An intelligent cloud platform for engineering safety monitoring

Abstract

The present invention relates to the field of engineering monitoring technology, specifically to an engineering safety intelligent monitoring cloud platform, including a data acquisition and transmission module, a data screening and processing module, a data processing and analysis module, a monitoring report generation module, a multi-platform interaction integration module and a data storage module. The present invention performs multi-layer screening and intelligent analysis on the platform data through the functions of data primary screening, secondary re-screening and multi-project intelligent analysis, screens a large amount of data input by the monitoring platform, removes errors and abnormal information and data in the massive data, ensures the authenticity and reliability of the data, and avoids the impact of data abnormalities on subsequent judgments of engineering safety; and performs transmission analysis on the connection data to obtain the transmission status and interaction log. When the interaction log corresponds to an error, an error report is generated based on the corresponding error item, which facilitates the interaction and integration of data on multiple platforms, autonomously analyzes abnormal information of platform interaction, and improves the user's rejection efficiency.

Description

Technical Field

[0001] The invention relates to the field of engineering monitoring technology, specifically an engineering safety intelligent monitoring cloud platform. Background Art

[0002] With urban development, it is becoming increasingly common to carry out underground construction projects such as subways, civil air defense, and high-rise building basements in complex environments with dense buildings and crisscrossing pipelines. All sectors of society have also put forward higher requirements for project safety. Currently, most monitoring data is stored in paper form. However, with the continuous advancement of technology, various monitoring platforms have sprung up like mushrooms after rain. These various monitoring platforms are similar in nature, and their basic functions mainly include data uploading, data solving, data storage, and report issuance.

[0003] Traditional engineering safety monitoring platforms lack the ability to perform intelligent data analysis. Large amounts of data are not analyzed after storage, making it difficult to ensure the authenticity and reliability of the data. When data anomalies occur, it will affect subsequent judgments on engineering safety. In addition, in large-scale engineering construction or regional engineering monitoring, multiple different monitoring platforms may be used at the same time, making data interaction and integration between platforms difficult. Summary of the Invention

[0004] The present invention provides an engineering safety intelligent monitoring cloud platform for solving the above-mentioned technical problems.

[0005] The first aspect of the present invention provides an engineering safety intelligent monitoring cloud platform, including a data acquisition and transmission module, a data screening and processing module, a data processing and analysis module, a monitoring report generation module, a multi-platform interactive integration module and a data storage module.

[0006] The data acquisition and transmission module monitors project data through the data upload unit, and transmits the collected monitoring project data to the data storage module; the data upload unit supports mobile phone APP Bluetooth upload, automatic upload, serial port upload, result method upload and original file upload; the monitoring project data includes but is not limited to the horizontal displacement, vertical displacement, groundwater level, various stresses, anchor cable tension, deep horizontal displacement, cracks, and vacuum degree monitoring data generated within the engineering project.

[0007] The data screening and processing module is used to obtain monitoring project data and perform data screening and analysis on the monitoring project data to obtain engineering abnormality information, identify the engineering abnormality information to obtain engineering abnormality points, generate corresponding abnormality information to be verified based on the engineering abnormality point information, and mark the corresponding remaining monitoring project data as preferred engineering monitoring data.

[0008] As a further improvement of the present invention, data screening and analysis are performed on the monitoring project data, which is specifically as follows: data screening includes primary data screening and secondary re-screening, and the corresponding data compliance in the monitoring project data is obtained by performing primary data screening on the monitoring project data. When the data compliance of the monitoring project data corresponds to non-compliance, the monitoring project data corresponding to the non-compliance is marked as primary information to be verified, and the monitoring project data whose data compliance corresponds to compliance is secondary re-screened to obtain data deviation. When the data deviation corresponds to data deviation, the corresponding re-screened information to be verified is generated, and the primary information to be verified and the re-screened information to be verified are combined to obtain abnormal information to be verified.

[0009] As a further improvement of the present invention, the monitoring project data is preliminarily screened, and the specific preliminarily screening method is as follows:

[0010] Based on the monitoring project data, data measurement information is obtained, and the data measurement information includes instrument accuracy, calibration data, inclinometer data, and equipment usage information; the pre-set standard measurement accuracy interval corresponding to each monitoring project data is obtained, and the instrument accuracy corresponding to each monitoring project data is overlapped and matched with the corresponding standard measurement accuracy interval. When the instrument accuracy corresponding to the monitoring project data exceeds the standard measurement accuracy interval, accuracy abnormality information is generated as accuracy abnormality monitoring project data;

[0011] According to the calibration data, the calibration period and data measurement time point of each instrument are obtained, and the calibration period of each instrument is identified to obtain the current calibration status of each instrument. The calibration status includes normal calibration and out of calibration period. The data measurement time point of each monitoring item data is matched with the calibration period to obtain the corresponding calibration status. When the calibration status corresponds to out of calibration period, calibration abnormality information is generated as calibration abnormality monitoring item data;

[0012] Based on the inclinometer data, the depth value of the inclinometer hole of each engineering period is obtained, and the depth comparison of the inclinometer hole depth values ​​corresponding to two adjacent engineering periods is performed. If the inclinometer hole depth values ​​are inconsistent, the corresponding inclinometer anomaly information is generated as the inclinometer anomaly monitoring project data;

[0013] Obtain device usage information of the upload device corresponding to each monitoring project data, the device usage information includes the upload address and device number of the input device corresponding to each monitoring project data, compare the upload addresses of each monitoring project data corresponding to the same device number to obtain the upload address type, obtain a pre-set address type warning line, and generate device abnormality information as device abnormality monitoring project data when the upload address type corresponding to each uploading device exceeds the address type warning line;

[0014] The accuracy anomaly monitoring project data, calibration anomaly monitoring project data, inclination anomaly monitoring project data and equipment anomaly monitoring project data are collected and the corresponding monitoring project data are marked as non-compliant data.

[0015] As a further improvement of the present invention, the monitoring project data corresponding to the data compliance is subjected to a secondary re-screening, and the specific re-screening method is as follows:

[0016] Based on the compliant monitoring project data, the deep horizontal displacement data and support axial force data corresponding to each monitoring project data are obtained; the inclinometer probe length and inclination angle are obtained according to the deep horizontal displacement data, the inclinometer tube is divided into multiple inclinometer measurement sections, and the inclinometer probe length and inclinometer inclination angle corresponding to a certain inclinometer measurement section are normalized and the linear displacement method formula is used to calculate the inclinometer probe length and inclinometer inclination angle. Calculate the horizontal displacement ΔL of the building within the depth range of the inclinometer tube i ; Where L represents the length of the inclinometer probe; θ i It is represented as the inclination angle of the inclinometer in the i-th inclinometer measurement section; the value of n is a positive integer; the horizontal displacement is identified to obtain the displacement direction of the top of the inclinometer tube. When the displacement direction of the inclinometer tube corresponds to moving out of the foundation pit, the corresponding inclinometer deviation information is generated.

[0017] According to the support axial force data, the elastic modulus of concrete and steel bars, the cross-sectional area of ​​concrete and steel bars, and the natural frequency measured by strain gauge are obtained, and the concrete support axial force calculation formula is used. Calculated concrete support axial force N c ; Among them, N c Expressed as support axial force; E c 、E t Expressed as the elastic modulus of concrete and steel; A c 、A t Expressed as the cross-sectional area of ​​concrete and steel bar; k jε Expressed as the steel string rebar gauge / strain gauge constant; f ji and f j0 Both represent the natural frequency measured by the strain gauge; obtain the support axial force warning value given by the design, compare the concrete support axial force with the support axial force warning value, and generate corresponding axial force abnormality information when the concrete support axial force exceeds the support axial force warning value.

[0018] Obtain the single measurement change value corresponding to the data of each compliance monitoring item, and obtain the expected rate given by the design. Use a divider to calculate the single measurement change value and the expected rate to obtain the multiple by which the single measurement change value exceeds the expected rate. When the excess multiple is greater than the preset upper limit of the multiple, generate corresponding data change abnormal information.

[0019] The inclination deviation information, axial force anomaly information and data change anomaly information are all set as output signals. When any one or more output signals appear in each compliant monitoring project data, the corresponding compliant monitoring project data will be marked as deviation monitoring project data, and the remaining compliant monitoring project data after removing the deviation monitoring project data will be marked as preferred engineering monitoring data.

[0020] The data processing and analysis module divides the engineering points into multiple monitoring sections, obtains the preferred engineering monitoring data and identifies the preferred engineering monitoring data to obtain the data collection position of the corresponding monitoring data point, matches the data collection position corresponding to each monitoring data point with the position of the monitoring section to obtain the position distance between the monitoring data point and the monitoring section, obtains the corresponding monitoring data point within the distance range given by the corresponding design of each monitoring section, aggregates the monitoring data points within the corresponding distance range of each monitoring section to obtain a section point group, and performs multi-project monitoring and analysis on the preferred engineering monitoring data of the section point group corresponding to the monitoring section to obtain safety alarm information.

[0021] As a further improvement of the present invention, the preferred engineering monitoring data of the corresponding profile point group of the monitoring profile is subjected to multi-project monitoring analysis, and the specific analysis steps are as follows:

[0022] A1: Based on the monitoring data of the preferred project, a comprehensive analysis of the deep horizontal displacement and the slope top horizontal displacement is carried out. According to the schematic diagram of the horizontal displacement point and the turning point, it is assumed that the measuring point A(X A , Y A ), measuring point B(X B , Y B ), DM1 and DM2 are the slope corner points, and a virtual segment surface is set. The monitoring points set in each straight line segment should be divided into the same segment surface. For example, A and B are the DM1-DM2 segment surface range, and C, D, and E are the DM2-DM3 segment surface range. The DM1-DM2 segment surface can be expressed using the straight line equation Expressed as follows, where Y DM1 、Y DM2 They are respectively represented as the vertical coordinates of the two slope corner points, X DM1 、X DM2 They are respectively expressed as the horizontal coordinates of the two slope corner points, and the formula The distance from the monitoring point to the virtual segment surface is calculated, and the distance from the monitoring point to the virtual segment surface is the horizontal displacement distance of the slope top;

[0023] Based on the formula in the above analysis The deep horizontal displacement distance is calculated, and the slope top horizontal displacement distance and the deep horizontal displacement distance are input into the comparator for comparison to obtain the displacement distance difference. When the displacement distance difference exceeds the distance difference threshold given by the design, displacement abnormal status information is generated.

[0024] A2: Based on the monitoring data of the preferred project, a comprehensive analysis of the axial force and the horizontal displacement of the slope top is performed. According to the monitoring diagram of the slope top horizontal displacement points A and B, the monitoring data of the preferred project corresponding to the two monitoring points A and B are obtained and the support axial force of the monitoring point is calculated using the displacement method and the support axial force calculation formula;

[0025] The calculation formula of the support axial force by the shift calculation method is expressed as Calculate the monitoring point support axial force N c Among them, L n It is represented by the support length of the nth measurement, L0 is represented by the initial support length of the concrete; σ c Expressed as concrete stress, when the concrete strength grade is less than or equal to C50, When the concrete strength grade is greater than C50,

[0026] Among them, f cu,k Expressed as the standard value of concrete cube compressive strength; f cm Expressed as the average value of axial compressive strength; ε c It is expressed as the compressive strain of concrete, that is, the compressive strain of the support is measured in real time by the strain gauge, and ε0 is expressed as the compressive stress of concrete reaches f c When the calculated ε0 value is less than 0.002, the concrete compressive strain is taken as 0.002;

[0027] Based on the monitoring diagram of the horizontal displacement of points A and B at the top of the slope, the displacements at both ends of the support are consistent with the horizontal displacement of the top of the slope at both ends. The linear displacement method support axial force is calculated using the linear displacement method formula in the above analysis. The difference between the support axial force of the monitoring point corresponding to the displacement calculation method and the support axial force of the linear displacement method is calculated to obtain the calculated difference value. When the calculated difference value is greater than the calculated difference upper limit value given by the design, the corresponding axial force abnormal status information is generated.

[0028] A3: Based on the data storage module, groundwater level data and surface settlement data are obtained for analysis. The groundwater level data are identified to obtain a groundwater level change signal, which includes a water level rise signal, a water level drop signal, and a water level unchanged signal. Similarly, the surface settlement data are identified to obtain a corresponding surface settlement signal, which includes a surface rise signal, a surface drop signal, and a surface unchanged signal. The water level change signal and the surface settlement signal are combined to obtain a combined state signal and marked as SX and DX respectively. The combined state signal is expressed as (SX, DX). A pre-designed abnormal combined state signal is obtained. The abnormal combined state information corresponds to the generation of corresponding surface settlement water level abnormality information when the change trends of the water level change signal and the surface settlement signal are different.

[0029] A4: The displacement abnormality status information, axial force abnormality status information and surface subsidence water level abnormality information are combined to generate safety alarm information.

[0030] The monitoring report generation module is used to obtain abnormal information to be verified, non-compliant data, deviation monitoring project data, and safety alarm information, and identify the abnormal information to be verified, non-compliant data, deviation monitoring project data, and safety alarm information to obtain corresponding monitoring abnormality information. The monitoring abnormality information includes the above-mentioned abnormal information and the abnormal collection information corresponding to the abnormal data, and generates a corresponding abnormal verification report based on the abnormal collection information.

[0031] The multi-platform interaction integration module is used to obtain the connection data between the current cloud platform and other platforms, and perform transmission analysis on the connection data to obtain the transmission status. The interaction log is generated according to the transmission status. When the interaction log corresponds to an error, an error report is generated based on the corresponding error item.

[0032] As a further improvement of the present invention, transmission analysis is performed on the connection data, and the specific transmission analysis steps are as follows:

[0033] The connection data is decoded by a data decoder to obtain the connection information between the current platform and the remaining platforms. The connection information includes connection parameters and data transmission parameters. The connection matching degree of the connection parameters between the current platform and the remaining platforms is identified by a sensor. When the connection matching degree is less than the pre-designed matching lower limit value, the corresponding matching exception information is generated.

[0034] According to the data transmission parameters, the data transmission volume and transmission frequency of the current platform and the other platforms are obtained; based on the data transmission volume, the corresponding pre-transmission data volume and post-transmission data volume before and after the data transmission are obtained, and the transmission volume difference between the pre-transmission data volume and the post-transmission data volume is calculated by a subtractor. When the transmission volume difference is greater than a predetermined transmission volume difference threshold, a corresponding transmission abnormality signal is generated; based on the transmission frequency, the normal transmission frequency interval when the current platform and the other platforms are transmitted is obtained, the transmission frequency of the current platform and the other platforms is matched with the corresponding normal transmission frequency interval, and the transmission duration corresponding to the transmission frequency exceeding the normal transmission frequency interval is marked as abnormal transmission duration. When the proportion of the abnormal transmission duration in the total transmission duration exceeds the designed threshold, the corresponding frequency abnormality information is generated; the matching abnormality information, the transmission abnormality signal and the frequency abnormality information are combined to generate a transmission error alarm with the transmission status as shown in FIG.

[0035] The data storage module stores the information and data generated by the above modules through random access memory.

[0036] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0037] 1. The present invention performs multi-layer screening and intelligent analysis on platform data through the functions of data primary screening, secondary screening and multi-project intelligent analysis, screens the large amount of data input by the monitoring platform, removes errors and abnormal information and data in the massive data, ensures the authenticity and reliability of the data, and avoids the impact of data anomalies on subsequent judgment of engineering safety.

[0038] 2. The present invention obtains the connection data between the current cloud platform and other platforms, and performs transmission analysis on the connection data to obtain the transmission status, and generates an interaction log according to the transmission status. When the interaction log corresponds to an error, an error report is generated based on the corresponding error item, which facilitates the interaction and integration of data from multiple platforms, autonomously analyzes the abnormal information of platform interaction, and improves the user's rejection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for the description of the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present application.

[0040] Figure 1 It is a principle block diagram of the present invention;

[0041] Figure 2 Schematic diagram of horizontal displacement points and corner points of the present invention;

[0042] Figure 3 Schematic diagram of monitoring the horizontal displacement of points A and B at the top of a slope according to the present invention. DETAILED DESCRIPTION

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0044] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1-3 In an embodiment of the present invention, an embodiment of an engineering safety intelligent monitoring cloud platform includes:

[0045] The data acquisition and transmission module monitors project data through the data upload unit, and transmits the collected monitoring project data to the data storage module; the data upload unit supports mobile phone APP Bluetooth upload, automatic upload, serial port upload, result method upload and original file upload, providing flexible and changeable data upload modes; the monitoring project data includes but is not limited to the horizontal displacement, vertical displacement, groundwater level, various stresses, anchor cable tension, deep horizontal displacement, cracks, and vacuum degree monitoring data generated within the engineering project.

[0046] The data screening and processing module obtains the monitoring project data and performs data screening and analysis on the monitoring project data to obtain engineering abnormality information, identifies the engineering abnormality information to obtain engineering abnormality points, generates corresponding abnormality information to be verified based on the engineering abnormality point information, and marks the corresponding remaining monitoring project data as preferred engineering monitoring data.

[0047] Perform data screening and analysis on the monitoring project data, specifically: data screening includes primary data screening and secondary re-screening, and obtain the corresponding data compliance in the monitoring project data by performing primary data screening on the monitoring project data. When the data compliance of the monitoring project data corresponds to non-compliance, the monitoring project data corresponding to the non-compliance is marked as preliminary information to be verified, and the monitoring project data whose data compliance corresponds to compliance is subjected to secondary re-screening to obtain data deviation. When the data deviation corresponds to data deviation, the corresponding re-screened information to be verified is generated, and the preliminary information to be verified and the re-screened information to be verified are combined to obtain abnormal information to be verified.

[0048] Conduct preliminary screening of monitoring project data. The specific screening methods are as follows:

[0049] Based on the monitoring project data, data measurement information is obtained, and the data measurement information includes instrument accuracy, calibration data, inclinometer data, and equipment usage information; the pre-set standard measurement accuracy interval corresponding to each monitoring project data is obtained, and the instrument accuracy corresponding to each monitoring project data is overlapped and matched with the corresponding standard measurement accuracy interval. When the instrument accuracy corresponding to the monitoring project data exceeds the standard measurement accuracy interval, accuracy abnormality information is generated as accuracy abnormality monitoring project data;

[0050] According to the calibration data, the calibration period and data measurement time point of each instrument are obtained, and the calibration period of each instrument is identified to obtain the current calibration status of each instrument. The calibration status includes normal calibration and out of calibration period. The data measurement time point of each monitoring item data is matched with the calibration period to obtain the corresponding calibration status. When the calibration status corresponds to out of calibration period, calibration abnormality information is generated as calibration abnormality monitoring item data;

[0051] Based on the inclinometer data, the depth value of the inclinometer hole of each engineering period is obtained, and the depth comparison of the inclinometer hole depth values ​​corresponding to two adjacent engineering periods is performed. If the inclinometer hole depth values ​​are inconsistent, the corresponding inclinometer anomaly information is generated as the inclinometer anomaly monitoring project data;

[0052] Obtain device usage information of the upload device corresponding to each monitoring project data, the device usage information includes the upload address and device number of the input device corresponding to each monitoring project data, compare the upload addresses of each monitoring project data corresponding to the same device number to obtain the upload address type, obtain a pre-set address type warning line, and generate device abnormality information as device abnormality monitoring project data when the upload address type corresponding to each uploading device exceeds the address type warning line;

[0053] The accuracy anomaly monitoring project data, calibration anomaly monitoring project data, inclination anomaly monitoring project data and equipment anomaly monitoring project data are collected and the corresponding monitoring project data are marked as non-compliant data.

[0054] The data compliance of the monitoring items that are compliant will be re-screened for the second time. The specific re-screening method is as follows:

[0055] Based on the compliant monitoring project data, the deep horizontal displacement data and support axial force data corresponding to each monitoring project data are obtained; the inclinometer probe length and inclination angle are obtained according to the deep horizontal displacement data, the inclinometer tube is divided into multiple inclinometer measurement sections, and the inclinometer probe length and inclinometer inclination angle corresponding to a certain inclinometer measurement section are normalized and the linear displacement method formula is used to calculate the inclinometer probe length and inclinometer inclination angle. Calculate the horizontal displacement ΔL of the building within the depth range of the inclinometer tube i ; Where L represents the length of the inclinometer probe; θ i It is represented as the inclination angle of the inclinometer in the i-th inclinometer measurement section; n is a positive integer; the horizontal displacement is identified to obtain the displacement direction of the top of the inclinometer tube. When the displacement direction of the inclinometer tube corresponds to moving out of the foundation pit, the corresponding inclinometer deviation information is generated; during inclinometer measurement, the bottom of the inclinometer tube is not completely stable and may deviate to a certain extent, resulting in deviation in the measurement results and an overall offset.

[0056] According to the support axial force data, the elastic modulus of concrete and steel bars, the cross-sectional area of ​​concrete and steel bars, and the natural frequency measured by strain gauge are obtained, and the concrete support axial force calculation formula is used. Calculated concrete support axial force N c ; Among them, N c Expressed as support axial force; E c 、E t Expressed as the elastic modulus of concrete and steel; A c 、A tExpressed as the cross-sectional area of ​​concrete and steel bar; k jε Expressed as the steel string rebar gauge / strain gauge constant; f ji and f j0 Both represent the natural frequency measured by the strain gauge; obtain the support axial force warning value given by the design, compare the concrete support axial force with the support axial force warning value, and generate corresponding axial force abnormality information when the concrete support axial force exceeds the support axial force warning value.

[0057] Obtain the single measurement change value corresponding to the data of each compliance monitoring item, and obtain the expected rate given by the design. Use a divider to calculate the single measurement change value and the expected rate to obtain the multiple by which the single measurement change value exceeds the expected rate. When the excess multiple is greater than the preset upper limit of the multiple, generate corresponding data change abnormal information.

[0058] The inclination deviation information, axial force anomaly information and data change anomaly information are all set as output signals. When any one or more output signals appear in each compliant monitoring project data, the corresponding compliant monitoring project data will be marked as deviation monitoring project data, and the remaining compliant monitoring project data after removing the deviation monitoring project data will be marked as preferred engineering monitoring data.

[0059] The data processing and analysis module divides the engineering points into multiple monitoring sections, obtains the preferred engineering monitoring data and identifies the preferred engineering monitoring data to obtain the data collection position of the corresponding monitoring data point, matches the data collection position corresponding to each monitoring data point with the position of the monitoring section to obtain the position distance between the monitoring data point and the monitoring section, obtains the corresponding monitoring data point within the distance range given by the corresponding design of each monitoring section, aggregates the monitoring data points within the corresponding distance range of each monitoring section to obtain a section point group, and performs multi-project monitoring and analysis on the preferred engineering monitoring data of the section point group corresponding to the monitoring section to obtain safety alarm information.

[0060] The selected engineering monitoring data of the corresponding profile point group of the monitoring profile are subjected to multi-project monitoring analysis. The specific analysis steps are as follows:

[0061] A1: Based on the monitoring data of the preferred project, a comprehensive analysis of the deep horizontal displacement and the slope top horizontal displacement is carried out. According to the schematic diagram of the horizontal displacement point and the turning point, it is assumed that the measuring point A(X A , Y A ), measuring point B(X B , Y B ), DM1 and DM2 are the slope corner points, and a virtual segment surface is set. The monitoring points set in each straight line segment should be divided into the same segment surface. For example, A and B are the DM1-DM2 segment surface range, and C, D, and E are the DM2-DM3 segment surface range. The DM1-DM2 segment surface can be expressed using the straight line equation Expressed as follows, where Y DM1、Y DM2 They are respectively represented as the vertical coordinates of the two slope corner points, X DM1 、X DM2 They are respectively expressed as the horizontal coordinates of the two slope corner points, and the formula The distance from the monitoring point to the virtual segment surface is calculated, and the distance from the monitoring point to the virtual segment surface is the horizontal displacement distance of the slope top;

[0062] Based on the formula in the above analysis The deep horizontal displacement distance is calculated, and the slope top horizontal displacement distance and the deep horizontal displacement distance are input into the comparator for comparison to obtain the displacement distance difference. When the displacement distance difference exceeds the distance difference threshold given by the design, displacement abnormal status information is generated.

[0063] A2: Based on the monitoring data of the preferred project, a comprehensive analysis of the axial force and the horizontal displacement of the slope top is performed. According to the monitoring diagram of the slope top horizontal displacement points A and B, the monitoring data of the preferred project corresponding to the two monitoring points A and B are obtained and the support axial force of the monitoring point is calculated using the displacement method and the support axial force calculation formula;

[0064] The calculation formula of the support axial force by the shift calculation method is expressed as Calculate the monitoring point support axial force N c ; Where L0 represents the initial length of the concrete support beam; L n Expressed as the support length of the nth measurement; σ c Expressed as concrete stress, when the concrete strength grade is less than or equal to C50, When the concrete strength grade is greater than C50, Among them, f cu,k Expressed as the standard value of concrete cube compressive strength; f cm Expressed as the average value of axial compressive strength; ε c It is expressed as the compressive strain of concrete, that is, the compressive strain of the support is measured in real time by the strain gauge, and ε0 is expressed as the compressive stress of concrete reaches f c When the calculated ε0 value is less than 0.002, the concrete compressive strain is taken as 0.002; the concrete strength grade C50 means that the standard value of the concrete cube compressive strength is 50MPa;

[0065] Based on the monitoring diagram of the horizontal displacement of points A and B at the top of the slope, the displacements at both ends of the support are consistent with the horizontal displacement of the top of the slope at both ends. The linear displacement method support axial force is calculated using the linear displacement method formula in the above analysis. The difference between the support axial force of the monitoring point corresponding to the displacement calculation method and the support axial force of the linear displacement method is calculated to obtain the calculated difference value. When the calculated difference value is greater than the calculated difference upper limit value given by the design, the corresponding axial force abnormal status information is generated.

[0066] A3: Based on the data storage module, groundwater level data and surface settlement data are obtained and analyzed. The groundwater level data is identified to obtain a groundwater level change signal, which includes a water level rise signal, a water level drop signal, and a water level unchanged signal. Similarly, the surface settlement data is identified to obtain a corresponding surface settlement signal, which includes a surface rise signal, a surface drop signal, and a surface unchanged signal. The water level change signal and the surface settlement signal are combined to obtain a combined state signal and labeled SX and DX respectively. The combined state signal is represented as (SX, DX). A pre-designed abnormal combined state signal is obtained. The abnormal combined state information corresponds to the generation of corresponding surface settlement water level abnormality information when the change trends of the water level change signal and the surface settlement signal are different. As the groundwater level drops, the effective stress of the soil increases accordingly. At this time, the effective stress of the soil increases, causing surface settlement. In addition, during the excavation process, the support structure will undergo lateral deformation, resulting in a "settlement trough" on the surface. Therefore, under normal circumstances, if the groundwater level drops and the ground surface rises, a measurement error should have occurred.

[0067] A4: The displacement abnormality status information, axial force abnormality status information and surface subsidence water level abnormality information are combined to generate safety alarm information.

[0068] The monitoring report generation module obtains abnormal information to be verified, non-compliant data, deviation monitoring project data, and safety alarm information, and identifies the abnormal information to be verified, non-compliant data, deviation monitoring project data, and safety alarm information to obtain corresponding monitoring abnormality information. The monitoring abnormality information includes the above-mentioned abnormal information and the abnormal collection information corresponding to the abnormal data, and generates a corresponding abnormal verification report based on the abnormal collection information.

[0069] The multi-platform interaction integration module obtains the connection data between the current cloud platform and other platforms, and performs transmission analysis on the connection data to obtain the transmission status, generates an interaction log based on the transmission status, and generates an error report based on the corresponding error item when the interaction log corresponds to an error; for example, the error report corresponds to the connection between the current platform and other platforms being too low and requiring a change of the matching strategy, the transmission volume being abnormal and there being transmission congestion, and the transmission frequency being too low corresponding to a connection failure.

[0070] Perform transmission analysis on the connection data. The specific transmission analysis steps are as follows:

[0071] The connection data is decoded by a data decoder to obtain the connection information between the current platform and the remaining platforms. The connection information includes connection parameters and data transmission parameters; the connection parameters include but are not limited to the network connection address, port number, and transmission protocol. The connection matching degree of the connection parameters between the current platform and the remaining platforms is identified by the sensor. When the connection matching degree is less than the pre-designed matching lower limit value, the corresponding matching exception information is generated.

[0072] According to the data transmission parameters, the data transmission volume and transmission frequency of the current platform and the other platforms are obtained; based on the data transmission volume, the corresponding pre-transmission data volume and post-transmission data volume before and after the data transmission are obtained, and the transmission volume difference between the pre-transmission data volume and the post-transmission data volume is calculated by a subtractor. When the transmission volume difference is greater than a predetermined transmission volume difference threshold, a corresponding transmission abnormality signal is generated; based on the transmission frequency, the normal transmission frequency interval when the current platform and the other platforms are transmitted is obtained, the transmission frequency of the current platform and the other platforms is matched with the corresponding normal transmission frequency interval, and the transmission duration corresponding to the transmission frequency exceeding the normal transmission frequency interval is marked as abnormal transmission duration. When the proportion of the abnormal transmission duration in the total transmission duration exceeds the designed threshold, the corresponding frequency abnormality information is generated; the matching abnormality information, the transmission abnormality signal and the frequency abnormality information are combined to generate a transmission error alarm with the transmission status as shown in FIG.

[0073] The data storage module stores the information and data generated by the above modules through random access memory; the storage includes but is not limited to monitoring project data, abnormal information to be verified, non-compliant data, deviation monitoring project data, and safety alarm information.

[0074] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An engineering safety intelligent monitoring cloud platform, including a data acquisition and transmission module and a data storage module, characterized in that: Also includes: The data screening and processing module is used to obtain monitoring project data and perform data screening and analysis on it to obtain engineering abnormality information, identify engineering abnormality points from the engineering abnormality information, generate corresponding abnormality to be verified information based on the engineering abnormality point information, and mark the corresponding remaining monitoring project data as preferred engineering monitoring data; The data processing and analysis module divides the project points into multiple monitoring sections, obtains the preferred project monitoring data, identifies the data collection locations of the corresponding monitoring data points, matches the data collection locations of each monitoring data point with the location of the monitoring section to obtain the location distance between the monitoring data point and the monitoring section, obtains the corresponding monitoring data points within the distance range given by the design for each monitoring section, aggregates the monitoring data points within the corresponding distance range of each monitoring section to obtain a section point group, and performs multi-project monitoring analysis on the preferred project monitoring data of the section point group corresponding to the monitoring section to obtain safety alarm information; The multi-project monitoring analysis is performed on the preferred engineering monitoring data of the corresponding profile point group of the monitoring profile, and the specific analysis is as follows: Based on the monitoring data of the selected project, a comprehensive analysis of the deep horizontal displacement and the slope top horizontal displacement is performed to obtain the abnormal displacement status information, which is specifically: According to the horizontal displacement point and corner point diagram, it is assumed that the measuring point A(X A , Y A ), measuring point B(X B , Y B ), DM1 and DM2 are the slope corner points, and a virtual segment surface is set. The monitoring points set in each straight line segment should be divided into the same segment surface. Set A and B as the DM1-DM2 segment surface range, and C, D, and E as the DM2-DM3 segment surface range; the DM1-DM2 segment surface can be used with the straight line equation Expressed as DM1 、Y DM2 They are respectively represented as the vertical coordinates of the two slope corner points, X DM1 、X DM2 They are respectively expressed as the horizontal coordinates of the two slope corner points, and the formula The distance from the monitoring point to the virtual segment surface is calculated, and the distance from the monitoring point to the virtual segment surface is the horizontal displacement distance of the slope top; Based on the formula The deep horizontal displacement distance is calculated; where L is the length of the inclinometer probe; θ i The inclination angle of the inclinometer in the i-th inclinometer measurement section is represented by n, which is a positive integer. The horizontal displacement distance of the slope top and the horizontal displacement distance of the deep layer are input into the comparator for comparison to obtain the displacement distance difference. When the displacement distance difference exceeds the distance difference threshold given by the design, a displacement abnormality status message is generated. Based on the monitoring data of the selected project, the axial force and the horizontal displacement of the slope top are comprehensively analyzed to obtain the abnormal state information of the axial force; Based on the data storage module, groundwater level data and surface subsidence data are obtained for analysis to obtain abnormal information of surface subsidence water level; Abnormal displacement status information, abnormal axial force status information and abnormal surface subsidence water level information are combined to generate safety alarm information; The monitoring report generation module is used to obtain abnormal information to be verified, non-compliant data, deviation monitoring project data and safety alarm information and identify the corresponding monitoring abnormal information. The monitoring abnormal information includes each abnormal information and the abnormal collection information corresponding to the abnormal data, and generates the corresponding abnormal verification report based on the abnormal collection information; The multi-platform interaction integration module is used to obtain the connection data between the current cloud platform and other platforms, and perform transmission analysis on the connection data to obtain the transmission status. The interaction log is generated according to the transmission status. When the interaction log corresponds to an error, an error report is generated based on the corresponding error item.

2. The engineering safety intelligent monitoring cloud platform according to claim 1 is characterized in that: The data acquisition and transmission module monitors project data through a data upload unit and transmits the collected monitoring project data to a data storage module; the data upload unit supports mobile phone APP Bluetooth upload, automatic upload, serial port upload, result method upload and original file upload; the monitoring project data includes horizontal displacement, vertical displacement, groundwater level, various stresses, anchor cable tension, deep horizontal displacement, cracks, and vacuum degree monitoring data generated within the engineering project.

3. The engineering safety intelligent monitoring cloud platform according to claim 1 is characterized in that: The data screening and analysis of the monitoring project data is specifically as follows: data screening includes primary data screening and secondary re-screening, and the corresponding data compliance in the monitoring project data is obtained by performing primary data screening on the monitoring project data. When the data compliance of the monitoring project data corresponds to non-compliance, the monitoring project data corresponding to the non-compliance is marked as primary information to be verified, and the monitoring project data whose data compliance corresponds to compliance is secondary re-screened to obtain data deviation. When the data deviation corresponds to data deviation, the corresponding re-screened information to be verified is generated, and the primary information to be verified and the re-screened information to be verified are combined to obtain abnormal information to be verified.

4. The engineering safety intelligent monitoring cloud platform according to claim 3 is characterized in that: The specific initial screening method for the monitoring project data is as follows: Obtain data measurement information based on the monitoring project data; obtain a pre-set standard measurement accuracy interval corresponding to each monitoring project data, and match the instrument accuracy corresponding to each monitoring project data with the corresponding standard measurement accuracy interval. When the instrument accuracy corresponding to the monitoring project data exceeds the standard measurement accuracy interval, generate accuracy abnormality information as accuracy abnormality monitoring project data; The calibration period and data measurement time point of each instrument are obtained according to the calibration data, the calibration period of each instrument is identified to obtain the current calibration status of each instrument, the data measurement time point of each monitoring item data is matched with the calibration period to obtain the corresponding calibration status, and when the calibration status corresponds to exceeding the calibration period, calibration abnormality information is generated as calibration abnormality monitoring item data; Based on the inclinometer data, the depth value of the inclinometer hole of each engineering period is obtained, and the depth comparison of the inclinometer hole depth values ​​corresponding to two adjacent engineering periods is performed. If the inclinometer hole depth values ​​are inconsistent, the corresponding inclinometer anomaly information is generated as the inclinometer anomaly monitoring project data; Obtain the device usage information of the uploading device corresponding to each monitoring project data, compare the upload addresses of each monitoring project data corresponding to the same device number to obtain the upload address type, obtain the pre-set address type warning line, and when the upload address type corresponding to each uploading device exceeds the address type warning line, generate device abnormality information as device abnormality monitoring project data; collect the accuracy abnormality monitoring project data, calibration abnormality monitoring project data, inclination abnormality monitoring project data and equipment abnormality monitoring project data, and mark the corresponding monitoring project data as non-compliant data.

5. The engineering safety intelligent monitoring cloud platform according to claim 1 is characterized in that: The data compliance of the monitoring project data is re-screened for the second time, and the specific re-screening method is as follows: Based on the compliant monitoring project data, the deep horizontal displacement data and support axial force data corresponding to each monitoring project data are obtained; the inclinometer probe length and inclination angle are obtained according to the deep horizontal displacement data, the inclinometer tube is divided into multiple inclinometer measurement sections, and the inclinometer probe length and inclinometer inclination angle corresponding to a certain inclinometer measurement section are normalized and the linear displacement method formula is used to calculate the inclinometer probe length and inclinometer inclination angle. Calculate the horizontal displacement ΔL of the building within the depth range of the inclinometer tube i Identify the horizontal displacement to obtain the displacement direction of the top of the inclinometer tube. When the displacement direction of the inclinometer tube corresponds to moving out of the foundation pit, generate the corresponding inclinometer deviation information. According to the support axial force data, the elastic modulus of concrete and steel bars, the cross-sectional area of ​​concrete and steel bars, and the natural frequency measured by strain gauge are obtained, and the concrete support axial force calculation formula is used. Calculated concrete support axial force N c ; Among them, N c Expressed as support axial force; E c 、E t Expressed as the elastic modulus of concrete and steel; A c 、A t Expressed as the cross-sectional area of ​​concrete and steel bar; k jε Expressed as the steel string rebar gauge / strain gauge constant; f ji and f j0 Both represent the natural frequency measured by the strain gauge; obtain the support axial force warning value given by the design, compare the concrete support axial force with the support axial force warning value, and generate corresponding axial force abnormality information when the concrete support axial force exceeds the support axial force warning value; Obtain the single measurement change value corresponding to the data of each compliance monitoring item, and obtain the expected rate given by the design. Use a divider to calculate the single measurement change value and the expected rate to obtain the multiple by which the single measurement change value exceeds the expected rate. When the multiple exceeds the preset upper limit, generate corresponding data change abnormal information; The inclination deviation information, axial force anomaly information and data change anomaly information are all set as output signals. When any one or more output signals appear in each compliant monitoring project data, the corresponding compliant monitoring project data will be marked as deviation monitoring project data, and the remaining compliant monitoring project data after removing the deviation monitoring project data will be marked as preferred engineering monitoring data.

6. The engineering safety intelligent monitoring cloud platform according to claim 5 is characterized in that: The comprehensive analysis of axial force and horizontal displacement of slope top based on the optimized engineering monitoring data is as follows: According to the monitoring diagram of the horizontal displacement of the slope top A and B points, the optimal engineering monitoring data corresponding to the two monitoring points A and B are obtained and the supporting axial force of the monitoring point is calculated by the displacement method and the supporting axial force calculation formula; The calculation formula of the support axial force by displacement method is expressed as follows: Calculate the monitoring point support axial force N c ; Where L0 represents the initial length of the concrete support beam; L n Expressed as the support length of the nth measurement; σ c Expressed as concrete stress, when the concrete strength grade is less than or equal to C50, When the concrete strength grade is greater than C50, Among them, f cu,k Expressed as the standard value of concrete cube compressive strength; f cm Expressed as the average value of axial compressive strength; ε c It is expressed as the compressive strain of concrete, and ε0 is expressed as the compressive stress of concrete reaching f c When the calculated ε0 value is less than 0.002, the concrete compressive strain is taken as 0.002; Based on the fact that the displacements of the supports at both ends of the slope top horizontal displacement points A and B are consistent with the horizontal displacements of the slope tops at both ends, the linear displacement method support axial force is calculated using the linear displacement method formula. The difference between the monitoring point support axial force corresponding to the displacement calculation method and the linear displacement method support axial force is calculated to obtain the calculated difference value. When the calculated difference value is greater than the calculated difference upper limit value given by the design, the corresponding axial force abnormal state signal is generated.

7. The engineering safety intelligent monitoring cloud platform according to claim 6 is characterized in that: The data storage module is used to obtain groundwater level data and surface subsidence data for analysis, which is specifically as follows: The groundwater level data is identified to obtain a groundwater level change signal, which includes a water level rise signal, a water level drop signal, and a water level unchanged signal. Similarly, the surface settlement data is identified to obtain a corresponding surface settlement signal, which includes a surface rise signal, a surface drop signal, and a surface unchanged signal. The water level change signal and the surface settlement signal are combined to obtain a combined state signal and marked as SX and DX respectively. The combined state signal is expressed as (SX, DX), and a pre-designed abnormal combined state signal is obtained. The abnormal combined state information corresponds to the generation of corresponding surface settlement water level abnormality information when the change trends of the water level change signal and the surface settlement signal are different.

8. The engineering safety intelligent monitoring cloud platform according to claim 1 is characterized in that: The transmission analysis of the connection data is performed, and the specific transmission analysis steps are as follows: The connection data is decoded by a data decoder to obtain the connection information between the current platform and the other platforms, including connection parameters and data transmission parameters; the connection matching degree between the connection parameters of the current platform and the other platforms is identified by a sensor, and when the connection matching degree is less than the pre-designed matching lower limit, the corresponding matching exception information is generated; According to the data transmission parameters, the data transmission volume and transmission frequency of the current platform and the other platforms are obtained; based on the data transmission volume, the corresponding pre-transmission data volume and post-transmission data volume before and after the data transmission are obtained, and the transmission volume difference between the pre-transmission data volume and the post-transmission data volume is calculated by a subtractor. When the transmission volume difference is greater than a predetermined transmission volume difference threshold, a corresponding transmission abnormality signal is generated; based on the transmission frequency, the normal transmission frequency interval when the current platform and the other platforms are transmitted is obtained, the transmission frequency of the current platform and the other platforms is matched with the corresponding normal transmission frequency interval, and the transmission duration corresponding to the transmission frequency exceeding the normal transmission frequency interval is marked as abnormal transmission duration. When the proportion of the abnormal transmission duration in the total transmission duration exceeds the designed threshold, the corresponding frequency abnormality information is generated; the matching abnormality information, the transmission abnormality signal and the frequency abnormality information are combined to generate a transmission error alarm with the transmission status as shown in FIG.

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