A quality detection management system and method for hydraulic engineering

Abstract

The application discloses a quality detection management system and method for water conservancy projects, and relates to the technical field of quality detection management. The quality detection management system for water conservancy projects comprises a pre-warning and timeliness evaluation module, a pre-warning optimization effective determination module and an information integration optimization module. The application determines whether to perform pre-warning through a concrete mixer state factor, if yes, performs fault pre-warning and timeliness evaluation, and determines whether to perform fault pre-warning optimization, otherwise, continues to monitor the working state of the concrete mixer, then determines whether to perform management information integration effective determination based on a cement paste density standard deviation, and finally determines whether to perform management information integration optimization based on the result of the management information integration effective determination, thereby improving the fault pre-warning effectiveness in the quality detection management of water conservancy projects, and solving the problem of low fault pre-warning effectiveness in the quality detection management of water conservancy projects caused by the asynchronization between data collection and transmission in the prior art.

Description

Technical Field

[0001] This invention relates to the field of quality inspection and management technology, and in particular to a quality inspection and management system and method for water conservancy projects. Background Technology

[0002] Quality inspection and management of water conservancy projects involves analyzing various data collected in real time to ensure timely and effective management of construction quality. This primarily includes equipment monitoring, construction progress tracking, and quality assessment. Equipment monitoring refers to real-time monitoring of the operational status of various equipment used during construction to ensure efficient and stable operation. Construction progress tracking refers to real-time monitoring of the project's progress to ensure each stage of construction proceeds according to plan. Quality assessment refers to a comprehensive evaluation of the quality of structures such as concrete and dams to ensure all construction stages meet design requirements and technical standards.

[0003] Among these aspects, fault early warning is particularly important in equipment monitoring. Fault early warning refers to processing the collected data to determine if there are any signs of abnormality or fault, and issuing timely warning signals to intervene and prevent the fault from occurring or escalating. In water conservancy projects, common faults include, but are not limited to, equipment mechanical faults, electrical faults, and sensor faults.

[0004] For example, the invention patent announcement CN117291429B discloses a method for assessing the quality and safety risks of water conservancy projects based on big data analysis. This method includes: collecting comprehensive construction data, environmental data, and tidal data in real time by setting up detection points around the construction site and using multiple sensors; establishing a digital twin model of the tidal power station project construction; and preprocessing the collected image data, geographic information, construction data, and environmental data using the digital twin model; obtaining the comprehensive construction coefficient Jzxs, environmental coefficient Hjxs, and tidal energy coefficient Cxxs based on the collected first, second, and third datasets; performing correlation analysis on the comprehensive construction coefficient Jzxs, environmental coefficient Hjxs, and tidal energy coefficient Cxxs after dimensionless processing to obtain the comprehensive quality coefficient Zlxs; setting a preset risk assessment threshold F; and using the comprehensive quality coefficient Zhxs obtained through correlation analysis and the digital twin model to analyze the assessment results based on big data to obtain the assessment results and generate an optimization scheme.

[0005] For example, patent application CN116663962A discloses a quality testing and analysis system for dam materials in water conservancy projects. This system includes: a data acquisition module, a data processing module, an analysis and prediction module, a report output module, a database management module, and a system security module. The data acquisition module collects physical, chemical, and mechanical property data of the dam materials, including density, strength, toughness, water absorption, and permeability. The data processing module processes the collected data, including data cleaning, data analysis, and data mining, to extract relevant information. The analysis and prediction module uses machine learning technology to analyze and predict based on the data processing results, identifying material quality problems and predicting potential faults and damage. The report output module outputs the analysis and prediction results as a report for engineers and relevant personnel to refer to, facilitating the development of corresponding repair and maintenance plans. The database management module manages the data in the system, including data storage, backup, and recovery. The system security module ensures system security, including user authentication, access control, and data encryption.

[0006] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0007] In existing technologies, concrete is one of the most commonly used materials in dam construction, and the uniformity and strength of concrete mixing directly determine the stability of the dam. If the concrete mixer malfunctions, resulting in uneven mixing or over-mixing, the quality of the concrete cannot be guaranteed, which may lead to problems such as cracks and insufficient strength in the dam, seriously affecting the durability and structural stability of the dam.

[0008] Many construction equipment monitoring systems are not real-time, and faults often occur suddenly. Low-frequency monitoring cannot capture early abnormal signals from equipment in time, resulting in the system failing to provide timely fault warnings. Furthermore, the lack of effective data transmission and integration mechanisms between quality inspection and management systems prevents real-time collaboration, leading to low effectiveness of fault warnings in water conservancy projects due to asynchrony between data acquisition and transmission. Summary of the Invention

[0009] This application provides a quality inspection management system and method for water conservancy projects, which solves the problem of low effectiveness of fault early warning in the quality inspection management of water conservancy projects due to the asynchrony between data acquisition and transmission in the prior art, and improves the effectiveness of fault early warning in the quality inspection management of water conservancy projects.

[0010] This application provides a quality inspection and management system for water conservancy projects, including: a timely early warning assessment module, an effective early warning optimization judgment module, and an information integration and optimization module. The timely early warning assessment module processes equipment status analysis parameters in concrete quality inspection of water conservancy projects to obtain concrete mixer status factors and determines whether to issue an early warning. If so, it assesses the timeliness of the early warning based on parameters during the early warning process and determines whether to optimize the early warning; otherwise, it continues to monitor the working status of the concrete mixer. The effective early warning optimization judgment module determines whether to perform effective management information integration based on the standard deviation of cement paste density after early warning optimization if early warning optimization is performed; otherwise, it determines whether to perform effective management information integration based on the standard deviation of cement paste density. The information integration and optimization module determines whether to perform management information integration optimization based on the result of the effective management information integration judgment. If management information integration optimization is not performed, it provides direct feedback; otherwise, it performs subsequent concrete quality inspection in water conservancy projects after management information integration optimization.

[0011] This application provides a quality inspection and management method for water conservancy projects, including the following steps: S1, processing the equipment status analysis parameters in the quality inspection of concrete in water conservancy projects to obtain the concrete mixer status factor, and determining whether to issue an early warning. If so, the timeliness of the early warning is assessed based on the parameters in the early warning process of the concrete mixer, and it is determined whether to optimize the early warning. Otherwise, the working status of the concrete mixer continues to be monitored; S2, if the early warning is optimized, the standard deviation of the cement paste density after the early warning is optimized is used to determine whether to make a valid determination of management information integration. Otherwise, the standard deviation of the cement paste density is used to determine whether to make a valid determination of management information integration; S3, based on the result of the valid determination of management information integration, it is determined whether to optimize management information integration. If management information integration is not optimized, feedback is given directly. Otherwise, after the management information integration is optimized, the quality inspection of concrete in subsequent water conservancy projects is carried out.

[0012] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0013] 1. The system determines whether to issue an early warning based on the state factors of the concrete mixer, then assesses the timeliness of the early warning to determine whether to optimize it. Next, it determines whether to effectively integrate management information based on the standard deviation of cement paste density. Finally, it determines whether to optimize management information integration based on the results of the effective management information integration assessment. This improves the integration of transmitted data in the early warning of concrete mixer faults, thereby enhancing the effectiveness of early warning in the quality inspection and management of water conservancy projects. It effectively solves the problem of low effectiveness of early warning in the quality inspection and management of water conservancy projects due to the asynchrony between data acquisition and transmission in existing technologies.

[0014] 2. By analyzing the actual fault warning occurrence time, sensor average acquisition standard deviation, and fault identification accuracy coefficient, a fault warning timeliness assessment index is obtained, thereby ensuring the comprehensiveness of the fault warning timeliness assessment, quantitatively evaluating the timeliness of fault warnings for the working status of the concrete mixer, and thus improving the timeliness of fault warnings for the working status of the concrete mixer, as well as improving the working efficiency and safety of the concrete mixer.

[0015] 3. By determining whether data transmission optimization should be performed based on data acquisition and transmission time, and then determining whether data flow optimization should be performed based on data transfer time, and finally determining whether fault repair process optimization should be performed based on actual construction equipment repair response time, problems in the fault repair process of concrete mixer working status can be identified and optimized in a timely manner, providing a basis for the implementation of optimization measures, improving data transmission efficiency, and thus improving the effectiveness of concrete mixer fault repair. Attached Figure Description

[0016] Figure 1 This application provides a schematic diagram of the structure of a quality inspection and management system for water conservancy projects.

[0017] Figure 2 A flowchart of the early warning timeliness assessment module provided in the embodiments of this application;

[0018] Figure 3 The flowcharts for the early warning optimization effectiveness determination module and the information integration optimization module provided in the embodiments of this application are as follows:

[0019] Figure 4 This is a flowchart of a quality inspection and management method for water conservancy projects, provided as an embodiment of this application. Detailed Implementation

[0020] This application provides a quality inspection management system and method for water conservancy projects, which solves the problem of low effectiveness of fault early warning in the quality inspection management of water conservancy projects due to the asynchrony between data acquisition and transmission in the prior art. The system determines whether to issue an early warning based on the state factor of the concrete mixer. If so, it performs a fault early warning timeliness assessment and determines whether to optimize the fault early warning. Otherwise, it continues to monitor the working status of the concrete mixer. Then, it determines whether to effectively integrate management information based on the standard deviation of cement paste density. Finally, it determines whether to optimize the management information integration based on the result of the effective management information integration assessment. This improves the effectiveness of fault early warning in the quality inspection management of water conservancy projects.

[0021] The technical solution in this application aims to address the problem of low effectiveness of fault early warning in the quality inspection and management of water conservancy projects due to the asynchrony between data acquisition and transmission. The overall approach is as follows:

[0022] The system determines whether to issue an early warning by analyzing the state factors of the concrete mixer, then assesses the timeliness of the early warning to determine whether to optimize it, and finally determines whether to effectively integrate management information based on the standard deviation of cement paste density. This improves the effectiveness of early warning in the quality inspection and management of water conservancy projects.

[0023] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0024] As a first embodiment, such as Figure 1 The diagram shown is a structural schematic of a quality inspection and management system for water conservancy projects provided in an embodiment of this application. The quality inspection and management system for water conservancy projects provided in this embodiment of this application includes: an early warning timeliness assessment module, an early warning optimization effectiveness judgment module, and an information integration and optimization module.

[0025] The early warning timeliness assessment module is used to process the equipment status analysis parameters in the quality inspection of concrete in water conservancy projects, obtain the concrete mixer status factor, and determine whether to issue an early warning. If so, it performs a fault early warning timeliness assessment based on the parameters in the concrete mixer fault early warning process, which serves as the fault early warning timeliness assessment index, and determines whether to optimize the fault early warning. Otherwise, it does not issue an early warning and continues to monitor the working status of the concrete mixer.

[0026] Understandably, the early warning timeliness assessment module provides a basis for subsequent early warning optimization by evaluating the timeliness of fault early warnings, thereby improving the accuracy and timeliness of fault early warnings and better adapting to the construction process and fault types of water conservancy projects. The assessment results determine whether to optimize the fault early warning system, avoiding unnecessary optimization work and improving the operational efficiency and resource utilization of concrete mixer working status fault monitoring in the water conservancy project quality inspection management system, thus providing a more reliable guarantee for the quality inspection of water conservancy projects.

[0027] The early warning optimization validity determination module is used to determine whether to perform management information integration validity determination based on the standard deviation of cement slurry density after fault early warning optimization if such optimization is performed; otherwise, it uses the same standard deviation to determine whether management information integration validity determination is performed. This module provides a basis for subsequent management information integration validity determination by judging the standard deviation of cement slurry density, and further considers management information integration to provide a basis for optimization.

[0028] The information integration and optimization module is used to determine whether to perform management information integration and optimization based on the results of the effective judgment of management information integration. If management information integration and optimization is not performed, feedback is given directly; otherwise, after management information integration and optimization, the quality inspection of concrete in subsequent water conservancy projects is carried out.

[0029] It is important to understand that the information integration and optimization module determines whether to perform optimization based on the results of effective management information integration, ensuring that the optimization work is targeted and effective. Through continuous optimization of management information integration, the integration of information in the monitoring of concrete mixer working status faults can be improved, providing managers with more accurate and comprehensive decision support, and further enhancing the quality inspection and management level of water conservancy projects. If management information integration and optimization are not performed, feedback will be provided, and relevant fault information will be fed back to the designated personnel, enabling them to understand the working status of the concrete mixer and the feedback of fault information in a timely manner, and to grasp the quality inspection and management status of water conservancy projects.

[0030] Before designing a quality inspection and management system for water conservancy projects, a database is established to store various preset data. The database includes, but is not limited to, preset sensor acquisition standard deviation, preset fault identification accuracy coefficient, and fault warning-occurrence duration mapping set. Various preset values ​​are directly set by technical personnel. The preset sensor acquisition standard deviation can be set based on preset personnel, such as by representing it through the average value of sensor acquisition standard deviation over historical time periods in the database. In addition, various values ​​in the database can be set and fine-tuned by technical personnel based on actual debugging.

[0031] In this embodiment, as Figure 2The flowchart shown is a flowchart of the early warning timeliness assessment module provided in this application embodiment. The specific logic is as follows: the equipment status analysis parameters in the quality inspection of concrete in water conservancy projects are processed to obtain the concrete mixer status factor. If the concrete mixer status factor is less than the first preset mixer status threshold, an early warning is issued immediately. Otherwise, if the concrete mixer status factor is less than the second preset mixer status threshold, an early warning is issued according to the preset fault early warning - occurrence duration. Otherwise, no early warning is issued. If an early warning is issued, a fault early warning timeliness assessment is performed. If the fault early warning timeliness assessment index is less than the first preset fault early warning timeliness assessment threshold, a fault early warning optimization is performed. Otherwise, if the fault early warning timeliness assessment index is less than the second preset fault early warning timeliness assessment threshold obtained from the preset database, an early warning is issued according to the corrected fault early warning - occurrence duration. Otherwise, the working status of the concrete mixer is monitored, and an early warning optimization judgment module is used.

[0032] like Figure 3 The diagram shows a flowchart of the early warning optimization effectiveness determination module and the information integration optimization module provided in this application embodiment. The specific logic is as follows: If fault early warning optimization is performed, the early warning optimization effectiveness determination module determines whether the standard deviation of the cement slurry density after optimization is greater than the preset standard deviation of cement slurry density obtained from the preset database. If the standard deviation of the cement slurry density after optimization is greater than the preset standard deviation of cement slurry density obtained from the preset database, then the management information integration effectiveness determination is performed; otherwise, the working status of the concrete mixer continues to be monitored. If fault early warning optimization is not performed, the module determines whether the standard deviation of the cement slurry density is greater than the preset standard deviation of cement slurry density obtained from the preset database. If the standard deviation of the cement slurry density is greater than the preset standard deviation of cement slurry density obtained from the preset database, then the management information integration effectiveness determination is performed. If the data acquisition-transmission time is greater than the preset data acquisition-transmission time obtained from the preset database, the data flow time will be determined after data transmission optimization; otherwise, the data flow time will be determined directly. The specific steps for determining the data flow time are as follows: If the data flow time is greater than the preset data flow time obtained from the preset database, the actual construction equipment repair response time will be determined after data flow optimization; otherwise, the actual construction equipment repair response time will be determined directly. The specific steps for determining the actual construction equipment repair response time are as follows: If the actual construction equipment repair response time is greater than the preset construction equipment repair response time obtained from the preset database, the fault repair process will be optimized; otherwise, feedback will be provided.

[0033] Although concrete mixers are equipped with sensors, the number of sensors is limited and cannot cover all critical components. Sensors are mainly concentrated on vulnerable or critical parts, while monitoring of other components may be overlooked, leading to some potential faults going undetected. Furthermore, sensors primarily collect data under specific operating conditions, and for comprehensive health monitoring of the concrete mixer (e.g., multi-dimensional data such as temperature, humidity, and vibration frequency), the limited data collection frequency or incomplete coverage means the data cannot fully reflect the overall health status of the concrete mixer. Traditional maintenance methods rely on operating experience and regular inspections, failing to fully utilize big data analytics and other technologies to predict fault occurrences. Equipment fault information is not promptly shared with construction management, resulting in delayed fault feedback and hindering timely repair or replacement measures. This slow information transmission affects the speed of fault warning response and management efficiency.

[0034] This application, through its early warning timeliness assessment module, can detect potential fault risks in concrete mixers in advance, issue timely warnings, prevent further escalation of faults, reduce the risk of abnormal concrete mixer operation and delays in water conservancy projects, and improve the quality and safety of water conservancy projects. Through its early warning optimization effectiveness judgment module, it can quickly evaluate the effect of fault early warning optimization, thereby improving the integration of information in concrete mixer operation status fault monitoring, and thus improving the construction quality and efficiency of water conservancy projects. Through its information integration optimization module, it improves the accuracy and efficiency of concrete quality control, avoids quality control problems caused by inconsistent information, and thus enhances the effectiveness of fault early warning in the quality inspection and management of water conservancy projects.

[0035] Furthermore, the equipment condition analysis parameters in the quality inspection of concrete in water conservancy projects are processed to obtain the state factor of the concrete mixer. The specific method is as follows:

[0036] The equipment condition analysis parameters are subjected to relative deviation processing to obtain standardized equipment condition analysis parameters, including temperature change amplitude, vibration frequency standard deviation, pressure standard deviation, and cement slurry density standard deviation. In this application, relative deviation processing means that the absolute value of the difference between the measured value and the preset value is used to perform a ratio calculation with the preset value. The preset values ​​corresponding to the temperature change amplitude, vibration frequency standard deviation, pressure standard deviation, and cement slurry density standard deviation are set by preset personnel. In this application, preset personnel refers to the management personnel in water conservancy projects.

[0037] The temperature variation range is represented by the average value obtained by processing the temperature deviation of the concrete mixer between every two adjacent time points within a preset time period. The standard deviation of the standardized vibration frequency is obtained by processing the standard deviation of the vibration frequency of the concrete mixer within the preset time period. The standard deviation of the standardized pressure is obtained by processing the standard deviation of the pressure of the hydraulic system in the concrete mixer within the preset time period. The standard deviation of the standardized cement paste density is obtained by processing the standard deviation of the cement paste density of the concrete within the preset time period. The temperature is obtained by a temperature sensor installed on the concrete mixer. The vibration frequency is obtained by a vibration frequency sensor installed on the concrete mixer. The pressure is obtained by a pressure sensor installed on the concrete mixer. The cement paste density is obtained by a cement paste density sensor installed on the concrete mixer.

[0038] The state factors of the concrete mixer are obtained by coupling the standardized equipment state analysis parameters. The state factors of the concrete mixer are used to quantify the working state of the concrete mixer.

[0039] In this embodiment, by using relative deviation processing, the dimensional differences of various parameters are eliminated, allowing for comparison of equipment status analysis parameters with different units and ranges. Through coupling processing, the working status of the concrete mixer can be evaluated from multiple perspectives (temperature, vibration, pressure, cement paste density), ensuring that all performance aspects of the concrete mixer are within normal ranges. This provides a basis for subsequent fault early warning optimization, improving the stability and early warning capabilities of the concrete mixer. Ultimately, this enhances the effectiveness of fault early warning in the quality inspection and management of water conservancy projects.

[0040] Further, the specific procedure for determining whether to issue an early warning is as follows:

[0041] A1: If the state factor of the concrete mixer is less than the first preset state threshold of the mixer obtained from the preset database, an early warning will be issued immediately; otherwise, A2 will be executed. The first preset state threshold of the mixer is set by preset personnel, for example, by the difference between the average value of the state factor of the concrete mixer and three times the standard deviation over a historical period.

[0042] By setting a first preset mixer status threshold, serious malfunctions or abnormalities that may occur in the concrete mixer can be quickly identified, and timely warnings can be issued, enabling the preset personnel to take measures to repair or handle the situation quickly.

[0043] A2. If the state factor of the concrete mixer is less than the second preset state threshold of the mixer, a warning will be issued according to the preset fault warning - occurrence duration; otherwise, no warning will be issued. The second preset state threshold of the mixer is set by preset personnel, for example, by the average value of the state factor of the concrete mixer over a historical period.

[0044] When the condition factor of the concrete mixer does not meet the conditions for immediate warning, the evaluation of the condition of the concrete mixer is further refined by introducing a second preset mixer condition threshold and a concrete mixer condition deviation coefficient.

[0045] The preset fault warning - occurrence duration represents the result obtained by inputting the concrete mixer state deviation coefficient into the fault warning - occurrence duration mapping set. The concrete mixer state deviation coefficient is obtained by performing relative deviation processing on the concrete mixer state factor and the second preset mixer state threshold. The fault warning - occurrence duration mapping set is a collection obtained from the preset database that represents the mapping relationship between the concrete mixer state deviation coefficient and the preset fault warning - occurrence duration.

[0046] Determining whether to issue an early warning based on the relationship between the concrete mixer's condition deviation coefficient and the fault warning-occurrence duration mapping set allows for a more reasonable scheduling of warnings and avoids the adverse effects of improperly set warning times. For example, if the concrete mixer's condition deviation coefficient is smaller, it indicates that the mixer's abnormality is relatively minor, and the warning duration can be appropriately extended to reduce unnecessary warning interference.

[0047] In this embodiment, the graded early warning system can improve the accuracy and effectiveness of fault warnings for the concrete mixer's operating status, enabling pre-set personnel to better understand the concrete mixer's operating status, make reasonable decisions, and prevent the concrete mixer's faults from escalating further, thereby reducing maintenance costs and project losses, and ultimately improving the construction efficiency and quality of water conservancy projects.

[0048] Furthermore, the timeliness of fault warnings is assessed based on parameters generated during the fault warning process of the concrete mixer. The specific method is as follows:

[0049] The relative deviation between the actual fault warning occurrence time and the preset fault warning occurrence time obtained from the preset database is processed and used as the fault warning occurrence time deviation coefficient. In the formula, YUT represents the actual fault warning-occurrence time, which is the time difference between the issuance of a fault warning and the actual occurrence of the fault, recorded by the formula. This indicates the preset fault warning duration; by calculating the fault warning duration deviation coefficient, the timeliness of the fault response is quantitatively evaluated.

[0050] The average standard deviation of sensor acquisition is compared with the preset standard deviation of sensor acquisition obtained from the preset database, and the result is used as the comparison coefficient of the average standard deviation of sensor acquisition. In the formula, CAI represents the average standard deviation of sensor data acquisition, which is obtained by averaging the standard deviations of data acquired by all sensors. The preset sensor acquisition standard deviation is set by preset personnel, for example, by the average value of the sensor acquisition standard deviation over a historical period. The comparison processing in this application refers to performing ratio processing. By calculating the comparison coefficient of the average sensor acquisition standard deviation, the stability of the sensor measurement data in the concrete mixer is reflected, which is helpful to evaluate the stability of the sensor in the fault identification process in the concrete mixer, thereby affecting the accuracy and timeliness of fault warning.

[0051] The fault identification accuracy coefficient is compared with a preset fault identification accuracy coefficient obtained from a preset database, and this comparison coefficient is used as the fault identification accuracy comparison coefficient. In the formula, ZUN represents the fault identification accuracy coefficient, which is calculated by the ratio of the actual number of accurate fault warnings to the total number of fault warnings; the actual number of accurate fault warnings represents the number of times the warning was confirmed as accurate by preset personnel after the fault warning was issued. This represents the preset fault identification accuracy coefficient, which is set by preset personnel. For example, it can be represented by the average value of the fault identification accuracy coefficient over a historical period. By calculating the fault identification accuracy comparison coefficient, it reflects the performance of fault identification in the working state of the concrete mixer.

[0052] A fault warning timely assessment compensation value is introduced. After assigning and coupling the fault warning-occurrence duration deviation coefficient and the sensor average acquisition standard deviation comparison coefficient, an inverse proportional operation is performed to obtain the fault warning timely coefficient. The fault warning timely assessment compensation value includes the first fault warning timely assessment compensation value and the second fault warning timely assessment compensation value.

[0053] A third fault warning timely assessment compensation value is introduced. After assigning a value to the fault identification accuracy comparison coefficient, it is coupled with the fault warning timeliness coefficient to serve as the fault warning timeliness assessment index. The fault warning timeliness assessment index is used to quantitatively assess the timeliness of fault warnings in the working state of the concrete mixer.

[0054] The specific constraint expression for the fault early warning timeliness assessment index is as follows:

[0055] ;

[0056] In the formula, JS represents the fault warning timeliness assessment index. This indicates that the compensation value should be assessed promptly in the first fault warning. This indicates that the compensation value should be assessed promptly for the second fault warning. This indicates that the compensation value should be assessed promptly in response to the third fault warning.

[0057] The relevant fault warning timely assessment compensation values ​​are obtained from a preset database. The first fault warning timely assessment compensation value represents the influence of the actual fault warning-occurrence duration on the fault warning timeliness assessment index; the second fault warning timely assessment compensation value represents the influence of the sensor's average acquisition standard deviation on the fault warning timeliness assessment index; and the third fault warning timely assessment compensation value represents the influence of the fault identification accuracy coefficient on the fault warning timeliness assessment index. The sum of these three values ​​is 1. For example, the actual fault warning-occurrence duration and the preset first fault warning timely assessment compensation value form an actual fault warning-occurrence duration mapping set. The real-time actual fault warning-occurrence duration is then input into the database. The system generates a first fault warning timely assessment compensation value by mapping the actual fault warning to the occurrence duration. The sensor average acquisition standard deviation and the preset second fault warning timely assessment compensation value form a sensor average acquisition standard deviation mapping set. The real-time sensor average acquisition standard deviation is input into this mapping set to obtain the corresponding second fault warning timely assessment compensation value. The fault identification accuracy coefficient and the preset third fault warning timely assessment compensation value form a fault identification accuracy coefficient mapping set. The real-time fault identification accuracy coefficient is input into this mapping set to obtain the corresponding third fault warning timely assessment compensation value. The mapping relationships can be one-to-one or many-to-one.

[0058] In this embodiment, the average standard deviation of sensor acquisition reflects the dispersion of sensor measurement data. A larger average standard deviation means greater fluctuations in the equipment status analysis parameters acquired by the sensor, resulting in poorer quality parameters. This may lead to difficulties in accurately determining whether the equipment status analysis parameters truly reflect changes in the working state of the concrete mixer in the water conservancy project, thus increasing the fault warning-occurrence time deviation coefficient. High fault identification accuracy means accurately determining whether a fault has occurred in the working state of the concrete mixer in the water conservancy project and the severity of the fault. If the fault can be accurately identified, a timely warning can be issued, reducing the fault warning-occurrence time deviation coefficient. A larger average standard deviation of sensor acquisition increases the noise in the sensor-acquired data, masking the true fault signal and making it difficult to extract useful information from the noise, thereby reducing the accuracy of fault identification.

[0059] Through the above steps, the comprehensiveness of the fault warning timeliness assessment is ensured, and the timeliness of fault warnings for the working status of the concrete mixer is comprehensively and quantitatively evaluated, thereby improving the working efficiency and safety of the concrete mixer and ultimately enhancing the timeliness of fault warnings for the working status of the concrete mixer.

[0060] Further, determine whether to perform fault warning optimization. The specific process is as follows:

[0061] B1. If the fault warning timeliness assessment index is less than the first preset fault warning timeliness assessment threshold obtained from the preset database, then fault warning optimization is performed and B3 is executed; otherwise, B2 is executed. The first preset fault warning timeliness assessment threshold is set by preset personnel, for example, by the difference between the average value of the fault warning timeliness assessment index and three times the standard deviation over a historical period.

[0062] By judging the relationship between the fault warning timeliness assessment index and the first preset fault warning timeliness assessment threshold, it is possible to quickly identify situations where the warning timeliness is poor, promptly initiate the fault warning optimization process, avoid the expansion of faults in the working state of the concrete mixer due to untimely warnings, and reduce the quality loss of water conservancy projects.

[0063] B2, if the fault warning timeliness assessment index is less than the second preset fault warning timeliness assessment threshold obtained from the preset database, then a warning is issued according to the corrected fault warning-occurrence duration. The corrected fault warning-occurrence duration means that the second fault warning timeliness assessment deviation coefficient is used to correct the preset fault warning-occurrence duration. Otherwise, no fault warning optimization is performed. The second preset fault warning timeliness assessment threshold is set by preset personnel, for example, by the average value of the fault warning timeliness assessment index over a historical period. In this application, the specific method for correction is to perform a product operation.

[0064] The second fault warning timeliness assessment deviation coefficient is obtained by performing relative deviation processing on the fault warning timeliness assessment index and the second preset fault warning timeliness assessment threshold.

[0065] By adopting a fault warning system based on the duration of occurrence, the system can avoid excessive interference with the operation of the water conservancy project's quality inspection and management system, while also improving the timeliness and accuracy of fault warnings for the concrete mixer's working status to a certain extent. This balances the overall performance of the water conservancy project's quality inspection and management system with the effectiveness of fault warnings.

[0066] B3. If the fault warning timeliness assessment index after sensor calibration optimization management is less than the first preset fault warning timeliness assessment threshold obtained from the preset database, then data acquisition frequency optimization management will be carried out; otherwise, fault warning optimization will end. By further optimizing data acquisition frequency management, the problem of warning timeliness will be gradually and thoroughly solved, thereby improving the monitoring accuracy of the working status of concrete mixers in water conservancy projects and thus avoiding potential water conservancy project quality problems.

[0067] Specifically, the specific process of sensor calibration optimization management is as follows: According to the initial calibration cycle, the sensors on the concrete mixer are calibrated. The initial calibration cycle represents the result obtained by inputting the fault warning timeliness assessment index into the calibration cycle mapping set. The calibration cycle mapping set is a set obtained from a preset database that represents the mapping relationship between the fault warning timeliness assessment index and the initial calibration cycle. The initial calibration cycle refers to the cycle in which the sensors on the concrete mixer are calibrated for the first time.

[0068] Within the initial calibration period, if the average fault warning timeliness assessment index of the preset quality inspection count is less than the first preset fault warning timeliness assessment threshold, the initial calibration period is corrected according to the current first fault warning timeliness assessment deviation coefficient to obtain the corrected calibration period. The first fault warning timeliness deviation coefficient is obtained by performing relative deviation processing on the fault warning timeliness assessment index and the first preset fault warning timeliness assessment threshold. The average fault warning timeliness assessment index is obtained by averaging the fault warning timeliness assessment index of the preset quality inspection count. The preset quality inspection count is set by preset personnel.

[0069] By adjusting the calibration cycle of the sensors, sensor errors can be eliminated, ensuring that the sensors installed on the concrete mixer can detect faults in a timely manner and provide early warnings during operation, thereby improving the accuracy of data acquisition.

[0070] B4. If the fault warning timeliness assessment index after data acquisition frequency optimization management is less than the first preset fault warning timeliness assessment threshold obtained from the preset database, then the preset mixer status threshold optimization is performed; otherwise, the fault warning optimization ends. By further optimizing the preset mixer status threshold, the potential of the early warning system for the working status of concrete mixers in the quality inspection and management system of water conservancy projects can be further explored.

[0071] Specifically, data acquisition frequency optimization management means that data acquisition of equipment status analysis parameters is performed according to the corrected data acquisition frequency. The corrected data acquisition frequency is obtained by correcting the data acquisition frequency of the corresponding sensor through the first fault warning timeliness deviation coefficient.

[0072] Adjusting the data acquisition frequency according to actual conditions reduces resource consumption while ensuring timely detection of concrete mixer malfunctions. The revised data acquisition frequency ensures more accurate and real-time data acquisition, enabling timely detection of any abnormalities in the concrete mixer's operation and improving the overall stability and responsiveness of the concrete mixer malfunction early warning system within the water conservancy project's quality inspection and management system.

[0073] B5. If the timeliness evaluation index of the fault warning after optimization of the preset mixer status threshold is less than the first preset fault warning timeliness evaluation threshold obtained from the preset database, feedback will be provided; otherwise, the fault warning optimization will end. By providing further feedback, the preset personnel can be prompted to further analyze the problem and continuously improve the fault warning system for the working status of the concrete mixer, thereby improving the accuracy of the fault warning for the working status of the concrete mixer.

[0074] Specifically, the optimization process for the preset mixer status threshold is as follows: If the average fault warning timeliness assessment index of the preset quality inspection count is less than the first preset fault warning timeliness assessment threshold, the preset mixer status threshold is corrected according to the preset mixer status threshold correction factor; otherwise, the preset mixer status threshold is not optimized. The preset mixer status threshold correction factor is obtained by coupling the service life of the construction equipment and the deviation coefficient of the first fault warning timeliness assessment. The service life of the construction equipment is obtained by recording the fault warning system of the concrete mixer's working status.

[0075] By optimizing the preset mixer status thresholds, dynamic adjustments can be made based on actual usage (such as the equipment's age) and the performance of fault warnings, thereby improving the accuracy and timeliness of fault warnings.

[0076] As can be seen from the above, fault warning optimization includes sensor calibration optimization management, data acquisition frequency optimization management, and preset mixer status threshold optimization.

[0077] In this embodiment, the above steps can improve the timeliness of fault warning and the accuracy of fault identification for the working status of concrete mixers, thereby improving the efficiency of concrete quality inspection and management in water conservancy projects and providing reliable technical support for water conservancy projects.

[0078] Furthermore, based on the optimized standard deviation of cement slurry density according to fault warnings, the determination of whether management information integration is effective is made. The specific process is as follows:

[0079] At the end of the preset fault repair cycle, determine whether the standard deviation of the cement slurry density after the fault warning optimization is greater than the preset standard deviation of the cement slurry density obtained from the preset database:

[0080] If the standard deviation of cement slurry density after fault warning optimization is greater than the preset standard deviation of cement slurry density obtained from the preset database, then the management information integration is effectively judged; otherwise, the working status of the concrete mixer continues to be monitored. The preset fault repair cycle is set by preset personnel.

[0081] In this embodiment, setting a preset fault repair cycle helps determine the timing for implementing fault warning optimization. Evaluating the effectiveness of fault warning optimization at the end of the preset fault repair cycle is a way to ensure its effectiveness. This allows for timely identification of whether the fault warning optimization has achieved the expected results within the preset fault repair cycle, ensuring that the concrete mixer is in optimal operating condition. This enables effective monitoring of the concrete mixer's operating status and rapid fault response, ensuring the quality of concrete and the smooth progress of the production process in water conservancy projects. Ultimately, this improves the effectiveness of fault warning in the quality inspection and management of water conservancy projects.

[0082] Furthermore, based on the results of the effective assessment of management information integration, a decision is made on whether to proceed with management information integration and optimization. The specific process is as follows:

[0083] C1: If the data acquisition-transmission duration is greater than the preset data acquisition-transmission duration obtained from the preset database, then execute C2 after data transmission optimization; otherwise, execute C2 directly. The data acquisition-transmission duration is represented by the time difference between the completion of data acquisition of the recorded concrete working status and the completion of data transmission (data to the early warning system of the concrete mixer working status). The preset data acquisition-transmission duration is set by preset personnel, for example, by the average value of data acquisition-transmission duration over a historical time period.

[0084] Specifically, data transmission optimization means dividing the transmission priority of concrete mixers according to the warning status; the transmission priority includes a first transmission priority, a second transmission priority, and a third transmission priority. The first transmission priority represents the highest transmission priority of concrete mixer fault information in the case of immediate warning. The second transmission priority represents the medium priority of concrete mixer fault information in the case of warning according to the preset fault warning-occurrence duration. The third transmission priority represents the lowest transmission priority of concrete mixer fault information in the case of no warning.

[0085] By optimizing data transmission, problems in the data transmission process can be identified and addressed in a timely manner. This ensures that urgent and important fault information is transmitted to designated personnel as soon as possible, enabling them to respond quickly, handle faults promptly, reduce mixer downtime, and improve concrete production efficiency.

[0086] C2: If the data transfer time is greater than the preset data transfer time obtained from the preset database, then C3 will be executed after data transfer optimization; otherwise, C3 will be executed directly. The data transfer time represents the time required for data to be transferred between various subsystems, and is represented by the average of the time required for data to be transferred between any two subsystems. The subsystems of the water conservancy project quality inspection management system include the equipment management subsystem, the construction progress management subsystem, and the quality subsystem management system. The preset data transfer time is set by preset personnel, for example, by the average of the data transfer time in a historical time period.

[0087] Specifically, data flow optimization means combining the real-time communication protocol (Message Queuing Telemetry Transport, MQTT) to split the transmitted data into a preset number of small packets for batch transmission. The transmitted data includes equipment status analysis parameters of the concrete mixer and corresponding fault information; the preset number is set by preset personnel; and batch transmission is carried out through batch transmission technology.

[0088] Optimizing data flow can improve the stability of data transmission. If a small packet encounters a problem during transmission, only that small packet needs to be retransmitted, instead of the entire data, reducing the amount and time spent on retransmissions. Furthermore, batch transmission better adapts to different network environments, improving data transmission efficiency. This, in turn, enhances the efficiency of data processing and analysis within the water conservancy project's quality inspection and management system. Optimizing data flow reduces the waiting time of data within the system, speeds up data processing, and enables personnel to obtain analysis results more quickly and make timely decisions, thus contributing to improved quality and construction efficiency in water conservancy projects.

[0089] C3. If the actual construction equipment repair response time is greater than the preset construction equipment repair response time obtained from the preset database, the fault repair process will be optimized; otherwise, feedback will be provided. The actual construction equipment repair response time represents the actual time taken from the discovery of a fault in a concrete mixer in a water conservancy project to the start of repairs by preset personnel. It is recorded by the fault early warning system for the working status of the concrete mixer. The preset construction equipment repair response time is set by preset personnel, for example, by the average value of construction equipment repair response times over a historical time period.

[0090] Specifically, the optimization process for fault repair is as follows: If the actual repair response time of the construction equipment is longer than the preset repair response time for the number of quality inspections, the repair response time is corrected based on the effective integration correction factor of management information to obtain the corrected repair response time. The effective integration correction factor of management information is obtained by coupling the relative deviation of data acquisition-transmission time, data flow time and actual repair response time. The effective integration correction factor of management information is used to correct the preset repair response time of construction equipment to make it more consistent with the actual situation.

[0091] If the actual repair response time of the construction equipment is longer than the corrected repair response time, feedback will be sent directly to the designated personnel; otherwise, the working status of the concrete mixer will continue to be monitored.

[0092] By optimizing the fault repair process, problems in the fault repair process of concrete mixers can be identified and addressed in a timely manner. Optimizing the fault repair process can shorten the downtime of concrete mixers, reduce the impact of concrete mixer failures on the construction progress and quality of water conservancy projects, and timely feedback of relevant early warning information can help the pre-planning personnel fully understand the system's operating status and equipment maintenance, and take corresponding measures, such as increasing maintenance personnel and adjusting maintenance plans, to ensure that the concrete mixer can be restored to normal operation as soon as possible.

[0093] As can be seen from the above, the optimization of management information integration includes optimization of data transmission, optimization of data flow, and optimization of fault repair process.

[0094] In this embodiment, the above steps improve the efficiency of information transmission in the quality inspection and management system of water conservancy projects, thereby improving the timeliness and accuracy of transmitted data. This ensures that the quality inspection and management system of water conservancy projects can obtain the latest data from the site in a timely manner, providing a reliable basis for subsequent data analysis and decision-making. Consequently, the effectiveness of fault early warning in the quality inspection and management of water conservancy projects is improved.

[0095] As a second embodiment, such as Figure 4 The diagram shown is a flowchart of a quality inspection and management method for water conservancy projects provided in this application embodiment. The method includes the following steps:

[0096] S1 processes the equipment status analysis parameters in the quality inspection of concrete in water conservancy projects to obtain the concrete mixer status factor, and determines whether to issue an early warning. If so, it evaluates the timeliness of the early warning based on the parameters in the early warning process of the concrete mixer and determines whether to optimize the early warning. Otherwise, it continues to monitor the working status of the concrete mixer.

[0097] This step, through the calculation of the concrete mixer's state factors, enables an accurate assessment of the concrete mixer's state, providing a basis for subsequent fault early warning implementation. This allows for the timely detection of potential faults, preventing concrete quality problems caused by equipment malfunctions and ensuring the quality of water conservancy projects. Furthermore, the timely assessment of fault early warnings ensures the timeliness of fault warnings regarding the concrete mixer's operating status within the water conservancy project's quality inspection and management system. This allows for responses before or as early as possible to mitigate the risks associated with potential faults. Timely warnings also enable proactive measures to reduce the impact of faults on concrete quality and project progress.

[0098] S2, if fault warning optimization is performed, then the effective determination of management information integration is based on the standard deviation of cement slurry density after fault warning optimization; otherwise, the effective determination of management information integration is based on the standard deviation of cement slurry density.

[0099] This step, by determining the standard deviation of cement paste density, helps ensure the effectiveness of management information integration; the optimized fault early warning system can reduce false alarms and missed alarms, improving the accuracy and timeliness of fault early warning in the quality inspection and management system of water conservancy projects; even without fault early warning optimization, the determination based on the standard deviation of cement paste density can provide a valid reference for the pre-set personnel to determine whether management information needs to be integrated, thereby monitoring and adjusting the concrete mixing process.

[0100] S3 determines whether to optimize the management information integration based on the results of the effective assessment. If optimization is not performed, feedback is provided directly; otherwise, quality testing of concrete in subsequent water conservancy projects is conducted after optimization. Optimizing the management information integration makes subsequent quality testing more accurate, ensuring timely response and processing at each step; thus improving the effectiveness of fault early warning in the quality testing management of water conservancy projects.

[0101] In summary, this application embodiment determines whether to issue an early warning by using the state factor of the concrete mixer, then performs a fault early warning timeliness assessment to determine whether to optimize the fault early warning, then determines whether to effectively integrate management information based on the standard deviation of cement paste density, and finally determines whether to optimize management information integration based on the result of the effective management information integration assessment. This improves the integration of transmitted data in the fault early warning of the concrete mixer, thereby improving the effectiveness of fault early warning in the quality inspection and management of water conservancy projects. It effectively solves the problem of low effectiveness of fault early warning in the quality inspection and management of water conservancy projects caused by the asynchrony between data acquisition and transmission in the prior art.

[0102] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] This invention is described with reference to flowchart illustrations and / or block diagrams of systems, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0106] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0107] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A quality inspection and management system for water conservancy projects, characterized in that, include: The module includes a timely warning assessment module, an effective warning optimization judgment module, and an information integration and optimization module. The early warning timeliness assessment module is used to process the equipment status analysis parameters in the quality inspection of concrete in water conservancy projects, obtain the concrete mixer status factor, and determine whether to issue an early warning. If so, it performs a fault early warning timeliness assessment based on the parameters in the fault early warning process of the concrete mixer and determines whether to optimize the fault early warning. Otherwise, it continues to monitor the working status of the concrete mixer. The early warning optimization validity determination module is used to determine whether to perform management information integration validity determination based on the standard deviation of cement slurry density after fault early warning optimization if fault early warning optimization is performed; otherwise, it determines whether to perform management information integration validity determination based on the standard deviation of cement slurry density. The information integration and optimization module is used to determine whether to perform management information integration and optimization based on the result of the effective determination of management information integration. If management information integration and optimization is not performed, feedback is given directly; otherwise, after management information integration and optimization, the quality inspection of concrete in subsequent water conservancy projects is carried out. The process involves analyzing the equipment condition parameters in the quality inspection of concrete in water conservancy projects to obtain the state factor of the concrete mixer. The specific method is as follows: The equipment condition analysis parameters are subjected to relative deviation processing to obtain standardized equipment condition analysis parameters, which include temperature change amplitude, vibration frequency standard deviation, pressure standard deviation and cement slurry density standard deviation. The concrete mixer state factor is obtained by coupling the standardized equipment state analysis parameters. The concrete mixer state factor is used to quantify the working state of the concrete mixer. The method for assessing the timeliness of fault warnings based on parameters in the fault warning process of concrete mixers is as follows: The relative deviation between the actual fault warning-occurrence duration and the preset fault warning-occurrence duration obtained from the preset database is processed and used as the fault warning-occurrence duration deviation coefficient. The average standard deviation of sensor acquisition is compared with the preset standard deviation of sensor acquisition obtained from the preset database, and the result is used as the comparison coefficient of the average standard deviation of sensor acquisition. The fault identification accuracy coefficient is compared with the preset fault identification accuracy coefficient obtained from the preset database and used as the fault identification accuracy comparison coefficient. A fault early warning timely assessment compensation value is introduced. After assigning and coupling the fault early warning-occurrence duration deviation coefficient and the sensor average acquisition standard deviation comparison coefficient, an inverse proportional operation is performed to obtain the fault early warning timely coefficient. The fault early warning timely assessment compensation value includes a first fault early warning timely assessment compensation value and a second fault early warning timely assessment compensation value. A third fault warning timely assessment compensation value is introduced. After assigning a value to the fault identification accuracy comparison coefficient, it is coupled with the fault warning timeliness coefficient to serve as the fault warning timeliness assessment index. The fault warning timeliness assessment index is used to quantitatively assess the timeliness of fault warnings for the working status of the concrete mixer.

2. The quality inspection and management system for water conservancy projects as described in claim 1, characterized in that... The specific process for determining whether to issue a warning is as follows: A1: If the state factor of the concrete mixer is less than the first preset mixer state threshold obtained from the preset database, an early warning will be issued immediately; otherwise, A2 will be executed. A2, If the state factor of the concrete mixer is less than the second preset mixer state threshold, then a warning will be issued according to the preset fault warning - occurrence duration; otherwise, no warning will be issued. The preset fault warning-occurrence duration represents the result obtained by inputting the concrete mixer state deviation coefficient into the fault warning-occurrence duration mapping set. The concrete mixer state deviation coefficient is obtained by performing relative deviation processing on the concrete mixer state factor and the second preset mixer state threshold.

3. The quality inspection and management system for water conservancy projects as described in claim 1, characterized in that... The specific process for determining whether to perform fault warning optimization is as follows: B1. If the fault warning timeliness assessment index is less than the first preset fault warning timeliness assessment threshold obtained from the preset database, then perform fault warning optimization and execute B3; otherwise, execute B2. B2. If the fault warning timeliness assessment index is less than the second preset fault warning timeliness assessment threshold obtained from the preset database, then a warning is issued according to the corrected fault warning-occurrence duration. The corrected fault warning-occurrence duration means that the second fault warning timeliness assessment deviation coefficient is used to correct the preset fault warning-occurrence duration. Otherwise, no fault warning optimization is performed. The second fault warning timeliness assessment deviation coefficient is obtained by performing relative deviation processing on the fault warning timeliness assessment index and the second preset fault warning timeliness assessment threshold. The fault early warning optimization includes sensor calibration optimization management, data acquisition frequency optimization management, and preset mixer status threshold optimization. B3. If the fault warning timeliness evaluation index after sensor calibration optimization management is less than the first preset fault warning timeliness evaluation threshold obtained from the preset database, then data acquisition frequency optimization management will be performed; otherwise, fault warning optimization will end. B4. If the fault warning timeliness evaluation index after data acquisition frequency optimization management is less than the first preset fault warning timeliness evaluation threshold obtained from the preset database, then the preset mixer status threshold optimization is performed; otherwise, the fault warning optimization ends. B5. If the fault warning timeliness evaluation index after optimization of the preset mixer status threshold is less than the first preset fault warning timeliness evaluation threshold obtained from the preset database, then feedback is provided; otherwise, the fault warning optimization ends.

4. The quality inspection and management system for water conservancy projects as described in claim 3, characterized in that... The specific process for sensor calibration optimization management is as follows: The sensors on the concrete mixer are calibrated according to the initial calibration cycle, where the initial calibration cycle represents the result obtained by inputting the fault early warning timeliness assessment index into the calibration cycle mapping set. If the average fault warning timeliness assessment index of the preset quality inspection number is less than the first preset fault warning timeliness assessment threshold during the initial calibration period, the initial calibration period is corrected according to the current first fault warning timeliness assessment deviation coefficient to obtain the corrected calibration period. The first fault warning timeliness assessment deviation coefficient is obtained by performing relative deviation processing on the fault warning timeliness assessment index and the first preset fault warning timeliness assessment threshold. The data acquisition frequency optimization management refers to collecting data on equipment status analysis parameters according to the corrected data acquisition frequency. The corrected data acquisition frequency is obtained by correcting the data acquisition frequency of the corresponding sensor through the first fault early warning timeliness assessment deviation coefficient. The specific process for optimizing the preset mixer state threshold is as follows: If the average fault warning timeliness assessment index of the preset quality inspection number is less than the first preset fault warning timeliness assessment threshold, then the preset mixer state threshold is corrected according to the preset mixer state threshold correction factor; otherwise, the preset mixer state threshold is not optimized. The preset mixer state threshold correction factor is obtained by coupling the service life of the construction equipment and the first fault warning timeliness assessment deviation coefficient.

5. The quality inspection and management system for water conservancy projects as described in claim 1, characterized in that... The specific process for determining whether the management information integration is effective based on the standard deviation of cement slurry density optimized by fault early warning is as follows: At the end of the preset fault repair cycle, determine whether the standard deviation of the cement slurry density after the fault warning optimization is greater than the preset standard deviation of the cement slurry density obtained from the preset database: If the standard deviation of cement slurry density after fault warning optimization is greater than the preset standard deviation of cement slurry density obtained from the preset database, then the management information integration is effectively judged; otherwise, the working status of the concrete mixer continues to be monitored.

6. The quality inspection and management system for water conservancy projects as described in claim 1, characterized in that... The management information integration and optimization includes data transmission optimization, data flow optimization, and fault repair process optimization. The specific process for determining whether to perform management information integration optimization based on the result of the effective assessment of management information integration is as follows: C1: If the data acquisition-transmission duration is greater than the preset data acquisition-transmission duration obtained from the preset database, then execute C2 after data transmission optimization; otherwise, execute C2 directly. C2: If the data transfer time is greater than the preset data transfer time obtained from the preset database, then execute C3 after data transfer optimization; otherwise, execute C3 directly. C3: If the actual repair response time of the construction equipment is greater than the preset repair response time of the construction equipment obtained from the preset database, then the fault repair process will be optimized; otherwise, feedback will be provided.

7. The quality inspection and management system for water conservancy projects as described in claim 6, characterized in that... The data transmission optimization refers to prioritizing the transmission of concrete mixers according to the warning status. The data flow optimization refers to combining a real-time communication protocol to split the transmitted data into a preset number of small packets for batch transmission. The transmitted data includes equipment status analysis parameters of the concrete mixer and corresponding fault information. The specific process for optimizing the fault repair procedure is as follows: If the actual repair response time of the construction equipment is longer than the preset repair response time, the repair response time is corrected according to the effective integration correction factor of management information to obtain the corrected repair response time. The effective integration correction factor of management information is obtained by coupling the relative deviation of data acquisition-transmission time, data flow time and actual repair response time. If the actual repair response time of the construction equipment is longer than the corrected repair response time, feedback will be sent directly to the designated personnel; otherwise, the working status of the concrete mixer will continue to be monitored.

8. A quality inspection and management method for water conservancy projects, used to implement the quality inspection and management system for water conservancy projects as described in any one of claims 1-7, characterized in that... This includes the following steps: S1, process the equipment status analysis parameters in the quality inspection of concrete in water conservancy projects to obtain the concrete mixer status factor, and determine whether to issue an early warning. If so, evaluate the timeliness of the early warning based on the parameters in the early warning process of the concrete mixer and determine whether to optimize the early warning. Otherwise, continue to monitor the working status of the concrete mixer. S2, if fault warning optimization is performed, then the effective determination of management information integration is based on the standard deviation of cement slurry density after fault warning optimization; otherwise, the effective determination of management information integration is based on the standard deviation of cement slurry density. S3 determines whether to optimize the management information integration based on the results of the effective assessment. If the optimization is not performed, feedback is provided directly. Otherwise, the quality inspection of concrete in subsequent water conservancy projects is conducted after the optimization is completed.

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