Steam curing detection system applied to intelligent beam field

Abstract

The invention discloses a steam-curing detection system applied to an intelligent beam field, relates to the technical field of steam-curing detection, and discloses a steam-curing detection point setting module, a steam-curing detection execution module, a detection abnormal sample marking module, a detection execution adjustment module and a detection period modification module. A steam-curing detection point setting module, a steam-curing detection execution module and a detection abnormal sample marking module are arranged, and a plurality of steam-curing detection points at equal intervals are divided on the concrete beam body, so that the comprehensiveness and balance of steam-curing detection are ensured, and the requirement for precise steam-curing detection of the large-size concrete beam body is met; and all-around detection analysis is carried out on each steam curing detection point of the concrete beam body based on a certain period, and the steam curing detection points with high detection requirements on the concrete beam body are preferentially detected and analyzed, so that the position with poor steam curing performance on the concrete beam body is efficiently and accurately found.

Description

Technical Field

[0001] The present invention relates to the field of steaming detection technology, and more specifically, to a steaming detection system applied to a smart beam yard. Background Art

[0002] In the modern construction industry, smart beam yards, as important component prefabrication sites, have extremely high requirements for the production quality and efficiency of concrete beams. Steaming, as a key link in the production process of concrete beams, is essential for improving the strength and durability of concrete. The steaming process accelerates the hardening process of concrete by controlling parameters such as temperature and humidity, thereby improving its physical properties.

[0003] However, traditional steam curing detection methods often have many shortcomings. On the one hand, facing large-scale concrete beams, it is impossible to perform comprehensive and balanced detection, which easily leads to one-sided and inaccurate detection results. On the other hand, traditional detection methods lack intelligent and automated means, have low detection efficiency, and it is difficult to detect and deal with abnormal situations in the steam curing process in a timely manner.

[0004] Therefore, the present invention proposes a steaming detection system applied to a smart beam yard. Summary of the invention

[0005] In view of the deficiencies in the prior art, the object of the present invention is to provide a steaming detection system for use in a smart beam yard.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A steaming detection system applied to a smart beam yard, comprising a steaming detection point setting module, a steaming detection execution module, a detection abnormality marking module, a detection execution adjustment module, and a detection cycle modification module;

[0008] The steam curing detection point setting module divides a plurality of steam curing detection points at equal intervals on the concrete beam before the concrete beam is steam cured;

[0009] The curing detection execution module obtains the curing detection requirement value of the curing detection point on the concrete beam body every time the curing detection cycle node is reached during the curing process of the concrete beam body, and then generates a curing detection sequence;

[0010] The detection abnormality marking module detects the curing detection points on the concrete beam body in sequence according to the curing detection sequence, completes the detection of each curing detection point, obtains the curing depth detection value of the curing detection point, and determines whether to mark the curing detection point as a curing detection abnormality point based on the comparison result of the curing depth detection value and the curing depth detection critical value;

[0011] When an abnormal steaming detection point appears, the detection execution adjustment module marks all other undetected steaming detection points as abnormal steaming detection points, generates an abnormal steaming detection sequence, and detects the abnormal steaming detection points in sequence according to the abnormal steaming detection sequence;

[0012] The detection cycle modification module obtains a steam-curing detection modification value of the concrete beam body when all steam-curing detection points on the concrete beam body have completed detection, and determines whether to modify the cycle length of the steam-curing detection cycle based on a comparison result between the steam-curing detection modification value and the steam-curing detection modification limit value.

[0013] Furthermore, the steaming detection demand value of the steaming detection point is obtained by the following steps: obtaining the s steaming depth detection values ​​previously obtained at the steaming detection point, sorting all the steaming depth detection values ​​in the order of acquisition, performing difference calculation on two adjacent steaming depth detection values ​​after sorting and taking the absolute value to obtain the depth detection floating value, summing up all the depth detection floating values ​​and taking the average to obtain the depth detection floating mean Ajp, summing up all the steaming depth detection values ​​and taking the average to obtain the depth detection mean Ajy, and using the formula The steaming detection requirement value Nmt of the steaming detection point is obtained, wherein b1 is the detection floating mean coefficient, and b2 is the depth detection mean coefficient.

[0014] Furthermore, the steam curing detection sequence is generated by the following steps: all the steam curing detection points on the concrete beam are sorted in descending order according to the values ​​of the steam curing detection demand values, and the steam curing detection sequence is generated in the sorted order.

[0015] Further, each pair of steaming detection points is tested to obtain the steaming depth detection value of the steaming detection point, specifically: various steaming index data of the steaming detection point are collected, and the steaming index models corresponding to the various steaming index data are obtained. The various steaming index data are respectively input into the corresponding steaming index models to obtain the steaming index compliance values ​​of the various steaming index data, and the discrete mean value of the steaming index Ptdg is obtained. The steaming index compliance values ​​of all the steaming index data are summed and averaged to obtain the steaming average compliance value Bmg. The steaming index compliance high value and the steaming index compliance low value are set. When the steaming index compliance value of the steaming index data is greater than or equal to the steaming index compliance high value, the steaming index data is marked as steaming compliance data, and the total number of steaming compliance data is marked as Rz. When the steaming index compliance value of the steaming index data is less than or equal to the steaming index compliance low value, the steaming index data is marked as steaming failure data, and the total number of steaming failure data is marked as Ek. The formula is used The steaming depth detection value Zsh of the steaming detection point is obtained, wherein v1 is the steaming index dispersion coefficient, v2 is the steaming average standard-reaching coefficient, v3 is the steaming standard-reaching coefficient, and v4 is the steaming non-standard coefficient.

[0016] Furthermore, the discrete mean Ptdg of the steaming index is obtained by the following steps: all the steaming index data are matched in pairs into a steaming index group, the difference between the steaming index compliance values ​​of two steaming index data in the steaming index group is calculated and the absolute value is taken to obtain the discrete value of the steaming index of the steaming index group, the discrete values ​​of the steaming index of all the steaming index groups are summed and the average is taken to obtain the discrete mean Ptdg of the steaming index.

[0017] Furthermore, based on the comparison result between the steaming depth detection value and the steaming depth detection critical value, it is determined whether to mark the steaming detection point as a steaming detection abnormal point, specifically: setting the steaming depth detection critical value, when the steaming depth detection value of the steaming detection point is greater than or equal to the steaming depth detection critical value, marking the steaming detection point as a steaming detection abnormal point, when the steaming depth detection value of the steaming detection point is less than the steaming depth detection critical value, continuing to detect the next steaming detection point according to the steaming detection sequence.

[0018] Furthermore, the steaming abnormal inspection sequence is generated by the following steps: obtaining the abnormal inspection correlation value of each steaming abnormal inspection point, sorting all the steaming abnormal inspection points in descending order according to the numerical value of the abnormal inspection correlation value, and generating the steaming abnormal inspection sequence according to the sorting order.

[0019] Furthermore, the abnormal detection related value of the steaming abnormal detection point is obtained by the following steps: determine a steaming abnormal detection point, calculate the distance difference between the steaming abnormal detection point and the steaming abnormal detection point to obtain the detection point spacing Lc, obtain the steaming depth detection value of the steaming abnormal detection point and the steaming abnormal detection point obtained at the previous cycle node, sum the two steaming depth detection values ​​to obtain the depth detection additional value Rw, calculate the difference between the two steaming depth detection values ​​and take the absolute value to obtain the depth detection gap value Yd, and use the formula Obtain the abnormal inspection related value Atp of the steaming abnormal inspection point.

[0020] Further, based on the comparison result of the steaming detection modification value and the steaming detection modification limit value, it is determined whether to modify the cycle length of the steaming detection cycle, specifically: the steaming detection modification limit value is set, and when the steaming detection modification value is greater than the steaming detection modification limit value, the steaming detection modification limit value is calculated as a ratio with the steaming detection modification value to obtain a modification ratio e, and the cycle length of the steaming detection cycle is adjusted to T SC e .

[0021] Furthermore, the steam-curing detection modification value of the concrete beam body is obtained through the following steps: the total number of steam-curing detection abnormal points is obtained and marked as Ewcu, the steam-curing depth detection values ​​of the steam-curing detection abnormal points are summed and averaged to obtain the abnormal depth detection value Fbmk, and the steam-curing detection modification value Jxg of the concrete beam body is obtained using the formula Jxg=Ewcu*j1+Fbmk*j2, wherein j1 is the detection abnormality quantity coefficient, and j2 is the abnormal depth detection coefficient.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. Set up a steam curing detection point setting module, a steam curing detection execution module, and a detection abnormality marking module, and divide multiple steam curing detection points with equal spacing on the concrete beam to ensure the comprehensiveness and balance of the steam curing detection, meet the precision steam curing detection of large-sized concrete beams, and conduct a comprehensive detection and analysis on each steam curing detection point of the concrete beam based on a certain period, and give priority to the detection and analysis of the steam curing detection points with high detection requirements on the concrete beam, so as to ensure efficient and accurate discovery of the locations on the concrete beam with poor steam curing performance;

[0024] 2. Set up the detection execution adjustment module and the detection cycle modification module. When a position with poor steam-curing performance appears on the concrete beam, quickly adjust the detection order of the remaining steam-curing detection points on the concrete beam, and then quickly screen out the remaining positions with poor steam-curing performance, which significantly improves the response speed and pertinence of the detection, and dynamically adjusts the steam-curing detection cycle according to the comprehensive steam-curing performance of the concrete beam to ensure that the concrete beam is detected with a reasonable steam-curing detection cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a system module diagram of a steaming detection system applied to a smart beam yard;

[0026] Figure 2 This is a system operation flow chart of a steaming detection system applied to a smart beam yard;

[0027] Figure 3 The present invention is a flow chart for determining whether to mark a steaming detection point as a steaming detection abnormal point. DETAILED DESCRIPTION

[0028] Reference Figures 1 to 3 A steaming detection system applied to a smart beam yard includes a steaming detection point setting module, a steaming detection execution module, a detection abnormality marking module, a detection execution adjustment module, and a detection cycle modification module.

[0029] Steaming detection setting point module: set the duration of the steaming detection cycle to T SC(During the steam-curing process of the concrete beam, the steam-curing detection cycle is infinitely repeated). Before the concrete beam is steam-cured, a plurality of steam-curing detection points with equal spacing are divided on the concrete beam.

[0030] Steam-curing detection execution module: During the steam-curing process of the concrete beam, whenever it reaches a period node of the steam-curing detection cycle, the steam-curing detection demand value of the steam-curing detection point on the concrete beam is obtained, and then a steam-curing detection sequence is generated (the steam-curing detection sequence contains all the steam-curing detection points on the concrete beam, and the steam-curing detection points are sorted in a certain order).

[0031] The curing detection sequence is generated by the following steps: all the curing detection points on the concrete beam are sorted in descending order according to the values ​​of the curing detection requirement values, and the curing detection sequence is generated in the sorted order (for example, there are four curing detection points on the concrete beam, namely, curing detection point a, curing detection point b, curing detection point c, and curing detection point d, and the curing detection requirement value of curing detection point a>the curing detection requirement value of curing detection point c>the curing detection requirement value of curing detection point b>the curing detection requirement value of curing detection point d, then the curing detection sequence is curing detection point a, curing detection point c, curing detection point b, and curing detection point d).

[0032] The steaming detection demand value of the steaming detection point is obtained by the following steps: obtain the s steaming depth detection values ​​obtained before the steaming detection point, sort all the steaming depth detection values ​​in the order of acquisition, calculate the difference between the two adjacent steaming depth detection values ​​after sorting and take the absolute value to obtain the depth detection floating value, sum up all the depth detection floating values ​​and take the average to obtain the depth detection floating mean Ajp, sum up all the steaming depth detection values ​​and take the average to obtain the depth detection mean Ajy, and use the formula The steaming detection requirement value Nmt of the steaming detection point is obtained, where b1 is the detection floating mean coefficient, b2 is the depth detection mean coefficient, the value of b1 is 0.42, and the value of b2 is 0.44.

[0033] Detection abnormality marking module: detect the steam-curing detection points on the concrete beam body in sequence according to the steam-curing detection sequence, complete the detection of each steam-curing detection point, obtain the steam-curing depth detection value of the steam-curing detection point, set the steam-curing depth detection critical value (the steam-curing depth detection critical value is the set threshold of the steam-curing detection system), when the steam-curing depth detection value of the steam-curing detection point is greater than or equal to the steam-curing depth detection critical value, mark the steam-curing detection point as a steam-curing detection abnormality point, when the steam-curing depth detection value of the steam-curing detection point is less than the steam-curing depth detection critical value, continue to detect the next steam-curing detection point according to the steam-curing detection sequence.

[0034] After each pair of steaming-curing detection points are tested, the steaming-curing depth detection value of the steaming-curing detection point is obtained, specifically: various steaming-curing index data of the steaming-curing detection point are collected (the steaming-curing index data include the internal temperature of the beam body, the internal humidity of the beam body, the slump of the beam body, the expansion of the beam body, the air content of the beam body, etc.), and the steaming-curing index models corresponding to the various steaming-curing index data are obtained. The various steaming-curing index data are input into the corresponding steaming-curing index models respectively to obtain the steaming-curing index compliance values ​​of the various steaming-curing index data, and all the steaming-curing index data are matched into a steaming-curing index group. The steaming-curing index compliance values ​​of two steaming-curing index data in the steaming-curing index group are calculated by difference and absolute value to obtain the discrete value of the steaming-curing index of the steaming-curing index group, and the discrete values ​​of the steaming-curing index of all the steaming-curing index groups are summed and averaged to obtain the discrete mean value Ptdg of the steaming-curing index. The steaming index standard values ​​of the steaming index data are summed and averaged to obtain the average steaming standard value Bmg, and the steaming index standard high value and the steaming index standard low value are set (the steaming index standard high value is greater than the steaming index standard low value, and the steaming index standard high value and the steaming index standard low value are both set thresholds of the steaming detection system). When the steaming index standard value of the steaming index data is greater than or equal to the steaming index standard high value, the steaming index data is marked as steaming standard data, and the total number of steaming standard data is marked as Rz. When the steaming index standard value of the steaming index data is less than or equal to the steaming index standard low value, the steaming index data is marked as steaming failure data, and the total number of steaming failure data is marked as Ek. When the steaming index standard value of the steaming index data is between the steaming index standard high value and the steaming index standard low value, no further processing is performed, and the formula is used. The steaming depth detection value Zsh of the steaming detection point is obtained, where v1 is the steaming index dispersion coefficient, v2 is the steaming average standard-reaching coefficient, v3 is the steaming standard-reaching coefficient, and v4 is the steaming non-standard coefficient. The value of v1 is 2.31, the value of v2 is 1.52, the value of v3 is 0.79, and the value of v4 is 0.81.

[0035] Each type of steaming curing index data corresponds to a steaming curing index model. The difference between different steaming curing index models lies only in the difference in training data. In a specific embodiment of the present invention, a construction method of a steaming curing index model corresponding to the internal temperature of a beam body is disclosed: a plurality of internal temperatures of a beam body are collected to construct a neural network model. The internal temperature of the beam body is used as training data of the neural network model. A steaming curing index compliance value is assigned to each training data. The value range of the steaming curing index compliance value is (1.1-4.9). The larger the value of the steaming curing index compliance value, the more the internal temperature of the beam body meets the steaming curing index. The smaller the value of the steaming curing index compliance value, the less the internal temperature of the beam body meets the steaming curing index. The training data is divided into a training set, a validation set, and a test set according to a set ratio of 4:1:1. The neural network is iteratively trained on the training set, the validation set, and the test set. After the training is completed, a steaming curing index model of the internal temperature of the beam body is constructed.

[0036] If the purpose is to construct a steam-curing index model for beam slump, then for multiple beam slumps, the larger the value of the steam-curing index compliance value is, the more the beam slump meets the steam-curing index, and the smaller the value of the steam-curing index compliance value is, the less the beam slump meets the steam-curing index.

[0037] A steam-curing detection point setting module, a steam-curing detection execution module and a detection abnormality marking module are set up to divide a plurality of equally spaced steam-curing detection points on the concrete beam to ensure the comprehensiveness and balance of the steam-curing detection and meet the precision steam-curing detection of large-size concrete beams. A comprehensive detection and analysis is performed on each steam-curing detection point of the concrete beam based on a certain period, and priority is given to the detection and analysis of the steam-curing detection points with high detection requirements on the concrete beam, to ensure efficient and accurate discovery of locations on the concrete beam with poor steam-curing performance.

[0038] Detection execution adjustment module: When an abnormal steaming detection point appears, the remaining steaming detection points that have not been detected are marked as abnormal steaming detection points, and the abnormal detection related value of each abnormal steaming detection point is obtained. All the abnormal steaming detection points are sorted in descending order according to the value of the abnormal detection related value, and a steaming abnormal detection sequence is generated in the sorting order. The abnormal steaming detection points are detected in sequence according to the steaming abnormal detection sequence.

[0039] The abnormal inspection related value of the steaming abnormal inspection point is obtained by the following steps: determine a steaming abnormal inspection point, calculate the distance difference between the steaming abnormal inspection point and the steaming abnormal detection point to obtain the inspection point spacing Lc, obtain the steaming depth detection value of the steaming abnormal inspection point and the steaming abnormal detection point obtained at the previous cycle node, sum the two steaming depth detection values ​​to obtain the depth detection additional value Rw, calculate the difference between the two steaming depth detection values ​​and take the absolute value to obtain the depth detection gap value Yd, and use the formula Obtain the abnormal inspection related value Atp of the steaming abnormal inspection point.

[0040] Detection cycle modification module: When all steam curing detection points on the concrete beam body are tested, the steam curing detection modification value of the concrete beam body is obtained, and the steam curing detection modification limit is set (the steam curing detection modification limit is the set threshold of the steam curing detection system). When the steam curing detection modification value is greater than the steam curing detection modification limit, the steam curing detection modification limit is calculated with the steam curing detection modification value to obtain the modification ratio e, and the period length of the steam curing detection cycle is adjusted to T SC e When the steaming detection modification value is less than or equal to the steaming detection modification limit, no further processing is performed.

[0041] The steam-curing detection modification value of the concrete beam body is obtained through the following steps: the total number of steam-curing detection abnormal points is obtained and marked as Ewcu, the steam-curing depth detection values ​​of the steam-curing detection abnormal points are summed and averaged to obtain the abnormal depth detection value Fbmk, and the steam-curing detection modification value Jxg of the concrete beam body is obtained using the formula Jxg=Ewcu*j1+Fbmk*j2, where j1 is the detection abnormality quantity coefficient, j2 is the abnormal depth detection coefficient, the value of j1 is 0.73, and the value of j2 is 0.34.

[0042] A detection execution adjustment module and a detection cycle modification module are set up. When a position with poor steam-curing performance appears on the concrete beam, the detection order of the remaining steam-curing detection points on the concrete beam is quickly adjusted, and the remaining positions with poor steam-curing performance are quickly screened out, which significantly improves the response speed and pertinence of the detection. The steam-curing detection cycle is dynamically adjusted according to the comprehensive steam-curing performance of the concrete beam to ensure that the concrete beam is detected with a reasonable steam-curing detection cycle.

[0043] The above formulas are all dimensionless and numerical calculations are performed, and the preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0044] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0045] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0046] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0047] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0048] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0049] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0050] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A steaming detection system applied to a smart beam yard, characterized in that: It includes a steaming test point setting module, a steaming test execution module, a test abnormality marking module, a test execution adjustment module, and a test cycle modification module; The steam curing detection point setting module divides a plurality of steam curing detection points at equal intervals on the concrete beam before the concrete beam is steam cured; The curing detection execution module obtains the curing detection requirement value of the curing detection point on the concrete beam body every time the curing detection cycle node is reached during the curing process of the concrete beam body, and then generates a curing detection sequence; The detection abnormality marking module detects the curing detection points on the concrete beam body in sequence according to the curing detection sequence, completes the detection of each curing detection point, obtains the curing depth detection value of the curing detection point, and determines whether to mark the curing detection point as a curing detection abnormality point based on the comparison result of the curing depth detection value and the curing depth detection critical value; When an abnormal steaming detection point appears, the detection execution adjustment module marks all other undetected steaming detection points as abnormal steaming detection points, generates an abnormal steaming detection sequence, and detects the abnormal steaming detection points in sequence according to the abnormal steaming detection sequence; The detection cycle modification module obtains a steam-curing detection modification value of the concrete beam body when all steam-curing detection points on the concrete beam body have completed detection, and determines whether to modify the cycle length of the steam-curing detection cycle based on a comparison result between the steam-curing detection modification value and the steam-curing detection modification limit value.

2. According to claim 1, a steaming detection system applied to a smart beam field is characterized in that: The steaming detection demand value of the steaming detection point is obtained by the following steps: obtain the s steaming depth detection values ​​obtained before the steaming detection point, sort all the steaming depth detection values ​​in the order of acquisition, calculate the difference between the two adjacent steaming depth detection values ​​after sorting and take the absolute value to obtain the depth detection floating value, sum up all the depth detection floating values ​​and take the average to obtain the depth detection floating mean Ajp, sum up all the steaming depth detection values ​​and take the average to obtain the depth detection mean Ajy, and use the formula The steaming detection requirement value Nmt of the steaming detection point is obtained, wherein b1 is the detection floating mean coefficient, and b2 is the depth detection mean coefficient.

3. The steaming detection system applied to the smart beam field according to claim 1 is characterized in that: The steam curing detection sequence is generated by the following steps: all the steam curing detection points on the concrete beam are sorted in descending order according to the values ​​of the steam curing detection demand values, and the steam curing detection sequence is generated in the sorted order.

4. The steaming detection system applied to the smart beam field according to claim 1 is characterized in that: After each test is completed for a steaming detection point, the steaming depth test value of the steaming detection point is obtained, specifically: various steaming index data of the steaming detection point are collected, and the steaming index models corresponding to the various steaming index data are obtained. The various steaming index data are input into the corresponding steaming index models respectively to obtain the steaming index compliance values ​​of the various steaming index data, and the discrete mean value of the steaming index Ptdg is obtained. The steaming index compliance values ​​of all the steaming index data are summed and averaged to obtain the steaming average compliance value Bmg. The steaming index compliance high value and the steaming index compliance low value are set. When the steaming index compliance value of the steaming index data is greater than or equal to the steaming index compliance high value, the steaming index data is marked as steaming compliance data, and the total number of steaming compliance data is marked as Rz. When the steaming index compliance value of the steaming index data is less than or equal to the steaming index compliance low value, the steaming index data is marked as steaming failure data, and the total number of steaming failure data is marked as Ek. The formula is used The steaming depth detection value Zsh of the steaming detection point is obtained, wherein v1 is the steaming index dispersion coefficient, v2 is the steaming average standard-reaching coefficient, v3 is the steaming standard-reaching coefficient, and v4 is the steaming non-standard coefficient.

5. The steaming detection system applied to the smart beam field according to claim 4 is characterized in that: The discrete mean value Ptdg of the steaming index is obtained by the following steps: all the steaming index data are matched in pairs into a steaming index group, the difference between the steaming index compliance values ​​of two steaming index data in the steaming index group is calculated and the absolute value is taken to obtain the discrete value of the steaming index of the steaming index group, the discrete values ​​of the steaming index of all the steaming index groups are summed up and the average is taken to obtain the discrete mean value Ptdg of the steaming index.

6. The steaming detection system applied to the smart beam field according to claim 1 is characterized in that: Based on the comparison result of the steaming depth detection value and the steaming depth detection critical value, it is determined whether to mark the steaming detection point as a steaming detection abnormal point, specifically: setting the steaming depth detection critical value, when the steaming depth detection value of the steaming detection point is greater than or equal to the steaming depth detection critical value, the steaming detection point is marked as a steaming detection abnormal point, when the steaming depth detection value of the steaming detection point is less than the steaming depth detection critical value, continue to detect the next steaming detection point according to the steaming detection sequence.

7. The steaming detection system applied to the smart beam yard according to claim 1 is characterized in that: The steaming abnormal inspection sequence is generated by the following steps: obtaining the abnormal inspection correlation value of each steaming abnormal inspection point, sorting all the steaming abnormal inspection points in descending order according to the abnormal inspection correlation value, and generating the steaming abnormal inspection sequence according to the sorting order.

8. The steaming detection system applied to the smart beam field according to claim 7 is characterized in that: The abnormal inspection related value of the steaming abnormal inspection point is obtained by the following steps: determine a steaming abnormal inspection point, calculate the distance difference between the steaming abnormal inspection point and the steaming abnormal detection point to obtain the inspection point spacing Lc, obtain the steaming depth detection value of the steaming abnormal inspection point and the steaming abnormal detection point obtained at the previous cycle node, sum the two steaming depth detection values ​​to obtain the depth detection additional value Rw, calculate the difference between the two steaming depth detection values ​​and take the absolute value to obtain the depth detection gap value Yd, and use the formula Obtain the abnormal inspection related value Atp of the steaming abnormal inspection point.

9. The steaming detection system applied to the smart beam field according to claim 1 is characterized in that: Based on the comparison result of the steaming detection modification value and the steaming detection modification limit value, determine whether to modify the cycle length of the steaming detection cycle, specifically: set the steaming detection modification limit value, when the steaming detection modification value is greater than the steaming detection modification limit value, calculate the ratio of the steaming detection modification limit value to the steaming detection modification value, obtain the modification ratio e, and adjust the cycle length of the steaming detection cycle to T SC e .

10. The steaming detection system applied to the smart beam field according to claim 1 is characterized in that: The steam curing detection modification value of the concrete beam body is obtained through the following steps: obtain the total number of steam curing detection abnormal points and mark them as Ewcu, sum the steam curing depth detection values ​​of the steam curing detection abnormal points and take the average to obtain the abnormal depth detection value Fbmk, and use the formula Jxg=Ewcu*j1+Fbmk*j2 to obtain the steam curing detection modification value Jxg of the concrete beam body, where j1 is the detection abnormality quantity coefficient, and j2 is the abnormal depth detection coefficient.

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