A building material detection method and device combined with an inductively coupled plasma mass spectrometer

Abstract

The present application relates to the technical field of building material testing, and in particular to a building material testing method and apparatus incorporating a plasma mass spectrometer. The method comprises: obtaining the impurity content of multiple testing points on a building material; selecting the testing points according to the material type contained in the building material; performing a structural strength analysis based on the service scenario of the building material when the impurity content at the testing point exceeds a preset value for the corresponding material type; and outputting a test failure prompt message in response to the structural strength not meeting the corresponding service scenario. The present application can effectively determine the matching degree between the strength of the building material and the service scenario, avoiding the problem of being unable to make adjustments based on specific construction conditions, resulting in an inability to fully utilize the building material.

Description

Technical Field

[0001] The present application relates to the technical field of building material detection, and in particular to a building material detection method and device combined with a plasma mass spectrometer. Background Art

[0002] Building materials refer to the various materials used in construction projects. Their quality is often directly related to the structural safety of a building. For example, steel with excessive impurity content may not be able to withstand the designed stress, leading to the risk of collapse during use. Therefore, building material testing helps ensure that building materials can withstand the test of time and environmental factors.

[0003] At present, the testing of building materials mostly relies on industry standards and cannot be adjusted based on specific construction conditions, resulting in the inability to fully utilize building materials. Summary of the Invention

[0004] Based on this, it is necessary to provide a building material detection method and device combined with a plasma mass spectrometer to address the above technical problems.

[0005] In a first aspect, the present application provides a method for detecting building materials using a plasma mass spectrometer, the method comprising:

[0006] Obtain the impurity content of multiple testing points of the building materials; the testing points are selected according to the material types contained in the building materials;

[0007] When the impurity content at the detection point exceeds the preset value for the corresponding material type, a structural strength analysis is performed based on the service scenario of the building material;

[0008] In response to the structural strength not meeting the corresponding service scenario, a detection failure prompt message is output.

[0009] In one embodiment, the building material includes building steel and concrete; and the method further comprises:

[0010] The detection depth is determined based on the depth of concrete covering the building steel bars, and multiple detection points are selected on the building steel bars and concrete according to the detection depth;

[0011] Sampling is performed at the selected detection points to obtain test samples, and the sample impurity analysis is performed using a plasma mass spectrometer;

[0012] In response to the phosphorus content of the test sample corresponding to the building steel bars exceeding the first preset value, the sulfur content exceeding the second preset value, the sulfide content of the test sample corresponding to the concrete exceeding the third preset value, or the chloride content exceeding the fourth preset value, it is judged that the impurity content of the test point exceeds the preset value of the corresponding material type.

[0013] In one embodiment, the step of performing structural strength analysis according to the service scenario of the building material includes:

[0014] Construct a three-dimensional structural model of the target building in the service scenario; the target building is constructed based on building materials;

[0015] Through the three-dimensional structural model and the quality characteristics of building materials, the stress analysis of the target building is carried out to obtain the stress distribution of each building structure corresponding to the building materials in the target building;

[0016] Determine the bearing points of each building structure based on stress distribution, and classify the bearing points according to the preset load classification rules;

[0017] Select multiple bearing points from high to low according to the load level to conduct structural strength analysis.

[0018] In one embodiment, the method further comprises:

[0019] Conducting structural strength tests on multiple batches of building materials to be tested; the multiple batches of building materials to be tested include building steel bars having different phosphorus and sulfur contents, and concrete having different sulfide and phosphide contents;

[0020] Based on the test results, a correlation model between impurity content and structural strength is constructed, and the phosphorus content and sulfur content of the steel bars in each batch of tested building materials, as well as the sulfide content and phosphide content of the concrete, are input into the correlation model for training to obtain a trained correlation model;

[0021] The trained correlation model calculates the degradation coefficient of the structural strength of building materials under different impurity contents, taking the standard structural strength as the benchmark. The standard structural strength is used to represent the structural strength when the impurity content does not exceed the preset value of the corresponding material type.

[0022] The structural strength of the bearing points is evaluated based on the impurity content of the building materials at the selected bearing points and the corresponding degradation coefficient.

[0023] In one embodiment, the method further comprises:

[0024] Obtain meteorological data for the areas where the reference and target buildings are located, as well as the service life of the reference buildings. Meteorological data includes annual precipitation, maximum daily precipitation, annual average precipitation acidity, and wind force level. The reference building represents a building with the same structure and building materials as the selected bearing points.

[0025] According to the service life of the reference building and the meteorological data of the area where the reference building is located, the linear relationship between the service life and meteorological data under the same building structure and building materials is fitted;

[0026] Construct a simulation model of the building structure corresponding to the selected bearing points of the target building, and predict the service life of the target building based on the meteorological data and linear relationship of the area where the target building is located;

[0027] In response to the service life of the target building being less than the preset service life, an early warning prompt message indicating that the structural strength of the bearing point is unqualified is output; the early warning prompt message is used to indicate that the impurity content of the building materials of the target building exceeds the preset value of the corresponding material type.

[0028] In one embodiment, the method further comprises:

[0029] When outputting the warning prompt information, respectively obtaining a first difference between the phosphorus content in the building steel bars of the target building and a first preset value, a second difference between the sulfur content and a second preset value, a third difference between the sulfide content in the concrete and a third preset value, and a fourth difference between the chloride content and a fourth preset value;

[0030] Adjusting the non-negative values of the first difference, the second difference, the third difference, and the fourth difference in sequence according to preset intervals until the service life of the target building meets the preset service life;

[0031] When the first difference, the second difference, the third difference and the fourth difference are all non-negative numbers, a prompt message indicating that the building materials of the target building are qualified is output.

[0032] In a second aspect, the present application provides a building material detection device combined with a plasma mass spectrometer, the device comprising:

[0033] An acquisition module is used to obtain the impurity content of multiple detection points of the building material; the detection points are selected according to the material type contained in the building material;

[0034] An analysis module is used to perform structural strength analysis based on the service scenario of the building material when the impurity content at the detection point exceeds the preset value of the corresponding material type;

[0035] The output module is used to output a detection failure prompt message in response to the structural strength not meeting the corresponding service scenario.

[0036] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method provided in the first aspect of the present application are implemented.

[0037] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in the first aspect of the present application.

[0038] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the method provided in the first aspect of the present application.

[0039] The above-mentioned method and device for detecting building materials combined with a plasma mass spectrometer can realize separate detection based on the various material types contained in the building materials by selecting multiple detection points, thereby reducing the detection error of the impurity content of the building materials. When the impurity content exceeds the preset value of the corresponding material type, the structural strength analysis is performed from the perspective of impurity content combined with the service scenario of the building materials, thereby effectively determining the matching degree between the strength of the building materials and the service scenario, avoiding the problem of not being able to make adjustments based on the specific construction conditions, resulting in the inability to fully utilize the building materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 A flowchart of the steps for determining whether a building material meets a service scenario based on impurity content in one embodiment;

[0042] Figure 2 A flowchart of the steps of extracting and analyzing impurities from building materials in one embodiment;

[0043] Figure 3 A flowchart of the steps for determining the bearing point according to the load level in one embodiment;

[0044] Figure 4 A flowchart of steps for evaluating an anchorage point in one embodiment;

[0045] Figure 5 A flowchart of the steps for determining whether the impurity content meets the standard based on the service life in one embodiment;

[0046] Figure 6 A flow chart of the steps for determining the impurity content in a material type required to reach the service life in one embodiment;

[0047] Figure 7The figure is a structural block diagram of a building material detection device in one embodiment. DETAILED DESCRIPTION

[0048] To make the above-mentioned objects, features, and advantages of the present application more clearly understood, the specific embodiments of the present application are described in detail below with reference to the accompanying drawings. The following description sets forth many specific details to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways than those described herein, and those skilled in the art can make similar improvements without violating the scope of the present application. Therefore, the present application is not limited to the specific embodiments disclosed below.

[0049] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0050] In an exemplary embodiment, Figure 1 As shown, the present application provides a construction material detection method combined with a plasma mass spectrometer, the method comprising the following steps S102 to S106.

[0051] S102, obtaining the impurity content of multiple detection points of the building material; the detection points are selected according to the material type contained in the building material.

[0052] Specifically, the method provided in the embodiments of the present application can directly test in-service building materials to evaluate the structural strength of the building materials. Therefore, the structural strength test performed is based on an integrated molding state constructed with materials of multiple types.

[0053] Furthermore, during the process of testing the formed building materials, drilling can be performed on the building materials to take samples, so as to ensure that each material type in the integrally formed building materials can be sampled.

[0054] For example, when the integrally formed building material is reinforced concrete, the detection points are selected by determining the positions of the steel bars covered by the concrete, and the steel bars and concrete are sampled separately after drilling.

[0055] Specifically, the impurity content of multiple detection points includes selecting corresponding detection points for each material type, and also includes selecting multiple detection points on the same material type, and accumulating the impurity content of each detection point of the same material type and then removing the average value.

[0056] S104: When the impurity content at the detection point exceeds a preset value corresponding to the material type, a structural strength analysis is performed according to the service scenario of the building material.

[0057] Specifically, the service scene of a building material is used to indicate the structural position where the building material serves. For example, in a bridge, the service scene may be a pier or a bridge deck; in a floor, the service scene may be a longitudinal load-bearing wall or a transverse load-bearing wall.

[0058] S106: In response to the structural strength not meeting the corresponding service scenario, outputting a detection failure prompt message.

[0059] Specifically, the structural strength not meeting the corresponding service scenario is used to indicate that the structural strength is lower than the minimum structural strength required by the service scenario.

[0060] An embodiment of the present application provides a building material detection method combined with a plasma mass spectrometer. The method can realize separate detection based on the various material types contained in the building materials by selecting multiple detection points, thereby reducing the detection error of the impurity content of the building materials. When the impurity content exceeds the preset value of the corresponding material type, the structural strength analysis is performed from the perspective of the impurity content combined with the service scenario of the building materials, thereby effectively determining the matching degree between the strength of the building materials and the service scenario, avoiding the problem of not being able to make adjustments based on the specific construction conditions, resulting in the inability to fully utilize the building materials.

[0061] In an exemplary embodiment, Figure 2 As shown, the building materials include building steel bars and concrete; the method further includes the following steps S202 to S206.

[0062] S202: determining a detection depth based on the depth of concrete covering the building steel bars, and selecting a plurality of detection points on the building steel bars and concrete according to the detection depth.

[0063] S204: Sampling is performed according to the selected detection points to obtain detection samples, and the sample is analyzed for impurities using a plasma mass spectrometer.

[0064] Specifically, an inductively coupled plasma mass spectrometer (ICP-MS) is an analytical instrument that combines inductively coupled plasma (ICP) technology with mass spectrometry. It has the characteristics of fast, accurate and good stability, and can be effectively used to extract trace impurities contained in construction steel bars and concrete.

[0065] S206, in response to the phosphorus content of the test sample corresponding to the building steel bars exceeding the first preset value, the sulfur content exceeding the second preset value, the sulfide content of the test sample corresponding to the concrete exceeding the third preset value, or the chloride content exceeding the fourth preset value, it is determined that the impurity content of the test point exceeds the preset value of the corresponding material type.

[0066] Specifically, the first preset value may be 0.045% of the total amount of construction steel bars, the second preset value may be 0.03% of the total amount of construction steel bars, the third preset value may be 3.5% of the total amount of concrete, and the fourth preset value may be 0.4% of the total amount of concrete.

[0067] In an exemplary embodiment, Figure 3 As shown, the steps of performing structural strength analysis according to the service scenario of building materials are as follows: Steps S1042 to S1048.

[0068] S1042, constructing a three-dimensional structural model of a target building in a service scenario; the target building is constructed based on building materials.

[0069] Specifically, by constructing a three-dimensional structural model of a target building using the building materials provided in the embodiments of the present application, it is possible to analyze the stress distribution of the building materials based on the building structure to be analyzed, the quality and structural characteristics of the building materials, and the structural strength required of the building materials under different structural conditions, given the impurities in the building materials.

[0070] S1044: Perform stress analysis on the target building using the three-dimensional structural model and the quality characteristics of the building materials to obtain stress distribution of each building structure corresponding to the building materials in the target building.

[0071] S1046: Determine the bearing points of each building structure based on the stress distribution, and classify the bearing points into load levels according to a preset load level classification rule.

[0072] Specifically, the load level division rule can be based on the maximum value of the load borne by the building materials in each building structure to be analyzed, determine the stress value of the highest level load in the load level, and divide the load levels from high to low according to preset intervals.

[0073] Furthermore, given the stress value corresponding to the highest load level, multiple load levels with stress values from high to low are selected according to the size of the stress distribution to determine the position of the bearing point with the largest stress value. This position corresponds to the structural strength of the maximum stress that the building material should be able to withstand.

[0074] S1048, select multiple bearing points from high to low according to the load level to conduct structural strength analysis.

[0075] In an exemplary embodiment, Figure 4 As shown, the method further includes the following steps S302 to S308.

[0076] in:

[0077] S302, performing structural strength tests on multiple batches of building materials to be tested; the multiple batches of building materials to be tested include building steel bars having different phosphorus and sulfur contents, and concrete having different sulfide and phosphide contents.

[0078] Specifically, in order to further explore the impact of different impurity contents on structural strength, structural strength tests can be conducted on building materials whose phosphorus and sulfur contents of building steel bars are different and whose sulfide and phosphide contents of the contained concrete are different.

[0079] S304: Based on the test results, a correlation model between impurity content and structural strength is constructed, and the phosphorus content and sulfur content of the steel bars in each batch of tested building materials, as well as the sulfide content and phosphide content of the concrete are input into the correlation model for training to obtain a trained correlation model.

[0080] Specifically, by constructing an association relationship model, the impact of different impurity contents on structural strength can be effectively determined, and based on this, the impurity content that can meet the required structural strength can be determined.

[0081] S306, using the trained association model, and taking the standard structural strength as a benchmark, calculate the degradation coefficient of the structural strength of the building materials under different impurity contents; the standard structural strength is used to represent the structural strength when the impurity content does not exceed the preset value of the corresponding material type.

[0082] Specifically, the standard structural strength represents the impurity content of the material type corresponding to the preset value.

[0083] Furthermore, given a preset value of impurity content corresponding to a standard structural strength, the trained association model can determine the percentage of degradation of the structural strength corresponding to each impurity content relative to the standard structural strength performance, thereby determining the degradation coefficient of the structural strength corresponding to each impurity content relative to the standard structural strength.

[0084] S308: Evaluate the structural strength of the selected bearing point based on the impurity content of the building material at the bearing point and the corresponding degradation coefficient.

[0085] Specifically, when determining the degradation coefficient of the structural strength corresponding to each impurity content relative to the standard structural strength, the decrease or increase in the structural strength of the bearing point can be determined according to the impurity content of the building materials at the selected bearing point, thereby forming an evaluation result of the structural strength.

[0086] In an exemplary embodiment, Figure 5As shown, the method further includes the following steps S402 to S408.

[0087] in:

[0088] S402, obtaining meteorological data of the areas where the reference building and the target building are located in the big data, as well as the service life of the reference building; the meteorological data includes annual precipitation, maximum daily precipitation, annual average precipitation acidity, and wind force level; the reference building represents a building with the same building structure and building materials as the selected bearing point.

[0089] Specifically, in order to further analyze the impact of different impurity contents on the structural strength of the target building, the service life of the target building can be observed to determine whether building materials with different impurity contents can meet service expectations based on the service life.

[0090] Furthermore, by crawling big data, we can obtain the degree of influence of different meteorological data on existing buildings when the building materials and building structures are the same as those of the target building. Therefore, we can obtain the meteorological factors with the strongest correlation with building aging, including annual precipitation, maximum daily precipitation, annual average precipitation acidity and wind level.

[0091] S404: fitting a linear relationship between the service life and the meteorological data under the same building structure and building materials based on the service life of the reference building and the meteorological data of the area where the reference building is located.

[0092] Specifically, we can obtain multiple linear relationships between service life and meteorological data lines based on different annual precipitation, maximum daily precipitation, annual average precipitation acidity, and wind speed levels. During the fitting process, we can use interpolation to incorporate multiple meteorological factors into the linear relationship.

[0093] S406: Construct a simulation model of the building structure corresponding to the selected bearing point of the target building, and predict the service life of the target building based on the meteorological data and linear relationship of the area where the target building is located.

[0094] Specifically, based on the fitted linear relationship and the meteorological data of the area where the target building is located, the service life of the target building can be effectively determined.

[0095] S408: In response to the service life of the target building being less than the preset service life, outputting a warning prompt message indicating that the structural strength of the bearing point is unqualified; the warning prompt message is used to indicate that the impurity content of the building materials of the target building exceeds the preset value of the corresponding material type.

[0096] Specifically, when the service life of the target building is less than the expected service life of the building, a warning prompt message is output, which can instruct the user to determine that the building materials used for the target building are not suitable.

[0097] In an exemplary embodiment, Figure 6 As shown, the method further includes the following steps S502 to S506.

[0098] in:

[0099] S502, when outputting the warning prompt information, respectively obtain a first difference between the phosphorus content in the building steel bars of the target building and the first preset value, a second difference between the sulfur content and the second preset value, a third difference between the sulfide content in the concrete and the third preset value, and a fourth difference between the chloride content and the fourth preset value.

[0100] Specifically, when the target building is unqualified, the difference between each impurity content and the preset value is obtained respectively, which can effectively determine whether the building materials of the target building are unqualified due to the impurity content, so as to verify the early warning prompt information.

[0101] S504: adjusting the non-negative values of the first difference, the second difference, the third difference, and the fourth difference in sequence according to preset intervals until the service life of the target building meets the preset service life.

[0102] Specifically, when adjusting the non-negative values of the first difference, the second difference, the third difference and the fourth difference so that the service life of the target building meets the preset service life, the influence of each impurity content on the building materials is essentially adjusted, and the correlation between the impurity content and the service life in the building materials is enhanced.

[0103] In one embodiment, when the service life of the target building meets the preset service life, the impurity content value of each building material is output as the impurity content value of the standard structural strength required of the building material under the same meteorological conditions.

[0104] S506: When the first difference, the second difference, the third difference, and the fourth difference are all non-negative numbers, output a prompt message indicating that the building materials of the target building are qualified.

[0105] Specifically, the first difference, the second difference, the third difference, and the fourth difference are all non-negative numbers, which is used to indicate that the impurity content does not exceed the preset value of the corresponding material type, indicating that the reason for the unsatisfactory service life is not due to the impurity content of the building materials, which can provide a basis for analysis in other directions.

[0106] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0107] Based on the same inventive concept, embodiments of the present application also provide a building material detection device for implementing the aforementioned method for detecting building materials incorporating a plasma mass spectrometer. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more of the following embodiments of the building material detection device can be found in the aforementioned definition of the method for detecting building materials incorporating a plasma mass spectrometer, and will not be further elaborated here.

[0108] Second, as Figure 7 As shown, the present application also provides a building material detection device, the device comprising:

[0109] The acquisition module 701 is used to obtain the impurity content of multiple detection points of the building material; the detection points are selected according to the material type contained in the building material;

[0110] Analysis module 702, configured to perform structural strength analysis based on the service scenario of the building material when the impurity content at the detection point exceeds a preset value corresponding to the material type;

[0111] The output module 703 is configured to output a detection failure prompt message in response to the structural strength not meeting the corresponding service scenario.

[0112] In a third aspect, the present application also provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the aforementioned method for detecting building materials in combination with a plasma mass spectrometer are implemented.

[0113] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the aforementioned method for detecting building materials in combination with a plasma mass spectrometer.

[0114] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the aforementioned method for detecting building materials in combination with a plasma mass spectrometer.

[0115] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0116] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0117] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A building material detection method combined with a plasma mass spectrometer, characterized in that: The method comprises: Obtaining impurity content at multiple detection points of the building material; the detection points are selected according to the type of material contained in the building material; When the impurity content at the detection point exceeds a preset value corresponding to the material type, a structural strength analysis is performed according to the service scenario of the building material; In response to the structural strength not meeting the corresponding service scenario, outputting a detection failure prompt message; The building materials include building steel bars and concrete; a detection depth is determined based on the depth to which the concrete covers the building steel bars, and a plurality of detection points are selected on the building steel bars and the concrete according to the detection depth; sampling is performed according to the selected detection points to obtain detection samples, and the sample impurity analysis is performed using a plasma mass spectrometer; in response to the phosphorus content of the detection sample corresponding to the building steel bars exceeding a first preset value, the sulfur content exceeding a second preset value, the sulfide content of the detection sample corresponding to the concrete exceeding a third preset value, or the chloride content exceeding a fourth preset value, it is determined that the impurity content of the detection point exceeds the preset value corresponding to the material type; The step of performing a structural strength analysis according to the service scenario of the building material includes: constructing a three-dimensional structural model of a target building under the service scenario; the target building is constructed based on the building material; performing a stress analysis on the target building using the three-dimensional structural model and the quality characteristics of the building material to obtain a stress distribution of each building structure corresponding to the building material in the target building; determining the bearing points of each building structure based on the stress distribution, and classifying the bearing points according to a preset load level classification rule; and selecting a plurality of bearing points for the structural strength analysis according to the load level from high to low. Structural strength tests are conducted on multiple batches of building materials to be tested; the multiple batches of building materials to be tested are building materials to be tested, wherein the phosphorus content and sulfur content of the building steel bars contained in the multiple batches of building materials to be tested are different, and the sulfide content and phosphide content of the concrete contained in the multiple batches of building materials to be tested are different; based on the test results, a correlation model between impurity content and structural strength is constructed, and the phosphorus content and sulfur content of the building steel bars, as well as the sulfide content and phosphide content of the concrete in each batch of building materials to be tested are input into the correlation model for training to obtain a trained correlation model; using the trained correlation model, the degradation coefficient of the structural strength of the building materials under different impurity contents is calculated based on the standard structural strength; the standard structural strength is used to characterize the structural strength when the impurity content does not exceed the preset value corresponding to the material type; the structural strength of the selected bearing point building materials is evaluated according to the impurity content of the selected bearing point building materials and the corresponding degradation coefficient.

2. The method according to claim 1, characterized in that The method further comprises: Obtain meteorological data for the area where the reference building and the target building are located in the big data, as well as the service life of the reference building; the meteorological data includes annual precipitation, maximum daily precipitation, annual average precipitation acidity, and wind force level; the reference building represents a building with the same building structure and building materials as the selected bearing point; According to the service life of the reference building and the meteorological data of the area where the reference building is located, fitting a linear relationship between the service life and the meteorological data under the same building structure and building materials; Constructing a simulation model of the building structure corresponding to the selected bearing point of the target building, and predicting the service life of the target building based on meteorological data of the area where the target building is located and the linear relationship; In response to the service life of the target building being less than a preset service life, an early warning prompt message indicating that the structural strength of the bearing point is unqualified is output; the early warning prompt message is used to indicate that the impurity content of the building material of the target building exceeds a preset value corresponding to the material type.

3. The method according to claim 2, characterized in that The method further comprises: When outputting the warning prompt information, respectively obtaining a first difference between the phosphorus content in the steel bars of the target building and a first preset value, a second difference between the sulfur content and a second preset value, a third difference between the sulfide content in the concrete and a third preset value, and a fourth difference between the chloride content and a fourth preset value; adjusting the non-negative values of the first difference, the second difference, the third difference, and the fourth difference in sequence according to preset intervals until the service life of the target building meets the preset service life; When the first difference, the second difference, the third difference and the fourth difference are all non-negative numbers, a prompt message indicating that the building materials of the target building are qualified is output.

4. A building material detection device combined with a plasma mass spectrometer, applied to the method according to any one of claims 1 to 3, characterized in that: The device comprises: An acquisition module, configured to acquire the impurity content of a plurality of detection points of the building material; the detection points are selected according to the type of material contained in the building material; An analysis module, configured to perform a structural strength analysis based on the service scenario of the building material when the impurity content at the detection point exceeds a preset value corresponding to the material type; The output module is used to output detection failure prompt information in response to the structural strength not meeting the corresponding service scenario.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

7. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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