CN114745399A - Intelligent building engineering quality inspection and acceptance management system - Google Patents
Intelligent building engineering quality inspection and acceptance management system Download PDFInfo
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Abstract
The invention relates to an acceptance management system, in particular to an intelligent construction engineering quality acceptance management system, which can accurately identify an acceptance area from an acceptance image by utilizing an image identification detection module, detect the acceptance area according to an identification result, generate detection data, obtain a corresponding relevant acceptance rule from an acceptance rule generation module by a data comparison module based on the identification result, perform comparison analysis on the detection data and the relevant acceptance rule, generate relevant acceptance information by an acceptance information generation module, authenticate the acceptance information by a user network node, realize comprehensive evaluation on the construction engineering quality and simultaneously ensure the accuracy of the final acceptance result of an acceptance project; the technical scheme provided by the invention can effectively overcome the defects of poor acceptance result accuracy and incapability of comprehensively evaluating the quality of the construction engineering in the prior art.
Description
Technical Field
The invention relates to an acceptance management system, in particular to an intelligent construction engineering quality acceptance management system.
Background
The intelligent building optimally combines the structure, system, service and management of the building according to the requirements of users, thereby providing an efficient, comfortable and convenient humanized living environment for the users. The intelligent building is a product integrating modern science and technology, and the technical basis mainly comprises modern building technology, modern computer technology, modern communication technology and modern control technology.
The quality inspection and acceptance of the construction engineering is an important link before the engineering is put into use, the quality detection of the engineering in the inspection and acceptance process is an essential link, and the quality detection of the construction engineering directly reflects whether each data index in the construction engineering meets the standard or not, so the quality inspection and acceptance detection of the construction engineering is very necessary.
The existing construction engineering quality acceptance detection is basically realized by the fact that a supervisor goes to a construction site for field investigation, the existing construction engineering quality acceptance detection is still easily influenced by external environmental factors such as weather, and meanwhile the existing construction engineering quality acceptance detection is basically carried out in a sampling mode, so that a large error exists. Therefore, the existing acceptance detection of the construction engineering quality still has certain disadvantages, on one hand, the existing acceptance detection mode has lower efficiency, and the acceptance result has great errors, and on the other hand, the existing acceptance detection mode has many limitations and cannot carry out comprehensive evaluation on the construction engineering quality.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects in the prior art, the invention provides an intelligent construction engineering quality acceptance management system, which can effectively overcome the defects of poor acceptance result accuracy and incapability of comprehensively evaluating the construction engineering quality in the prior art.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
an intelligent construction engineering quality acceptance management system comprises a server, and a user network node and a non-user network node which are connected with the server;
the system also comprises an acceptance rule generating module which is used for generating a final acceptance rule under the condition that the user and the constructor confirm together;
the acceptance image receiving module is used for receiving an acceptance image sent on site;
the image identification detection module is used for identifying the area to be checked in the checking image, detecting the area to be checked according to the identification result and generating detection data;
the data comparison module is used for acquiring the corresponding relevant acceptance rule from the acceptance rule generation module based on the identification result of the image identification detection module and carrying out comparison analysis on the detection data and the relevant acceptance rule;
the acceptance information generating module is used for generating relevant acceptance information of the acceptance item according to the comparison and analysis result;
the acceptance result generating module is used for generating a final acceptance result of the acceptance item according to the relevant acceptance information confirmed by the user;
the early warning information generating module is used for generating acceptance early warning information according to the final acceptance result of the acceptance item;
the image recognition detection module pre-recognizes the acceptance image, intercepts at least one to-be-accepted region from the acceptance image, extracts multi-channel basic image features from the to-be-accepted region, extracts multi-channel high-dimensional image features on the basis of ensuring that the basic image features are not lost, performs feature fusion to obtain multi-channel fusion image features, and obtains a recognition result based on the fusion image features.
Preferably, the image recognition and detection module performs pre-recognition on the acceptance image, and intercepts at least one to-be-accepted area from the acceptance image, and includes:
and carrying out binarization processing, corrosion and/or expansion processing on the acceptance image, carrying out edge point detection on the processed image, carrying out connected domain detection on the detected edge points, and intercepting a corresponding area to be accepted in the acceptance image based on the position coordinates of each connected domain.
Preferably, the extracting the multi-channel basic image features in the region to be checked includes:
inputting the area to be checked into the lightweight network, and inputting the output results of a plurality of bottleneck layers of the lightweight network into the path aggregation network to obtain the multichannel basic image characteristics.
Preferably, the extracting the multi-channel high-dimensional image features on the basis of ensuring that the basic image features are not missing comprises:
inputting the multi-channel basic image features into a spatial pyramid pooling network, extracting to obtain multi-channel high-dimensional image features with standard dimensions, inputting the high-dimensional image features into a sub-pixel convolution network, and respectively inserting the low-resolution high-dimensional image features into a high-resolution feature spectrum to enhance the feature quality of the high-dimensional image features.
Preferably, the obtaining of the multi-channel fusion image feature after the feature fusion includes:
and performing feature fusion on the high-dimensional image features for enhancing the feature quality by using 1 x 1 convolution kernel to obtain multi-channel fusion image features, inputting the fusion image features into a classification network and a positioning network respectively, and identifying the position coordinates of the to-be-inspected area in the standard inspection image by combining with an output result.
Preferably, the server receives the construction acceptance rules sent by the non-user network nodes and stores the construction acceptance rules in an acceptance rule storage module, and the user network nodes modify/authenticate the construction acceptance rules;
and after the user network node is modified/authenticated, the server stores the construction acceptance rule to the acceptance rule storage module again until the two sides confirm the texts which are not modified any more.
Preferably, when both parties confirm the text which is not modified any more, the server generates a final acceptance rule through the acceptance rule generating module according to the text which is not modified any more.
Preferably, when the data comparison module determines that the difference between the detection data and the acceptance rule is within the threshold range, the acceptance information generation module determines that the detection data is accepted, generates relevant acceptance information, stores the relevant acceptance information into the acceptance information storage module, and authenticates the acceptance information by the user network node.
Preferably, the early warning information generating module comprehensively analyzes the final acceptance result of the acceptance project, and generates acceptance early warning information according to the difference between the detection data and the acceptance rule and the acceptance qualification proportion of the detection data.
Preferably, the system further comprises an actual measurement data receiving module for receiving actual measurement data sent on site and a detection data replacing module for replacing detection data with the actual measurement data, wherein when the deviation of the comparison and analysis result of the data comparison module is large, the detection data replacing module replaces the detection data with the actual measurement data on site and performs comparison and analysis on the actual measurement data on site and the relevant acceptance rules.
(III) advantageous effects
Compared with the prior art, the intelligent construction engineering quality acceptance management system provided by the invention has the following beneficial effects:
1) the server receives the construction acceptance rules sent by the non-user network nodes, modifies/authenticates the construction acceptance rules by the user network nodes, and generates final acceptance rules based on the text which is not modified by the server through an acceptance rule generation module when both sides confirm the text which is not modified any more, so that the user side and the non-user side negotiate in the aspect of the construction acceptance rules, and firm frame support is provided for ensuring the accuracy and precision of the acceptance results;
2) the image identification detection module can accurately identify the area to be checked and accepted from the checking and accepting image, the area to be checked and accepted is detected according to the identification result, detection data are generated, the data comparison module acquires the corresponding relevant checking and accepting rule from the checking and accepting rule generation module based on the identification result, the detection data and the relevant checking and accepting rule are subjected to comparison analysis, the relevant checking and accepting information is generated through the checking and accepting information generation module, the checking and accepting information is authenticated by the user network node, and the aim of comprehensively evaluating the quality of the construction project and ensuring the accuracy of the final checking and accepting result of the checking and accepting project is fulfilled.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a schematic diagram of the system of the present invention;
fig. 2 is a schematic flow chart of the image recognition and detection module recognizing the area to be checked in the checking image according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
An intelligent construction engineering quality acceptance management system is shown in fig. 1 and comprises a server, and a user network node and a non-user network node which are connected with the server; the system also comprises an acceptance rule generating module which is used for generating a final acceptance rule under the condition that the user and the constructor confirm together.
The server receives the construction acceptance rules sent by the non-user network nodes and stores the construction acceptance rules in an acceptance rule storage module, and the user network nodes modify/authenticate the construction acceptance rules. And after the user network node is modified/authenticated, the server stores the construction acceptance rule to the acceptance rule storage module again until the two sides confirm the texts which are not modified any more.
When both parties confirm the text which is not modified any more, the server generates a final acceptance rule through the acceptance rule generation module according to the text which is not modified any more, so that the negotiation between the user party and the non-user party is consistent in the aspect of construction acceptance rules, and solid frame support is provided for ensuring the accuracy and precision of acceptance results.
According to the technical scheme, the block chain can be used for storing, modifying and authenticating the construction acceptance rules on the chain, on one hand, a user can participate in formulation of the relevant construction acceptance rules of the personalized design, on the other hand, data privacy can be guaranteed, privacy data are prevented from being revealed, and the requirements of the user on the privacy of the personalized design data are fully met.
The acceptance image receiving module is used for receiving an acceptance image sent on site;
the image identification detection module is used for identifying the area to be checked in the checking image, detecting the area to be checked according to the identification result and generating detection data;
and the data comparison module is used for acquiring the corresponding relevant acceptance rule from the acceptance rule generation module based on the identification result of the image identification detection module and carrying out comparison analysis on the detection data and the relevant acceptance rule.
As shown in fig. 2, the image recognition and detection module performs pre-recognition on the acceptance image, intercepts at least one to-be-accepted region from the acceptance image, extracts multi-channel basic image features from the to-be-accepted region, extracts multi-channel high-dimensional image features on the basis of ensuring that the basic image features are not missing, performs feature fusion to obtain multi-channel fusion image features, and obtains a recognition result based on the fusion image features.
The image recognition and detection module is used for pre-recognizing the acceptance image, intercepting at least one area to be accepted from the acceptance image, identifying the position coordinate of the area to be accepted from the standard acceptance image, and the data comparison module is used for acquiring the corresponding relevant acceptance rule from the acceptance rule generation module based on the position coordinate and comparing and analyzing the detection data and the relevant acceptance rule. The interception of the to-be-checked area can be set according to the requirements of the user network node, and can also be set based on professional judgment of the non-user network node.
Specifically, the process of identifying the to-be-checked area in the checking image by the image identification and detection module includes:
the image identification detection module carries out binarization processing, corrosion and/or expansion processing on the acceptance image, carries out edge point detection on the processed image, carries out connected domain detection on the detected edge point, and intercepts a corresponding area to be accepted in the acceptance image based on the position coordinates of each connected domain;
inputting the area to be checked into a lightweight network, and inputting output results of a plurality of bottleneck layers of the lightweight network into a path aggregation network to obtain multi-channel basic image characteristics;
inputting the multi-channel basic image features into a spatial pyramid pooling network, extracting to obtain multi-channel high-dimensional image features with standard dimensions, inputting the high-dimensional image features into a sub-pixel convolution network, and respectively inserting the low-resolution high-dimensional image features into a high-resolution feature spectrum to enhance the feature quality of the high-dimensional image features;
and performing feature fusion on the high-dimensional image features for enhancing the feature quality by using 1 x 1 convolution kernel to obtain multi-channel fusion image features, inputting the fusion image features into a classification network and a positioning network respectively, and identifying the position coordinates of the to-be-inspected area in the standard inspection image by combining with an output result.
And the acceptance information generating module is used for generating the relevant acceptance information of the acceptance item according to the comparison and analysis result. And the acceptance result generating module is used for generating a final acceptance result of the acceptance item according to the relevant acceptance information confirmed by the user.
When the data comparison module judges that the difference between the detection data and the acceptance rule is in the threshold range, the acceptance information generation module judges that the detection data is qualified for acceptance, and meanwhile, the relevant acceptance information is generated and stored in the acceptance information storage module, and the user network node authenticates the acceptance information.
And the early warning information generating module is used for generating acceptance early warning information according to the final acceptance result of the acceptance item. And the early warning information generation module comprehensively analyzes the final acceptance result of the acceptance project and generates acceptance early warning information according to the difference between the detection data and the acceptance rule and the acceptance qualification proportion of the detection data.
According to the technical scheme, the image identification detection module can be used for accurately identifying the area to be checked and accepted from the checking and accepting image, the area to be checked and accepted is detected according to the identification result, detection data are generated, the data comparison module acquires the corresponding relevant checking and accepting rule from the checking and accepting rule generation module based on the identification result, the detection data and the relevant checking and accepting rule are subjected to comparison analysis, the relevant checking and accepting information is generated through the checking and accepting information generation module, the checking and accepting information is authenticated through the user network node, and the purpose of comprehensively evaluating the quality of the construction project and ensuring the accuracy of the final checking and accepting result of the checking and accepting project is achieved.
In this application technical scheme, still including the measured data receiving module that is used for receiving the on-the-spot actual measurement data that sends to and be used for replacing the measured data for measured data's measured data replacement module, when the contrastive analysis result deviation of data comparison module is great, measured data replacement module is with measured data replacement for on-the-spot actual measurement data, and carry out contrastive analysis to on-the-spot actual measurement data and relevant acceptance rule.
When the deviation of the comparison and analysis result of the data comparison module is large, the detection data generated by the image identification detection module can be replaced by the field actual measurement data through the detection data replacement module, so that the accuracy of the comparison and analysis result of the data comparison module can be ensured, and the accuracy of the final acceptance result of the acceptance item can be ensured.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (10)
1. The utility model provides an intelligent building engineering quality inspection management system which characterized in that: the system comprises a server, a user network node and a non-user network node, wherein the user network node and the non-user network node are connected with the server;
the system also comprises an acceptance rule generating module which is used for generating a final acceptance rule under the condition that the user and the constructor confirm together;
the acceptance image receiving module is used for receiving an acceptance image sent on site;
the image identification detection module is used for identifying the area to be checked in the checking image, detecting the area to be checked according to the identification result and generating detection data;
the data comparison module is used for acquiring a corresponding related acceptance rule from the acceptance rule generation module based on the identification result of the image identification detection module and performing comparison analysis on the detection data and the related acceptance rule;
the acceptance information generating module is used for generating relevant acceptance information of the acceptance item according to the comparison and analysis result;
the acceptance result generating module is used for generating a final acceptance result of the acceptance item according to the relevant acceptance information confirmed by the user;
the early warning information generating module is used for generating acceptance early warning information according to the final acceptance result of the acceptance item;
the image recognition detection module pre-recognizes the acceptance image, intercepts at least one to-be-accepted region from the acceptance image, extracts multi-channel basic image features from the to-be-accepted region, extracts multi-channel high-dimensional image features on the basis of ensuring that the basic image features are not lost, performs feature fusion to obtain multi-channel fusion image features, and obtains a recognition result based on the fusion image features.
2. The intelligent construction engineering quality acceptance management system according to claim 1, characterized in that: the image recognition detection module carries out pre-recognition on the acceptance image, intercepts at least one to-be-accepted area from the acceptance image and comprises:
and carrying out binarization processing, corrosion and/or expansion processing on the acceptance image, carrying out edge point detection on the processed image, carrying out connected domain detection on the detected edge point, and intercepting a corresponding area to be accepted in the acceptance image based on the position coordinates of each connected domain.
3. The intelligent construction project quality acceptance management system according to claim 2, wherein: the method for extracting the multi-channel basic image features in the region to be checked comprises the following steps:
and inputting the area to be checked into the lightweight network, and inputting output results of a plurality of bottleneck layers of the lightweight network into the path aggregation network to obtain the multichannel basic image characteristics.
4. The intelligent construction engineering quality acceptance management system according to claim 3, wherein: the method for extracting the multi-channel high-dimensional image features on the basis of ensuring that the basic image features are not missing comprises the following steps:
inputting the multi-channel basic image features into a spatial pyramid pooling network, extracting to obtain multi-channel high-dimensional image features with standard dimensions, inputting the high-dimensional image features into a sub-pixel convolution network, and respectively inserting the low-resolution high-dimensional image features into a high-resolution feature spectrum to enhance the feature quality of the high-dimensional image features.
5. The intelligent construction engineering quality acceptance management system according to claim 4, wherein: the obtaining of the multi-channel fusion image characteristics after the characteristic fusion, and the obtaining of the identification result based on the fusion image characteristics, comprises:
and performing feature fusion on the high-dimensional image features for enhancing the feature quality by using the convolution kernel of 1 to obtain multi-channel fusion image features, inputting the fusion image features into a classification network and a positioning network respectively, and identifying the position coordinates of the to-be-checked area in the standard checking image by combining the output result.
6. The intelligent construction project quality acceptance management system according to claim 1, wherein: the server receives the construction acceptance rules sent by the non-user network nodes and stores the construction acceptance rules into an acceptance rule storage module, and the user network nodes modify/authenticate the construction acceptance rules;
and after the user network node is modified/authenticated, the server stores the construction acceptance rule to the acceptance rule storage module again until the two sides confirm the texts which are not modified any more.
7. The intelligent construction project quality acceptance management system according to claim 6, wherein: and when both parties confirm the text which is not modified any more, the server generates a final acceptance rule through an acceptance rule generating module according to the text which is not modified any more.
8. The intelligent construction project quality acceptance management system according to claim 1, wherein: when the data comparison module judges that the difference between the detection data and the acceptance rule is in the threshold range, the acceptance information generation module judges that the detection data is qualified for acceptance, generates relevant acceptance information at the same time, stores the relevant acceptance information into the acceptance information storage module, and authenticates the acceptance information by the user network node.
9. The intelligent construction project quality acceptance management system according to claim 8, wherein: and the early warning information generation module comprehensively analyzes the final acceptance result of the acceptance project and generates acceptance early warning information according to the difference between the detection data and the acceptance rule and the acceptance qualification proportion of the detection data.
10. The intelligent construction project quality acceptance management system according to claim 9, wherein: the system also comprises an actual measurement data receiving module for receiving the actual measurement data sent on site and a detection data replacing module for replacing the detection data with the actual measurement data, wherein when the contrast analysis result of the data comparing module has larger deviation, the detection data replacing module replaces the detection data with the actual measurement data on site and performs contrast analysis on the actual measurement data on site and the relevant acceptance rules.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115865720A (en) * | 2023-02-27 | 2023-03-28 | 华中科技大学 | Construction acceptance management method and system based on block chain cross-chain network |
| CN116630974A (en) * | 2023-05-17 | 2023-08-22 | 广东智云城建科技有限公司 | Quick marking processing method and system for building image data |
| CN116823026A (en) * | 2023-06-05 | 2023-09-29 | 北京世拓天宇科技有限公司 | Engineering data processing system and method based on block chain |
| CN116976722A (en) * | 2023-06-28 | 2023-10-31 | 三峡科技有限责任公司 | Intelligent construction acceptance system based on big data |
| CN117237566A (en) * | 2023-11-16 | 2023-12-15 | 天宇正清科技有限公司 | House acceptance method, device, equipment and computer readable storage medium |
-
2022
- 2022-02-23 CN CN202210171051.5A patent/CN114745399A/en not_active Withdrawn
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115865720A (en) * | 2023-02-27 | 2023-03-28 | 华中科技大学 | Construction acceptance management method and system based on block chain cross-chain network |
| CN115865720B (en) * | 2023-02-27 | 2023-04-14 | 华中科技大学 | Construction acceptance management method and system based on block chain cross-chain network |
| CN116630974A (en) * | 2023-05-17 | 2023-08-22 | 广东智云城建科技有限公司 | Quick marking processing method and system for building image data |
| CN116630974B (en) * | 2023-05-17 | 2024-02-02 | 广东智云城建科技有限公司 | Quick marking processing method and system for building image data |
| CN116823026A (en) * | 2023-06-05 | 2023-09-29 | 北京世拓天宇科技有限公司 | Engineering data processing system and method based on block chain |
| CN116823026B (en) * | 2023-06-05 | 2024-05-31 | 中建正大科技有限公司 | Engineering data processing system and method based on block chain |
| CN116976722A (en) * | 2023-06-28 | 2023-10-31 | 三峡科技有限责任公司 | Intelligent construction acceptance system based on big data |
| CN117237566A (en) * | 2023-11-16 | 2023-12-15 | 天宇正清科技有限公司 | House acceptance method, device, equipment and computer readable storage medium |
| CN117237566B (en) * | 2023-11-16 | 2024-02-09 | 天宇正清科技有限公司 | House acceptance method, device, equipment and computer readable storage medium |
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