Traffic construction project completion detection method, system, medium and program product

Abstract

A traffic construction project completion detection method, system, medium and program product, in which the accuracy of the completion detection is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of traffic engineering detection, and particularly relates to a traffic construction project completion detection method and system, a medium and a program product. BACKGROUND

[0002] With the continuous expansion of the scale of traffic construction projects, the workload and complexity of project completion detection are increasing. Previously, traffic construction project completion detection was mainly completed by manual operation. Detection personnel need to manually record a large amount of detection data and compare these data with standards. This way not only has low work efficiency, but also is prone to data recording errors, missing detection items and other problems, which seriously affects the accuracy and reliability of the detection results.

[0003] In related technologies, an electronic detection information management platform can be established to realize automatic collection and storage of detection data, and the corresponding products are detected according to the detection information submitted by the construction unit to achieve the purpose of sampling detection, thereby improving the efficiency of project completion detection.

[0004] However, the samples for sampling detection by the current detection institution depend on the samples submitted by the construction unit. The construction unit may submit products that are determined to pass the detection, thereby reducing the randomness of sampling detection. Moreover, the construction unit may submit the report for detection before the project is completed, and the products that continue to be produced after detection lack detection, thereby reducing the accuracy of project completion detection. SUMMARY

[0005] The application provides a traffic construction project completion detection method, system, medium and program product, which are used to improve the accuracy of project completion detection.

[0006] In a first aspect, the application provides a traffic construction project completion detection method. In the case where a construction unit reports the information of a completed construction project, random sampling is performed in a detection sample library to obtain a preset number of detection numbers, and an initial detection report is generated.

[0007] It is determined whether there is a sample in the project information whose number is the same as the detection number.

[0008] If there is a sample whose number is the same as the detection number, a sample to be detected whose number is the same as the detection number is determined in the project information, and standard related information of the sample to be detected is extracted.

[0009] A detection work order corresponding to each sample to be detected is generated, and each detection work order is sent to a detection personnel terminal.

[0010] In a case where it is determined that the detection result input by the detection personnel terminal is received, the detection result is input into the handover detection system and compared with each standard-related information one by one;

[0011] An comparison result of each to-be-detected sample output by the handover detection system is obtained, and the comparison result is qualified or unqualified;

[0012] It is judged whether there is an unqualified comparison result;

[0013] If there is no unqualified, the detection result and the comparison result are added to an initial detection report to obtain a first final detection report;

[0014] If there is unqualified, the detection result and the to-be-detected sample corresponding to the unqualified are set in a preset format and added to the initial detection report to obtain a second final detection report;

[0015] If there is no all same sample, it is determined that a missing sample exists, and a defective to-be-detected sample with the same detection number as the detection number in the engineering information and standard-related information corresponding to the defective to-be-detected sample are determined, a detection work order corresponding to the to-be-detected sample is generated, and each detection work order is sent to the detection personnel terminal;

[0016] After the first final detection report or the second final detection report is generated, the missing sample is set in a preset format and added to the first final detection report or the second final detection report to obtain a third final detection report.

[0017] By adopting the above technical solution, the detection number is obtained by random sampling in the detection sample library, and classification processing is performed according to whether there is a sample with the same number in the engineering information, which improves the standardization and normalization of the detection process. The system automatically generates a detection work order and sends it to the detection personnel terminal, reducing the manual operation link and improving the work efficiency. The automatic comparison and classification processing mechanism of the detection result enables the qualified and unqualified samples to be processed in different ways, and the preset format ensures the standardization of the detection report. The special processing flow for the missing sample improves the completeness and accuracy of the detection report. The possibility of human error is reduced, the quality and reliability of the detection work are improved, and the traceability and reviewability of the detection data are improved through the standardized process and format specification.

[0018] In combination with some embodiments of the first aspect, in some embodiments, random sampling is performed in the detection sample library to obtain a preset number of detection numbers, specifically including:

[0019] Each sample in the engineering information to be completed by the construction unit is randomly assigned a matching number to obtain a detection sample library;

[0020] Randomly sample in the detection sample library to obtain a preset number of samples;

[0021] Determine the matching numbers corresponding to the preset number of samples to obtain a preset number of detection numbers.

[0022] By using the above technical solutions, the samples in the engineering information are randomly matched with the numbers, the detection sample library is established, and the random sampling in the sample library is performed, so that the randomness of the detection sample selection is improved. The mechanism of random matching with the numbers reduces the possibility of human intervention and improves the objectivity of the sampling process. The preset number limitation mechanism ensures the reasonable allocation of the detection workload and the optimization of the resource utilization, reduces the human manipulation in the detection process, improves the representativeness and credibility of the detection results, and optimizes the configuration efficiency of the detection resources.

[0023] In combination with some embodiments of the first aspect, in some embodiments, the detection work order corresponding to the sample to be detected is generated, and specifically includes:

[0024] The sample to be detected is sorted according to the construction process sequence to obtain a construction process sequence;

[0025] According to the standard related information of the sample to be detected, the detection standard parameters and the determination threshold values corresponding to each construction process are extracted;

[0026] A process detection flowchart is generated in combination with the construction process sequence, and the process detection flowchart includes the detection sequence between the construction processes;

[0027] A detection linkage mechanism between the construction processes is set based on the process detection flowchart, and the detection linkage mechanism includes the transmission relationship of the detection results and the mutual verification rule;

[0028] A detection work order template is generated according to the process detection flowchart and the detection linkage mechanism;

[0029] The detection standard parameters and the determination threshold values are filled into the detection work order template to obtain a detection work order.

[0030] By using the above technical solutions, the sample to be detected is sorted according to the construction process sequence, and the process detection flowchart is generated in combination with the detection standard parameters and the determination threshold values, so that a systematic detection flowchart management mechanism is established. The detection linkage mechanism reduces the omission and errors of the detection links by realizing the automatic transmission and mutual verification of the detection results between the processes. The automatic generation of the detection work order template and the parameter filling mechanism reduce the manual input links and improve the work efficiency. Through the standardized work order generation process, the standardization and consistency of the detection work are ensured, and the controllability and accuracy of the detection process are enhanced by setting the detection linkage mechanism.

[0031] In some embodiments of the first aspect, after the missing sample is set to the preset format and added to the first final detection report or the second final detection report to obtain the third final detection report, the method further comprises:

[0032] determining a final detection report, the final detection report being the first final detection report, the second final detection report, or the third final detection report;

[0033] receiving a self-check detection report sent by the construction unit, and determining whether the self-check detection report is the same as the final detection report;

[0034] if the self-check detection report is the same as the final detection report, recording the final detection report in a handover and completion detection system;

[0035] increasing a credit score of a preset value of the construction unit in the handover and completion detection system;

[0036] if the self-check detection report is not the same as the final detection report, deducting the credit score of the preset value in the handover and completion detection system;

[0037] sending a preset warning information to a management department terminal.

[0038] By using the above technical solution, the final detection report is compared with the self-check detection report of the construction unit, and a credit score reward and punishment mechanism is established, forming a quality supervision system. The automatic comparison and scoring mechanism of the system reduces the workload of manual operation and improves the supervision efficiency. The dynamic adjustment mechanism of the credit score effectively motivates and constrains the construction unit, prompting the construction unit to improve the self-check quality and work responsibility. The automatic push function of the warning information enables the management department to discover and handle problems in a timely manner, improving the timeliness and effectiveness of quality supervision.

[0039] In some embodiments of the first aspect, after the final detection report is compared with the self-check detection report of the construction unit, the method further comprises:

[0040] obtaining a total credit score of the construction unit, and determining a change number of a value change mode of the total credit score in a case where the total credit score is greater than a preset minimum credit score, the value change mode being increase or decrease;

[0041] in a case where the change number of the increase value change mode is less than the change number of the decrease value change mode, marking the construction unit as a warning construction unit.

[0042] By adopting the technical solution, the total credit score of the construction unit is obtained, and when the total credit score is greater than the preset minimum credit score, the credit status of the construction unit is judged according to the number of changes in the credit score value change mode. When the number of increasing changes is less than the number of decreasing changes, the construction unit is marked as a pre-warning construction unit. Based on the absolute value of the credit score, the trend of the credit score change is considered, so that the system can timely discover the tendency of the deterioration of the credit status of the construction unit. By observing the change trend of the credit score, even if the current credit score of the construction unit has not decreased to the minimum standard, the system can also identify potential problem construction units in advance. It can help the management department to take preventive measures before the construction quality problem causes serious consequences, reduce the engineering quality risk, reduce the rework cost, and improve the forward-looking and initiative of construction quality management.

[0043] In combination with some embodiments of the first aspect, in some embodiments, after determining the final detection report, the method further comprises:

[0044] According to the final detection report, dynamic quality assessment and static quality assessment are respectively performed on the completed construction product, to obtain corresponding dynamic quality assessment results and static quality assessment results;

[0045] A multi-level dynamic quality assessment system is established according to a preset multi-level hierarchical structure, and the preset multi-level hierarchical structure includes a construction project layer, a bid section layer, a unit engineering layer, a division engineering layer, and a detection parameter layer;

[0046] According to the investment amount information and the weight coefficient of each level of the multi-level dynamic quality assessment system, a hierarchical scoring calculation model is constructed in combination with the dynamic quality assessment results;

[0047] The result of the scoring calculation model is compared with a preset quality threshold to generate a real-time quality state report;

[0048] The real-time quality state report is pushed to a preset management platform at a preset time interval.

[0049] By adopting the technical solution, a multi-level dynamic quality assessment system is established, and different levels such as the construction project layer, the bid section layer, the unit engineering layer, the division engineering layer, and the detection parameter layer are systematically managed. In combination with the investment amount information and the weight coefficient of each level, a hierarchical scoring calculation model is constructed, so that the quality assessment results are more objective and accurate. By comparing the result of the scoring calculation model with a preset quality threshold, a real-time quality state report is generated, and is pushed to a preset management platform at a preset time interval, so that dynamic monitoring of the engineering quality state is realized, which facilitates timely discovery and positioning of quality problems and improves the quality management efficiency. The dynamic assessment and real-time pushing mechanism enables management personnel to timely master the engineering quality change situation and make a quick response, effectively preventing and controlling the engineering quality risk.

[0050] In some embodiments of the first aspect, in some embodiments, the construction product that has completed construction is respectively subjected to dynamic quality assessment and static quality assessment according to the final detection report, to obtain corresponding dynamic quality assessment results and static quality assessment results, specifically comprising:

[0051] The dynamic scores of the detection parameters are calculated according to the detection parameter data in the final detection report and the preset scoring standard;

[0052] The weight coefficient of the sub-division engineering is obtained, and the dynamic scores are weighted and calculated according to the weight coefficient to obtain the dynamic scores of the sub-division engineering;

[0053] The investment amount data of the unit engineering and the bid section are extracted, and the dynamic scores of the sub-division engineering are weighted and calculated with the investment amount data as the weight to obtain the dynamic quality assessment results;

[0054] The appearance quality assessment table and the quality assurance data assessment table are received, and the deduction items of the appearance quality assessment table and the quality assurance data assessment table are extracted based on the preset deduction rules to generate a deduction list;

[0055] The static quality assessment results are obtained according to the dynamic quality assessment results and the deduction list.

[0056] By using the above technical solution, the detection parameter data is subjected to dynamic score calculation, and the weight coefficient of the sub-division engineering is used for weighted calculation, and the investment amount data is used as the weight to calculate the dynamic quality assessment results, and the deduction items of the appearance quality assessment and the quality assurance data assessment are considered, and finally the static quality assessment results are obtained. This evaluation method combines quantitative detection data with qualitative evaluation, considers the importance of each part of the engineering, and also considers the influence of the investment scale, so that the evaluation results are more scientific and reasonable. Through the combination of dynamic quality assessment and static quality assessment, the engineering quality condition can be comprehensively reflected, the one-sidedness caused by a single evaluation method can be reduced, a more reliable basis for engineering quality management is provided, and the accuracy and reliability of quality management are improved.

[0057] In the second aspect, the embodiments of the present application provide a traffic construction project completion detection system, which comprises one or more processors and a memory; the memory is coupled with the one or more processors, and is used to store computer program codes, the computer program codes comprising computer instructions, and the one or more processors invoke the computer instructions to enable the system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0058] In the third aspect, the embodiments of the present application provide a computer readable storage medium comprising instructions, when the instructions run on a system, enable the system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0059] In a fourth aspect, the embodiments of the present application provide a computer program product, characterized in that when the computer program product runs on a system, the system executes the method described in any possible implementation manner of the first aspect.

[0060] The one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0061] 1. The present application provides a traffic construction project handover detection method, which randomly samples detection numbers in a detection sample library and classifies according to whether there are samples with the same number in the engineering information, thereby improving the standardization and normalization of the detection process. The system automatically generates detection work orders and sends them to the detection personnel terminal, reducing the manual operation link and improving the work efficiency. The automatic comparison and classification processing mechanism of the detection results enables the qualified and unqualified samples to be treated differently, and the preset format ensures the standardization of the detection report. The special processing flow for missing samples improves the completeness and accuracy of the detection report. Reducing the possibility of human error improves the quality and reliability of the detection work, and through standardized processes and format specifications, the traceability and reviewability of the detection data are improved.

[0062] 2. The present application provides a traffic construction project handover detection method, which compares the final detection report with the self-detection report of the construction unit and establishes a credit score reward and punishment mechanism, forming a quality supervision system. The automatic comparison and scoring mechanism of the system reduces the workload of manual operation and improves the supervision efficiency. The dynamic adjustment mechanism of the credit score effectively motivates and constrains the construction unit, prompting the construction unit to improve the self-detection quality and work responsibility. The automatic push function of the early warning information enables the management department to timely discover and handle problems, improving the timeliness and effectiveness of quality supervision.

[0063] 3. The present application provides a traffic construction project handover detection method, which establishes a multi-level dynamic quality evaluation system to systematically manage different levels such as the construction project layer, the bid section layer, the unit engineering layer, the sub-division engineering layer, and the detection parameter layer. Combined with the investment amount information and weight coefficients of each level, a hierarchical scoring calculation model is constructed, making the quality evaluation results more objective and accurate. By comparing the results of the scoring calculation model with the preset quality threshold, a real-time quality status report is generated and pushed to the preset management platform at a preset time interval, realizing dynamic monitoring of the engineering quality, facilitating timely discovery and positioning of quality problems, and improving the quality management efficiency. The dynamic evaluation and real-time push mechanism enables management personnel to timely grasp the engineering quality changes and respond quickly, effectively preventing and controlling engineering quality risks. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1 is a flowchart of a traffic construction project completion detection method in an embodiment of the present application.

[0065] Figure 2 is another flowchart of a traffic construction project completion detection method in an embodiment of the present application.

[0066] Figure 3 is an entity device structure diagram of a traffic construction project completion detection system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0067] The terms used in the following embodiments of the present application are only for the purpose of describing the specific embodiments and are not intended to be limiting of the present application. As used in the specification and the appended claims of the present application, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or," as used in the present application, refers to any or all possible combinations of one or more of the associated listed items.

[0068] Hereinafter, the terms "first" and "second" are only for the purpose of description and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0069] The following describes an embodiment of the present application with reference to the accompanying drawings. Figure 1 A traffic construction project completion detection method in an embodiment of the present application is described.

[0070] Please refer to Figure 1 is a flowchart of a traffic construction project completion detection method in an embodiment of the present application.

[0071] S101, in the case of determining that the construction unit reports the completed construction project information for detection, randomly sampling in the detection sample library to obtain a preset number of detection numbers, and generating an initial detection report;

[0072] In the case of determining that the construction unit reports the completed construction project information for detection, randomly sampling in the detection sample library, specifically: randomly assigning a matching number to each sample in the construction unit to be completed project information to obtain a detection sample library;

[0073] Randomly sampling in the detection sample library to obtain a preset number of samples;

[0074] The matching numbers corresponding to the preset number of samples are determined to obtain a preset number of detection numbers. After that, an initial detection report is generated.

[0075] This step reports the engineering information completed by the construction unit to the detection sample library, and randomly samples a preset number of detection numbers, and finally generates an initial detection report. Specifically, the system randomly assigns a matching number to each sample in the engineering information to be completed by the construction unit to construct a detection sample library. Then, the system randomly selects a preset number of samples from the detection sample library, and extracts the matching numbers corresponding to these samples as detection numbers. Finally, the system generates an initial detection report based on the selected samples, laying a foundation for subsequent detection work.

[0076] In this step, the system can use various random algorithms to extract samples from the detection sample library, such as simple random sampling, stratified sampling, etc., to ensure the representativeness of the samples. In addition, the system can also classify samples according to factors such as engineering type, construction stage, etc., and extract samples of different categories to improve the pertinence of detection. For the number of samples extracted, the system can dynamically adjust according to factors such as engineering scale, construction progress, etc., to balance the cost and quality of detection.

[0077] S102, judge whether there is a sample in the engineering information whose number is the same as the detection number;

[0078] This step judges whether there is a sample in the engineering information whose number is the same as the detection number, which is a simple logical judgment and will not be described here.

[0079] S103, determine the to-be-detected sample in the engineering information whose number is the same as the detection number, and extract the standard related information of the to-be-detected sample;

[0080] If there is a sample whose number is the same as the detection number, determine the to-be-detected sample in the engineering information whose number is the same as the detection number, and extract the standard related information of the to-be-detected sample.

[0081] If there is, determine these samples with the same number as the to-be-detected sample, and extract their standard related information to prepare for subsequent detection.

[0082] The system can use hash algorithm, string matching and other technologies to quickly judge whether there is a sample in the engineering information whose number is the same as the detection number. For a large number of engineering information, the system can also use a distributed computing framework to improve the judgment efficiency. Once the to-be-detected sample is determined, the system extracts its standard related information, such as material specifications, construction technology, etc., for formulating a detection scheme.

[0083] S104, generate a detection work order corresponding to each to-be-detected sample, and send each detection work order to the detection personnel terminal;

[0084] generating a detection work order corresponding to each sample to be detected, and sending each detection work order to a detection personnel terminal, specifically: sorting the samples to be detected according to the construction process sequence to obtain a construction process sequence;

[0085] According to the standard related information of the sample to be detected, the detection standard parameters and the determination threshold corresponding to each construction process are extracted;

[0086] Generate a process detection flowchart based on the construction process sequence, which includes the detection sequence between each construction process;

[0087] Based on the process detection flowchart, set the detection linkage mechanism between each construction process, and the detection linkage mechanism includes the transmission relationship of the detection results and the mutual verification rules;

[0088] Generate a detection work order template according to the process detection flowchart and the detection linkage mechanism;

[0089] Fill in the detection standard parameters and the determination threshold into the detection work order template to obtain the detection work order.

[0090] This step generates a corresponding detection work order according to the characteristics of the sample to be detected, and distributes the detection work order to the detection personnel. Specifically, the system first sorts the samples to be detected according to the construction process sequence to form a construction sequence. Then, the system draws a process detection flowchart based on the standard parameters and determination threshold of each construction process, and clearly defines the detection sequence of each process. On this basis, the system sets the detection linkage mechanism between processes and specifies the transmission and mutual verification rules of the detection results. Finally, the system fills in the standard parameters and threshold based on the process flowchart to generate a detection work order template, and instantiates it into a specific detection work order.

[0091] When generating a detection work order, the system can fully consider the characteristics of the sample to be detected, such as building type, construction stage, etc., and customize a highly targeted work order template. In addition, the system can also optimize the allocation strategy of the work order according to the professional expertise, workload, etc. of the detection personnel, and improve the detection efficiency. For complex projects, the system can also introduce a workflow engine to realize the automatic circulation and approval of the work order, reducing manual intervention.

[0092] When designing the detection linkage mechanism, the system may face problems such as complex inter-process dependency relationships and imperfect linkage rules. Therefore, the system can introduce ontology modeling technology to construct a knowledge graph of inter-process dependency relationships, and infer implicit linkage rules based on the graph. At the same time, the system can also continuously improve the linkage rule library through case learning, expert experience summary, etc. By optimizing the generation mechanism of the detection work order, the system can more efficiently and more standardized guide the detection work, and improve the engineering quality.

[0093] S105, in the case of determining that the detection result input by the detection personnel terminal is received, inputting the detection result into the handover and completion detection system to one by one compare with each standard related information;

[0094] In the data entry stage, the system can provide the detection personnel with a standardized data collection interface and entry template, guiding them to fill in the detection original data truthfully according to the work order requirements. At the same time, the system can also use Internet of Things sensors, mobile terminals and other automated means to collect detection process parameters in real time, reducing manual input links and improving data accuracy and reliability. The entered data is subjected to integrity check and logic audit by the system before being officially put into the comparison link.

[0095] In the comparison stage, the system first matches the detection result data with the quality standards specified in the work order, extracts the corresponding qualified value range, allowable deviation and other judgment basis. Then, the system uses scientific statistical methods such as hypothesis testing, confidence interval estimation, etc. to analyze the distribution characteristics of the detection data and compare them with the quality judgment conditions to give the pass or fail judgment of the single result. Next, the system can also consider the correlation between each single result, use weighted average, logical combination and other models to calculate comprehensive indicators to judge the overall qualification of the sample. For the judgment of qualitative indicators, the system can introduce fuzzy logic, evidence theory and other uncertainty reasoning methods to give relatively objective judgment results combined with the qualitative description of the detection personnel.

[0096] In the comparison process, the system may encounter problems such as lagging quality standards and lagging detection methods, resulting in insufficient scientificity and accuracy of the judgment. To solve these problems, the system should establish a dynamic updating mechanism for standard specifications and continuously optimize the relevant provisions according to new technologies and methods in engineering construction. In terms of detection means, the system can integrate new non-destructive testing, online monitoring and other technologies to expand the depth and breadth of detection. At the same time, the system should also support flexible comparison strategy configuration, allowing different judgment rules to be set according to the importance of the project, the risk level, etc. to improve the pertinence of quality control. In addition, in the face of the trend of increasing detection data, the system can also use big data analysis, machine learning and other emerging technologies to continuously optimize the judgment model and threshold, and constantly improve the intelligent level of the judgment.

[0097] S106, obtaining the comparison result of each to-be-detected sample output by the handover and completion detection system;

[0098] Obtaining the comparison result of each to-be-detected sample output by the handover and completion detection system, the comparison result being qualified or unqualified.

[0099] When obtaining the comparison result, the system extracts the qualified state of the single detection index on one hand, and comprehensively judges the overall qualifiedness of the sample on the other hand. For the single index, the system mainly matches the comparison result with the preset condition through logical judgment to obtain the conclusion of whether the quality requirement is met. For example, for quantitative indexes such as strength and size, the system judges whether they are within the specified allowable range; for qualitative indexes such as appearance and performance, the system judges whether they meet the qualitative description specified in the standard. For comprehensive judgment, the system needs to form a complete judgment spectrum according to the weighting rules, combination logic and the like specified in the quality standard on the basis of single comparison, make a grade division on the quality level of the sample, and give a unified conclusion of whether it is qualified or not.

[0100] S107, judging whether there is a comparison result that is unqualified;

[0101] This step judges the comparison result of each sample to be detected output by the system, and the purpose is to identify the detection batch with unqualified items.

[0102] S108, adding the detection result and the comparison result to the initial detection report to obtain a first final detection report;

[0103] If there is no unqualified item, the detection result and the comparison result are added to the initial detection report to obtain a first final detection report.

[0104] When it is judged that there is no unqualified item in the detection batch, the system adds the detection result and the comparison result of all samples to be detected to the initial detection report to generate a complete detection report as the final result of this detection.

[0105] In specific implementation, the system can use a document template engine such as Apache POI, iText, etc. to fill the detection and comparison data into a predefined report template. The system will read the original detection record of each sample to be detected one by one, extract the key data such as sample number, detection item name, quantitative result, technical index, etc. from it, and map these data to the corresponding fields in the template. At the same time, the system will also extract the comparison result and convert it into a suitable text expression for report display, such as “detection value XX, meets standard requirements, judged qualified”, and add it to the corresponding chapter of the report. After the data filling is completed, the system will automatically compile and render the template to generate a detection report document with complete structure and detailed content.

[0106] S109, setting the detection result corresponding to the unqualified item and the sample to be detected to a preset format and adding them to the initial detection report to obtain a second final detection report;

[0107] If there is an unqualified item, the detection result corresponding to the unqualified item and the sample to be detected are set to a preset format and added to the initial detection report to obtain a second final detection report.

[0108] When it is determined that there are unqualified items in the detection batch, the system adds the sample information and detection results corresponding to the unqualified detection items to the initial detection report in a special format, generates a detection report containing unqualified items as the final result of this detection, so that relevant parties can quickly identify problems and develop corrective measures.

[0109] When generating the report, in addition to filling in normal detection and comparison data, the system also needs to highlight and prominently display unqualified item data. For example, the system can use bold, underlined, etc. format for the basic information of unqualified samples, and use red font, background highlighting, etc. for unqualified detection results, so that they are immediately apparent in the report. At the same time, the system can also set a prominent warning prompt at the beginning of the report, listing all unqualified item names, sample numbers and other key information, to help report users quickly locate the problem. In addition, the system should also list the determination basis when filling in the unqualified detection records, and give specific deviation degree, over-standard multiple and other quantitative indicators, to provide a basis for subsequent analysis of problem causes and determination of disposal measures.

[0110] While highlighting unqualified information, the system should also avoid affecting the overall structure of the report and the listing of normal data. For example, the system can reserve a fixed area in the template to display unqualified items, and avoid covering other detection records when adding; it can also set a separate unqualified item summary table at the end of the article, displayed separately from normal detection data, to ensure that the report layout is reasonable and the focus is prominent. In view of the possible data omissions, format errors and other problems, the system should pre-set an exception handling mechanism, set default values, supplementary notes, etc., to maximize the integrity of the report, and if necessary, it can also mark suspected abnormalities that need to be manually reviewed, and prompt for review.

[0111] S110, determining a missing sample, and determining a residual sample to be detected in the engineering information corresponding to the detection number and standard related information corresponding to the residual sample to be detected;

[0112] If there is no sample that is completely the same, a missing sample is determined, and a residual sample to be detected in the engineering information corresponding to the detection number and standard related information corresponding to the residual sample to be detected are determined, and the steps of steps S104-S109 are repeatedly executed.

[0113] When the system does not find a sample information that completely matches the detection number, it can be determined that there is a missing sample in the task. At this time, the system will determine the actual matching residual sample, and extract the corresponding standard specification information, and then repeatedly execute steps S104-S109 to realize partial detection of the detection task with missing samples. The key here is how to identify the most likely sample to be detected from the incomplete match.

[0114] In a specific implementation, the system can use a fuzzy matching algorithm, such as regular expression, edit distance, etc. When the match is not completely consistent, the system can still find the highest similarity candidate sample. For example, the system can use regular expression to describe the character pattern of the detected number, allow the characters in some positions to be different, set a similarity threshold, and consider it as a successful match if the threshold is exceeded. The minimum edit distance algorithm can also be used to calculate the minimum number of editing operations required to convert the detected number and each sample number to the same number, and the smallest number is the best match. The matched sample may not be complete, but it can still be detected according to the process, filling in the detection gaps and improving the task completion rate. The subsequent system can repeatedly execute the detection sub-process until all incomplete samples have been detected.

[0115] S111, in the case where it is determined that there is a missing sample, setting the missing sample to a preset format and adding it to the first final detection report or the second final detection report to obtain a third final detection report.

[0116] After generating the first final detection report or the second final detection report, and in the case where it is determined that there is a missing sample, setting the missing sample to a preset format and adding it to the first final detection report or the second final detection report to obtain a third final detection report.

[0117] When it is finally confirmed that there is a detection number that cannot be matched to a sample, i.e., there is a completely missing sample, the system should supplement the relevant information of the missing sample based on the generated detection report (the first or second final report) to form the final total report (the third final report) of the detection task, and comprehensively reflect the complete situation of the detection to the owner, the supervisor, etc.

[0118] In a specific implementation, the special format processing method of unqualified items can be used to highlight the missing sample in the report. The system can set a missing sample special explanation block in a suitable position of the detection report, list the detection numbers that are finally confirmed to be missing one by one, and note that they are finally unable to be associated with specific engineering samples after multiple matching and manual investigation. At the same time, the system should also analyze and list the information such as the project categories and process ranges that these missing samples may involve according to the detection scheme, so as to facilitate the relevant parties to understand the potential risk points of missing detection. If necessary, the system can also statistically analyze the proportion of missing samples in the total task to prompt the degree of detection completeness. Through the complete disclosure of missing samples, the system reflects the objective limitations of the detection work to the management and decision-making layer, which helps them to comprehensively evaluate the actual situation of the project, and also provides an objective basis for subsequent targeted retesting and management optimization.

[0119] In the above embodiments, the detection number is randomly sampled in the detection sample library, and the samples with the same number are classified according to whether the number exists in the engineering information, thereby improving the standardization and normalization of the detection process. The system automatically generates a detection work order and sends it to the detection personnel terminal, reducing the manual operation link and improving the work efficiency. The automatic comparison and classification processing mechanism of the detection results enables the qualified and unqualified samples to be treated differently, and the preset format ensures the standardization of the detection report. The special processing flow for missing samples improves the completeness and accuracy of the detection report. The possibility of human error is reduced, the quality and reliability of the detection work are improved, and the traceability and reviewability of the detection data are improved through standardized processes and format specifications.

[0120] The above embodiments describe a specific implementation process of a traffic construction project handover detection method. This method effectively improves the efficiency and accuracy of the detection work through standardized detection processes and automated data processing. To further strengthen the supervision of construction units and improve the engineering quality control level, the following describes another traffic construction project handover detection method in the embodiments of the present application: Figure 2

[0121] Please refer to Figure 2 for another flowchart of a traffic construction project handover detection method in the embodiments of the present application.

[0122] S201, determine the final detection report and receive the self-inspection detection report sent by the construction unit, and determine whether the self-inspection detection report and the final detection report are the same.

[0123] Determine the final detection report and receive the self-inspection detection report sent by the construction unit, and determine whether the self-inspection detection report and the final detection report are the same. The final detection report is the first final detection report, the second final detection report, or the third final detection report.

[0124] The core of this step is to compare the consistency of the self-inspection report submitted by the construction unit and the official final detection report. By determining whether the contents of the two reports are the same, the system can preliminarily evaluate the effectiveness and accuracy of the construction unit's self-inspection work, providing a basis for subsequent credit scoring and early warning management.

[0125] ​In implementation, the system first needs to determine the archiving of the official final inspection report. Since there are three different types of final reports (first, second and third final inspection reports), the system can use conditional judgment statements such as switch-case statements to handle different types of reports. In each case, the system obtains the self-inspection report uploaded by the construction unit through file reading and other methods, and compares the key elements of the two reports, such as detection items, sample numbers, test results, evaluation criteria, etc.

[0126] S202, enter the final inspection report into the handover and completion inspection system;

[0127] If the same, the final inspection report is entered into the handover and completion inspection system.

[0128] When the self-inspection report submitted by the construction unit is consistent with the official inspection conclusion, the system archives the final inspection report and formally enters it into the handover and completion inspection management system. This marks the successful completion of the inspection task and the self-inspection and self-checking work of the construction unit is also recognized by the system.

[0129] In specific implementation, the system can use file transfer, database writing and other methods to upload the electronic version of the final inspection report to the designated directory or data table of the management system. For different formats of report files, the system can automatically match the corresponding storage scheme through file type recognition and other technologies, such as storing Word documents as doc or docx format, storing PDF reports as pdf format, etc. At the same time, to ensure the security and non-tamperability of the archives, the system can also perform digital signature, time stamping and other processing on the uploaded report files to prevent subsequent malicious tampering. On the management system side, the system can automatically classify and index the newly entered report files through metadata extraction and other methods to form a standardized report archive library, facilitating subsequent business applications.

[0130] S203, increase the credit score of the construction unit preset value in the handover and completion inspection system;

[0131] When the self-inspection report is consistent with the final inspection conclusion, it indicates that the construction unit can objectively evaluate the engineering quality and its self-inspection and self-checking work is effective. In this case, the system should give positive incentives and appropriately increase its credit score in the handover and completion inspection management system to encourage it to maintain a good level of self-management.

[0132] The system can preset the reputation score adding rules under various incentive situations, and match the corresponding adding strategies for consistent reporting. For example, X points can be added for each consistent reporting, and Y points can be added for consistent reporting for N times in a row. Through cumulative points, the reputation rating of the construction unit is continuously improved. When calculating the new reputation score, the system can use atomic operations to read the current reputation score into memory, add the newly obtained reputation score, and then write back to the database to ensure data consistency. At the same time, the system can also use the database transaction mechanism to ensure the atomicity of the entire scoring process, avoiding abnormal situations such as loss of intermediate results and data rollback.

[0133] S204, deducting a preset value of reputation score in the handover and completion detection system;

[0134] If not, a preset value of reputation score is deducted in the handover and completion detection system.

[0135] When the self-inspection report submitted by the construction unit is inconsistent with the final detection conclusion, it means that its self-inspection and self-checking are formalistic and insufficient attention is paid to engineering quality problems. At this time, the system needs to use the reputation score punishment mechanism to urge it to strengthen quality management and eliminate fraudulent behavior.

[0136] In specific implementation, the system can refer to the corresponding deduction strategy corresponding to the adding rule, such as deducting X points for each inconsistent reporting, and deducting Y points for inconsistent reporting for N times in a row, to deduct from the existing reputation score of the construction unit and reduce its reputation level in the management system. When deducting points, the system can also use atomic operations and database transaction mechanisms to ensure the consistency and atomicity of reputation score changes. After completing the deduction, the system should immediately enable the punishment measures linked to the reputation level, such as limiting the construction unit to participate in new project bidding, increasing the frequency of daily inspection, etc., to force it to reflect on the problems in its management through reputation loss. At the same time, the system should also real-time feedback the reputation changes of the construction unit to the superior management department or the owner, facilitating the industry supervisory department to strengthen supervision.

[0137] S205, sending a preset warning information to a management department terminal;

[0138] When it is determined that the self-inspection report submitted by the construction unit is inconsistent with the final detection conclusion, in addition to directly deducting the reputation score, the system should also timely send a warning information to the relevant management department to prompt it to strengthen the supervision of the construction unit and prevent problems from occurring.

[0139] S206, obtaining the total reputation score of the construction unit, and determining the number of changes of the value change mode of the total reputation score in the case where the total reputation score is greater than a preset minimum reputation score;

[0140] obtaining the total credit score of the construction unit, and determining the number of changes in the numerical change mode of the total credit score in a case where the total credit score is greater than a preset minimum credit score, the numerical change mode being increase or decrease.

[0141] After the reward and punishment of the credit score of the construction unit are completed, the system should further analyze the overall situation of the credit change, reveal the dynamic change trend of the quality management level, and develop follow-up management with a clear target. The core here is to comprehensively inventory the cumulative credit situation of the construction unit, and focus on the volatility of the credit score.

[0142] S207, in a case where the number of changes in the numerical change mode being increase is less than the number of changes in the numerical change mode being decrease, marking the construction unit as a pre-warning construction unit.

[0143] When the system finds in the credit score fluctuation analysis that the credit deduction times of the construction unit are significantly more than the credit increase times, it reflects that the quality control situation of the construction unit is worrying, and it is very likely to become a high-incidence area of quality and safety accidents. At this time, it is necessary to set a key attention mark for the construction unit, strengthen the pre-warning and in-process control, and eliminate the quality risk in the embryonic state.

[0144] Specifically, the system performs subtraction operation on the credit change times of the construction unit based on the result of the credit fluctuation analysis, and obtains the difference between the credit decrease times and the credit increase times. When the difference is greater than 0, that is, the credit decrease times are dominant, the system can determine that the management level of the construction unit presents a negative change trend, and needs to be given pre-warning control, and therefore automatically adds a pre-warning construction unit label to the construction unit. The label can be added to the construction unit archive library, become a key attribute describing the credit situation of the construction unit, and be associated with other management data for analysis, to comprehensively depict the risk map of the construction unit.

[0145] In the above embodiment, the final detection report is compared with the self-detection report of the construction unit, and a credit score reward and punishment mechanism is established, forming a quality supervision system. The automatic comparison and scoring mechanism of the system reduces the workload of manual operation and improves the supervision efficiency. The dynamic adjustment mechanism of the credit score forms an effective incentive and constraint effect on the construction unit, and promotes the construction unit to improve the self-detection quality and work responsibility. The automatic pushing function of the pre-warning information enables the management department to discover and handle problems in time, and improves the timeliness and effectiveness of quality supervision.

[0146] Further, in another embodiment, after determining the final detection report in step S101, the method further comprises: performing dynamic quality assessment and static quality assessment on the construction product which has completed construction according to the final detection report, to obtain corresponding dynamic quality assessment result and static quality assessment result;

[0147] A multi-level dynamic quality evaluation system is established according to a preset multi-level hierarchy, and the preset multi-level hierarchy includes a construction project layer, a bid layer, a unit engineering layer, a sub-division engineering layer and a detection parameter layer. Specifically, the dynamic scores of each detection parameter are calculated according to the detection parameter data in the final detection report and a preset scoring standard;

[0148] The weight coefficients of the sub-division engineering are obtained, and the dynamic scores are weighted and calculated according to the weight coefficients to obtain the dynamic scores of the sub-division engineering;

[0149] The investment amount data of the unit engineering and the bid are extracted, and the dynamic scores of the sub-division engineering are weighted and calculated according to the investment amount data as the weight to obtain the dynamic quality evaluation result;

[0150] The appearance quality evaluation table and the quality assurance data evaluation table are received, and the deduction items of the appearance quality evaluation table and the quality assurance data evaluation table are extracted based on a preset deduction rule to generate a deduction list;

[0151] The static quality evaluation result is obtained according to the dynamic quality evaluation result and the deduction list;

[0152] The investment amount information and the weight coefficients of each level are calculated according to the multi-level dynamic quality evaluation system, and a hierarchical scoring calculation model is constructed in combination with the dynamic quality evaluation result;

[0153] The result of the scoring calculation model is compared with a preset quality threshold to generate a real-time quality state report;

[0154] The real-time quality state report is pushed to a preset management platform at a preset time interval.

[0155] Firstly, based on the final detection report, the system will perform double-dimension evaluation on the products that have completed construction, i.e. dynamic quality evaluation and static quality evaluation. Among them, the dynamic quality evaluation adopts a five-level evaluation system, from top to bottom, the construction project layer, the bid layer, the unit engineering layer, the sub-division engineering layer and the detection parameter layer, forming a complete quality evaluation hierarchy.

[0156] In the specific evaluation process, the system first calculates the dynamic scores of each detection parameter according to the detection parameter data in the final detection report in combination with the preset scoring standard. Then, the dynamic scores are weighted and calculated through the weight coefficients of the sub-division engineering to obtain the dynamic scores of the sub-division engineering. Subsequently, the system will extract the investment amount data of the unit engineering and the bid as the weight factor to further weight and calculate the dynamic scores of the sub-division engineering, and finally obtain the dynamic quality evaluation result.

[0157] For static quality assessment, the system receives appearance quality assessment table and quality assurance data assessment table, extracts relevant deduction items according to preset deduction rules, and generates a deduction list. Combined with dynamic quality assessment results and the deduction list, the system finally obtains static quality assessment results.

[0158] After completing the basic assessment, the system further calculates the investment information and weight coefficients of each level, and constructs a hierarchical scoring calculation model combined with the dynamic quality assessment results. The calculation results of the model are compared with the preset quality threshold to generate real-time quality status reports. These reports are regularly pushed to the preset management platform at preset time intervals to realize real-time monitoring and dynamic management of the quality status.

[0159] In the above embodiments, a multi-level dynamic quality assessment system is established to systematically manage different levels such as the construction project layer, bid layer, unit engineering layer, division engineering layer, and detection parameter layer. Combined with the investment information and weight coefficients of each level, a hierarchical scoring calculation model is constructed to make the quality assessment results more objective and accurate. By comparing the results of the scoring calculation model with the preset quality threshold, real-time quality status reports are generated and pushed to the preset management platform at preset time intervals to realize dynamic monitoring of the engineering quality status, facilitate timely discovery and positioning of quality problems, and improve quality management efficiency. The dynamic assessment and real-time pushing mechanism enables management personnel to timely grasp the engineering quality changes and make rapid responses to effectively prevent and control engineering quality risks.

[0160] The system in the embodiments of the present application will be described from the perspective of hardware processing. Please refer to Figure 3 An entity device structure diagram of a traffic construction project completion detection system provided by the embodiments of the present application.

[0161] It should be noted that, Figure 3 The structure of the system shown is only an example and should not impose any limitation on the functions and use range of the embodiments of the present application.

[0162] As Figure 3As shown, the system includes a Central Processing Unit (CPU) 301 which can perform various appropriate actions and processes, such as executing the methods in the above embodiments, according to programs stored in a Read-Only Memory (ROM) 302 or loaded from a storage section 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for operation of the system are also stored. The CPU 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0163] Connected to the I / O interface 305 are an input section 306 including a camera, an infrared sensor, and the like; an output section 307 including a Liquid Crystal Display (LCD), a speaker, and the like; the storage section 308 including a hard disk, and the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as necessary. A removable media 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 310 as necessary, so that a computer program read therefrom is installed into the storage section 308 as necessary.

[0164] In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing a computer program for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by the communication section 309, and / or installed from the removable media 311. When the computer program is executed by the Central Processing Unit (CPU) 301, various functions defined in the present application are performed.

[0165] It should be noted that the computer-readable medium in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus. In the present application, the computer-readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which carries computer-readable computer programs. Such a propagated data signal can take many forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above.

[0166] The flowcharts and block diagrams in the drawings illustrate the possible implementation architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Each block in the flowcharts or block diagrams can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different orders than that shown in the drawings. For example, two blocks that are shown in succession can actually be executed substantially in parallel, and sometimes in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams or flowcharts, and the combination of blocks in the block diagrams or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0167] As another aspect, the present application also provides a computer readable storage medium, which can be included in the system described in the above embodiments, or can exist independently without being assembled into the system. The above storage medium carries one or more computer programs, which, when executed by a processor of a system, enable the system to implement the method provided in the above embodiments.

[0168] The above embodiments are only used to illustrate the technical solutions of the present application, but not limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still make modifications to the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0169] In the above embodiments, according to the context, the term "when" can be interpreted as meaning "if" or "after" or "in response to determining" or "in response to detecting". Similarly, according to the context, the phrase "upon determining" or "if detecting (the stated condition or event)" can be interpreted as meaning "if determining" or "in response to determining" or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)".

[0170] In the above embodiments, all or some of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or some of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or some of the processes or functions described in the embodiments of the present application are generated. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer readable storage medium, or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be magnetic media (for example, floppy disk, hard disk, magnetic tape), optical media (for example, DVD), or semiconductor media (for example, solid state disk) and the like.

[0171] Those skilled in the art can understand that all or part of the processes in the above-mentioned method embodiments can be implemented by a computer program instructing relevant hardware to complete, the program can be stored in a computer readable storage medium, and the program can include the processes of the above-mentioned method embodiments when executed. The aforementioned storage medium includes ROM or random storage memory RAM, magnetic disc or optical disc and various storage code medium.

Claims

1. A method for inspection upon completion of transportation construction projects, applied to a completion inspection system, characterized in that, include: When it is confirmed that the construction unit has submitted the completed construction information for inspection, random sampling is performed in the test sample library to obtain a preset number of test numbers, and an initial test report is generated. The process of randomly sampling in the test sample library to obtain a preset number of test numbers specifically includes: Each sample in the project information to be completed by the construction unit is randomly assigned a matching number to obtain the detection sample library; A preset number of samples are obtained by randomly sampling from the detection sample library; Determine the matching numbers corresponding to the preset number of samples to obtain the preset number of detection numbers; Determine whether there are any samples in the project information whose numbers are all identical to the detected numbers; If all identical samples exist, then identify the sample to be tested whose number in the project information is the same as the test number, and extract the standard-related information of the sample to be tested; Generate a test order that corresponds one-to-one with the sample to be tested, and send each test order to the tester's terminal; Upon confirming that the test results have been received from the testing personnel's terminal, the test results are input into the completion and handover testing system and compared one by one with the relevant information of each of the standards. Obtain the comparison result of each of the samples to be inspected output by the completion inspection system, wherein the comparison result is qualified or unqualified; Determine whether there is a comparison result indicating that the item is unqualified; If no non-compliance is found, the test results and the comparison results are added to the initial test report to obtain the first final test report; If any non-compliance exists, the test results and the sample to be tested corresponding to the non-compliance are set to a preset format and added to the initial test report to obtain a second final test report; If there are no identical samples, then the missing samples are identified, and the incomplete samples to be tested with the same test number in the project information and the standard-related information corresponding to the incomplete samples to be tested are identified. Then, the steps of generating a test work order that corresponds one-to-one with the test samples are executed, and each test work order is sent to the test personnel's terminal are executed. After generating the first final test report or the second final test report, the missing sample is set to the preset format and added to the first final test report or the second final test report to obtain the third final test report; Determine the final test report, which may be the first final test report, the second final test report, or the third final test report; Receive the self-inspection report sent by the construction unit, and determine whether the self-inspection report is the same as the final inspection report; If they are the same, the final test report will be entered into the completion and handover inspection system; The construction unit's pre-set reputation score is added to the completion and handover inspection system; If they are not the same, the preset value of the reputation score will be deducted from the completion inspection system. Send preset early warning information to the management department's terminal.

2. The method according to claim 1, characterized in that, The generation of a detection work order corresponding one-to-one with each of the samples to be detected specifically includes: The samples to be tested are sorted according to the construction procedure sequence to obtain the construction procedure sequence; Based on the standard-related information of the sample to be tested, extract the detection standard parameters and judgment thresholds corresponding to each construction process; A process inspection flowchart is generated based on the construction process sequence, and the process inspection flowchart includes the sequential inspection order between each of the construction processes. Based on the process inspection flowchart, an inspection linkage mechanism is set up between each of the construction processes. The inspection linkage mechanism includes the transmission relationship of inspection results and mutual verification rules. A test work order template is generated based on the process inspection flowchart and the inspection linkage mechanism. The detection standard parameters and the judgment threshold are filled into the detection work order template to obtain the detection work order.

3. The method according to claim 1, characterized in that, After sending the preset warning information to the management department terminal, the method further includes: Obtain the total credit score of the construction unit, and if the total credit score is greater than the preset minimum credit score, determine the number of times the total credit score changes in a certain way, wherein the change in a certain way is an increase or a decrease. If the number of changes in the numerical value that are increasing is less than the number of changes in the numerical value that are decreasing, the construction unit will be marked as a construction unit under warning.

4. The method according to claim 1, characterized in that, After determining the final test report, the method further includes: Based on the final inspection report, dynamic quality assessment and static quality assessment were conducted on the completed construction products to obtain the corresponding dynamic quality assessment results and static quality assessment results. A multi-level dynamic quality assessment system is established according to a preset multi-level hierarchical structure, which includes a project level, a section level, a unit project level, a sub-project level, and a testing parameter level. Based on the multi-level dynamic quality assessment system, the investment amount information and weight coefficients of each level are statistically analyzed, and a hierarchical scoring calculation model is constructed in combination with the dynamic quality assessment results. The results of the scoring calculation model are compared with a preset quality threshold to generate a real-time quality status report; The real-time quality status report is pushed to the preset management platform at preset time intervals.

5. The method according to claim 4, characterized in that, The process involves conducting dynamic and static quality assessments on the completed construction products based on the final inspection report, obtaining corresponding dynamic and static quality assessment results, specifically including: The dynamic score of each test parameter is calculated based on the test parameter data in the final test report and the preset scoring criteria. Obtain the weight coefficients of the sub-projects, and perform weighted calculations on the dynamic scores based on the weight coefficients to obtain the dynamic scores of the sub-projects; Extract the investment amount data of the unit project and the bid section, and use the investment amount data as the weight to calculate the dynamic score of the sub-project to obtain the dynamic quality assessment result; Receive the appearance quality assessment form and the quality assurance data assessment form, and extract the deduction items of the appearance quality assessment form and the quality assurance data assessment form based on the preset deduction rules, and generate a deduction list; The static quality assessment result is obtained based on the dynamic quality assessment result and the deduction list.

6. A completion and inspection system for transportation construction projects, characterized in that, The system includes: One or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the system to perform the method as described in any one of claims 1-5.

7. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the system, the system performs the method as described in any one of claims 1-5.

8. A computer program product, characterized in that, When the computer program product is run on the system, it causes the system to perform the method as described in any one of claims 1-5.

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