CN112307089B - Detection method and system applied to construction data - Google Patents
Detection method and system applied to construction data Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 48
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- 239000010959 steel Substances 0.000 claims description 20
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- 230000015271 coagulation Effects 0.000 claims description 10
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Abstract
The invention discloses a detection method and a detection system applied to construction data, which are used for acquiring real-time data, splitting data in a data distribution queue in the real-time data to obtain first data information, second data information and third data information, extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix; mapping the first characteristic coefficient, the second characteristic coefficient and the third characteristic coefficient into the target data matrix respectively, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirements. The position of potential safety hazard in tunnel construction can be accurately detected, reinforcing measures are adopted for the position with the potential safety hazard in advance, and thus the tunnel construction risk can be greatly reduced, and the life safety of constructors is ensured.
Description
Technical Field
The invention relates to the technical field of tunnel construction and data, in particular to a detection method and a detection system applied to construction data.
Background
With the continuous development of technology, the traditional method for detecting construction quality adopts a manual detection method, so that the efficiency is low, the labor is wasted, and the position with potential safety hazard can not be accurately detected.
By adopting the artificial intelligence method, the data are collected for the tunnel, so that the efficiency can be greatly improved, and the safety problem caused by tunnel construction can be reduced.
Disclosure of Invention
The technical problem to be solved by the invention is the technical problem of the background technology, and the invention aims to provide a detection method and a detection system for construction data, and solve the problem of tunnel safety.
The invention is realized by the following technical scheme:
a method of detection for application to construction data, the method comprising:
acquiring real-time data; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, wherein the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition;
splitting data of a data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars;
Extracting characteristic coefficients in the first data information to obtain first characteristic coefficients; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; extracting characteristic coefficients in the third data information to obtain third characteristic coefficients;
extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix;
mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirements.
Further, the specific steps of splitting data of the data distribution queue in the real-time data to obtain the first data information, the second data information and the third data information corresponding to the data distribution queue include:
After receiving the real-time data, extracting an information content area in the real-time data, and extracting area characteristics based on the information content area to obtain information area characteristics corresponding to the information content area; the information content area is an area where information related to the detection object in the real-time data is located;
dividing the information area features into plates to obtain first plate information, second plate information and third plate information corresponding to the information area features;
extracting object characteristics in the first plate information to obtain first data information corresponding to the first plate information; extracting object characteristics in the second plate information to obtain second data information corresponding to the second plate information; and extracting object characteristics in the third plate information to obtain third data information corresponding to the third plate information.
Further, extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix, wherein the specific steps include:
acquiring a plurality of preset data in a preset database and standard data indexes corresponding to the standard data;
Dividing the preset data and the standard data index into at least two standard data tolerance values according to the corresponding relation;
obtaining a coefficient value of each standard data tolerance value and a local plurality of preset data corresponding to the standard data tolerance value, wherein the local plurality of preset data are part of the plurality of preset data;
calculating error loss when fitting each standard data tolerance value to the standard data tolerance value corresponding to the preset data according to the coefficient value of each standard data tolerance value and the local multiple preset data, wherein the error loss comprises vertex loss;
fitting the standard data tolerance value to a corresponding standard data tolerance value in the plurality of preset data when the vertex loss converges;
after the fitting of the at least two standard data tolerance values, carrying out fusion processing on adjacent standard data tolerance values to obtain target data sets corresponding to the plurality of preset data;
and performing matrix processing on the target data set to obtain a target data matrix corresponding to the target data set.
Further, the specific step of mapping the first characteristic coefficient to the target data matrix and judging whether at least one mapping point exists comprises the following steps:
Extracting a first characteristic coefficient in advance, wherein the first characteristic coefficient comprises a preset information flow and a preset information quantity;
acquiring an information transmission rate corresponding to the information flow and a transmission data accommodation amount corresponding to the information amount;
generating a preset information bit rate based on the information transmission rate pair and the transmission data accommodation amount;
collecting real-time information flow and real-time information quantity in the first characteristic coefficient; extracting according to the real-time information flow and the real-time information quantity to obtain real-time information distribution values corresponding to the real-time information flow and the real-time information quantity;
the real-time information distribution value is judged to be larger than the preset information bit rate or not through fusion of the preset information bit rate and the real-time information distribution value, and if the real-time information distribution value is smaller than or equal to the preset information bit rate, a first information data set corresponding to the first characteristic coefficient is obtained;
mapping the first information data set to the target data matrix, judging whether the first information data set has at least one mapping point in the target data matrix, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient has no potential safety hazard information.
Further, the specific step of mapping the third feature coefficient to the target data matrix, and determining whether at least one mapping point exists includes:
acquiring second plate information, and a target field to which the second plate information belongs;
determining a target display area from a preset data control according to the target field;
generating a target area range according to the second plate information, wherein the target area range comprises effective information for displaying the second plate information, window information for providing path information and weight information for acquiring information coefficients;
generating an information chain according to the target area range and the effective information; mapping the information chain into the target data matrix, judging whether at least one mapping point exists, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient does not have potential safety hazard information.
The utility model provides a be applied to construction data's detecting system, the system includes data acquisition end and data processing terminal, data acquisition end with data processing terminal communication connection, data processing terminal specifically is used for:
Acquiring real-time data; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, wherein the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition;
splitting data of a data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars;
extracting characteristic coefficients in the first data information to obtain first characteristic coefficients; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; extracting characteristic coefficients in the third data information to obtain third characteristic coefficients;
extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix;
mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirements.
Further, the data processing terminal is specifically configured to:
after receiving the real-time data, extracting an information content area in the real-time data, and extracting area characteristics based on the information content area to obtain information area characteristics corresponding to the information content area; the information content area is an area where information related to the detection object in the real-time data is located;
dividing the information area features into plates to obtain first plate information, second plate information and third plate information corresponding to the information area features;
extracting object characteristics in the first plate information to obtain first data information corresponding to the first plate information; extracting object characteristics in the second plate information to obtain second data information corresponding to the second plate information; and extracting object characteristics in the third plate information to obtain third data information corresponding to the third plate information.
Further, the data processing terminal is specifically configured to:
acquiring a plurality of preset data in a preset database and standard data indexes corresponding to the standard data;
dividing the preset data and the standard data index into at least two standard data tolerance values according to the corresponding relation;
Obtaining a coefficient value of each standard data tolerance value and a local plurality of preset data corresponding to the standard data tolerance value, wherein the local plurality of preset data are part of the plurality of preset data;
calculating error loss when fitting each standard data tolerance value to the standard data tolerance value corresponding to the preset data according to the coefficient value of each standard data tolerance value and the local multiple preset data, wherein the error loss comprises vertex loss;
fitting the standard data tolerance value to a corresponding standard data tolerance value in the plurality of preset data when the vertex loss converges;
after the fitting of the at least two standard data tolerance values, carrying out fusion processing on adjacent standard data tolerance values to obtain target data sets corresponding to the plurality of preset data;
and performing matrix processing on the target data set to obtain a target data matrix corresponding to the target data set.
Further, the data processing terminal is specifically configured to:
extracting a first characteristic coefficient in advance, wherein the first characteristic coefficient comprises a preset information flow and a preset information quantity;
acquiring an information transmission rate corresponding to the information flow and a transmission data accommodation amount corresponding to the information amount;
Generating a preset information bit rate based on the information transmission rate pair and the transmission data accommodation amount;
collecting real-time information flow and real-time information quantity in the first characteristic coefficient; extracting according to the real-time information flow and the real-time information quantity to obtain real-time information distribution values corresponding to the real-time information flow and the real-time information quantity;
the real-time information distribution value is judged to be larger than the preset information bit rate or not through fusion of the preset information bit rate and the real-time information distribution value, and if the real-time information distribution value is smaller than or equal to the preset information bit rate, a first information data set corresponding to the first characteristic coefficient is obtained;
mapping the first information data set to the target data matrix, judging whether the first information data set has at least one mapping point in the target data matrix, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient has no potential safety hazard information.
Further, the data processing terminal is specifically configured to:
acquiring second plate information, and a target field to which the second plate information belongs;
determining a target display area from a preset data control according to the target field;
generating a target area range according to the second plate information, wherein the target area range comprises effective information for displaying the second plate information, window information for providing path information and weight information for acquiring information coefficients;
generating an information chain according to the target area range and the effective information; mapping the information chain into the target data matrix, judging whether at least one mapping point exists, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient does not have potential safety hazard information.
Compared with the prior art, the invention has the following advantages and beneficial effects:
acquiring real-time data; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, wherein the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition; splitting data of a data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars; extracting characteristic coefficients in the first data information to obtain first characteristic coefficients; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; extracting characteristic coefficients in the third data information to obtain third characteristic coefficients; extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix; mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirements. The position of potential safety hazard in tunnel construction can be accurately detected, reinforcing measures are adopted for the position with the potential safety hazard in advance, and thus the tunnel construction risk can be greatly reduced, and the life safety of constructors is ensured.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention. In the drawings:
fig. 1 is a schematic diagram of a construction system applied to construction data according to an embodiment of the present invention;
FIG. 2 is a flowchart of a detection method applied to construction data according to an embodiment of the present invention;
fig. 3 is a functional block diagram of a detection device applied to construction data according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
In order to improve the problems in the prior art, the embodiment of the invention provides an order data detection method and system applied to online electronic commerce, which can accurately and reliably detect real-time monitoring data, so that the Internet of things equipment corresponding to the real-time monitoring data can normally operate without data leakage, and the safety of data transmission is ensured.
For convenience in describing the above detection method and apparatus applied to construction data, please refer to fig. 1, which provides a schematic diagram of a communication architecture of a detection system 100 applied to construction data according to an embodiment of the present invention. The detection system 100 applied to construction data may include a data acquisition end 300 and a data processing terminal 200, where the data acquisition end 300 is communicatively connected to the data processing terminal 200.
In a specific embodiment, the data collection terminal 300 may be a desktop computer, a tablet computer, a notebook computer, a mobile phone, or other data collection terminals capable of implementing data processing and data communication, which is not limited herein.
In the above-mentioned to-be-processed, please refer to fig. 2 in combination, which is a schematic flow chart of the method for monitoring operation data of the internet of things device according to the embodiment of the present invention, the method for monitoring operation data of the internet of things device may be applied to the data acquisition end 300 in fig. 1, and further, the method for monitoring operation data of the internet of things device may specifically include the following descriptions of step S21 to step S25.
Step S21, acquiring real-time data; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, and the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition.
Step S22, splitting data of a data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars.
Step S23, extracting characteristic coefficients in the first data information to obtain first characteristic coefficients; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; and extracting the characteristic coefficient in the third data information to obtain a third characteristic coefficient.
Step S24, extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix.
Step S25, mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirements.
It will be appreciated that the real-time data is acquired while the above-described contents of steps S21 to S25 are performed; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, wherein the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition; splitting data of a data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars; extracting characteristic coefficients in the first data information to obtain first characteristic coefficients; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; extracting characteristic coefficients in the third data information to obtain third characteristic coefficients; extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix; mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirements. The position of potential safety hazard in tunnel construction can be accurately detected, reinforcing measures are adopted for the position with the potential safety hazard in advance, and thus the tunnel construction risk can be greatly reduced, and the life safety of constructors is ensured.
In the implementation process, when the data distribution queue in the real-time data is split, a data splitting error may occur, so that it is difficult to obtain accurate first data information, second data information and third data information, and in order to improve the technical problem, the step of splitting the data distribution queue in the real-time data to obtain the first data information, the second data information and the third data information corresponding to the data distribution queue described in step S22 may specifically include the following steps S221 to S223.
Step S221, after receiving the real-time data, extracting an information content area in the real-time data, and extracting area characteristics based on the information content area to obtain information area characteristics corresponding to the information content area; the information content area is an area where information related to the detection object in the real-time data is located.
Step S222, dividing the information area features into plates to obtain first plate information, second plate information and third plate information corresponding to the information area features.
Step S223, extracting object characteristics in the first plate information to obtain first data information corresponding to the first plate information; extracting object characteristics in the second plate information to obtain second data information corresponding to the second plate information; and extracting object characteristics in the third plate information to obtain third data information corresponding to the third plate information.
It can be understood that when the content described in the above steps S221 to S223 is executed, the data splitting error is avoided when the data distribution queue in the real-time data is split, so that accurate first data information, second data information and third data information can be obtained.
In a specific implementation process, extracting a plurality of preset data in a preset database, and when the plurality of preset data are subjected to matrix processing, a situation that the extracted plurality of preset data are inaccurate may occur, so as to obtain an inaccurate target data matrix, and in order to improve the technical problem, the step of extracting the plurality of preset data in the preset database described in step S24, and performing matrix processing on the plurality of preset data to obtain the target data matrix may specifically include the following steps S241-S247.
Step S241, a plurality of preset data in a preset database and standard data indexes corresponding to the standard data are obtained.
Step S242, dividing the plurality of preset data and the standard data index into at least two standard data tolerance values according to the corresponding relationship.
Step S243, obtaining a coefficient value of each standard data tolerance value and a local plurality of preset data corresponding to the standard data tolerance value, where the local plurality of preset data is a part of the plurality of preset data.
Step S244, calculating an error loss when fitting each standard data tolerance value to a standard data tolerance value corresponding to the plurality of preset data according to the coefficient value of each standard data tolerance value and the local plurality of preset data, where the error loss includes a vertex loss.
Step S245, fitting the standard data tolerance value to a corresponding standard data tolerance value in the plurality of preset data when the vertex loss converges.
Step S246, after the fitting of the at least two standard data tolerance values, performing fusion processing on adjacent standard data tolerance values to obtain target data sets corresponding to the plurality of preset data.
And step S247, performing matrix processing on the target data set to obtain a target data matrix corresponding to the target data set.
It can be understood that, when the content described in the above steps S241 to S247 is executed, a plurality of preset data in the preset database is extracted, and when the matrix processing is performed on the plurality of preset data, a plurality of extracted preset data can be accurately obtained, so that an accurate target data matrix is obtained.
In a specific implementation process, when the first feature coefficient is mapped to the target data matrix, the first feature coefficient may appear, so that it cannot be determined whether at least one mapping point exists, and in order to improve the technical problem, the step of mapping the first feature coefficient to the target data matrix, described in step S25, and determining whether at least one mapping point exists may specifically include the following descriptions in steps S251 to S256.
Step S251, extracting a first feature coefficient in advance, where the first feature coefficient includes a preset information flow and a preset information amount.
Step S252, acquiring an information transmission rate corresponding to the information stream and a transmission data accommodation amount corresponding to the information amount.
Step S253, generating a preset information bit rate based on the information transmission rate pair and the transmission data holding amount.
Step S254, collecting real-time information flow and real-time information quantity in the first characteristic coefficient; and extracting according to the real-time information flow and the real-time information quantity to obtain real-time information distribution values corresponding to the real-time information flow and the real-time information quantity.
Step S255, determining whether the real-time information distribution value is greater than the preset information bit rate by fusing the preset information bit rate and the real-time information distribution value, and if the real-time information distribution value is less than or equal to the preset information bit rate, obtaining a first information data set corresponding to the first characteristic coefficient.
Step S256, mapping the first information data set to the target data matrix, determining whether at least one mapping point exists in the target data matrix for the first information data set, if at least one mapping point exists in the target data matrix for the first information data set, determining that potential safety hazard information exists in the first feature coefficient, and if at least one mapping point does not exist in the target data matrix for the first information data set, determining that potential safety hazard information does not exist in the first feature coefficient.
It will be appreciated that when the above description of step S251 to step S256 is performed, the first feature coefficient is prevented from being present when the first feature coefficient is mapped into the target data matrix, so that it is possible to accurately determine whether or not at least one mapping point exists.
In a specific implementation process, when mapping the first feature coefficient to the target data matrix, a third feature coefficient may occur, so that it cannot be determined whether at least one mapping point exists, and in order to improve the technical problem, the step of mapping the third feature coefficient to the target data matrix and determining whether at least one mapping point exists as described in step S25 may specifically include the following steps a to d.
And a step a of acquiring second plate information and a target field to which the second plate information belongs.
And b, determining a target display area from a preset data control according to the target field.
And c, generating a target area range according to the second plate information, wherein the target area range comprises effective information for displaying the second plate information, window information for providing path information and weight information for acquiring information coefficients.
Step d, generating an information chain according to the target area range and the effective information; mapping the information chain into the target data matrix, judging whether at least one mapping point exists, if so, judging that the third characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient does not have potential safety hazard information.
It will be appreciated that when performing the above description of steps a-d, the third feature factor is avoided when mapping the third feature factor into the target data matrix, so that it is possible to accurately determine whether at least one mapping point exists.
Based on the same inventive concept, a detection system applied to construction data is also provided, the system comprises a data acquisition end and a data processing terminal, the data acquisition end is in communication connection with the data processing terminal, and the data processing terminal is specifically used for:
acquiring real-time data; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, wherein the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition;
Splitting data of a data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars;
extracting characteristic coefficients in the first data information to obtain first characteristic coefficients; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; extracting characteristic coefficients in the third data information to obtain third characteristic coefficients;
extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix;
mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirements.
Further, the data processing terminal is specifically configured to:
after receiving the real-time data, extracting an information content area in the real-time data, and extracting area characteristics based on the information content area to obtain information area characteristics corresponding to the information content area; the information content area is an area where information related to the detection object in the real-time data is located;
dividing the information area features into plates to obtain first plate information, second plate information and third plate information corresponding to the information area features;
extracting object characteristics in the first plate information to obtain first data information corresponding to the first plate information; extracting object characteristics in the second plate information to obtain second data information corresponding to the second plate information; and extracting object characteristics in the third plate information to obtain third data information corresponding to the third plate information.
Further, the data processing terminal is specifically configured to:
acquiring a plurality of preset data in a preset database and standard data indexes corresponding to the standard data;
dividing the preset data and the standard data index into at least two standard data tolerance values according to the corresponding relation;
Obtaining a coefficient value of each standard data tolerance value and a local plurality of preset data corresponding to the standard data tolerance value, wherein the local plurality of preset data are part of the plurality of preset data;
calculating error loss when fitting each standard data tolerance value to the standard data tolerance value corresponding to the preset data according to the coefficient value of each standard data tolerance value and the local multiple preset data, wherein the error loss comprises vertex loss;
fitting the standard data tolerance value to a corresponding standard data tolerance value in the plurality of preset data when the vertex loss converges;
after the fitting of the at least two standard data tolerance values, carrying out fusion processing on adjacent standard data tolerance values to obtain target data sets corresponding to the plurality of preset data;
and performing matrix processing on the target data set to obtain a target data matrix corresponding to the target data set.
Further, the data processing terminal is specifically configured to:
extracting a first characteristic coefficient in advance, wherein the first characteristic coefficient comprises a preset information flow and a preset information quantity;
acquiring an information transmission rate corresponding to the information flow and a transmission data accommodation amount corresponding to the information amount;
Generating a preset information bit rate based on the information transmission rate pair and the transmission data accommodation amount;
collecting real-time information flow and real-time information quantity in the first characteristic coefficient; extracting according to the real-time information flow and the real-time information quantity to obtain real-time information distribution values corresponding to the real-time information flow and the real-time information quantity;
the real-time information distribution value is judged to be larger than the preset information bit rate or not through fusion of the preset information bit rate and the real-time information distribution value, and if the real-time information distribution value is smaller than or equal to the preset information bit rate, a first information data set corresponding to the first characteristic coefficient is obtained;
mapping the first information data set to the target data matrix, judging whether the first information data set has at least one mapping point in the target data matrix, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient has no potential safety hazard information.
Further, the data processing terminal is specifically configured to:
acquiring second plate information, and a target field to which the second plate information belongs;
determining a target display area from a preset data control according to the target field;
generating a target area range according to the second plate information, wherein the target area range comprises effective information for displaying the second plate information, window information for providing path information and weight information for acquiring information coefficients;
generating an information chain according to the target area range and the effective information; mapping the information chain into the target data matrix, judging whether at least one mapping point exists, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient does not have potential safety hazard information.
Based on the same inventive concept as described above, please refer to fig. 3 in combination, a functional block diagram of a detection device 500 applied to construction data is also provided, and a detailed description about the detection device 500 applied to construction data is as follows.
A detection device 500 for application to construction data, for application to an electronic apparatus, the device 500 comprising:
The data acquisition wood block 510 is used for acquiring real-time data; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, wherein the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition;
the data analysis module 520 performs data splitting on the data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars;
an extracting module 530, configured to extract a feature coefficient in the first data information to obtain a first feature coefficient; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; extracting characteristic coefficients in the third data information to obtain third characteristic coefficients;
the matrix module 540 is configured to extract a plurality of preset data in a preset database, and perform matrix processing on the plurality of preset data to obtain a target data matrix;
a determining module 550, configured to map the first feature coefficient to the target data matrix, and determine whether at least one mapping point exists; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirements.
Comprehensively, acquiring real-time data; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, wherein the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition; splitting data of a data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars; extracting characteristic coefficients in the first data information to obtain first characteristic coefficients; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; extracting characteristic coefficients in the third data information to obtain third characteristic coefficients; extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix; mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirements. The position of potential safety hazard in tunnel construction can be accurately detected, reinforcing measures are adopted for the position with the potential safety hazard in advance, and thus the tunnel construction risk can be greatly reduced, and the life safety of constructors is ensured.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (8)
1. A method for detecting construction data, the method comprising:
acquiring real-time data; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, wherein the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition;
splitting data of a data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars;
extracting characteristic coefficients in the first data information to obtain first characteristic coefficients; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; extracting characteristic coefficients in the third data information to obtain third characteristic coefficients;
Extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix;
mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirement;
the data processing terminal is specifically configured to: mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not comprises the following specific steps:
extracting a first characteristic coefficient in advance, wherein the first characteristic coefficient comprises a preset information flow and a preset information quantity;
acquiring an information transmission rate in the information stream and a transmission data accommodation amount corresponding to the information amount;
generating a preset information bit rate based on the information transmission rate and the transmission data holding capacity;
Collecting real-time information flow and real-time information quantity in the first characteristic coefficient; extracting according to the real-time information flow and the real-time information quantity to obtain real-time information distribution values corresponding to the real-time information flow and the real-time information quantity;
the real-time information distribution value is judged to be larger than the preset information bit rate or not through fusion of the preset information bit rate and the real-time information distribution value, and if the real-time information distribution value is smaller than or equal to the preset information bit rate, a first information data set corresponding to the first characteristic coefficient is obtained;
mapping the first information data set into the target data matrix, judging whether the first information data set has at least one mapping point in the target data matrix, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient has no potential safety hazard information.
2. The method for detecting construction data according to claim 1, wherein the specific step of splitting data of the data distribution queue in the real-time data to obtain the first data information, the second data information and the third data information corresponding to the data distribution queue comprises:
After receiving the real-time data, extracting an information content area in the real-time data, and extracting area characteristics based on the information content area to obtain information area characteristics corresponding to the information content area; the information content area is an area where information related to the detection object in the real-time data is located;
dividing the information area features into plates to obtain first plate information, second plate information and third plate information corresponding to the information area features;
extracting object characteristics in the first plate information to obtain first data information corresponding to the first plate information; extracting object characteristics in the second plate information to obtain second data information corresponding to the second plate information; and extracting object characteristics in the third plate information to obtain third data information corresponding to the third plate information.
3. The method for detecting construction data according to claim 1, wherein the specific step of extracting a plurality of preset data in a preset database, performing matrix processing on the plurality of preset data, and obtaining a target data matrix comprises:
Acquiring a plurality of preset data in a preset database and standard data indexes corresponding to the standard data; dividing the preset data and the standard data index into at least two standard data tolerance values according to the corresponding relation;
obtaining a coefficient value of each standard data tolerance value and a local plurality of preset data corresponding to the standard data tolerance value, wherein the local plurality of preset data are part of the plurality of preset data;
calculating error loss when fitting each standard data tolerance value to the standard data tolerance value corresponding to the preset data according to the coefficient value of each standard data tolerance value and the local multiple preset data, wherein the error loss comprises vertex loss;
fitting the standard data tolerance value to a corresponding standard data tolerance value in the plurality of preset data when the vertex loss converges;
after the fitting of the at least two standard data tolerance values, carrying out fusion processing on adjacent standard data tolerance values to obtain target data sets corresponding to the plurality of preset data;
and performing matrix processing on the target data set to obtain a target data matrix corresponding to the target data set.
4. The method for detecting construction data according to claim 1, wherein the specific step of mapping the third characteristic coefficient to the target data matrix and determining whether at least one mapping point exists comprises:
acquiring second plate information, and a target field to which the second plate information belongs;
determining a target display area from a preset database according to the target field;
generating a target area range according to the second plate information, wherein the target area range comprises effective information for displaying the second plate information, window information for providing path information and weight information for acquiring information coefficients;
generating an information chain according to the target area range and the effective information; mapping the information chain into the target data matrix, judging whether at least one mapping point exists, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient does not have potential safety hazard information.
5. The utility model provides a be applied to construction data's detecting system, its characterized in that, the system includes data acquisition end and data processing terminal, data acquisition end with data processing terminal communication connection, data processing terminal specifically is used for:
Acquiring real-time data; the real-time data is obtained by data acquisition of the structure in the tunnel by the data acquisition end, wherein the content of the data acquisition comprises concrete setting strength, steel bar size and steel bar distribution condition;
splitting data of a data distribution queue in the real-time data to obtain first data information, second data information and third data information corresponding to the data distribution queue; the first data information is used for representing the coagulation strength of the concrete, the second data information is used for representing the size of the reinforcing steel bars, and the third data information is used for representing the distribution condition of the reinforcing steel bars;
extracting characteristic coefficients in the first data information to obtain first characteristic coefficients; extracting characteristic coefficients in the second data information to obtain second characteristic coefficients; extracting characteristic coefficients in the third data information to obtain third characteristic coefficients;
extracting a plurality of preset data in a preset database, and performing matrix processing on the plurality of preset data to obtain a target data matrix;
mapping the first characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the second characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; mapping the third characteristic coefficient into the target data matrix, and judging whether at least one mapping point exists or not; if at least one mapping point exists, the detection object corresponding to the characteristic coefficient does not meet the requirement; if at least one mapping point does not exist, the detection object corresponding to the characteristic coefficient meets the requirement;
The data processing terminal is specifically configured to:
extracting a first characteristic coefficient in advance, wherein the first characteristic coefficient comprises a preset information flow and a preset information quantity;
acquiring an information transmission rate in the information stream and a transmission data accommodation amount corresponding to the information amount;
generating a preset information bit rate based on the information transmission rate and the transmission data holding capacity;
collecting real-time information flow and real-time information quantity in the first characteristic coefficient; extracting according to the real-time information flow and the real-time information quantity to obtain real-time information distribution values corresponding to the real-time information flow and the real-time information quantity;
the real-time information distribution value is judged to be larger than the preset information bit rate or not through fusion of the preset information bit rate and the real-time information distribution value, and if the real-time information distribution value is smaller than or equal to the preset information bit rate, a first information data set corresponding to the first characteristic coefficient is obtained;
mapping the first information data set into the target data matrix, judging whether the first information data set has at least one mapping point in the target data matrix, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient has no potential safety hazard information.
6. The system for detecting construction data according to claim 5, wherein the data processing terminal is specifically configured to:
after receiving the real-time data, extracting an information content area in the real-time data, and extracting area characteristics based on the information content area to obtain information area characteristics corresponding to the information content area; the information content area is an area where information related to the detection object in the real-time data is located;
dividing the information area features into plates to obtain first plate information, second plate information and third plate information corresponding to the information area features;
extracting object characteristics in the first plate information to obtain first data information corresponding to the first plate information; extracting object characteristics in the second plate information to obtain second data information corresponding to the second plate information; and extracting object characteristics in the third plate information to obtain third data information corresponding to the third plate information.
7. The system for detecting construction data according to claim 5, wherein the data processing terminal is specifically configured to:
Acquiring a plurality of preset data in a preset database and standard data indexes corresponding to the standard data;
dividing the preset data and the standard data index into at least two standard data tolerance values according to the corresponding relation;
obtaining a coefficient value of each standard data tolerance value and a local plurality of preset data corresponding to the standard data tolerance value, wherein the local plurality of preset data are part of the plurality of preset data;
calculating error loss when fitting each standard data tolerance value to the standard data tolerance value corresponding to the preset data according to the coefficient value of each standard data tolerance value and the local multiple preset data, wherein the error loss comprises vertex loss;
fitting the standard data tolerance value to a corresponding standard data tolerance value in the plurality of preset data when the vertex loss converges;
after the fitting of the at least two standard data tolerance values, carrying out fusion processing on adjacent standard data tolerance values to obtain target data sets corresponding to the plurality of preset data;
and performing matrix processing on the target data set to obtain a target data matrix corresponding to the target data set.
8. The system for detecting construction data according to claim 5, wherein the data processing terminal is specifically configured to:
acquiring second plate information, and a target field to which the second plate information belongs;
determining a target display area from a preset database according to the target field;
generating a target area range according to the second plate information, wherein the target area range comprises effective information for displaying the second plate information, window information for providing path information and weight information for acquiring information coefficients;
generating an information chain according to the target area range and the effective information; mapping the information chain into the target data matrix, judging whether at least one mapping point exists, if so, judging that the first characteristic coefficient has potential safety hazard information, and if not, judging that the first characteristic coefficient does not have potential safety hazard information.
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