gypsum mortar in order to accurately control the amount of cellulose ether.

[0003] In the process of testing the water retention performance of gypsum mortar, the traditional method is to use the light reflection characteristics of the gypsum mortar surface to test the water retention performance of the gypsum mortar; in the process of using light to extract the change of reflection intensity on the surface of the gypsum mortar, the uneven structural area on the surface of the gypsum mortar and the gypsum mortar after immersion in water will both have a reduced effect on the obtained reflection intensity. Because it is difficult to distinguish the effects of the two, the accuracy of the performance test results of the gypsum mortar is affected. Summary of the invention

[0004] In order to solve the above problems, the present invention provides an intelligent performance detection method for environmentally friendly gypsum mortar, the method comprising:

[0005] Obtain a number of gypsum mortar solidification samples to be tested; each gypsum mortar solidification sample to be tested includes a number of sample positions; each sample position corresponds to a reflection intensity before immersion in water and a reflection intensity after immersion in water;

[0006] According to the difference of reflection intensity before and after immersion in water at each sample position, the significance of reflection intensity change at each sample position is obtained; according to the significance of reflection intensity change, the influence of immersion in water at each sample position is obtained;

[0007] Any gypsum mortar solidification sample to be tested is recorded as a target gypsum mortar solidification sample to be tested; according to the water immersion influence degree, the water immersion influence confidence of each sample position on the target gypsum mortar solidification sample to be tested is obtained; according to the water immersion influence confidence degree, all the areas to be tested on the target gypsum mortar solidification sample to be tested are screened;

[0008] The area to be tested is used to test the water retention performance of the target gypsum mortar curing sample to be tested.

[0009] Preferably, the obtaining of the significance of the change in reflection intensity at each sample position according to the difference in reflection intensity before and after immersion in water at each sample position comprises the following specific methods:

[0010] For any gypsum mortar cured sample to be tested, the absolute value of the difference between the reflection intensity of the i-th sample position on the gypsum mortar cured sample before immersion in water and the reflection intensity of the i-th sample position after immersion in water is recorded as the first absolute value of the difference; the ratio of the first absolute value of the difference to the reflection intensity of the i-th sample position before immersion in water is taken as the significance of the change in reflection intensity of the i-th sample position on the gypsum mortar cured sample to be tested.

[0011] Preferably, the method of obtaining the water immersion influence degree of each sample position according to the significance of the reflection intensity change includes:

[0012] For the i-th sample position on any one of the gypsum mortar cured samples to be tested, if any one of the sample positions on the gypsum mortar cured sample to be tested has the same reflection intensity before immersion as the i-th sample position, the sample position is taken as the target sample position of the i-th sample position;

[0013] According to the significance of the change in the reflection intensity of the target sample position at the i-th sample position, the water infiltration influence factor of the i-th sample position on the gypsum mortar curing sample to be tested is obtained;

[0014] The water infiltration influence factors of all sample positions on the gypsum mortar curing sample to be tested are obtained, the water infiltration influence factors of all sample positions are linearly normalized, and each normalized water infiltration influence factor is recorded as the water infiltration influence degree.

[0015] Preferably, the specific formula for obtaining the water influencing factor of the i-th sample position on the gypsum mortar curing sample to be tested according to the significance of the change in reflection intensity of the target sample position at the i-th sample position is:

[0016]

[0017] In the formula, w i N represents the water intrusion influence factor of the i-th sample position on the gypsum mortar curing sample to be tested; i represents the total number of all target sample positions of the i-th sample position on the gypsum mortar curing sample to be tested; α i,r Indicates the significance of the change in reflection intensity of the rth target sample position at the i-th sample position on the gypsum mortar curing sample to be tested; It represents the mean value of the reflection intensity change significance of all sample positions on the gypsum mortar curing sample to be tested; || represents the absolute value.

[0018] Preferably, the method of obtaining the water impact confidence of each sample position on the target gypsum mortar cured sample to be tested according to the water impact degree includes the following specific methods:

[0019] According to the water immersion influence degree of all sample positions on the target gypsum mortar curing sample to be tested, an initial influence degree change curve is obtained;

[0020] The initial influence degree change curve and the influence degree change curves of all the gypsum mortar solidification samples to be tested except the target gypsum mortar solidification sample to be tested are dynamically regularized by using the DTW dynamic regularization algorithm; the regularized influence degree change curves of all the gypsum mortar solidification samples to be tested except the target gypsum mortar solidification sample to be tested are obtained;

[0021] Obtaining the regional distribution consistency of each data point in the initial influence degree change curve on the regularized influence degree change curve of each gypsum mortar solidification sample to be tested, except for the target gypsum mortar solidification sample to be tested;

[0022] According to the regional distribution consistency, the confidence of the flooding impact degree of each data point in the initial impact degree change curve is obtained;

[0023] For the water influence degree of any data point in the initial influence degree change curve, in the target gypsum mortar cured sample to be tested, each sample position with the same water influence degree as the data point is recorded as the first target sample position, and the confidence level of the water influence degree of the data point is used as the water influence confidence level of the first target sample position.

[0024] Preferably, the method of obtaining the initial influence degree variation curve according to the water immersion influence degrees of all sample positions on the target gypsum mortar curing sample to be tested includes the following specific methods:

[0025] Taking the water immersion influence degree of the sample position on the target gypsum mortar solidification sample to be tested as the horizontal coordinate, and the number of water immersion influence degrees on the target gypsum mortar solidification sample to be tested as the vertical coordinate, the water immersion influence degrees of all sample positions on the target gypsum mortar solidification sample to be tested are input into the two-dimensional coordinate system, and a number of data points are obtained. All the data points are fitted by the least squares method to form an influence degree change curve of the target gypsum mortar solidification sample to be tested, and recorded as the initial influence degree change curve.

[0026] Preferably, the obtaining of the regional distribution consistency of each data point in the initial influence degree change curve on the regularized influence degree change curve of each gypsum mortar cured sample to be tested, except for the target gypsum mortar cured sample to be tested, comprises the following specific methods:

[0027] For the kth data point in the initial influence degree change curve; obtain the target data point on the regularized influence degree change curve of the bth gypsum mortar cured sample to be tested corresponding to the kth data point, obtain the first area according to the position of the target data point, and obtain the convex hull area of ​​the first area of ​​the bth gypsum mortar cured sample to be tested corresponding to the kth data point;

[0028] The calculation method for obtaining the regional distribution consistency of the kth data point in the initial influence degree change curve on the regularized influence degree change curve of the bth gypsum mortar curing sample to be tested is:

[0029]

[0030] In the formula, β k,b Indicates the regional distribution consistency of the kth data point in the initial influence degree change curve on the regularized influence degree change curve of the bth gypsum mortar curing sample to be tested; n k,b The ordinate of the target data point on the regularized influence degree change curve of the bth gypsum mortar solidification sample to be tested, corresponding to the kth data point in the initial influence degree change curve; s k,b represents the convex hull area of ​​the first region of the bth gypsum mortar solidification sample to be tested corresponding to the kth data point in the initial influence degree change curve; n k,b-1 The ordinate of the target data point on the regularized influence degree change curve of the b-1th gypsum mortar solidification sample to be tested, corresponding to the kth data point in the initial influence degree change curve; s k,b-1 It represents the convex hull area of ​​the first region of the b-1 gypsum mortar curing sample to be tested corresponding to the kth data point in the initial influence degree change curve; || represents the absolute value; exp() represents the exponential function with a natural constant as the base.

[0031] Preferably, the method for acquiring the first area includes:

[0032] In the regularized influence degree change curve of the bth gypsum mortar solidification sample to be tested, the data point with the same horizontal coordinate as the kth data point is used as the target data point on the regularized influence degree change curve of the bth gypsum mortar solidification sample to be tested; in the bth gypsum mortar solidification sample to be tested, the sample position with the same horizontal coordinate as the target data point is used as the first sample position of the bth gypsum mortar solidification sample to be tested; the area formed by all the first sample positions of the bth gypsum mortar solidification sample to be tested is recorded as the first area of ​​the kth data point corresponding to the bth gypsum mortar solidification sample to be tested.

[0033] Preferably, the method of obtaining the confidence level of the water intrusion influence level of each data point in the initial influence level change curve according to the regional distribution consistency includes the following specific methods:

[0034] The mean of the regional distribution consistency of the kth data point in the initial influence degree change curve on the regularized influence degree change curve of all the gypsum mortar cured samples to be tested, except the target gypsum mortar cured sample to be tested, is recorded as the first mean; the product of the first mean and the water immersion influence degree of the kth data point in the initial influence degree change curve is used as the confidence factor of the water immersion influence degree of the kth data point in the initial influence degree change curve;

[0035] The confidence factors of the water immersion influence degree of all data points in the initial influence degree change curve are linearly normalized, and each normalized confidence factor is recorded as confidence degree.

[0036] Preferably, the screening according to the confidence level of water immersion influence to obtain all the areas to be tested on the target gypsum mortar cured sample to be tested includes the following specific methods:

[0037] A threshold parameter T is preset. For any sample position on the target gypsum mortar curing sample to be detected, if the confidence of the water immersion effect of the sample position is greater than or equal to the threshold parameter T, the sample position is recorded as the area to be detected.

[0038] The beneficial effects of the technical solution of the present invention are as follows: the present invention obtains the water immersion influence confidence of each sample position on the target gypsum mortar cured sample to be detected according to the water immersion influence degree; screening is performed according to the water immersion influence confidence degree to obtain all the areas to be detected on the target gypsum mortar cured sample to be detected; the significance of the reflection intensity change characterizes the degree to which the reflection intensity of the sample position is affected by water immersion, resulting in a reduction in the reflection intensity, and the greater the degree of the water immersion influence, the less likely the sample position belongs to the uneven structure area, and the more likely it belongs to the area to be detected; the water retention performance of the target gypsum mortar cured sample to be detected is tested using the area to be detected; thereby avoiding the uneven structure area on the gypsum mortar surface that will reduce the acquired reflection intensity in the process of extracting the reflection intensity change of the gypsum mortar surface using light, and by distinguishing the uneven structure area on the gypsum mortar surface from the area to be detected, the performance test result of the gypsum mortar is made more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 This is a flow chart of the steps of an intelligent performance detection method for an environmentally friendly gypsum mortar according to the present invention;

[0041] Figure 2 The present invention is a characteristic relationship flow chart of an intelligent performance detection method for an environmentally friendly gypsum mortar. DETAILED DESCRIPTION

[0042] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the intelligent performance detection method of an environmentally friendly gypsum mortar proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0043] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0044] The specific scheme of the intelligent performance detection method of an environmentally friendly gypsum mortar provided by the present invention is described in detail below with reference to the accompanying drawings.

[0045] See also Figure 1 , which shows a flowchart of a method for intelligently detecting the performance of an environmentally friendly gypsum mortar provided by an embodiment of the present invention, the method comprising the following steps:

[0046] Step S001: Obtain the reflection intensity of each sample position on a number of gypsum mortar curing samples to be tested before and after immersion in water.

[0047] It should be noted that due to the certain unevenness of the surface of the gypsum mortar, it will affect the reflection and refraction of light. The uneven surface will cause the light to be reflected and refracted multiple times on the surface, thereby reducing the reflectivity; and the wetness of the gypsum mortar surface will also affect its reflectivity. The wet surface will absorb part of the light, causing the reflectivity to decrease.

[0048] Specifically, it is necessary to first collect the reflection intensity of each sample position on a number of gypsum mortar curing samples to be tested before and after immersion in water. The specific process is as follows:

[0049] The gypsum mortar product to be tested is stirred evenly, poured into a mold for shaping, and the gypsum mortar to be tested is taken out after solidification and forming to obtain a plurality of solidified gypsum mortar samples to be tested.

[0050] For any gypsum mortar solidification sample to be tested, the minimum unit area is preset to be 5 square millimeters, and a number of sample positions are divided on the gypsum mortar solidification sample to be tested; the gypsum mortar solidification sample to be tested is dried under standard conditions to ensure that there is no obvious moisture on the surface of the gypsum mortar solidification sample to be tested, and the reflectivity testing instrument is used to extract the reflection characteristics of the gypsum mortar solidification sample to be tested in a dry state; the reflection intensity of each sample position on the gypsum mortar solidification sample to be tested before immersion in water is obtained.

[0051] Then, the gypsum mortar cured sample to be tested in a dry state is immersed in water for a certain period of time, and a reflectivity testing instrument is used to extract the reflection characteristics of the gypsum mortar cured sample to be tested in the immersed state; and the reflection intensity after immersion in water is obtained for each sample position on the gypsum mortar cured sample to be tested.

[0052] At this point, the reflection intensity before and after immersion in water of each sample position on a number of gypsum mortar curing samples to be tested is obtained by the above method.

[0053] Step S002: according to the difference of reflection intensity before and after immersion in water at each sample position, obtain the significance of reflection intensity change at each sample position; according to the significance of reflection intensity change, obtain the influence of immersion in water at each sample position.

[0054] It should be noted that the uneven structure of the surface of the gypsum mortar cured sample to be tested and the immersion effect will both reduce the light reflection intensity, but the reduction effects are different. The uneven structure is more inclined to cause multiple reflections and refractions of light in a small local area on the surface, and there are multiple angle changes, which reduces the amount of light entering the detection device and reduces the reflectivity; and on the surface of the gypsum mortar cured sample to be tested after immersion in water, the moisture will fill the pores inside the mortar and the tiny depressions on the surface, changing the light properties of the mortar. In the water-containing state, refraction and scattering occur inside the gypsum mortar, causing the light to propagate repeatedly in the medium, increasing the attenuation and scattering of light, and reducing the intensity of the reflected light; it will form regional change characteristics on the surface of the gypsum mortar, thereby achieving accurate classification of all sample positions on the gypsum mortar cured sample to be tested.

[0055] 1. Obtain the significance of the change in reflection intensity at each sample position on each gypsum mortar curing sample to be tested.

[0056] It should be noted that, since the same sample position on each gypsum mortar solidification sample to be tested has reflection intensity monitoring data of both dry state and immersed state, the reflection intensity of the same sample position on the gypsum mortar solidification sample to be tested before and after immersion is subtracted. The greater the difference, the greater the impact of immersion on the gypsum mortar solidification sample to be tested, and the better the water retention performance of the gypsum mortar solidification sample to be tested.

[0057] Therefore, according to the difference in reflection intensity before and after immersion in water at each sample position on the gypsum mortar curing sample to be tested, the significance of the change in reflection intensity at each sample position is obtained.

[0058] For any gypsum mortar solidification sample to be tested, as an example, the calculation method for obtaining the significance of the change in reflection intensity at the i-th sample position on the gypsum mortar solidification sample to be tested is:

[0059]

[0060] In the formula, α i represents the significance of the change in reflection intensity at the i-th sample position on the gypsum mortar curing sample to be tested; f i represents the reflection intensity of the i-th sample position on the gypsum mortar curing sample to be tested before immersion; f i ′ It represents the reflection intensity of the i-th sample position on the gypsum mortar cured sample to be tested after immersion in water; || represents the absolute value.

[0061] At this point, the significance of the change in reflection intensity at each sample position on each gypsum mortar curing sample to be tested is obtained.

[0062] 2. Obtain the water impact degree of each sample position on each gypsum mortar curing sample to be tested.

[0063] It should be noted that the significance of the change in reflection intensity represents the degree to which the reflection intensity at the sample position is affected by water immersion, resulting in a decrease in reflection intensity. The greater the degree to which it is affected by water immersion, the less likely it is that the sample position belongs to an uneven structure area. By measuring the differences in the significance of the change in reflection intensity at the sample position on the entire gypsum mortar cured sample to be tested, the larger the value, the greater the impact of the water immersion treatment on the reflection intensity, that is, the smaller the impact of the uneven structure area.

[0064] Therefore, according to the significance of the change in reflection intensity, the water immersion influence degree of each sample position on each gypsum mortar curing sample to be tested is obtained.

[0065] For the i-th sample position on any gypsum mortar cured sample to be tested, if any sample position on the gypsum mortar cured sample to be tested has the same reflection intensity before immersion as the i-th sample position, the sample position is used as the target sample position of the i-th sample position; as an example, the calculation method for obtaining the immersion influence factor of the i-th sample position on the gypsum mortar cured sample to be tested is:

[0066]

[0067] In the formula, wi N represents the water intrusion influence factor of the i-th sample position on the gypsum mortar curing sample to be tested; i represents the total number of all target sample positions of the i-th sample position on the gypsum mortar curing sample to be tested; α i,r Indicates the significance of the change in reflection intensity of the rth target sample position at the i-th sample position on the gypsum mortar curing sample to be tested; It represents the mean value of the reflection intensity change significance of all sample positions on the gypsum mortar curing sample to be tested; || represents the absolute value.

[0068] Furthermore, the water intrusion influence factors of all sample positions on the gypsum mortar curing sample to be tested are obtained, the water intrusion influence factors of all sample positions are linearly normalized, and each normalized water intrusion influence factor is recorded as a water intrusion influence degree.

[0069] So far, the water immersion influence degree of each sample position on each gypsum mortar curing sample to be tested is obtained through the above method.

[0070] Step S003: According to the water immersion influence degree, obtain the water immersion influence confidence of each sample position on the target gypsum mortar solidification sample to be tested; screen according to the water immersion influence confidence degree to obtain all the areas to be tested on the target gypsum mortar solidification sample to be tested.

[0071] It should be noted that since there will be corresponding differences in the influence of water immersion at the same sample position on multiple gypsum mortar solidification samples to be tested, which is mainly caused by the different uneven structures on the surface of the gypsum mortar solidification samples to be tested, the influence of water immersion at the sample position should be matched and analyzed for the same sample position on multiple gypsum mortar solidification samples to be tested, so as to obtain the confidence of each sample position, which is used to divide the regional properties of the sample position; since the influence of water immersion on the surface reflection intensity of the gypsum mortar solidification samples to be tested is more likely to cause an overall reduction in the reflection intensity of the vast majority of the areas, it is reflected in the influence of water immersion at the sample position on multiple gypsum mortar solidification samples to be tested. Therefore, it is necessary to conduct a regional dispersion characteristic analysis of the influence of water immersion at each sample position on multiple gypsum mortar solidification samples to be tested.

[0072] Specifically, any gypsum mortar solidification sample to be tested is recorded as the target gypsum mortar solidification sample to be tested, the water immersion influence degree of the sample position on the target gypsum mortar solidification sample to be tested is used as the horizontal coordinate, and the number of water immersion influence degrees on the target gypsum mortar solidification sample to be tested is used as the vertical coordinate. The water immersion influence degrees of all sample positions on the target gypsum mortar solidification sample to be tested are input into the two-dimensional coordinate system, and a number of data points are obtained. All the data points are fitted by the least squares method to form an influence degree change curve of the target gypsum mortar solidification sample to be tested, and the curve is recorded as the initial influence degree change curve. Then, the influence degree change curve of each gypsum mortar solidification sample to be tested is obtained.

[0073] The DTW dynamic regularization algorithm is used to dynamically regularize the initial influence degree change curve and the influence degree change curves of all gypsum mortar solidification samples to be tested except the target gypsum mortar solidification sample to be tested; the regularized influence degree change curves of all gypsum mortar solidification samples to be tested except the target gypsum mortar solidification sample to be tested are obtained.

[0074] For the kth data point in the initial influence degree change curve; in the regularized influence degree change curve of the bth gypsum mortar solidification sample to be tested, the data point with the same horizontal coordinate as the kth data point is used as the target data point on the regularized influence degree change curve of the bth gypsum mortar solidification sample to be tested; in the bth gypsum mortar solidification sample to be tested, the sample position with the same horizontal coordinate as the target data point is used as the first sample position of the bth gypsum mortar solidification sample to be tested; the area formed by all the first sample positions of the bth gypsum mortar solidification sample to be tested is recorded as the first area of ​​the kth data point corresponding to the bth gypsum mortar solidification sample to be tested; and the convex hull area of ​​the first area is obtained by using the convex hull detection algorithm.

[0075] Among them, the least squares method, the DTW dynamic regularization algorithm and the convex hull detection algorithm are existing technologies and will not be described in detail in this embodiment.

[0076] As an example, the calculation method for obtaining the regional distribution consistency of the kth data point in the initial influence degree change curve on the regularized influence degree change curve of the bth gypsum mortar curing sample to be tested is:

[0077]

[0078] In the formula, β k,b Indicates the regional distribution consistency of the kth data point in the initial influence degree change curve on the regularized influence degree change curve of the bth gypsum mortar curing sample to be tested; n k,b The ordinate of the target data point on the regularized influence degree change curve of the bth gypsum mortar solidification sample to be tested, corresponding to the kth data point in the initial influence degree change curve; sk,b represents the convex hull area of ​​the first region of the bth gypsum mortar solidification sample to be tested corresponding to the kth data point in the initial influence degree change curve; n k,b-1 The ordinate of the target data point on the regularized influence degree change curve of the b-1th gypsum mortar solidification sample to be tested, corresponding to the kth data point in the initial influence degree change curve; s k,b-1 represents the convex hull area of ​​the first region of the b-1 gypsum mortar cured sample to be tested corresponding to the kth data point in the initial influence degree change curve; || represents taking the absolute value; exp() represents an exponential function with a natural constant as the base. The embodiment adopts the exp(-x) model to present the inverse proportional relationship and normalization processing, x is the input of the model, and the implementer can select the inverse proportional function and normalization function according to the actual situation.

[0079] At this point, the regional distribution consistency of the kth data point in the initial influence degree change curve on the regularized influence degree change curve of each gypsum mortar curing sample to be tested is obtained.

[0080] Specifically, the calculation method for obtaining the confidence factor of the water immersion influence degree of the kth data point in the initial influence degree change curve is:

[0081]

[0082] In the formula, γ k Represents the confidence factor of the water impact degree of the kth data point in the initial impact degree change curve; represents the mean value of the regional distribution consistency of the kth data point in the initial influence degree change curve on the regularized influence degree change curve of all the gypsum mortar curing samples to be tested except the target gypsum mortar curing sample to be tested; w k Indicates the water immersion influence degree of the kth data point in the initial influence degree change curve.

[0083] Furthermore, the confidence factors of the water immersion influence degree of all data points in the initial influence degree variation curve are linearly normalized, and each normalized confidence factor is recorded as confidence degree.

[0084] For the water influence degree of any data point in the initial influence degree change curve, in the target gypsum mortar cured sample to be tested, each sample position with the same water influence degree as the data point is recorded as the first target sample position, and the confidence level of the water influence degree of the data point is used as the water influence confidence level of the first target sample position.

[0085] At this point, the confidence level of the water immersion effect at each sample position on the target gypsum mortar curing sample to be tested is obtained.

[0086] A threshold parameter T is preset, wherein this embodiment is described by taking T=0.92 as an example, and this embodiment is not specifically limited, wherein T is determined according to specific implementation conditions.

[0087] For any sample position on the target gypsum mortar cured sample to be detected, if the water immersion influence confidence of the sample position is greater than or equal to the threshold parameter T, the sample position is recorded as the area to be detected.

[0088] At this point, all the areas to be tested on the target gypsum mortar cured sample to be tested are obtained through the above method.

[0089] Step S004: using the area to be tested to test the water retention performance of the target gypsum mortar curing sample to be tested.

[0090] Specifically, the reflection intensity of all the areas to be tested on the target gypsum mortar cured sample before and after immersion in water is input into the trained neural network to obtain the water retention performance index of the target gypsum mortar cured sample to be tested; wherein the neural network used in this embodiment is CNN, and the method for obtaining the data set for training the neural network is:

[0091] A large number of gypsum mortar solidification samples with marked water retention performance indicators and the reflection intensity of all areas on each gypsum mortar solidification sample before and after immersion in water are collected, and the area to be detected is artificially marked in each gypsum mortar solidification sample, and the reflection intensity of the marked area to be detected before and after immersion in water is recorded as the reflection intensity label of the area to be detected; a large number of gypsum mortar solidification samples with marked water retention performance indicators and their corresponding reflection intensity labels of the area to be detected are collected to form a data set; the neural network is trained using the data set, and the loss function used in the training process is a mean square error loss function; the specific training process is a well-known content of the neural network, and the specific training process will not be repeated in this embodiment.

[0092] See also Figure 2 , which shows a characteristic relationship flow chart of an intelligent performance detection method for environmentally friendly gypsum mortar.

[0093] At this point, this embodiment is completed.

[0094] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent performance detection method for environmentally friendly gypsum mortar, characterized in that: The method comprises the following steps: Obtain a number of gypsum mortar solidification samples to be tested; each gypsum mortar solidification sample to be tested includes a number of sample positions; each sample position corresponds to a reflection intensity before immersion in water and a reflection intensity after immersion in water; According to the difference of reflection intensity before and after immersion in water at each sample position, the significance of reflection intensity change at each sample position is obtained; according to the significance of reflection intensity change, the influence of immersion in water at each sample position is obtained; Any gypsum mortar solidification sample to be tested is recorded as a target gypsum mortar solidification sample to be tested; according to the water immersion influence degree, the water immersion influence confidence of each sample position on the target gypsum mortar solidification sample to be tested is obtained; according to the water immersion influence confidence degree, all the areas to be tested on the target gypsum mortar solidification sample to be tested are screened; Using the area to be tested, the water retention performance of the target gypsum mortar curing sample to be tested is tested; The specific method of obtaining the significance of the change of the reflection intensity of each sample position according to the difference of the reflection intensity before and after immersion in water includes: For any gypsum mortar solidification sample to be tested, The reflection intensity before immersion at the sample position is The absolute value of the difference in reflection intensity after immersion at the sample position is recorded as the first absolute value of the difference; the first absolute value of the difference is recorded as the absolute value of the first difference. The ratio of the reflection intensity of the sample positions before immersion is used as the first reflection intensity of the gypsum mortar solidification sample to be tested. The significance of the change in reflection intensity at each sample location; The specific method of obtaining the water immersion influence degree of each sample position according to the significance of the reflection intensity change is as follows: For any gypsum mortar curing sample to be tested If any sample position on the gypsum mortar solidification sample to be tested is The reflection intensity of the sample positions before immersion is the same, and the sample positions are taken as The target sample position for each sample position; According to The reflection intensity change significance of the target sample position at the sample position is obtained on the gypsum mortar curing sample to be tested. Water influencing factors at each sample location; Obtain the water infiltration influence factors of all sample positions on the gypsum mortar curing sample to be tested, linearly normalize the water infiltration influence factors of all sample positions, and record each normalized water infiltration influence factor as a water infiltration influence degree; According to the The reflection intensity change significance of the target sample position at the sample position is obtained on the gypsum mortar curing sample to be tested. The specific formula for the flooding influence factor at each sample location is: ； In the formula, Indicates the number of Water influencing factors at each sample location; Indicates the number of The total number of all target sample positions for sample positions; Indicates the number of The sample position The significance of the change in reflection intensity at each target sample position; It represents the mean value of the change significance of the reflection intensity of all sample positions on the gypsum mortar curing sample to be tested; Indicates taking the absolute value; The specific method of obtaining the water impact confidence of each sample position on the target gypsum mortar cured sample to be tested according to the water impact degree is as follows: According to the water immersion influence degree of all sample positions on the target gypsum mortar curing sample to be tested, an initial influence degree change curve is obtained; use The dynamic regularization algorithm dynamically regularizes the initial influence degree change curve and the influence degree change curves of all the gypsum mortar solidification samples to be tested except the target gypsum mortar solidification sample to be tested; and obtains the regularized influence degree change curves of all the gypsum mortar solidification samples to be tested except the target gypsum mortar solidification sample to be tested; Obtaining the regional distribution consistency of each data point in the initial influence degree change curve on the regularized influence degree change curve of each gypsum mortar solidification sample to be tested, except for the target gypsum mortar solidification sample to be tested; According to the regional distribution consistency, the confidence of the flooding impact degree of each data point in the initial impact degree change curve is obtained; For the water infiltration influence degree of any data point in the initial influence degree variation curve, in the target gypsum mortar cured sample to be tested, each sample position having the same water infiltration influence degree as the data point is recorded as the first target sample position, and the confidence level of the water infiltration influence degree of the data point is taken as the water infiltration influence confidence level of the first target sample position; The specific method of obtaining the initial influence degree change curve according to the water immersion influence degree of all sample positions on the target gypsum mortar curing sample to be tested includes: The water immersion influence degree of the sample position on the target gypsum mortar solidification sample to be detected is taken as the horizontal coordinate, and the number of water immersion influence degrees on the target gypsum mortar solidification sample to be detected is taken as the vertical coordinate. The water immersion influence degrees of all sample positions on the target gypsum mortar solidification sample to be detected are input into the two-dimensional coordinate system, and a number of data points are obtained. All data points are fitted by the least square method to form an influence degree change curve of the target gypsum mortar solidification sample to be detected, and recorded as the initial influence degree change curve; The specific method of obtaining the regional distribution consistency of each data point in the initial influence degree change curve on the regularized influence degree change curve of each gypsum mortar solidification sample to be tested, except for the target gypsum mortar solidification sample to be tested, includes: For the initial impact change curve data points; get the The data point corresponds to the The target data point on the regularized influence change curve of the gypsum mortar solidification sample to be tested is obtained according to the position of the target data point, and the first area is obtained. The data point corresponds to the The convex hull area of ​​the first region of the gypsum mortar cured sample to be tested; Get the initial influence change curve The data point in The calculation method for the regional distribution consistency on the regularized influence change curve of the gypsum mortar curing sample to be tested is: ； In the formula, Indicates the initial influence change curve The data point in The regional distribution consistency of the regularized influence change curve of the gypsum mortar curing samples to be tested; Indicates the initial influence change curve The data point corresponds to the The ordinate of the target data point on the regularized influence change curve of the gypsum mortar curing sample to be tested; Indicates the initial influence change curve The data point corresponds to the The convex hull area of ​​the first region of the gypsum mortar cured sample to be tested; Indicates the initial influence change curve The data point corresponds to the The ordinate of the target data point on the regularized influence change curve of the gypsum mortar curing sample to be tested; Indicates the initial influence change curve The data point corresponds to the The convex hull area of ​​the first region of the gypsum mortar cured sample to be tested; Indicates taking the absolute value; represents an exponential function with a natural constant as base; The method for obtaining the first area includes: In the In the regularized influence change curve of the first gypsum mortar solidification sample to be tested, The data points with the same horizontal coordinates are taken as the The data point corresponds to the The target data point on the regularized influence change curve of the gypsum mortar solidification sample to be tested; Among the gypsum mortar solidification samples to be tested, the sample position with the same horizontal coordinate as the target data point is taken as the first The first sample position of the gypsum mortar solidification sample to be tested; The area formed by all the first sample positions of the gypsum mortar solidification samples to be tested is recorded as The data point corresponds to the a first area of ​​a gypsum mortar cured sample to be tested; The specific method of obtaining the confidence level of the water intrusion influence level of each data point in the initial influence level change curve according to the regional distribution consistency is as follows: The initial influence change curve The mean of the regional distribution consistency of the data points on the regularized influence change curve of all the gypsum mortar curing samples to be tested, except the target gypsum mortar curing sample to be tested, is recorded as the first mean; the first mean is compared with the first mean in the initial influence change curve. The product of the water influencing degrees of the data points is used as the first The confidence factor of the water impact of each data point; The confidence factors of the water immersion influence degree of all data points in the initial influence degree change curve are linearly normalized, and each normalized confidence factor is recorded as confidence degree.

2. According to claim 1, an intelligent performance detection method for environmentally friendly gypsum mortar is characterized in that: The specific method of screening according to the confidence level of water immersion to obtain all the areas to be tested on the target gypsum mortar curing sample to be tested includes: Preset a threshold parameter For any sample position on the target gypsum mortar cured sample to be tested, if the confidence of the water impact at the sample position is greater than or equal to the threshold parameter , and record the sample position as the area to be detected.

Images