Constructional engineering quality detection system and method based on cloud computing

Abstract

The invention discloses a building engineering quality detection system and method based on cloud computing, and belongs to the technical field of building quality detection. The system comprises a humidity evaluation module, an interference evaluation module and an equipment adjustment module. Wherein the humidity evaluation module is used for dividing the constructional engineering according to regions, and judging whether the constructional engineering enters the interference evaluation module or not according to underground environment data of each detection region; the interference evaluation module is used for acquiring an environmental interference index according to the underground humidity evaluation measurement, the distance between each detection area and the equipment and the geological structure data of each detection area, and adjusting the sound wave signal of the detection equipment for the first time; and the equipment adjusting module is used for calculating the deviation index of the detection equipment according to the echo intensity of the detection equipment, adjusting and feeding back the sound wave signal of the equipment according to the environment interference index, and monitoring the quality of the underground construction engineering by using the adjusted detection equipment, so that efficient and accurate monitoring of the quality of the underground construction engineering is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of building quality inspection, and particularly to a building engineering quality inspection system and method based on cloud computing. Background Art

[0002] The quality inspection of underground construction projects refers to the use of various detection techniques and means to monitor and evaluate building structures, soils, rocks, construction materials, etc. during the construction process of underground projects to ensure the safety, stability and durability of the projects. With the acceleration of the urbanization process, the construction of underground construction projects such as subways, underground parking lots, underground pipelines, etc. has become increasingly important, and the demand for quality inspection has become more urgent.

[0003] The existing quality inspection technologies for underground construction projects achieve comprehensive monitoring and evaluation of underground structures through a variety of non-destructive testing technologies, including ground-penetrating radar, laser scanning, acoustic wave detection, sensor technology, etc. These technologies can detect important parameters such as the structural integrity of underground buildings, the characteristics of soils and rocks, the quality of materials, and deformation and stress in real time to ensure the safety and stability of the projects.

[0004] For example, a method and device for detecting the quality of bricks for building construction disclosed in the invention patent announcement with the publication number of CN118641646B includes: obtaining first ultrasonic images corresponding to each first preset detection point of a plurality of brick samples; using the first ultrasonic images corresponding to each first preset detection point of the brick samples to determine the local interference degrees of each first preset detection point of the brick samples; using the local interference degrees of each first preset detection point of the brick samples to determine the overall interference degree of the brick samples; constructing second ultrasonic images corresponding to each second preset detection point of a virtual sample corresponding to the brick samples according to the overall interference degrees of each brick sample; and training a target model through the first ultrasonic images corresponding to each first preset detection point of the brick samples and the second ultrasonic images corresponding to each first preset detection point of the virtual sample to obtain a brick detection model.

[0005] For example, a device for detecting building wall defects using ultrasonic waves disclosed in the patent application with the publication number CN115791963A includes a feeding component, a guiding component, a driving component, and a detecting component. There are two guiding components, which are respectively located on both sides of the wall along the thickness direction. The guiding component includes a guiding rod and a sliding seat. One end of the guiding rod is connected to the feeding component, and the feeding component is used to drive the entire detecting device to move along the length direction of the wall. The sliding seat is slidably connected to the guiding rod. The driving component is used to drive the sliding seat to slide. The detecting component includes an ultrasonic transmitting probe, an ultrasonic receiving probe, and an ultrasonic detector. The ultrasonic transmitting probe is fixedly connected to the sliding seat of one guiding component, the ultrasonic receiving probe is connected to the sliding seat of the other guiding component, and the ultrasonic detector is electrically connected to both the ultrasonic transmitting probe and the ultrasonic receiving probe.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it is found that the above technology has at least the following technical problems:

[0007] In the prior art, when using ultrasonic waves to detect the quality of underground construction projects, due to the complex geological structure of the underground space, the signals of the detection equipment are constantly refracted during the data acquisition process, causing the originally concentrated ultrasonic energy to disperse in all directions, resulting in a weakening of the signal intensity propagating along the original detection direction, causing signal attenuation, and further affecting the positioning accuracy of the equipment and the reliability of the measurement results. Summary of the Invention

[0008] The embodiments of the present application provide a building engineering quality detection system and method based on cloud computing, which solve the problems in the prior art that when using ultrasonic waves to detect the quality of underground construction projects, due to the complex geological structure of the underground space, the signals of the detection equipment are constantly refracted during the data acquisition process, causing the originally concentrated ultrasonic energy to disperse in all directions, resulting in a weakening of the signal intensity propagating along the original detection direction, causing signal attenuation, and further affecting the positioning accuracy of the equipment and the reliability of the measurement results.

[0009] The embodiments of the present application provide a cloud computing-based building engineering quality detection system and method, including: a humidity evaluation module, an interference evaluation module, a device adjustment module, and a building detection database; wherein, the humidity evaluation module is used to divide the underground building project into each detection area according to the regional area, obtain the underground environmental data and the underground environmental evaluation threshold of each detection area, and judge whether to enter the interference evaluation module; the interference evaluation module is used to obtain the distance between each detection area and the detection device, obtain the geological structure interference parameter of each detection area according to the distance between each detection area and the detection device, monitor the geological structure data of each detection area for comprehensive analysis to obtain the environmental interference index, and initially adjust the acoustic signal of the detection device according to the environmental interference index; the device adjustment module is used to obtain the incident wave intensity and each echo intensity of the detection device, obtain the reference for each echo intensity according to the incident wave intensity, obtain the detection device deviation index according to each echo intensity and the reference for each echo intensity, adjust and feedback the acoustic signal of the detection device according to the detection device deviation index and the environmental interference index, and use the adjusted detection device to monitor the building engineering quality.

[0010] Further, the steps of obtaining the underground environmental data and the underground environmental evaluation threshold of each detection area and judging whether to enter the interference evaluation module include: the underground environmental data includes soil humidity, air humidity, and groundwater content; obtain the reference soil humidity, allowable deviation soil humidity, reference air humidity, allowable deviation air humidity, reference groundwater content, and allowable deviation groundwater content from the building detection database, and comprehensively analyze to obtain the underground humidity evaluation metric, and the underground humidity evaluation metric represents the quantitative data of the combined influence degree of soil humidity, air humidity, and groundwater content on the humidity condition in the underground environment; compare the underground humidity evaluation metric with the underground environmental evaluation threshold, and if the underground humidity evaluation metric is greater than or equal to the underground environmental evaluation threshold, enter the interference evaluation module.

[0011] Further, the steps of obtaining the geological structure interference parameter of each detection area according to the distance between each detection area and the detection device include: obtain the first distance threshold and the second distance threshold from the building detection database; compare the distance between each detection area and the detection device with the first distance threshold and the second distance threshold respectively. If the distance between a certain detection area and the detection device is less than the first distance threshold, mark this detection area as a slightly affected area. If the distance between a certain detection area and the detection device is greater than or equal to the first distance threshold and less than the second distance threshold, mark this detection area as a moderately affected area. If the distance between a certain detection area and the detection device is greater than or equal to the second threshold, mark this detection area as a severely affected area, and match the geological structure interference parameter of each detection area according to the influence level of each detection area.

[0012] Further, the steps of comprehensively analyzing the geological structure data of each detection area to obtain the environmental interference index include: the geological structure data includes crack depth, crack length, and crack density; obtaining critical geological structure data, critical underground humidity assessment metrics, and critical geological structure interference index from the building detection database, where the critical geological structure data includes critical crack depth, critical crack length, and critical crack density; comprehensively analyzing the geological structure data of each detection area, the geological structure interference parameters of each detection area, and the critical geological structure data to obtain the geological structure interference index of each detection area, and the geological structure interference index represents the quantitative data of the degree of influence of the geological structure data and the geological structure interference parameters on the environment of the monitoring area; comprehensively analyzing the underground humidity assessment metrics, the geological structure interference index of each detection area, the critical underground humidity assessment metrics, and the critical geological structure interference index to obtain the environmental interference index, and the environmental interference index represents the quantitative data of the degree of influence of the underground humidity assessment metrics and the geological structure interference index on the detection quality of the underground construction project.

[0013] Further, the steps of initially adjusting the acoustic signal of the detection device according to the environmental interference index include: obtaining the environmental interference index threshold from the building detection database; comparing the environmental interference index with the environmental interference index threshold, if the environmental interference index is less than the environmental interference index threshold, no additional processing is performed, if the environmental interference index is greater than or equal to the environmental interference index threshold, the noise reduction function of the detection device is activated.

[0014] Further, the steps of obtaining the detection device deviation index according to each echo intensity and referring to each echo intensity include: the echoes include surface echoes, bottom echoes, and reflected echoes; marking the absolute value of the difference between the surface echo intensity and the reference surface echo intensity as the deviation surface echo intensity; marking the absolute value of the difference between the bottom echo intensity and the reference bottom echo intensity as the deviation bottom echo intensity; marking the absolute value of the difference between the reflected echo intensity and the reference reflected echo intensity as the deviation reflected echo intensity; comprehensively analyzing the deviation surface echo intensity, the deviation bottom echo intensity, the deviation reflected echo intensity, and the reference echo intensities to obtain the detection device deviation index, and the detection device deviation index represents the quantitative data of the degree of influence of the surface echo, the bottom echo, and the reflected echo on the detection accuracy of the echo signal.

[0015] Further, the steps of adjusting and feeding back the acoustic wave signal of the detection device according to the detection device deviation index and the environmental interference index include: obtaining the critical detection device deviation index and the critical environmental interference index from the building detection database; comprehensively analyzing the detection device deviation index, the environmental interference index, the critical detection device deviation index and the critical environmental interference index to obtain an equipment accuracy evaluation value, where the equipment accuracy evaluation value represents the quantitative data of the influence degree of the detection device deviation index and the environmental interference index on the accuracy of the equipment monitoring result, and adjusting the acoustic wave signal of the detection device according to the equipment accuracy evaluation value.

[0016] Further, the steps of adjusting the acoustic wave signal of the detection device according to the equipment accuracy evaluation value include: obtaining the equipment accuracy evaluation threshold from the building detection database; comparing the equipment accuracy evaluation value with the equipment accuracy evaluation threshold. If the equipment accuracy evaluation value is greater than or equal to the equipment accuracy evaluation threshold, directly use the detection device to conduct building engineering quality detection. If the equipment accuracy evaluation value is less than the equipment accuracy evaluation threshold, mark the difference between the equipment accuracy evaluation threshold and the equipment accuracy evaluation value as the deviation equipment accuracy evaluation value, and adjust the acoustic wave signal of the detection device according to the deviation equipment accuracy evaluation value.

[0017] Further, the steps of adjusting the acoustic wave signal of the detection device according to the deviation equipment accuracy evaluation value include: obtaining the first deviation threshold and the second deviation threshold from the building detection database; comparing the deviation equipment accuracy evaluation value with the first deviation threshold and the second deviation threshold respectively. If the deviation equipment accuracy evaluation value is less than the first deviation threshold, mark the detection device as a first-level deviation device. If the deviation equipment accuracy evaluation value is greater than or equal to the first deviation threshold and less than the second deviation threshold, mark the detection device as a second-level deviation device. If the deviation equipment accuracy evaluation value is greater than or equal to the second deviation threshold, mark the detection device as a third-level deviation device; adjusting the acoustic wave signal of the detection device according to the deviation level.

[0018] Further, a building engineering quality detection method based on cloud computing is characterized in that: it includes: dividing the underground building project into each detection area according to the regional area, obtaining the underground environment data and the underground environment evaluation threshold of each detection area, and judging whether to enter the interference evaluation module; obtaining the distance between each detection area and the detection equipment, and obtaining the geological structure interference parameter of each detection area according to the distance between each detection area and the detection equipment, and simultaneously monitoring the geological structure data of each detection area for comprehensive analysis to obtain the environmental interference index, and initially adjusting the acoustic signal of the detection equipment according to the environmental interference index; obtaining the incident wave intensity and each echo intensity of the detection equipment, obtaining the reference echo intensity according to the incident wave intensity, and obtaining the detection equipment deviation index according to each echo intensity and the reference echo intensity, and adjusting and feeding back the acoustic signal of the detection equipment according to the detection equipment deviation index and the environmental interference index, and using the adjusted detection equipment to monitor the building engineering quality.

[0019] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0020] 1. By providing a building engineering quality detection system and method based on cloud computing, the present invention can accurately evaluate the environmental interference factors of different detection areas, dynamically adjust the performance of the detection equipment, and thus achieve efficient and accurate monitoring of the building engineering quality, ensuring that the interference factors in the detection process are effectively controlled.

[0021] 2. By initially adjusting the acoustic signal of the detection equipment according to the environmental interference index, the present invention effectively reduces the influence of external environmental interference on the detection result, and thus realizes more accurate building engineering quality monitoring, ensuring that the detection equipment can provide stable and reliable measurement data under various environmental conditions.

[0022] 3. By adjusting and feeding back the acoustic signal of the detection equipment according to the detection equipment deviation index and the environmental interference index, the present invention optimizes the working state of the detection equipment, reduces the influence of environmental interference on the detection accuracy, and thus realizes more accurate and stable building engineering quality monitoring, improving the reliability and accuracy of the detection result. Description of the Drawings

[0023] Figure 1 It is a schematic structural diagram of a building engineering quality detection system based on cloud computing provided by an embodiment of the present application.

[0024] Figure 2 It is a change diagram of the equipment accuracy evaluation value of a building engineering quality detection system based on cloud computing provided by an embodiment of the present application.

[0025] Figure 3Flowchart of the method for detecting the quality of construction projects based on cloud computing provided by the embodiments of the present application. Detailed implementation manners

[0026] By providing a system and method for detecting the quality of construction projects based on cloud computing, the embodiments of the present application solve the problem in the prior art that when using ultrasonic waves to detect the quality of underground construction projects, due to the complex geological structure of the underground space, the signals of the detection equipment are constantly refracted during the data acquisition process, causing the originally concentrated ultrasonic energy to be dispersed in all directions, resulting in a decrease in the signal intensity propagating along the original detection direction, causing signal attenuation, and further affecting the positioning accuracy of the equipment and the reliability of the measurement results. By dividing the underground construction project into each detection area according to the regional area, obtaining the underground environmental data and the underground environmental evaluation threshold of each detection area and determining whether to enter the interference evaluation module; obtaining the distance between each detection area and the detection equipment, and obtaining the geological structure interference parameter of each detection area according to the distance between each detection area and the detection equipment, and simultaneously monitoring the comprehensive analysis of the geological structure data of each detection area to obtain the environmental interference index, and initially adjusting the acoustic signal of the detection equipment according to the environmental interference index; obtaining the incident wave intensity and each echo intensity of the detection equipment, obtaining the reference echo intensity according to the incident wave intensity, and obtaining the detection equipment deviation index according to each echo intensity and the reference echo intensity, and adjusting the feedback of the acoustic signal of the detection equipment according to the detection equipment deviation index and the environmental interference index, and using the adjusted detection equipment to monitor the quality of the construction project, realizing the efficient and accurate monitoring of the quality of the construction project.

[0027] The technical solution in the embodiments of the present application aims to solve the problem that when using ultrasonic waves to detect the quality of underground construction projects, due to the complex geological structure of the underground space, the signals of the detection equipment are constantly refracted during the data acquisition process, causing the originally concentrated ultrasonic energy to be dispersed in all directions, resulting in a decrease in the signal intensity propagating along the original detection direction, causing signal attenuation, and further affecting the positioning accuracy of the equipment and the reliability of the measurement results. The general idea is as follows:

[0028] By dividing the construction project into areas, obtaining the underground environmental data of each area, comparing it with the evaluation threshold, determining whether to enter the interference evaluation module, combining the geological structure interference parameter with the geological structure data, and then evaluating the environmental interference index to initially adjust the acoustic signal of the detection equipment. Further, by monitoring the incident wave and echo intensities, the performance index of the detection equipment is obtained, and combining the performance index and the environmental interference index, the acoustic signal is feedback-adjusted, realizing the efficient and accurate monitoring of the quality of the construction project.

[0029] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0030] As Figure 1 shown, it is a schematic structural diagram of a building engineering quality inspection system based on cloud computing provided by an embodiment of the present application. The building engineering quality inspection system based on cloud computing provided by an embodiment of the present application includes: a humidity evaluation module, an interference evaluation module, a device adjustment module, and a building inspection database; wherein, the humidity evaluation module is used to divide the underground building project into each inspection area according to the regional area, obtain the underground environmental data and underground environmental evaluation threshold of each inspection area and determine whether to enter the interference evaluation module; the interference evaluation module is used to obtain the distance between each inspection area and the inspection device, and obtain the geological structure interference parameter of each inspection area according to the distance between each inspection area and the inspection device, and at the same time monitor and comprehensively analyze the geological structure data of each inspection area to obtain the environmental interference index, and initially adjust the acoustic wave signal of the inspection device according to the environmental interference index; the device adjustment module is used to obtain the incident wave intensity and each echo intensity of the inspection device, and obtain the reference echo intensity corresponding to each incident wave intensity according to the incident wave intensity, wherein the reference echo intensity corresponding to each incident wave intensity of each building material is preset in the building inspection database, and a mapping set is formed between the incident wave intensity of each building material and the reference echo intensity. After inputting the building material and the incident wave intensity into the mapping set, the required reference echo intensity can be obtained, and the inspection device deviation index is obtained according to each echo intensity and the reference echo intensity, and the acoustic wave signal of the inspection device is adjusted and fed back according to the inspection device deviation index and the environmental interference index, and the building engineering quality is monitored by using the adjusted inspection device.

[0031] In this embodiment, through the humidity evaluation module and the interference evaluation module, the system can dynamically analyze the interference of the geological structure and the underground environment on the detection, optimize the acoustic wave signal, and significantly improve the accuracy of the detection results; the device adjustment module dynamically adjusts the acoustic wave signal according to the real-time data to ensure that the device is always in the best working state and adapts to the complex and changeable detection environment; by comprehensively analyzing the geological structure and underground environment data, the system can adapt to various complex geological conditions and ensure the reliability of the detection results.

[0032] In addition, the building inspection database is used to store the relevant data of the building engineering quality inspection system based on cloud computing, including: critical soil humidity, critical air humidity, critical groundwater content, underground humidity evaluation metric influence factor corresponding to soil humidity, first distance threshold, second distance threshold, etc. The data in the building inspection database can be obtained by cooperating with the meteorological department or using its public data interface, or by cooperating with organizations such as the building industry association or standardization organization, or from the data contributed by enterprises such as building material suppliers and building construction enterprises.

[0033] Further, the steps of obtaining the underground environmental data and the underground environmental assessment threshold for each detection area and determining whether to enter the interference assessment module include: The underground environmental data includes soil humidity, air humidity, and groundwater content; obtaining the reference soil humidity, allowable deviation of soil humidity, reference air humidity, allowable deviation of air humidity, reference groundwater content, and allowable deviation of groundwater content from the building detection database, and comprehensively analyzing to obtain the underground humidity assessment metric, which represents the quantitative data of the combined influence degree of soil humidity, air humidity, and groundwater content on the humidity condition in the underground environment; comparing the underground humidity assessment metric with the underground environmental assessment threshold. If the underground humidity assessment metric is greater than or equal to the underground environmental assessment threshold, it indicates that there may be significant interference in the current environment and it is necessary to enter the interference assessment module for further analysis. If the underground humidity assessment metric is less than the underground environmental assessment threshold, it indicates that the current environment is relatively stable with little interference and there is no need to enter the interference assessment module.

[0034] Among them, the obtaining method of the underground humidity assessment metric is as follows:

[0035]

[0036] In the formula, EE1 represents the underground humidity assessment metric, α1 represents the influence factor of the underground humidity assessment metric corresponding to soil humidity, α2 represents the influence factor of the underground humidity assessment metric corresponding to air humidity, α3 represents the influence factor of the underground humidity assessment metric corresponding to groundwater content, R 1i represents the soil humidity of the i-th detection area, R2 represents the reference soil humidity, R0 represents the allowable deviation of soil humidity, F 1i represents the air humidity of the i-th detection area, F2 represents the reference air humidity, F0 represents the allowable deviation of air humidity, A 1i represents the groundwater content of the i-th monitoring area, A0 represents the allowable deviation of groundwater content, e is the natural constant, where i is the number of each detection area, i = 1, 2, 3,..., N, and N is the total number of detection areas.

[0037] α1, α2, and α3 are the influencing factors of the underground humidity assessment metric corresponding to the preset soil humidity, air humidity, and groundwater content in the building detection database respectively. These influencing factors are numerical indicators for measuring the influence of the above-mentioned underground environmental data on the underground humidity assessment metric. Specifically, there is a mapping relation table for each of the soil humidity, air humidity, and groundwater content. The table records each possible value of the underground environmental data and its corresponding influencing factor of the underground humidity assessment metric. These mapping relations can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate the underground humidity assessment metric of a certain construction project, the measured soil humidity, air humidity, and groundwater content can be input into their respective mapping relation tables respectively, and the influencing factors of the underground humidity assessment metric corresponding to these values can be quickly found. The value range of the influencing factor is between 0 and 1.

[0038] In this embodiment, the soil humidity can be directly measured by using a soil humidity sensor; the air humidity can be directly obtained by using a humidity sensor; the groundwater content can be measured by a water level gauge or a groundwater detection sensor. The higher the soil humidity and groundwater content, the more obvious the attenuation of ultrasonic waves in the medium. The air humidity indirectly affects the propagation of ultrasonic waves on the surface by affecting the soil surface humidity. The three are interrelated. For example, the groundwater content directly affects the soil humidity. The higher the groundwater content, the usually greater the soil humidity; the air humidity affects the evaporation rate of the soil surface layer, thus affecting the soil humidity. The underground humidity assessment metric obtained through comprehensive analysis reflects the humidity state of the underground environment, forming a complete humidity distribution system from the surface layer (air humidity) to the deep layer (groundwater content), and it can be judged whether the current environment is suitable for ultrasonic detection. The larger the underground humidity assessment metric, the more it will cause an increase in the conductivity of the soil or rock formation, resulting in an increase in the propagation speed of ultrasonic waves and the attenuation degree of signals. According to the comparison result of the underground humidity assessment metric and the threshold, the system can dynamically decide whether to enter the interference assessment module to avoid unnecessary waste of computing resources.

[0039] Further, the steps of obtaining the geological structure interference parameters for each detection area according to the distance between each detection area and the detection device include: obtaining a first distance threshold and a second distance threshold from the building detection database; comparing the distances between each detection area and the detection device with the first distance threshold and the second distance threshold respectively. If the distance between a certain detection area and the detection device is less than the first distance threshold, it indicates that the signal propagation will not be greatly affected, and then mark this detection area as a slightly affected area. If the distance between a certain detection area and the detection device is greater than or equal to the first distance threshold and less than the second distance threshold, it indicates that the signal propagation may be interfered to a certain extent, and then mark this detection area as a medium affected area. If the distance between a certain detection area and the detection device is greater than or equal to the second threshold, it indicates that the signal propagation is blocked or attenuated severely, which may seriously affect the detection result, and then mark this detection area as a severely affected area. Obtain the geological structure interference parameters for each detection area according to the matching of the influence levels of each detection area, and obtain the mapping set of geological structure interference parameters corresponding to the influence levels of each detection area from the building detection database, where this mapping set is obtained by corresponding each influence level of each detection area with each geological structure interference parameter one by one. Input the influence levels of each detection area into the mapping set to obtain the geological structure interference parameters for each detection area.

[0040] In this embodiment, the geological structure interference parameter is a quantitative value used to evaluate the interference effect of the distance between each detection area and the detection device on the detection device. The first distance threshold is a relatively close range from the detection device to the detection area. In this range, the signal is less interfered and may only be slightly affected, which is applicable to the area where the signal propagation is relatively smooth. The second distance threshold is a relatively far distance range. Generally, within this range, the signal will be greatly interfered or attenuated, belonging to the area with relatively serious influence. By setting different distance thresholds, the influence degree of interference in different areas can be effectively divided. Using the geological structure interference parameters obtained by matching the influence levels of each detection area, the interference situation of each detection area can be evaluated more accurately.

[0041] Further, the steps of monitoring the geological structure data of each detection area for comprehensive analysis to obtain the environmental interference index include: the geological structure data includes crack depth, crack length, and crack density; obtaining critical geological structure data, critical underground humidity assessment metrics, and critical geological structure interference index from the building detection database, where the critical geological structure data includes critical crack depth, critical crack length, and critical crack density; comprehensively analyzing the geological structure data of each detection area, the geological structure interference parameters of each detection area, and the critical geological structure data to obtain the geological structure interference index of each detection area, and the geological structure interference index represents the quantitative data of the degree of influence of the geological structure data and the geological structure interference parameters on the environment of the monitoring area; comprehensively analyzing the underground humidity assessment metrics, the geological structure interference index of each detection area, the critical underground humidity assessment metrics, and the critical geological structure interference index to obtain the environmental interference index, and the environmental interference index represents the quantitative data of the degree of influence of the underground humidity assessment metrics and the geological structure interference index on the detection quality of the underground construction project.

[0042] Among them, the acquisition method of the environmental interference index is as follows:

[0043]

[0044] In the formula, EI1 represents the environmental interference index, Pr 1i represents the geological structure interference index of the i-th detection area, α4 represents the influence factor of the geological structure interference index corresponding to the crack depth, α5 represents the influence factor of the geological structure interference index corresponding to the crack length, α6 represents the influence factor of the geological structure interference index corresponding to the crack density, W 1ij represents the j-th crack depth of the i-th detection area, W0 represents the critical crack depth, L 1ij represents the j-th crack length of the i-th detection area, L0 represents the critical crack length, S 1i represents the crack density of the i-th detection area, S0 represents the critical crack density, Pr 2i represents the geological structure interference parameter of the i-th detection area, where j is the number of each crack, j = 1, 2, 3..., M, M is the total number of cracks, α7 represents the influence factor of the environmental interference index corresponding to the geological structure interference index, α8 represents the influence factor of the environmental interference index corresponding to the underground humidity assessment metrics, EE1 represents the underground humidity assessment metrics, and EE0 represents the critical underground humidity assessment metrics.

[0045] α4, α5, and α6 are the influence factors of the geological structure interference index corresponding to the preset crack depth, crack length, and crack density in the building detection database respectively. These influence factors are numerical indicators for measuring the influence of the above geological structure data on the geological structure interference index. Specifically, there is a mapping relationship table for each of the crack depth, crack length, and crack density. The table records each possible parameter value and its corresponding influence factor of the geological structure interference index. These mapping relationships can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate the geological structure interference index of a certain detection area, the measured crack depth, crack length, and crack density can be input into their respective corresponding mapping relationship tables respectively, and the influence factors of the geological structure interference index corresponding to these values can be quickly found. The value range of the influence factor is between 0 and 1.

[0046] α7 and α8 are the influence factors of the environmental interference index corresponding to the preset geological structure interference index and the underground humidity assessment measure in the building detection database respectively. These influence factors are numerical indicators for measuring the influence of the above parameters on the environmental interference index. Specifically, there is a mapping relationship table for each of the geological structure interference index and the underground humidity assessment measure. The table records each possible parameter value and its corresponding influence factor of the environmental interference index. These mapping relationships can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate the environmental interference index of a certain construction project, the measured geological structure interference index and the underground humidity assessment measure can be input into their respective corresponding mapping relationship tables respectively, and the influence factors of the environmental interference index corresponding to these values can be quickly found. The value range of the influence factor is between 0 and 1.

[0047] In this embodiment, a crack is a broken or fractured part in a rock or soil structure. The crack depth represents the vertical distance from the crack surface to the crack bottom, and the crack length represents the horizontal extension distance of the crack. The crack density represents the number of cracks within a single detection area. Geological structure data can be obtained by directly measuring the crack depth using drilling equipment or by detecting with ground penetrating radar, etc. The three are interrelated. For example, cracks with a greater depth are usually accompanied by a longer crack length, which has a more significant impact on the stability of the geological structure. Areas with a high crack density are usually accompanied by more shallow cracks, and the crack depth and length are not very large. The increase in crack depth and length will cause more reflections, refractions, and scatterings of ultrasonic signals during propagation, resulting in increased signal attenuation. By comprehensively analyzing the obtained geological structure interference index, the interference intensity of the geological structure in the current area on ultrasonic detection can be evaluated. The greater the geological structure interference index, the higher the complexity of the propagation path of the ultrasonic signal, which may cause refraction or reflection of the signal during propagation, further increasing signal attenuation and distortion. In addition, there is an interaction between the underground humidity assessment metric and the geological structure interference index. Areas with too high humidity may cause an increase in the conductivity of the soil or rock layer, and ultrasonic signals will be more obstructed during propagation, resulting in increased attenuation. At the same time, complex geological structures (such as cracks and faults) may change the propagation path of the signal, leading to signal distortion or multiple attenuations, thereby affecting the detection results. By combining the underground humidity assessment metric and the geological structure interference index, the attenuation of ultrasonic signals in underground construction projects can be predicted more accurately, and at the same time, it helps to reveal the complex influence of the underground environment (humidity and geological structure) on the propagation of ultrasonic signals, making the application of ultrasonic detection in engineering quality monitoring more precise.

[0048] Further, the steps for initially adjusting the acoustic signal of the detection device according to the environmental interference index include: obtaining the environmental interference index threshold from the building detection database; comparing the environmental interference index with the environmental interference index threshold. If the environmental interference index is less than the environmental interference index threshold, no additional processing is performed. If the environmental interference index is greater than or equal to the environmental interference index threshold, the noise reduction function of the detection device is activated.

[0049] In this embodiment, the environmental interference index threshold is a critical value for evaluating the environmental interference situation. When the environmental interference index exceeds the environmental interference index threshold, it may cause the signals detected by the device to be inaccurate, and the device automatically activates the noise reduction function (including methods such as filtering, gain compensation, reflected wave identification and processing, inversion algorithms, and wavelet analysis to reduce noise, enhance, extract features, and analyze the signals), reducing the influence of external interference. By automatically adjusting the working mode of the device according to the environmental interference index, the adaptability of the device in different environments can be greatly improved, ensuring the long-term stable operation of the detection device.

[0050] Further, the steps of obtaining the detection device deviation index according to each echo intensity and referring to each echo intensity include: the echoes include surface echoes, bottom echoes, and reflection echoes; marking the absolute value of the difference between the surface echo intensity and the reference surface echo intensity as the deviation surface echo intensity; marking the absolute value of the difference between the bottom echo intensity and the reference bottom echo intensity as the deviation bottom echo intensity; marking the absolute value of the difference between the reflection echo intensity and the reference reflection echo intensity as the deviation reflection echo intensity; comprehensively analyzing the deviation surface echo intensity, the deviation bottom echo intensity, the deviation reflection echo intensity, and referring to each echo intensity to obtain the detection device deviation index, and the detection device deviation index represents the quantification data of the influence degree of the surface echo, the bottom echo, and the reflection echo on the detection accuracy of the echo signal.

[0051] Among them, the obtaining method of the detection device deviation index is as follows:

[0052]

[0053] In the formula, WQ1 represents the detection device deviation index, β1 represents the detection device deviation index influence factor corresponding to the deviation surface echo intensity, β2 represents the detection device deviation index influence factor corresponding to the deviation bottom echo intensity, β3 represents the detection device deviation index influence factor corresponding to the deviation reflection echo intensity, U1 represents the deviation surface echo intensity, U0 represents the reference surface echo intensity, B1 represents the deviation bottom echo intensity, B0 represents the reference bottom echo intensity, T1 represents the deviation reflection echo intensity, and T0 represents the reference reflection echo intensity.

[0054] β1, β2, and β3 are respectively the detection device deviation index influence factors corresponding to the preset deviation surface echo intensity, deviation bottom echo intensity, and deviation reflection echo intensity in the building detection database, and these influence factors are numerical indexes for measuring the influence size of the above echo intensity data on the detection device deviation index. Specifically, there is a mapping relation table for each of the deviation surface echo intensity, deviation bottom echo intensity, and deviation reflection echo intensity, and the table records each possible parameter value and its corresponding detection device deviation index influence factor, and these mapping relations can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate a certain detection device deviation index, the measured deviation surface echo intensity, deviation bottom echo intensity, and deviation reflection echo intensity can be respectively input into their corresponding mapping relation tables, and the detection device deviation index influence factors corresponding to these values can be quickly found, where the value range of the influence factor is between 0 and 1.

[0055] In this embodiment, the surface echo intensity refers to the signal intensity of the signal reflected from the surface of a certain known material when the signal emitted by the ultrasonic probe encounters it. The bottom echo intensity refers to the signal intensity of the signal reflected after the ultrasonic wave passes through a certain material and encounters the bottom surface of a certain known material. The reflected echo refers to the signal intensity of the signal that returns to the probe after refraction, reflection, or scattering occurs inside a certain known material in a construction project. All of them can be directly obtained by the detection device. Through comprehensive analysis, the deviation index of the detection device comprehensively reflects the difference between the actual echo intensity and the expected echo intensity, and can be used to evaluate the influence parameters of the detection device after being affected by environmental interference.

[0056] Further, the steps of adjusting and feeding back the acoustic wave signal of the detection device according to the detection device deviation index and the environmental interference index include: obtaining the critical detection device deviation index and the critical environmental interference index from the building detection database; comprehensively analyzing the detection device deviation index, the environmental interference index, the critical detection device deviation index, and the critical environmental interference index to obtain the device accuracy evaluation value. The device accuracy evaluation value represents the quantitative data of the influence degree of the detection device deviation index and the environmental interference index on the accuracy of the device monitoring result, and adjusts the acoustic wave signal of the detection device according to the device accuracy evaluation value.

[0057] Among them, the obtaining method of the device accuracy evaluation value is as follows:

[0058]

[0059] In the formula, WS represents the device accuracy evaluation value, β4 represents the device accuracy evaluation influence factor corresponding to the detection device deviation index, β5 represents the device accuracy evaluation influence factor corresponding to the environmental interference index, WQ1 represents the detection device deviation index, WQ0 represents the critical detection device deviation index, EI1 represents the environmental interference index, and EI0 represents the critical environmental interference index.

[0060] β4 and β5 are respectively the device accuracy evaluation influence factors corresponding to the detection device deviation index and the environmental interference index preset in the building detection database. These influence factors are numerical indicators for measuring the influence degree of the above parameters on the device accuracy evaluation value. Specifically, there is a mapping relationship table for each of the detection device deviation index and the environmental interference index. The table records each possible parameter value and its corresponding device accuracy evaluation influence factor. These mapping relationships can be one-to-one or many-to-one. For example, in practical applications, when it is necessary to evaluate the accuracy of a certain device, the measured detection device deviation index and environmental interference index can be respectively input into their corresponding mapping relationship tables, and the device accuracy evaluation influence factors corresponding to these values can be quickly found. The value range of the influence factor is between 0 and 1.

[0061] In this embodiment, the device deviation index reflects the accuracy and deviation of the device itself. However, these deviations may be affected by environmental factors. The environmental interference index reflects the degree of influence of the surrounding environment on the performance of the device, especially the changes in interference signals or geological structures. The device accuracy evaluation value obtained through comprehensive analysis can effectively indicate the actual detection ability of the device under specific environmental conditions, and then can accurately monitor the performance and accuracy of the ultrasonic device, while reducing the errors caused by environmental changes and improving the reliability of building engineering quality inspection.

[0062] Set the device accuracy evaluation influence factor corresponding to the device deviation index of the detection device to 0.6, the device accuracy evaluation influence factor corresponding to the environmental interference index to 0.4, the device deviation index of the detection device to 1.2, the critical device deviation index of the detection device to 1, and the critical environmental interference index to 1.5. Calculate the device accuracy evaluation value when the environmental interference index is continuously increasing. As shown in Table 1, which is the data table of the device accuracy evaluation value of the building engineering quality inspection system based on cloud computing.

[0063] Table 1 Data Table of Device Accuracy Evaluation Value of Building Engineering Quality Inspection System Based on Cloud Computing

[0064] Number <![CDATA[EI1]]> WS 1 1.3 0.484 2 1.4 0.478 3 1.5 0.472 4 1.6 0.466 5 1.7 0.460

[0065] As Figure 2 shown, it is the change diagram of the device accuracy evaluation value of the building engineering quality inspection system based on cloud computing provided by the embodiment of the present application. As shown in Table 1 and Figure 2 it can be seen that when the device accuracy evaluation influence factor corresponding to the device deviation index of the detection device, the device accuracy evaluation influence factor corresponding to the environmental interference index, the device deviation index of the detection device, the critical device deviation index of the detection device, and the critical environmental interference index remain unchanged, and the environmental interference index is continuously increasing, the device accuracy evaluation value is continuously decreasing.

[0066] Furthermore, the steps of adjusting the acoustic signal of the detection device according to the device accuracy evaluation value include: obtaining the device accuracy evaluation threshold from the building detection database; comparing the device accuracy evaluation value with the device accuracy evaluation threshold. If the device accuracy evaluation value is greater than or equal to the device accuracy evaluation threshold, directly use the detection device for building engineering quality inspection. If the device accuracy evaluation value is less than the device accuracy evaluation threshold, mark the difference between the device accuracy evaluation threshold and the device accuracy evaluation value as the deviation device accuracy evaluation value, and adjust the acoustic signal of the detection device according to the deviation device accuracy evaluation value.

[0067] In this embodiment, the deviation device accuracy evaluation value refers to the difference between the device accuracy evaluation value and the device accuracy evaluation threshold, and the device accuracy evaluation threshold is the minimum accuracy requirement that the device must meet during building detection. By comparing the device accuracy evaluation value with the evaluation threshold, it can be determined whether the current device has sufficient accuracy for actual detection. And by adjusting the acoustic signal of the detection device according to the deviation device accuracy evaluation value, it can be ensured that the measurement result of the device is within a reasonable range, thereby improving the accuracy of the detection.

[0068] Further, the steps of adjusting the acoustic signal of the detection device according to the deviation device accuracy evaluation value include: obtaining a first deviation threshold and a second deviation threshold from the building detection database; comparing the deviation device accuracy evaluation value with the first deviation threshold and the second deviation threshold respectively. If the deviation device accuracy evaluation value is less than the first deviation threshold, the detection device is marked as a first-level deviation device. If the deviation device accuracy evaluation value is greater than or equal to the first deviation threshold and less than the second deviation threshold, the detection device is marked as a second-level deviation device. If the deviation device accuracy evaluation value is greater than or equal to the second deviation threshold, the detection device is marked as a third-level deviation device; adjusting the acoustic signal of the detection device according to the deviation level.

[0069] In this embodiment, by comparing the accuracy evaluation value of the device with the first deviation threshold and the second deviation threshold, the health status of the device can be effectively classified, ensuring appropriate adjustment strategies are adopted for devices with different deviation levels. When the deviation level of the detected device is level one, the operating parameters of the device are automatically adjusted. For example, the amplification factor is dynamically adjusted according to the current signal strength. For instance, when the target signal strength is greater than the current signal strength, the ratio of the difference between the target signal strength and the current signal strength to the current signal strength is the amplification factor that needs to be increased, and the adjustment is made according to this ratio; according to the data fluctuation situation, the sampling frequency is dynamically adjusted to avoid over-dense or over-sparse data. For example, when the data fluctuation is greater than the data fluctuation threshold, the sampling frequency is increased by a preset multiple to capture details, etc. At the same time, linear regression or Kalman filtering algorithms are used to predict and compensate for errors; when the deviation level is level two, more complex signal processing algorithms (such as wavelet transform, Fourier transform) are used to filter noise. At the same time, by increasing the number of data verification times (such as CRC verification) and the correction frequency, the reliability of the data is ensured, and weighted average method or Bayesian estimation method is used to fuse multi-sensor data; when the deviation level is level three, the system sends an alarm to the operator. The alarm information includes the specific fault type of the device (by comparing the current state parameters with the preset threshold to determine whether it exceeds the normal range. For example, if the signal-to-noise ratio is less than the preset threshold, it is determined as a signal noise excessive fault), the difference between the deviation device accuracy evaluation value and the second deviation threshold, and the basic information of the device (such as device number, device type, device location, etc.). Before the device is repaired, the manual monitoring frequency is increased to ensure the controllability of the device operating state.

[0070] Further, a building engineering quality detection method based on cloud computing, characterized in that it includes: dividing the underground building engineering into each detection area according to the regional area, obtaining the underground environment data and the underground environment evaluation threshold of each detection area and determining whether to enter the interference evaluation module; obtaining the distance between each detection area and the detection device, and obtaining the geological structure interference parameter of each detection area according to the distance between each detection area and the detection device. At the same time, the geological structure data of each detection area is monitored and comprehensively analyzed to obtain the environmental interference index, and the acoustic wave signal of the detection device is initially adjusted according to the environmental interference index; obtaining the incident wave intensity and each echo intensity of the detection device, obtaining the reference for each echo intensity according to the incident wave intensity, and obtaining the detection device deviation index according to each echo intensity and the reference for each echo intensity, and adjusting and feeding back the acoustic wave signal of the detection device according to the detection device deviation index and the environmental interference index, and using the adjusted detection device to monitor the building engineering quality.

[0071] In summary, in this embodiment, by dividing the construction project into regions, obtaining the underground environmental data of each region, comparing it with the evaluation threshold, determining whether to enter the interference evaluation module, combining the geological structure interference parameters with the geological structure data, and then evaluating the environmental interference index to initially adjust the acoustic signal of the detection device. Further, by monitoring the incident wave and echo intensities, the performance indicators of the detection device are obtained, and combining the performance indicators and the environmental interference index, the acoustic signal is feedback-adjusted, achieving efficient and accurate monitoring of the construction project quality.

[0072] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, systems, methods, or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0073] The present invention is described with reference to the flowcharts and / or block diagrams of systems, methods, devices (systems and methods), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or a plurality of flows and / or blocks

[0074] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the flows Figure 1 or a plurality of flows and / or blocks

[0075] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are performed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide means for implementing the functions specified in Figure 1 one or more of the flows Figure 1Steps of the functions specified in one or more boxes.

[0076] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0077] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A building engineering quality inspection system based on cloud computing, characterized in that, Including: A humidity assessment module, an interference assessment module, a device adjustment module, and a building detection database; Among them, the humidity assessment module is used to divide the underground construction project into each detection area according to the regional area, obtain the underground environment data and the underground environment assessment threshold of each detection area, and determine whether to enter the interference assessment module; The interference assessment module is used to obtain the distance between each detection area and the detection device, obtain the geological structure interference parameter of each detection area according to the distance between each detection area and the detection device, monitor the comprehensive analysis of the geological structure data of each detection area to obtain the environmental interference index, and initially adjust the acoustic signal of the detection device according to the environmental interference index; The device adjustment module is used to obtain the incident wave intensity and each echo intensity of the detection device, obtain the reference for each echo intensity according to the incident wave intensity, obtain the detection device deviation index according to each echo intensity and the reference for each echo intensity, adjust and feedback the acoustic signal of the detection device according to the detection device deviation index and the environmental interference index, and use the adjusted detection device to monitor the quality of the construction project.

2. The cloud computing-based construction project quality inspection system according to claim 1, characterized in that: The steps of obtaining the underground environment data and the underground environment assessment threshold of each detection area and determining whether to enter the interference assessment module include: The underground environment data includes soil humidity, air humidity, and groundwater content; Obtain the reference soil humidity, allowable deviation soil humidity, reference air humidity, allowable deviation air humidity, reference groundwater content, and allowable deviation groundwater content from the building detection database, and comprehensively analyze to obtain the underground humidity assessment metric. The underground humidity assessment metric represents the quantitative data of the degree of influence of soil humidity, air humidity, and groundwater content on the humidity condition in the underground environment; Compare the underground humidity assessment metric with the underground environment assessment threshold. If the underground humidity assessment metric is greater than or equal to the underground environment assessment threshold, enter the interference assessment module.

3. The cloud computing-based construction project quality inspection system according to claim 1, wherein, The steps of obtaining the geological structure interference parameter of each detection area according to the distance between each detection area and the detection device include: Obtain the first distance threshold and the second distance threshold from the building detection database; Compare the distance between each detection area and the detection device with the first distance threshold and the second distance threshold respectively. If the distance between a certain detection area and the detection device is less than the first distance threshold, mark this detection area as a slightly affected area. If the distance between a certain detection area and the detection device is greater than or equal to the first distance threshold and less than the second distance threshold, mark this detection area as a moderately affected area. If the distance between a certain detection area and the detection device is greater than or equal to the second threshold, mark this detection area as a severely affected area, and match the geological structure interference parameter of each detection area according to the influence level of each detection area.

4. The cloud computing-based building engineering quality inspection system according to claim 1, characterized in that: The steps of monitoring the comprehensive analysis of the geological structure data of each detection area to obtain the environmental interference index include: The geological structure data includes crack depth, crack length, and crack density; Obtain critical geological structure data, critical underground humidity assessment metrics, and critical geological structure interference indices from the building detection database. The critical geological structure data includes critical crack depth, critical crack length, and critical crack density; Comprehensively analyze the geological structure data of each detection area, the geological structure interference parameters of each detection area, and the critical geological structure data to obtain the geological structure interference index of each detection area. The geological structure interference index represents the quantitative data of the degree of influence of the geological structure data and the geological structure interference parameters on the environment of the monitoring area; Comprehensively analyze the underground humidity assessment metrics, the geological structure interference indices of each detection area, the critical underground humidity assessment metrics, and the critical geological structure interference indices to obtain the environmental interference index. The environmental interference index represents the quantitative data of the degree of influence of the underground humidity assessment metrics and the geological structure interference index on the detection quality of the underground construction project; 5. The cloud computing-based building engineering quality inspection system according to claim 4, characterized in that: The step of initially adjusting the acoustic signal of the detection device according to the environmental interference index includes: Obtain the environmental interference index threshold from the building detection database; Compare the environmental interference index with the environmental interference index threshold. If the environmental interference index is less than the environmental interference index threshold, no additional processing is performed. If the environmental interference index is greater than or equal to the environmental interference index threshold, activate the noise reduction function of the detection device.

6. The cloud computing-based construction project quality inspection system according to claim 1, wherein: The step of obtaining the detection device deviation index according to each echo intensity and referring to each echo intensity includes: The echoes include surface echoes, bottom echoes, and reflected echoes; Mark the absolute value of the difference between the surface echo intensity and the reference surface echo intensity as the deviation surface echo intensity; Mark the absolute value of the difference between the bottom echo intensity and the reference bottom echo intensity as the deviation bottom echo intensity; Mark the absolute value of the difference between the reflected echo intensity and the reference reflected echo intensity as the deviation reflected echo intensity; Comprehensively analyze the deviation surface echo intensity, the deviation bottom echo intensity, the deviation reflected echo intensity, and the reference echo intensities to obtain the detection device deviation index. The detection device deviation index represents the quantitative data of the degree of influence of the surface echo, the bottom echo, and the reflected echo on the detection accuracy of the echo signal; 7. The cloud computing-based building engineering quality inspection system according to claim 1, characterized in that: The step of adjusting the feedback of the acoustic signal of the detection device according to the detection device deviation index and the environmental interference index includes: Obtain the critical detection device deviation index and the critical environmental interference index from the building detection database; Comprehensively analyze the detection device deviation index, the environmental interference index, the critical detection device deviation index, and the critical environmental interference index to obtain the device accuracy evaluation value. The device accuracy evaluation value represents the quantitative data of the degree of influence of the detection device deviation index and the environmental interference index on the accuracy of the device monitoring result, and adjust the acoustic signal of the detection device according to the device accuracy evaluation value.

8. The cloud computing-based building engineering quality inspection system according to claim 7, characterized in that: The step of adjusting the acoustic signal of the detection device according to the device accuracy evaluation value includes: Obtain the device accuracy evaluation threshold from the building detection database; Compare the device accuracy evaluation value with the device accuracy evaluation threshold. If the device accuracy evaluation value is greater than or equal to the device accuracy evaluation threshold, directly use the detection device to conduct building engineering quality inspection. If the device accuracy evaluation value is less than the device accuracy evaluation threshold, mark the difference between the device accuracy evaluation threshold and the device accuracy evaluation value as the deviation device accuracy evaluation value, and adjust the acoustic signal of the detection device according to the deviation device accuracy evaluation value.

9. The cloud computing-based building engineering quality inspection system according to claim 8, wherein: The steps of adjusting the acoustic signal of the detection device according to the deviation device accuracy evaluation value include: Obtain the first deviation threshold and the second deviation threshold from the building detection database; Compare the deviation device accuracy evaluation value with the first deviation threshold and the second deviation threshold respectively. If the deviation device accuracy evaluation value is less than the first deviation threshold, mark the detection device as a first-level deviation device. If the deviation device accuracy evaluation value is greater than or equal to the first deviation threshold and less than the second deviation threshold, mark the detection device as a second-level deviation device. If the deviation device accuracy evaluation value is greater than or equal to the second deviation threshold, mark the detection device as a third-level deviation device; Adjust the acoustic signal of the detection device according to the deviation level.

10. A method for detecting the quality of construction projects based on cloud computing, which is applied to the system for detecting the quality of construction projects based on cloud computing according to any one of claims 1-9, characterized in that : including: Divide the underground construction project into each detection area according to the regional area, obtain the underground environment data and the underground environment evaluation threshold of each detection area, and judge whether to enter the interference evaluation module; Obtain the distance between each detection area and the detection device, obtain the geological structure interference parameter of each detection area according to the distance between each detection area and the detection device, simultaneously monitor the geological structure data of each detection area for comprehensive analysis to obtain the environmental interference index, and initially adjust the acoustic signal of the detection device according to the environmental interference index; Obtain the incident wave intensity and each echo intensity of the detection device, obtain the reference for each echo intensity according to the incident wave intensity, obtain the detection device deviation index according to each echo intensity and the reference for each echo intensity, conduct adjustment feedback on the acoustic signal of the detection device according to the detection device deviation index and the environmental interference index, and use the adjusted detection device to monitor the building engineering quality.

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