Building Quality and Safety Management Method Based on Big Data

Abstract

The present invention discloses a building quality and safety management method based on big data. The present invention relates to the technical field of building management. By integrating a variety of sensors and data analysis means, the risks during the transportation of glass curtain walls are monitored and evaluated in real time. Through the collection and analysis of pressure, displacement, and vibration data, this method can timely identify risks such as unstable installation, uneven pressure, and excessive vibration that may occur during transportation. The comprehensive evaluation of various risk data provides a multi-level risk level detection and classification mechanism. According to the transportation risk assessment value of the glass curtain wall, different levels of detection measures are taken to ensure that high-risk glass curtain walls are subject to more stringent detection and management. Overall, it can achieve precise management of the transportation process of glass curtain walls, improve the level of building quality and safety guarantee, reduce risks and losses, and optimize the safety and efficiency of the construction and transportation links.

Description

Technical Field

[0001] The present invention relates to the technical field of building management, and specifically to a building quality and safety management method based on big data. Background Art

[0002] A Chinese invention with the publication number CN118657446A discloses a building engineering quality and safety tracking management system based on big data, including: a building engineering information acquisition module, a warehouse material detection module, a warehouse material analysis module, a construction material detection module, a completed building detection module, a material quality and safety analysis module, a quality and safety tracking management terminal, and a database; by comprehensively analyzing the accumulated materials, construction materials, and completed materials of a building project, the quality and safety of the engineering materials corresponding to the building project are analyzed, ensuring the engineering quality of the building project to the greatest extent, reducing material defects and problems during construction, thereby extending the service life of the building, reducing maintenance and repair costs, and improving the sustainable development ability.

[0003] In building engineering, as an exterior building material, glass curtain walls are important and are widely used in modern high-rise buildings. Due to the large weight, large volume, and fragility of glass curtain walls, the safety of glass curtain walls during transportation and installation has always been an important issue in the industry. With the continuous development of big data, the Internet of Things, and sensing technologies, more and more construction industries have begun to explore how to use advanced technologies to improve the safety and efficiency during transportation and installation. However, most of the existing technologies focus on the monitoring of a single link, lacking effective management, detection, and evaluation after the transportation process of glass curtain walls, and also lacking comprehensive monitoring and evaluation of the safety risks during the transportation process of glass curtain walls. Summary of the Invention

[0004] Aiming at the deficiencies of the existing technology, the present invention provides a building quality and safety management method based on big data, which solves the problems in the background art.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A building quality and safety management method based on big data, including:

[0006] Step 1: Place the glass curtain wall to be transported on the mounting rack, mark the installation position of the mounting rack, and at the same time number and identify the glass curtain wall to be transported. Record the storage of each numbered and identified glass curtain wall on the corresponding installation position of the mounting rack.

[0007] Step 2: During transportation, collect pressure data of the glass curtain wall placed on the mounting rack, and evaluate the fixing risk situation of the glass curtain wall during transportation by analyzing the pressure data to determine the fixing risk impact value.

[0008] The content of determining the fixed risk impact value includes:

[0009] BS1: For the glass curtain walls placed on the mounting brackets, all are regarded as target glass curtain walls, and the fixed risk impact value is determined through the following steps;

[0010] BS2: Obtain the pressure value of each current sensor on the target glass curtain wall, and mark it as , and , where represents the th sensor, represents the current moment, represents the total number of sensors on the target glass curtain wall, and then determine the pressure distribution of the target glass curtain wall at the current moment , denoted as : ;

[0011] BS3: Then, unify the pressure values of different sensors to the same dimension, and perform normalization processing on each pressure value to obtain the normalized pressure distribution data : ;

[0012] BS4: Set within the time window , determine the pressure fluctuation degree of the contact area between the glass curtain wall and the mounting bracket;

[0013] BS5: Then calculate the change rate of the pressure data through the following formula :

[0014] ;

[0015] Wherein, is the acquisition time interval, and ;

[0016] Statistically analyze the change rates of all sensors on the target curtain wall, and obtain the total number of pressure mutations through the following:

[0017] ;

[0018] Wherein, is an indicator function, which takes the value of 1 when the pressure change rate exceeds the threshold, and 0 otherwise, is the preset threshold;

[0019] BS6: According to the pressure fluctuation degree and the total number of pressure mutations , determine the fixed risk impact value at the current moment ;

[0020] Step 3: Collect the displacement data of the glass curtain wall placed on the mounting rack, and evaluate the displacement risk situation of the glass curtain wall during transportation by analyzing the displacement data to determine the displacement risk impact value;

[0021] Step 4: Collect the vibration data of the mounting rack where the glass curtain wall is placed on the mounting rack, and evaluate the vibration risk situation of the glass curtain wall during transportation by analyzing the vibration data to determine the vibration risk impact value;

[0022] Step 5: Conduct a transportation risk assessment based on the fixed risk impact value, displacement risk impact value of each glass curtain wall placed on the mounting rack, and the vibration risk value of the glass curtain wall during transportation evaluated by analyzing the vibration data to determine the transportation risk assessment value of each glass curtain wall, and classify the inspection level of each glass curtain wall according to the transportation risk assessment value.

[0023] As a further solution of the present invention: In the said Step 1, the specific method of storing and recording on the installation position of the corresponding mounting rack where each numbered and identified glass curtain wall is placed is as follows:

[0024] AS1: Mark the installation position of the mounting rack as , where , is the total number of installation positions of the mounting rack for this transportation;

[0025] AS2: Number and identify the glass curtain walls to be transported as , where , is the total number of glass curtain walls to be transported in this time, and ;

[0026] AS3: Then store and record on the installation position of the corresponding mounting rack where each numbered and identified glass curtain wall is placed.

[0027] As a further solution of the present invention: After Step BS6 in the said Step 2, it further includes:

[0028] BS7: Obtain the total time of the target glass curtain wall during transportation, denoted as , and determine pressure data collection times by using the formula , and at the same time obtain the fixed risk impact value at each collection time through Steps BS2 - BS6, where ; Determine the fixed risk impact value of the target glass curtain wall during transportation through the following formula:

[0029] ;

[0030] Among them, is the risk impact factor.

[0031] As a further solution of the present invention: in the third step, the displacement data of the glass curtain wall placed on the mounting frame is collected, and the displacement risk situation of the glass curtain wall during transportation is evaluated by analyzing the pressure data. The specific method for determining the displacement risk impact value is as follows:

[0032] CS1: Regarding the glass curtain wall placed on the mounting frame as the target glass curtain wall, the displacement risk impact value is determined through the following steps;

[0033] CS2: Through the set acquisition time interval One data acquisition of the relative displacement between the target glass curtain wall and the mounting frame is performed, and it is marked as ; Obtain the total time of the target glass curtain wall during transportation, denoted as , by using the formula , determine displacement data acquisition times, where ;

[0034] Then, through the formula determine the total displacement amount of the target glass curtain wall during transportation;

[0035] CS3: Obtain the maximum relative displacement between the target glass curtain wall and the mounting frame among the displacement data acquisition times, denoted as

[0036] ; Combining the total displacement amount of the target glass curtain wall during transportation, determine the displacement risk impact value of the target glass curtain wall during transportation through the following formula :

[0037] ;

[0038] Among them, and are the weight coefficients.

[0039] As a further solution of the present invention: in the fourth step, the vibration data of the mounting frame where the glass curtain wall is placed on the mounting frame is collected, and the vibration risk situation of the glass curtain wall during transportation is evaluated by analyzing the vibration data. The specific method for determining the vibration risk impact value is as follows:

[0040] DS1: Set the acquisition time interval to Collect the vibration data x(t) at each time point during transportation, and perform denoising processing on the original vibration data x(t); then use the moving average or exponential smoothing method to smooth the data, where t represents the current moment;

[0041] DS2: Then determine a time window W, and calculate the variance of the vibration signal within the time window W. The time window W means that z times of vibration data are collected within this time window W. The variance of the vibration signal within the time window W is reflected by the following formula:

[0042] ;

[0043] Among them, represents the variance of the vibration signal within the time window W, represents the b-th collected vibration data among the z times of vibration data, and , is the mean value of the vibration data within the time window W:

[0044] ;

[0045] DS3: Then calculate the vibration change rate of the vibration data within the time window W through the following formula :

[0046] ;

[0047] Among them, represents the vibration data at the previous moment of the current moment within the time window W;

[0048] Obtain the total number z of the collected vibration data in the time window W, obtain the preset limit threshold , and count all the change rates in the time window W that exceed the preset limit threshold through the following formula

[0049] ;

[0050] Among them, is the indicator function, which takes the value of 1 when the vibration change rate exceeds the threshold, and 0 otherwise;

[0051] DS4: Obtain the variance of the vibration signal within the time window W and the number of all change rates in the time window W that exceed the preset limit threshold , and determine the vibration risk impact value within the time window W through the following formula

[0052] ;

[0053] Among them, and are weight coefficients;

[0054] DS5: Obtain the total duration of the glass curtain wall during transportation, denoted as ;

[0055] Then, use the formula to determine the total number of time windows of the glass curtain wall during transportation , and through steps DS1 - DS4, determine vibration risk impact values corresponding to the time windows, and mark them as , among which, ; At the same time, determine the vibration risk impact value through the following formula ;

[0056] ;

[0057] Among them, is the weight coefficient.

[0058] As a further solution of the present invention: In the fifth step, the specific method for determining the transportation risk assessment value of each glass curtain wall according to the fixed risk impact value, displacement risk impact value of each glass curtain wall placed on the mounting rack, and the vibration risk value of the glass curtain wall during transportation by analyzing vibration data is as follows:

[0059] Regard each glass curtain wall placed on the mounting rack as the target glass curtain wall to determine its transportation risk assessment value, obtain the fixed risk impact value, displacement risk impact value of the target glass curtain wall, and the vibration risk value of the glass curtain wall during transportation by analyzing vibration data to determine the transportation risk assessment value. Specifically, the transportation risk assessment value of the target glass curtain wall is determined through the following formula :

[0060] ;

[0061] Among them, , and are weight coefficients, is the fixed risk impact value, is the displacement risk impact value, is the vibration risk impact value.

[0062] As a further solution of the present invention: The specific method for classifying the detection level of each glass curtain wall according to the transportation risk assessment value is as follows:

[0063] Based on the transportation risk assessment value of the target glass curtain wall Conduct inspection level classification:

[0064] If , it indicates that the transportation risk of the target glass curtain wall is relatively small, and primary inspection is adopted;

[0065] If , it indicates that the transportation risk of the target glass curtain wall is relatively large, and secondary inspection is adopted;

[0066] If , it indicates that the transportation risk of the target glass curtain wall is on the high side, and tertiary inspection is adopted;

[0067] Among them, , are preset values, and .

[0068] The present invention provides a building quality and safety management method based on big data. Compared with the prior art, it has the following beneficial effects:

[0069] The building quality and safety management method based on big data proposed by the present invention can monitor and evaluate the risks of glass curtain walls during transportation in real time by integrating multiple sensors and data analysis means. Through the collection and analysis of pressure, displacement, and vibration data, this method can timely identify risks such as unstable installation, uneven pressure, and excessive vibration that may occur during transportation. The comprehensive evaluation of various risk data provides a multi-level risk level detection and classification mechanism. According to the transportation risk assessment value of the glass curtain wall, different levels of inspection measures are taken to ensure that high-risk glass curtain walls are subject to more stringent inspections and management. Generally speaking, the present invention can achieve precise management of the transportation process of glass curtain walls, improve the building quality and safety guarantee level, reduce risks and losses, and optimize the safety and efficiency of the construction and transportation links. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The following further describes the present invention with reference to the accompanying drawings.

[0071] Figure 1 is the step flow chart of the building quality and safety management method based on big data of the present invention; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0072] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0073] Example 1, please refer to Figure 1 , the present invention provides a building quality and safety management method based on big data, including;

[0074] Step 1: Place the glass curtain wall to be transported on the mounting rack, mark the installation position of the mounting rack, and at the same time, number and identify the glass curtain wall to be transported. Record the storage of each numbered glass curtain wall on the corresponding installation position of the mounting rack;

[0075] The specific method of placing the glass curtain wall to be transported on the mounting rack, marking the installation position of the mounting rack, numbering and identifying the glass curtain wall to be transported, and recording the storage of each numbered glass curtain wall on the corresponding installation position of the mounting rack is as follows:

[0076] AS1: Mark the installation position of the mounting rack as , where , is the total number of installation positions of the mounting rack for this transportation;

[0077] AS2: Number and identify the glass curtain wall to be transported as , where , is the total number of glass curtain walls to be transported for this time, and ;

[0078] AS3: Then record the storage of each numbered glass curtain wall on the corresponding installation position of the mounting rack;

[0079] It should be noted that when transporting the glass curtain wall, an installation rack or a special fixing device needs to be used to ensure safety and avoid glass breakage or displacement. The glass curtain wall is usually a large-area glass panel and is easily damaged during transportation. The above-mentioned placing the glass curtain wall to be transported on the mounting rack specifically refers to effectively fixing the glass curtain wall by reasonably using appropriate suction cup devices, soft pads, support frames, etc.;

[0080] Before transporting the glass curtain wall, place it safely on the mounting rack, mark the position of each mounting rack, number and identify each glass curtain wall, and record the specific position of its mounting rack. This measure effectively ensures the positioning accuracy and traceability of the glass curtain wall during transportation. Since the glass curtain wall is usually large in size and vulnerable to damage, displacement or loss may occur during transportation. Marking and numbering can greatly reduce these risks, thus avoiding glass breakage or confusion. In addition, by recording the position of the mounting rack, it is convenient to track and manage each glass curtain wall in real time during transportation, improving management efficiency and accuracy, and ensuring safety and standardization during transportation.

[0081] Step 2: During transportation, collect pressure data of the glass curtain wall placed on the mounting rack, and evaluate the fixing risk situation of the glass curtain wall during transportation by analyzing the pressure data to determine the fixing risk impact value.

[0082] Specifically, the collection of pressure data for all glass curtain walls placed on the mounting rack is mainly achieved by installing pressure sensors at the key contact parts between the glass curtain wall and the mounting rack, and recording the pressure value of each sensor in real time.

[0083] During the transportation process, the specific method of collecting pressure data of the glass curtain wall placed on the mounting rack and evaluating the fixing risk situation of the glass curtain wall during transportation by analyzing the pressure data to determine the fixing risk impact value is as follows:

[0084] BS1: For the glass curtain walls placed on the mounting rack, each is regarded as the target glass curtain wall, and the fixing risk impact value is determined through the following steps;

[0085] BS2: Obtain the pressure value of each current sensor of the target glass curtain wall and mark it as , and , where represents the rd sensor, represents the current moment, represents the total number of sensors on the target glass curtain wall, and then determine the pressure distribution of the target glass curtain wall at the current moment , denoted as : ;

[0086] BS3: Then, unify the pressure values of different sensors to the same dimension, and normalize each pressure value through the following formula: , to obtain the normalized pressure distribution data : ;

[0087] Among them, and They are the minimum and maximum pressure values of all sensors at the current moment respectively;

[0088] BS4: Set within the time window to determine the pressure fluctuation degree of the contact area between the glass curtain wall and the mounting frame through the following formula :

[0089] ;

[0090] wherein, is the average pressure value at the current moment ; the pressure fluctuation degree , indicating that the more uneven the pressure distribution is, the higher the possible risk during transportation;

[0091] BS5: Then calculate the change rate of the pressure data through the following formula :

[0092] ;

[0093] wherein, is the acquisition time interval, and ;

[0094] Statistical analysis is performed on the change rates of all sensors on the target curtain wall to obtain the total number of pressure mutations :

[0095] ;

[0096] wherein, is the indicator function, which takes the value of 1 when the pressure change rate exceeds the threshold, and 0 otherwise, is the preset threshold, which is specifically determined by professional staff;

[0097] BS6: According to the pressure fluctuation degree and the total number of pressure mutations , determine the fixed risk impact value at the current moment through the following formula

[0098] ;

[0099] wherein, , are weight coefficients, which are specifically determined by professional staff;

[0100] BS7: Obtain the total time of the target glass curtain wall during transportation, denoted as , and determine by using the formula At each pressure data acquisition moment, the fixed risk impact value at each acquisition moment is obtained through steps BS2 - BS6 , where ; The fixed risk impact value of the target glass curtain wall during transportation is determined by the following formula :

[0101] ;

[0102] where is the risk impact factor, which is specifically set by professional staff;

[0103] By collecting the pressure data at the contact part between the glass curtain wall and the installation rack in real time during transportation, the pressure distribution of the glass curtain wall during transportation can be analyzed in detail; The deployment of pressure sensors can monitor the pressure fluctuations in key areas. Combining the fluctuation degree and mutation situation of the pressure data, the possible installation risks during transportation can be effectively evaluated; For example, if the pressure in a certain area is too large or too small, it may mean that the support of the fixing device is uneven or there is a risk of loosening, which may cause the glass curtain wall to shift or be damaged; By analyzing the pressure data, potential risks can be identified in a timely manner and preventive measures can be taken, thereby improving transportation safety and reducing transportation accidents caused by uneven pressure or improper fixation;

[0104] Step Three: Collect displacement data of the glass curtain wall placed on the installation rack, and evaluate the displacement risk situation of the glass curtain wall during transportation by analyzing the displacement data to determine the displacement risk impact value;

[0105] Specifically, the collection of displacement data of all glass curtain walls placed on the installation rack is mainly obtained by installing displacement sensors and tilt sensors. The displacement sensor records the relative displacement between the glass curtain wall and the installation rack in real time, and the tilt sensor is used to record the tilt angle of the glass curtain wall in real time;

[0106] The specific method for collecting displacement data of the glass curtain wall placed on the installation rack and evaluating the displacement risk situation of the glass curtain wall during transportation by analyzing the pressure data to determine the displacement risk impact value is as follows:

[0107] CS1: For all glass curtain walls placed on the installation rack, take them as the target glass curtain wall and determine the displacement risk impact value through the following steps;

[0108] CS2: Conduct a data collection of the relative displacement between the target glass curtain wall and the installation rack at a set acquisition time interval once, and mark it as ; Obtain the total time of the target glass curtain wall during transportation, denoted as , by using the formula , determine displacement data acquisition times, where , in this embodiment, , ;

[0109] Then, through the formula determine the total displacement of the target glass curtain wall during transportation ;

[0110] CS3: Obtain the moment with the largest relative displacement between the target glass curtain wall and the mounting frame among the displacement data acquisition times, denoted as ;

[0111] Combine the total displacement of the target glass curtain wall during transportation, and determine the displacement risk impact value of the target glass curtain wall during transportation through the following formula :

[0112] ;

[0113] Among them, and are weight coefficients, which are specifically determined by professional staff;

[0114] The acquisition of displacement data can provide the displacement situation of the glass curtain wall during transportation; this step helps to detect potential installation instability problems of the glass curtain wall in advance; avoid risks caused by excessive displacement of the glass curtain wall during transportation, improve the stability of the installation process, and ensure the safe transportation of the glass curtain wall;

[0115] Step Four: Collect vibration data of the mounting frame where the glass curtain wall placed on the mounting frame is located, and evaluate the vibration risk situation of the glass curtain wall during transportation by analyzing the vibration data to determine the vibration risk impact value;

[0116] Specifically, the collection of vibration data of the mounting frame where all the glass curtain walls placed on the mounting frame are located is mainly obtained by installing vibration sensors;

[0117] The specific method for collecting vibration data of the mounting frame where the glass curtain wall placed on the mounting frame is located and evaluating the vibration risk situation of the glass curtain wall during transportation by analyzing the vibration data to determine the vibration risk impact value is:

[0118] DS1: Set the acquisition time interval to be , collect the vibration data x(t) at each time point during transportation, perform denoising processing on the original vibration data x(t) to remove the high-frequency components generated by noise and ensure the reliability of the data; then use the moving average or exponential smoothing method to smooth the data, reduce the short-term fluctuations, and make the main trend clearer; where t represents the current moment;

[0119] DS2: Determine a time window W, calculate the variance of the vibration signal within the time window W. The time window W indicates that z times of vibration data are collected within this time window W. The variance of the vibration signal within the time window W is reflected by the following formula:

[0120] ;

[0121] Among them, represents the variance of the vibration signal within the time window W, represents the b-th collected vibration data among the z times of vibration data, and , is the mean value of the vibration data within the time window W:

[0122] ;

[0123] DS3: Then calculate the vibration change rate of the vibration data within the time window W through the following formula :

[0124] ;

[0125] Among them, represents the vibration data at the previous moment of the current moment within the time window W;

[0126] Obtain the total number z of the collected vibration data in the time window W, obtain the preset limit threshold , and count the number of all change rates exceeding the preset limit threshold through the following formula:

[0127] ;

[0128] Among them, is the indicator function, which takes the value of 1 when the vibration change rate exceeds the threshold, and 0 otherwise;

[0129] DS4: Obtain the variance of the vibration signal within the time window W and the number of all change rates exceeding the preset limit threshold , and determine the vibration risk impact value within the time window W through the following formula :

[0130] ;

[0131] Among them, 、 are weight coefficients;

[0132] DS5: Obtain the total duration of the glass curtain wall during transportation, denoted as , in this embodiment, ;

[0133] Then use the formula to determine the total number of time windows of the glass curtain wall during transportation , through steps DS1 - DS4, determine vibration risk impact values corresponding to time windows, and mark them as , among which, ; at the same time, determine the vibration risk impact value through the following formula

[0134] ;

[0135] Among them, is the weight coefficient, which is specifically determined by professional staff;

[0136] The acquisition and analysis of vibration data can effectively identify possible excessive vibration problems during transportation; during transportation, the mounting frame may generate certain vibrations due to external reasons or vibrations of transportation equipment. If these vibrations are too large or too frequent, they may cause damage to the glass curtain wall; by calculating the variance and change rate of vibration signals, abnormal vibration patterns are found.

[0137] Step Five: According to the fixed risk impact value, displacement risk impact value of each glass curtain wall placed on the mounting frame, and evaluate the vibration risk value of the glass curtain wall during transportation by analyzing vibration data to conduct a transportation risk assessment, determine the transportation risk assessment value of each glass curtain wall, and classify the inspection level of each glass curtain wall according to the transportation risk assessment value;

[0138] By comprehensively considering the fixed risk, installation risk, and vibration risk of each glass curtain wall, a comprehensive transportation risk assessment can be carried out for each glass curtain wall; this assessment method combines multiple data, uses quantitative analysis and weight coefficients for risk assessment, so that the risk situation of each glass curtain wall can be accurately quantified and the required inspection level can be judged.

[0139] Example 2. In the specific implementation process of this example, based on Example 1 and the difference from Example 1 is that this example explains the specific content of Step 5;

[0140] The transportation risk assessment value is determined according to the fixed risk impact value, displacement risk impact value of each glass curtain wall placed on the mounting rack, and the vibration risk value of the glass curtain wall during transportation by analyzing vibration data. The specific method for dividing the detection level of each glass curtain wall according to the transportation risk assessment value is as follows:

[0141] P1: Each glass curtain wall placed on the mounting rack is used as the target glass curtain wall to determine its transportation risk assessment value. Obtain the fixed risk impact value, displacement risk impact value of the target glass curtain wall, and the vibration risk value of the glass curtain wall during transportation by analyzing vibration data to determine the transportation risk assessment value. The transportation risk assessment value of the target glass curtain wall is specifically determined by the following formula :

[0142] ;

[0143] Among them, , and are weight coefficients, which are specifically determined by professional staff. is the fixed risk impact value. is the displacement risk impact value. is the vibration risk impact value;

[0144] P2: According to the transportation risk assessment value of the target glass curtain wall, conduct detection level division:

[0145] If , it indicates that the transportation risk of the target glass curtain wall is relatively small, and primary detection is adopted;

[0146] If , it indicates that the transportation risk of the target glass curtain wall is relatively large, and secondary detection is adopted;

[0147] If , it indicates that the transportation risk of the target glass curtain wall is on the high side, and tertiary detection is adopted;

[0148] Among them, , are preset values, which are specifically determined by professional staff, and ;

[0149] It should be noted that the higher the level of detection, the more rigorous it is. In this embodiment, the specific detection methods for the first-level detection, second-level detection, and third-level detection are determined by professional staff; in this embodiment, a basic detection is carried out on the glass curtain wall for the first-level detection to ensure that it has not been significantly damaged during transportation. The detection contents include: Surface defect inspection: Check whether there are cracks, chipped corners, scratches or damages visible to the naked eye on the glass surface; Edge integrity inspection: Check whether there are defects affecting safety such as cracks, notches, burrs, etc. on the glass edge; Preliminary stress detection: Use a polariscope to detect whether there are abnormal stress concentration areas on the glass, and preliminarily judge whether there are potential hazards caused by uneven stress; For the glass curtain wall for the second-level detection, enhanced detection is carried out. The detection contents include all the contents of the first-level detection, and the following contents are additionally added: Detection of microcracks inside the glass: Use ultrasonic or infrared detection technology to judge whether there are invisible cracks or stress damages inside the glass; Stress distribution detection: Measure the stress distribution at different points on the glass through stress sensors to ensure that there is no stress concentration phenomenon caused by transportation on the glass; Glass vibration response analysis: Analyze whether the glass has microscopic damages or structural fatigue due to transportation vibration through vibration test equipment; For the glass curtain wall for the third-level detection, strict detection is carried out. The detection contents include all the contents of the first-level detection and the second-level detection, and the following contents are additionally added: Glass structure integrity analysis: Use high-precision industrial CT or X-ray to scan the internal structure of the glass to ensure that there are no microscopic cracks or inclusions causing potential rupture risks; Three-dimensional stress distribution measurement: Use a high-precision stress tester to measure the overall stress distribution of the glass to ensure that there are no local abnormal stress points.

[0150] Embodiment 3. In the specific implementation process of this embodiment, it includes all the implementation processes of the above three groups of embodiments.

[0151] Some of the data in the above formula are numerically calculated after removing their dimensions, and the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0152] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A construction quality and safety management method based on big data, characterized in that: include: Step 1: Place the glass curtain wall to be transported on the mounting rack, mark the installation position of the mounting rack, and number the glass curtain wall to be transported, and place each numbered glass curtain wall at the installation position of the corresponding mounting rack and store and record it; Step 2: During transportation, pressure data of the glass curtain wall placed on the mounting rack is collected, and the fixing risk of the glass curtain wall during transportation is evaluated by analyzing the pressure data to determine the fixing risk impact value; The content of determining the fixed risk impact value includes: BS1: For the glass curtain walls placed on the mounting frame, all the glass curtain walls are taken as the target glass curtain walls and the fixed risk impact value is determined through the following steps; BS2: Get the current pressure value of each sensor of the target glass curtain wall and mark it as ,and ,in Indicates Sensors, Indicates the current moment, Represents the total number of sensors on the target glass curtain wall, thereby determining the target glass curtain wall at the current moment The pressure distribution is denoted as : ; BS3: Then, the pressure values ​​of different sensors are unified into the same dimension, and each pressure value is normalized to obtain the normalized pressure distribution data. : ; BS4: Set in time window Determine the pressure fluctuation in the contact area between the glass curtain wall and the mounting frame ; BS5: Then calculate the rate of change of pressure data using the following formula : ； in, is the collection time interval, and ; The change rates of all sensors on the target curtain wall are counted, and the total number of pressure mutations is obtained by the following method: : ； in, is an indicator function, which takes the value of 1 when the pressure change rate exceeds the threshold, otherwise it takes the value of 0. is the preset threshold; BS6: According to pressure fluctuation and the total number of pressure mutations , determine the current time Fixed risk impact value ; Step 3: Collect displacement data of the glass curtain wall placed on the mounting frame, evaluate the displacement risk of the glass curtain wall during transportation by analyzing the displacement data, and determine the impact value of the displacement risk; Step 4: Collect vibration data of the mounting frame on which the glass curtain wall is placed, evaluate the vibration risk of the glass curtain wall during transportation by analyzing the vibration data, and determine the vibration risk impact value; Step 5: Perform transportation risk assessment based on the fixed risk impact value and displacement risk impact value of each glass curtain wall placed on the mounting frame, as well as the vibration risk value of the glass curtain wall during transportation evaluated by analyzing the vibration data, determine the transportation risk assessment value of each glass curtain wall, and divide the inspection level of each glass curtain wall according to the transportation risk assessment value.

2. The construction quality and safety management method based on big data according to claim 1 is characterized in that: In the step 1, the specific method of placing each numbered glass curtain wall at the installation position of the corresponding installation frame and storing and recording the same is as follows: AS1: Mark the installation position of the mounting bracket ,in, , The total number of installation positions for the installation racks in this transport; AS2: Number and identify the glass curtain walls to be transported. ,in, , is the total number of glass curtain walls that need to be transported this time, and ; AS3: Then identify each number The glass curtain wall is placed in the installation position of the corresponding mounting frame Storage records are stored on.

3. The construction quality and safety management method based on big data according to claim 1 is characterized in that: In the step 2, after step BS6, the following steps are further included: BS7: Obtain the total time of the target glass curtain wall during transportation, recorded as , by using the formula ,Sure At each pressure data collection moment, the fixed risk impact value at each collection moment is obtained through steps BS2-BS6 ,in, ; Determine the fixed risk impact value of the target glass curtain wall during transportation by the following formula: : ； in, The risk influencing factor.

4. The construction quality and safety management method based on big data according to claim 3 is characterized in that: In the step 3, the displacement data of the glass curtain wall placed on the mounting frame is collected, and the displacement risk of the glass curtain wall during transportation is evaluated by analyzing the pressure data. The specific method for determining the displacement risk impact value is as follows: CS1: The glass curtain walls placed on the mounting frame are taken as the target glass curtain walls and the displacement risk impact value is determined through the following steps; CS2: By setting the acquisition time interval The relative displacement between the target glass curtain wall and the mounting frame is collected and marked as ; Get the total time of the target glass curtain wall during transportation, recorded as , by using the formula ,Sure displacement data collection time, among which, ; Then, through the formula Determine the total displacement of the target glass curtain wall during transportation ; CS3: Get The relative displacement between the target glass curtain wall and the mounting frame is the largest at the moment of displacement data collection , recorded as ; Combined with the total displacement of the target glass curtain wall during transportation , the displacement risk impact value of the target glass curtain wall during transportation is determined by the following formula: : ； in, and is the weight coefficient.

5. The construction quality and safety management method based on big data according to claim 1 is characterized in that: In the step 4, the vibration data of the mounting frame on which the glass curtain wall is placed is collected, and the vibration risk of the glass curtain wall during transportation is evaluated by analyzing the vibration data. The specific method for determining the vibration risk impact value is as follows: DS1: Set the collection time interval to , collect the vibration data x(t) at each time point during the transportation process, and perform denoising on the original vibration data x(t); then use the sliding average or exponential smoothing method to smooth the data, where t represents the current moment; DS2: Then determine a time window W and calculate the variance of the vibration signal within the time window W. The time window W means that z vibration data are collected within the time window W. The variance of the vibration signal within the time window W is expressed by the following formula: ； in, Expressed as the variance of the vibration signal within the time window W, It is represented as the bth collected vibration data among the zth vibration data, and , is the mean value of the vibration data in the time window W: ； DS3: Then calculate the vibration change rate of the vibration data within the time window W using the following formula: : ； in, It is represented as the vibration data of the moment before the current moment in the time window W; Get the total number z of vibration data collected in the time window W and get the preset limit threshold , all the change rates in the time window W are counted by the following formula Exceeding the preset limit threshold Quantity: ； in, is an indicator function, which takes the value of 1 when the vibration change rate exceeds the threshold, otherwise it takes the value of 0. DS4: Get the variance of the vibration signal within the time window W and all the rates of change in the time window W Exceeding the preset limit threshold Number of , the vibration risk impact value within the time window W is determined by the following formula : ； in, , is the weight coefficient; DS5: Get the total time taken by the glass curtain wall during transportation, recorded as ; Then use the formula , determine the total time window number of the glass curtain wall during transportation , through steps DS1-DS4, determine The vibration risk impact value corresponding to the time window is marked as ,in, ; At the same time, the vibration risk impact value is determined by the following formula ; ； in, is the weight coefficient.

6. The construction quality and safety management method based on big data according to claim 5 is characterized in that: In step 5, the transportation risk assessment value is determined based on the fixed risk impact value and the displacement risk impact value of each glass curtain wall placed on the mounting frame, and the vibration risk value of the glass curtain wall during transportation is assessed by analyzing the vibration data. The specific method for determining the transportation risk assessment value of each glass curtain wall is as follows: Each glass curtain wall placed on the mounting rack is taken as the target glass curtain wall to determine its transportation risk assessment value, obtain the fixed risk impact value and displacement risk impact value of the target glass curtain wall, and analyze the vibration data to evaluate the vibration risk value of the glass curtain wall during transportation to obtain the transportation risk assessment value. Specifically, the transportation risk assessment value of the target glass curtain wall is determined by the following formula: : ； in, , and is the weight coefficient, is the fixed risk impact value, is the displacement risk impact value, is the vibration risk impact value.

7. The construction quality and safety management method based on big data according to claim 6 is characterized in that: The specific method of classifying the inspection level of each glass curtain wall according to the transportation risk assessment value is as follows: According to the transportation risk assessment value of the target glass curtain wall Classification of detection levels: like , indicating that the transportation risk of the target glass curtain wall is relatively low, and the first-level inspection is adopted; like , indicating that the transportation risk of the target glass curtain wall is relatively high, and secondary inspection is adopted; like , indicating that the transportation risk of the target glass curtain wall is relatively high, and the third-level inspection is adopted; in, , is the default value, and .

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