Concrete production line process flow on-line monitoring management system

Abstract

The invention relates to the technical field of electronic engineering, and discloses a concrete production line process flow on-line monitoring management system, which comprises a proportion detection module used for calculating the batching proportion of raw materials, constructing the proportion detection module of the raw materials, and detecting the actual proportion data of concrete; the data acquisition module is used for configuring a sensor network of the technological process to acquire technological parameters of the technological process and concrete image data in real time; the final strength module is used for analyzing the final strength of the concrete; the production quality analysis module is used for respectively extracting workability characteristics and uniformity characteristics of the concrete image data, analyzing the workability of the concrete, analyzing the uniformity of the concrete and analyzing the production quality of the concrete; and the technological process optimization module is used for determining control optimization parameters of the technological process and executing optimization control of the technological process. The precise effect of online monitoring and management of the concrete production line technological process can be improved.

Description

Technical Field

[0001] The present invention relates to the field of electronic engineering technology, and in particular to an online monitoring and management system for a process flow of a concrete production line. Background Art

[0002] The process of concrete production line refers to the process of processing, mixing, transporting and pouring raw materials (such as cement, sand, stone, admixtures, additives, etc.) to produce concrete that meets quality requirements. The process of concrete production line uses a variety of sensors and camera equipment to monitor raw material ratios, temperature, humidity, pressure and other parameters online, so as to achieve accurate measurement of process parameters, ensure the accuracy of concrete ratio, and thus ensure the quality of concrete.

[0003] At present, the main method for monitoring the process flow of concrete production lines is video monitoring, which installs high-definition cameras to monitor the production process and equipment operating status in real time. However, this monitoring method is too single and cannot monitor the process parameters of the process flow, resulting in the inability to ensure the production quality of concrete. Summary of the invention

[0004] The present invention provides an online monitoring and management system for the technological process of a concrete production line, the main purpose of which is to improve the accuracy of the online monitoring and management of the technological process of a concrete production line.

[0005] To achieve the above-mentioned purpose, the present invention provides an online monitoring and management system for the process flow of a concrete production line, comprising: A ratio detection module is used to calculate the ratio of the raw materials corresponding to the concrete, build a ratio detection module for the raw materials based on the ratio, and use the ratio detection module to detect the actual ratio data of the concrete; A data acquisition module, used to configure a sensor network corresponding to the process flow of the concrete, and based on the sensor network, to collect process parameters and concrete image data of the process flow in real time; A final strength module, used to analyze the final strength of the concrete according to the process parameters and the actual mix ratio data using a trained concrete strength analysis model; a production quality analysis module, for respectively extracting workability features and uniformity features of the concrete image data, analyzing the workability of the concrete based on the workability features using a preset workability analysis algorithm, analyzing the uniformity of the concrete based on the uniformity features using a preset uniformity algorithm, and analyzing the production quality of the concrete according to the final strength, the workability and the uniformity; A process flow optimization module is used to define a multi-objective process optimization algorithm for the process flow based on the production quality, and to perform optimization control of the process flow based on the multi-objective process optimization algorithm.

[0006] Optionally, the calculating the batching ratio of the raw materials corresponding to the concrete includes: Analyzing the key materials of the raw materials, wherein the key materials include: water, cement and aggregate; Determining the water-binder ratio of the raw materials based on the production quality requirements of the concrete; Extracting the concrete density requirement of the production quality requirement, and calculating the coarse aggregate material coefficient and the fine aggregate material coefficient of the aggregate respectively based on the concrete density requirement; According to the water-cement ratio, the coarse aggregate material coefficient and the fine aggregate material coefficient, the proportion of the raw materials is calculated using the following formula: , , , , in, Indicates the proportion of ingredients. Indicates the water quality corresponding to water, represents the water-to-binder ratio, represents the cement mass corresponding to cement, Indicates the mass of aggregate corresponding to coarse aggregate, Indicates the mass of aggregate corresponding to fine aggregate, It represents the material coefficient of coarse aggregate. Indicates the fine aggregate material coefficient.

[0007] Optionally, the raw material ratio detection module is constructed based on the ingredient ratio, including: Constructing a detection module framework of the raw materials, and determining a raw material identification unit of the detection module framework according to the ingredient ratio; identifying the raw material type of the raw material according to the raw material identification unit; A weight sensor and a flow meter are configured for the detection module frame; Based on the weight sensor, determining the solid weight of the solid material corresponding to the raw material; Determining the liquid flow rate of the raw material corresponding to the liquid material according to the flow meter; Determine a ratio analysis unit of the detection module framework according to the raw material type, the solid weight and the liquid flow rate; Based on the raw material identification unit, the ratio analysis unit and the detection module framework, a ratio detection module for the raw materials is constructed.

[0008] Optionally, configuring the sensor network corresponding to the concrete process flow includes: Analyze the monitoring requirements of the process flow, and determine the sensor type and installation location of the sensor corresponding to the process flow according to the monitoring requirements; Construct the network architecture and communication protocol of the sensor, and plan the data transmission frequency and bandwidth requirements of the sensor; Constructing a communication network for the sensor according to the network architecture, the communication protocol, the data transmission frequency, and the bandwidth requirement; Based on the sensor type, the installation location and the communication network, a sensor network of the process flow is integrated.

[0009] Optionally, analyzing the final strength of the concrete according to the process parameters and the actual mix ratio data using a trained concrete strength analysis model includes: Extracting data features of the process parameters and the actual ratio data; Extracting a linear function of the concrete strength analysis model; Calculating model parameters and errors of the concrete strength analysis model according to the data characteristics; Based on the linear function, the data features, the model parameters and the error, the ultimate strength of the concrete is calculated using the following formula: , in, represents the final strength, represents the number of data features, Indicates Data features, Indicates The model parameters corresponding to the data features are Indicates error.

[0010] Optionally, respectively extracting the workability feature and the uniformity feature of the concrete image data comprises: Extracting a concrete flow contour of the concrete image data, and calculating a flow area and a flow shape of the concrete corresponding to the concrete image data based on the concrete flow contour; Analyzing the fluidity of the concrete according to the flow area and the flow shape; Analyzing texture features of the concrete image data, and analyzing cohesion, cohesive structure, and texture uniformity of the concrete based on the texture features; analyzing brightness features of the concrete image data, and identifying moisture areas of the concrete according to the brightness features; Analyzing the water retention of the concrete according to the moisture region, and determining the workability characteristics of the concrete according to the water retention, the cohesion, the cohesion structure and the fluidity; Calculating a color histogram of the concrete image data, and analyzing the structural uniformity of the concrete based on the color histogram; Based on the texture uniformity and the structural uniformity, a uniformity characteristic of the concrete is determined.

[0011] Optionally, the analyzing the workability of the concrete based on the workability characteristics using a preset workability analysis algorithm comprises: quantifying the workability characteristic to obtain a workability characteristic value; Analyzing feature correlations of the workability features, and determining feature weights of the workability features based on the feature correlations; According to the workability characteristic value and the characteristic weight, the workability of the concrete is analyzed using the workability analysis algorithm, wherein the workability analysis algorithm includes: , in, Indicates the workability of concrete. Expressed that The exponential function of the base, represents the number of tradeability features, Indicates The corresponding trait value of the trait is Indicates The feature weights corresponding to the transmissibility features are Represents a constant.

[0012] Optionally, the analyzing the uniformity of the concrete based on the uniformity feature and using a preset uniformity algorithm includes: calculating a characteristic coefficient of variation and a characteristic standard deviation of the uniformity characteristic; Analyzing a coefficient of variation weight of the characteristic coefficient of variation and a standard deviation weight of the characteristic standard deviation; The uniformity of the concrete is calculated using the uniformity algorithm according to the characteristic coefficient of variation, the characteristic standard deviation, the coefficient of variation weight, and the standard deviation weight, wherein the uniformity algorithm includes: , in, Indicates uniformity, represents the number of uniformity features, Indicates The coefficient of variation weight corresponding to the uniformity feature is Indicates The characteristic variation coefficient corresponding to the uniformity feature is Indicates The standard deviation weight corresponding to the uniformity feature, Indicates The characteristic standard deviation corresponding to the uniformity feature is Indicates the maximum value of the standard deviation of the uniformity feature. Represents the maximum value function.

[0013] Optionally, the multi-objective process optimization algorithm for defining the process flow based on the production quality includes: Determining multiple optimization objectives of the process flow according to the production quality; Constructing an optimization algorithm framework for the process flow, and determining a multi-objective function of the optimization algorithm framework according to the multiple optimization objectives; Analyzing the decision variables of the multi-objective function and constructing constraint conditions of the decision variables; Constructing an initial optimization algorithm for the process flow according to the constraint conditions, the multi-objective function and the optimization algorithm framework; The algorithm performance of the initial optimization algorithm is analyzed, and when the algorithm performance meets a preset algorithm performance standard, the initial optimization algorithm is used as the multi-objective process optimization algorithm of the process flow.

[0014] The embodiment of the present invention can ensure that the concrete product meets the relevant national and industry standards and specifications by calculating the batching ratio of the raw materials corresponding to the concrete, which is convenient for passing quality inspection and certification, while reducing unnecessary material waste, reducing production costs, and improving economic benefits; optionally, the embodiment of the present invention can realize automatic monitoring of the batching process by constructing a raw material ratio detection module based on the batching ratio, ensuring the accuracy of the raw material ratio in the concrete production process, reducing human errors, and improving product quality consistency and production efficiency; the embodiment of the present invention can monitor the key parameters in the process flow in real time by configuring the sensor network of the process flow corresponding to the concrete, realizing automatic control of the production process, reducing human intervention, and improving production efficiency; The embodiment of the invention analyzes the final strength of the concrete according to the process parameters and the actual mix ratio data using a trained concrete strength analysis model, and can quickly feedback concrete strength information, so that the production process can be adjusted in time, avoiding the production of unqualified products and improving production efficiency; the embodiment of the invention analyzes the production quality of the concrete according to the final strength, workability and uniformity, and can realize real-time monitoring of the production process through the analysis of these key performance indicators, timely discover problems and give feedback, so as to quickly adjust the production process, and finally, based on the multi-objective process optimization algorithm, the optimization control of the process flow can make the process flow more flexible, reduce fluctuations in the production process, and thus improve the stability and consistency of the product. Therefore, the precise effect of online monitoring and management of the process flow of the concrete production line is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A functional module diagram of an online monitoring and management system for a concrete production line process provided by an embodiment of the present invention; Figure 2 A schematic diagram of a process flow of an online monitoring and management method for a concrete production line process provided by an embodiment of the present invention; The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] In addition, the step sequence in the following method embodiments is only an example and not a strict limitation.

[0018] In fact, the server-side equipment deployed by the online monitoring and management system for the process flow of a concrete production line may be composed of one or more devices. The above-mentioned online monitoring and management system for the process flow of a concrete production line can be implemented as: a business instance, a virtual machine, and a hardware device. For example, the online monitoring and management system for the process flow of a concrete production line can be implemented as a business instance deployed on one or more devices in a cloud node. In simple terms, the online monitoring and management system for the process flow of a concrete production line can be understood as a software deployed on a cloud node, which is used to provide online monitoring and management services for the process flow of a concrete production line to each user end. Alternatively, the online monitoring and management system for the process flow of a concrete production line can also be implemented as a virtual machine deployed on one or more devices in a cloud node. Application software for managing each user end is installed in the virtual machine. Alternatively, the online monitoring and management system for the process flow of a concrete production line can also be implemented as a server end composed of many hardware devices of the same or different types, and one or more hardware devices are set to provide online monitoring and management services for the process flow of a concrete production line to each user end.

[0019] In terms of implementation, the online monitoring and management system for the process flow of concrete production lines and the user end are adapted to each other. That is, the online monitoring and management system for the process flow of concrete production lines is an application installed on the cloud service platform, and the user end is a client that establishes a communication connection with the application; or the online monitoring and management system for the process flow of concrete production lines is implemented as a website, and the user end is implemented as a web page; or the online monitoring and management system for the process flow of concrete production lines is implemented as a cloud service platform, and the user end is implemented as a small program in an instant messaging application.

[0020] Reference Figure 1 , which is a functional module diagram of an online monitoring and management system for a concrete production line process provided by an embodiment of the present invention.

[0021] The online monitoring and management system 100 for the process flow of a concrete production line of the present invention can be set in a cloud server. In terms of implementation, it can be used as one or more service devices, or it can be installed as an application on the cloud (e.g., a server, server cluster, etc. for online monitoring and management of the process flow of a concrete production line), or it can be developed as a website. According to the functions implemented, the online monitoring and management system 100 for the process flow of a concrete production line includes a mix ratio detection module 101, a data acquisition module 102, a final strength module 103, a production quality analysis module 104, and a process flow optimization module 105.

[0022] In the embodiment of the present invention, in the tracking of online monitoring and management of the process flow of the concrete production line, each of the above modules can be implemented independently and called with other modules. The call here can be understood as that a certain module can connect to multiple modules of another type and provide corresponding services to the multiple modules connected to it. In the online monitoring and management system of the process flow of the concrete production line provided by the embodiment of the present invention, the scope of application of the online monitoring and management architecture of the process flow of the concrete production line can be adjusted by adding modules and directly calling them without modifying the program code, so as to achieve cluster-based horizontal expansion, so as to achieve the purpose of quickly and flexibly expanding the online monitoring and management system of the process flow of the concrete production line. In practical applications, the above modules can be set in the same device or different devices, or they can be set in virtual devices, such as service instances in cloud servers.

[0023] In the following, in conjunction with specific embodiments, each component and specific workflow of the online monitoring and management system for the process flow of a concrete production line are described respectively.

[0024] The ratio detection module 101 is used to calculate the ratio of the raw materials corresponding to the concrete, and based on the ratio, construct a ratio detection module for the raw materials, and use the ratio detection module to detect actual ratio data of the concrete.

[0025] The embodiment of the present invention can ensure that the concrete product meets the relevant national and industry standards and specifications by calculating the batching ratio of the raw materials corresponding to the concrete, which is convenient for passing quality inspection and certification, while reducing unnecessary material waste, reducing production costs, and improving economic benefits. The batching ratio refers to the relative quantitative relationship between various raw materials (such as cement, water, aggregates, admixtures and additives) in the concrete production process, which is usually expressed in weight ratio or volume ratio.

[0026] As an embodiment of the present invention, the calculating the batching ratio of the raw materials corresponding to the concrete includes: Analyzing the key materials of the raw materials, wherein the key materials include: water, cement and aggregate; Determining the water-binder ratio of the raw materials based on the production quality requirements of the concrete; Extracting the concrete density requirement of the production quality requirement, and calculating the coarse aggregate material coefficient and the fine aggregate material coefficient of the aggregate respectively based on the concrete density requirement; According to the water-cement ratio, the coarse aggregate material coefficient and the fine aggregate material coefficient, the proportion of the raw materials is calculated using the following formula: , , , , in, Indicates the proportion of ingredients. Indicates the water quality corresponding to water, represents the water-to-binder ratio, represents the cement mass corresponding to cement, Indicates the mass of aggregate corresponding to coarse aggregate, Indicates the mass of aggregate corresponding to fine aggregate, It represents the material coefficient of coarse aggregate. Indicates the fine aggregate material coefficient.

[0027] Among them, the key materials refer to the main raw materials that play a decisive role in the performance of concrete. The aggregate refers to the inert material used in concrete, which constitutes the skeleton of concrete and provides the volume stability, durability and mechanical properties of concrete, including coarse aggregate (such as crushed stone, limestone, etc.) and fine aggregate (such as river sand, sea sand, etc.). The water-cement ratio refers to the ratio of the mass of water in the concrete mixture to the total mass of cement and cement substitutes (if any). The concrete density requirement refers to the specific density value that concrete needs to achieve during design, which reflects the compactness of concrete and the content of solid materials. The coarse aggregate material coefficient refers to the coefficient used to determine the proportional relationship between the amount of coarse aggregate and the total volume or total mass of concrete. The fine aggregate material coefficient refers to the coefficient used to determine the proportional relationship between the amount of fine aggregate and the total volume or total mass of concrete.

[0028] Optionally, the coarse aggregate material coefficient and the fine aggregate material coefficient of the aggregate respectively calculated based on the concrete density requirement may be calculated by an empirical formula method.

[0029] The embodiment of the present invention can realize automatic monitoring of the batching process by constructing the raw material ratio detection module based on the batching ratio, ensuring the accuracy of the raw material ratio in the concrete production process, reducing human errors, and improving the consistency of product quality and production efficiency. The ratio detection module refers to an integrated hardware and software system for monitoring and ensuring that the raw materials are accurately mixed according to a predetermined ratio during the concrete production process.

[0030] As an embodiment of the present invention, the ratio detection module of the raw materials is constructed based on the ratio of the ingredients, including: Constructing a detection module framework of the raw materials, and determining a raw material identification unit of the detection module framework according to the ingredient ratio; identifying the raw material type of the raw material according to the raw material identification unit; A weight sensor and a flow meter are configured for the detection module frame; Based on the weight sensor, determining the solid weight of the solid material corresponding to the raw material; Determining the liquid flow rate of the raw material corresponding to the liquid material according to the flow meter; Determine a ratio analysis unit of the detection module framework according to the raw material type, the solid weight and the liquid flow rate; Based on the raw material identification unit, the ratio analysis unit and the detection module framework, a ratio detection module for the raw materials is constructed.

[0031] Among them, the detection module framework refers to a systematic structure for detecting the raw material ratio in the concrete production process. The raw material identification unit refers to a component used to identify and confirm the various raw materials entering the batching system. The raw material type refers to the classification of various raw materials used in concrete production. The weight sensor refers to a sensor used to measure the weight of an object. The flow meter refers to an instrument used to measure the volume or mass flow rate of a fluid (liquid or gas) flowing in a pipeline. The solid weight refers to the actual weight of a solid substance under certain conditions. The liquid flow rate refers to the volume of a liquid passing through a certain cross-section within a certain period of time. The ratio analysis unit refers to a component used to analyze and control the raw material ratio.

[0032] The embodiment of the present invention can automatically detect the mix ratio by using the mix ratio detection module to detect the actual mix ratio data of the concrete, thereby improving production efficiency, reducing downtime, and achieving continuous production. The actual mix ratio data refers to data on the actual usage of raw materials collected by various sensors and measuring devices.

[0033] The data acquisition module 102 is used to configure a sensor network corresponding to the process flow of the concrete, and based on the sensor network, collect the process parameters and concrete image data of the process flow in real time. The embodiment of the present invention can monitor the key parameters in the process flow in real time by configuring the sensor network corresponding to the process flow of the concrete, realize the automatic control of the production process, reduce manual intervention, and improve production efficiency. The sensor network refers to a system composed of multiple sensors, which cooperate with each other to monitor, collect, process and transmit various parameters and data in the concrete production process.

[0034] As an embodiment of the present invention, the sensor network configured to correspond to the process flow of concrete includes: Analyze the monitoring requirements of the process flow, and determine the sensor type and installation location of the sensor corresponding to the process flow according to the monitoring requirements; Construct the network architecture and communication protocol of the sensor, and plan the data transmission frequency and bandwidth requirements of the sensor; Constructing a communication network for the sensor according to the network architecture, the communication protocol, the data transmission frequency, and the bandwidth requirement; Based on the sensor type, the installation location and the communication network, a sensor network of the process flow is integrated.

[0035] Among them, the monitoring requirements refer to the requirements for real-time or regular monitoring of a series of key parameters and states in the concrete production process in order to ensure production efficiency, product quality and safe production. The sensor type refers to different types of sensors used to sense and convert various physical or chemical quantities into measurable signals according to the monitoring requirements. The installation location refers to the specific location where the sensor is placed or installed to meet the monitoring requirements. The network architecture refers to the network layout and structure used to connect various monitoring devices, sensors, control units and data storage and analysis systems in a concrete production system. The communication protocol refers to a series of rules and standards that define how data is transmitted, received and processed in the sensor network. The data transmission frequency refers to the number of times data is transmitted from the sending device to the receiving device within a certain period of time, usually measured in packets or bits transmitted per second. The bandwidth requirement refers to the capacity of the network bandwidth required to ensure that data can be effectively transmitted. The communication network refers to the infrastructure used to connect various devices, sensors, controllers and computer systems so that they can exchange data and instructions with each other.

[0036] Optionally, the network architecture and communication protocol for constructing the sensor can be constructed by network protocol stack development technology.

[0037] The embodiment of the present invention can analyze the process parameters, optimize the production process, reduce unnecessary waiting time and resource waste, and improve production efficiency by collecting the process parameters and concrete image data of the process in real time based on the sensor network. The process parameters refer to key variables that need to be monitored and controlled during the concrete production process, such as temperature, humidity, pressure, mixing time, etc. The concrete image data refers to the visual information of the concrete surface and internal structure obtained by an image acquisition device (such as a camera, scanner, etc.).

[0038] The final strength module 103 is used to analyze the final strength of the concrete according to the process parameters and the actual mix ratio data using a trained concrete strength analysis model.

[0039] The embodiment of the present invention can quickly feedback concrete strength information by analyzing the final strength of the concrete according to the process parameters and the actual mix ratio data using a trained concrete strength analysis model, so that the production process can be adjusted in time to avoid the production of unqualified products and improve production efficiency. The concrete strength analysis model refers to a mathematical model for predicting and evaluating the compressive strength or other related strength characteristics of concrete. The final strength refers to the compressive strength of concrete when it reaches the design age under specified curing conditions.

[0040] As an embodiment of the present invention, analyzing the final strength of the concrete according to the process parameters and the actual mix ratio data using a trained concrete strength analysis model includes: Extracting data features of the process parameters and the actual ratio data; Extracting a linear function of the concrete strength analysis model; Calculating model parameters and errors of the concrete strength analysis model according to the data characteristics; Based on the linear function, the data features, the model parameters and the error, the ultimate strength of the concrete is calculated using the following formula: , in, represents the final strength, represents the number of data features, Indicates Data features, Indicates The model parameters corresponding to the data features are Indicates error.

[0041] The data features refer to variables extracted from process parameters and actual mix ratio data that can represent the properties and preparation process of concrete. The linear function refers to a function of the concrete strength analysis model that describes the linear relationship between two variables. The model parameters refer to variables used within the model to describe the relationship between data features and prediction targets. The error refers to the difference between the predicted value and the actual observed value in the data analysis model.

[0042] Optionally, the model parameters and errors of the concrete strength analysis model calculated according to the data characteristics may be calculated by a least squares method.

[0043] The production quality analysis module 104 is used to respectively extract the workability characteristics and uniformity characteristics of the concrete image data, analyze the workability of the concrete based on the workability characteristics using a preset workability analysis algorithm, analyze the uniformity of the concrete based on the uniformity characteristics using a preset uniformity algorithm, and analyze the production quality of the concrete according to the final strength, the workability and the uniformity.

[0044] The embodiment of the present invention can extract and analyze the features in real time by respectively extracting the workability features and uniformity features of the concrete image data, timely discover quality problems, and provide a basis for real-time adjustment of the production line. The workability features refer to features related to the fluidity, plasticity, cohesion and stability of concrete. The uniformity features refer to indicators that describe the consistency of the internal composition and properties of concrete.

[0045] As an embodiment of the present invention, the extracting workability features and uniformity features of the concrete image data respectively includes: Extracting a concrete flow contour of the concrete image data, and calculating a flow area and a flow shape of the concrete corresponding to the concrete image data based on the concrete flow contour; Analyzing the fluidity of the concrete according to the flow area and the flow shape; Analyzing texture features of the concrete image data, and analyzing cohesion, cohesive structure, and texture uniformity of the concrete based on the texture features; analyzing brightness features of the concrete image data, and identifying moisture areas of the concrete according to the brightness features; Analyzing the water retention of the concrete according to the moisture region, and determining the workability characteristics of the concrete according to the water retention, the cohesion, the cohesion structure and the fluidity; Calculating a color histogram of the concrete image data, and analyzing the structural uniformity of the concrete based on the color histogram; Based on the texture uniformity and the structural uniformity, a uniformity characteristic of the concrete is determined.

[0046] Among them, the concrete flow contour refers to the edge or boundary line formed by concrete during the flow process. The flow area refers to the size of the plane area covered by concrete during the flow process. The flow shape refers to the geometric shape or contour formed by concrete during the flow process. The fluidity refers to the ability of concrete to flow and fill a mold or other space under its own weight or slight external force. The texture feature refers to the quantitative description of the visual attributes of concrete, such as pattern, structure, roughness, regularity, etc. The cohesion refers to the bonding force between the components of concrete, reflecting the ability of the particles inside the concrete mixture to attract each other and maintain integrity. The cohesive structure refers to the solid and stable microstructure formed inside the concrete due to the bonding between cement paste and aggregate. The texture uniformity refers to the uniformity of the texture characteristics on the surface or inside of concrete, reflecting the consistency and regularity of the texture of concrete at the micro and macro levels. The brightness feature refers to the brightness of the pixels in the image. The moisture area refers to the area with high water content on the surface or inside of concrete. The water retention is the ability of concrete to retain internal water without loss. The color histogram refers to a statistical chart showing the frequency distribution of various colors in an image. The structural uniformity refers to the uniformity of the internal structure of concrete.

[0047] Optionally, the extracting of the concrete flow contour of the concrete image data may be performed by edge detection.

[0048] Optionally, the identifying of the moisture area of ​​the concrete according to the brightness feature may be performed by a color threshold method.

[0049] The embodiment of the present invention can monitor the concrete production process by analyzing the workability of the concrete based on the workability characteristics and using a preset workability analysis algorithm to ensure that the quality of each batch of concrete meets the standards. The workability analysis algorithm refers to a calculation method for evaluating the working performance of concrete. The workability refers to the performance of concrete that is easy to operate, transport, pour and form during the construction process.

[0050] As an embodiment of the present invention, the analyzing the workability of the concrete based on the workability characteristics using a preset workability analysis algorithm includes: quantifying the workability characteristic to obtain a workability characteristic value; Analyzing feature correlations of the workability features, and determining feature weights of the workability features based on the feature correlations; According to the workability characteristic value and the characteristic weight, the workability of the concrete is analyzed using the workability analysis algorithm, wherein the workability analysis algorithm includes: , in, Indicates the workability of concrete. Expressed that The exponential function of the base, represents the number of tradeability features, Indicates The corresponding trait value of the trait is Indicates The feature weights corresponding to the transmissibility features are Represents a constant.

[0051] The workability characteristic value refers to the quantitative measurement result of various aspects of concrete workability characteristics. The characteristic correlation refers to the degree and direction of the relationship between different characteristics or variables. The characteristic weight refers to the numerical value assigned to the relative importance of different characteristics or variables.

[0052] Optionally, the feature correlation of the analysis of the workability characteristics can be analyzed by regression analysis method.

[0053] The embodiment of the present invention analyzes the uniformity of the concrete by using a preset uniformity algorithm based on the uniformity feature, and can optimize the mixing, pouring and curing process of the concrete by analyzing the uniformity results, thereby improving production efficiency and quality control level. The uniformity algorithm refers to a calculation method for evaluating and quantifying the uniformity of a material, structure or system. The uniformity refers to the uniformity or consistency of a certain property of a concrete structure in space.

[0054] As an embodiment of the present invention, the step of analyzing the uniformity of the concrete based on the uniformity feature and using a preset uniformity algorithm includes: calculating a characteristic coefficient of variation and a characteristic standard deviation of the uniformity characteristic; Analyzing a coefficient of variation weight of the characteristic coefficient of variation and a standard deviation weight of the characteristic standard deviation; The uniformity of the concrete is calculated using the uniformity algorithm according to the characteristic coefficient of variation, the characteristic standard deviation, the coefficient of variation weight, and the standard deviation weight, wherein the uniformity algorithm includes: , in, Indicates uniformity, represents the number of uniformity features, Indicates The coefficient of variation weight corresponding to the uniformity feature is Indicates The characteristic variation coefficient corresponding to the uniformity feature is Indicates The standard deviation weight corresponding to the uniformity feature, Indicates The characteristic standard deviation corresponding to the uniformity feature is Indicates the maximum value of the standard deviation of the uniformity feature. Represents the maximum value function.

[0055] The embodiment of the present invention analyzes the production quality of the concrete according to the final strength, the workability and the uniformity, and can monitor the production process in real time, find problems in time and give feedback through the analysis of these key performance indicators, so as to quickly adjust the production process. The production quality refers to a series of quality standards and performance indicators achieved by concrete products during the production and manufacturing process.

[0056] Optionally, as an embodiment of the present invention, the analysis of the production quality of the concrete based on the final strength, the workability and the uniformity may be analyzed by a machine learning algorithm.

[0057] The process flow optimization module 105 is used to define a multi-objective process optimization algorithm for the process flow based on the production quality, and perform optimization control of the process flow based on the multi-objective process optimization algorithm.

[0058] In the embodiment of the present invention, a multi-objective process optimization algorithm is defined based on the production quality, and the process flow can be optimized by optimizing process parameters, reducing unnecessary processes and waiting time, and improving the operation efficiency of the production line. The multi-objective process optimization algorithm refers to a mathematical optimization method for simultaneously optimizing two or more conflicting objective functions.

[0059] As an embodiment of the present invention, the multi-objective process optimization algorithm based on defining the process flow according to the production quality includes: Determining multiple optimization objectives of the process flow according to the production quality; Constructing an optimization algorithm framework for the process flow, and determining a multi-objective function of the optimization algorithm framework according to the multiple optimization objectives; Analyzing the decision variables of the multi-objective function and constructing constraint conditions of the decision variables; Constructing an initial optimization algorithm for the process flow according to the constraint conditions, the multi-objective function and the optimization algorithm framework; The algorithm performance of the initial optimization algorithm is analyzed, and when the algorithm performance meets a preset algorithm performance standard, the initial optimization algorithm is used as the multi-objective process optimization algorithm of the process flow.

[0060] Among them, the multiple optimization objectives refer to multiple objectives that may conflict with each other that are pursued simultaneously during the optimization process. The optimization algorithm framework refers to a set of structures and processes used to solve optimization problems, which includes the basic components and execution steps of the algorithm. The multi-objective function refers to multiple objectives or objective functions that need to be optimized simultaneously in the optimization problem. The decision variable refers to the variable that affects the value of the optimization objective function. The constraint condition refers to the restriction imposed on the value range or solution of the decision variable in the optimization problem. The initial optimization algorithm refers to the first or preliminary optimization algorithm used when starting to solve an optimization problem. The algorithm performance refers to the performance of an algorithm in terms of efficiency, effect and resource consumption when performing a specific task. The preset algorithm performance standard refers to a series of performance indicators and thresholds set to meet specific application requirements.

[0061] Optionally, the multi-objective function of the optimization algorithm framework determined according to the multiple optimization objectives can be determined by a multi-objective genetic algorithm.

[0062] The embodiment of the present invention can make the process more flexible and reduce fluctuations in the production process by performing optimization control of the process flow based on the multi-objective process optimization algorithm, thereby improving the stability and consistency of the product.

[0063] Optionally, as an embodiment of the present invention, the performing of the optimization control of the process flow based on the multi-objective process optimization algorithm may be performed by calculating the optimization control parameters of the process flow.

[0064] The embodiment of the present invention can ensure that the concrete product meets the relevant national and industry standards and specifications by calculating the batching ratio of the raw materials corresponding to the concrete, which is convenient for passing quality inspection and certification, while reducing unnecessary material waste, reducing production costs, and improving economic benefits; optionally, the embodiment of the present invention can realize automatic monitoring of the batching process by constructing a raw material ratio detection module based on the batching ratio, ensuring the accuracy of the raw material ratio in the concrete production process, reducing human errors, and improving product quality consistency and production efficiency; the embodiment of the present invention can monitor the key parameters in the process flow in real time by configuring the sensor network of the process flow corresponding to the concrete, realizing automatic control of the production process, reducing human intervention, and improving production efficiency; The embodiment of the invention analyzes the final strength of the concrete according to the process parameters and the actual mix ratio data using a trained concrete strength analysis model, and can quickly feedback concrete strength information, so that the production process can be adjusted in time, avoiding the production of unqualified products and improving production efficiency; the embodiment of the invention analyzes the production quality of the concrete according to the final strength, workability and uniformity, and can realize real-time monitoring of the production process through the analysis of these key performance indicators, timely discover problems and give feedback, so as to quickly adjust the production process, and finally, based on the multi-objective process optimization algorithm, the optimization control of the process flow can make the process flow more flexible, reduce fluctuations in the production process, and thus improve the stability and consistency of the product. Therefore, the precise effect of online monitoring and management of the process flow of the concrete production line is improved.

[0065] like Figure 2 FIG. 1 is a flow chart of an online monitoring management method for a process flow of a concrete production line provided by an embodiment of the present invention. In this embodiment, the online monitoring management method for a process flow of a concrete production line includes: Calculating the proportion of raw materials corresponding to the concrete, building a proportion detection module for the raw materials based on the proportion, and using the proportion detection module to detect actual proportion data of the concrete; A sensor network is configured for the concrete process flow, and based on the sensor network, process parameters of the process flow and concrete image data are collected in real time; Analyzing the final strength of the concrete using a trained concrete strength analysis model according to the process parameters and the actual mix ratio data; Respectively extracting workability features and uniformity features of the concrete image data, analyzing the workability of the concrete based on the workability features using a preset workability analysis algorithm, analyzing the uniformity of the concrete based on the uniformity features using a preset uniformity algorithm, and analyzing the production quality of the concrete according to the final strength, the workability and the uniformity; Based on the production quality, a multi-objective process optimization algorithm for defining the process flow is defined, and based on the multi-objective process optimization algorithm, optimization control of the process flow is performed.

[0066] In the several embodiments provided by the present invention, it should be understood that the provided system and method can be implemented in other ways. For example, the system embodiment described above is only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0067] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A concrete production line process online monitoring and management system, characterized in that: The system comprises: A ratio detection module is used to calculate the ratio of the raw materials corresponding to the concrete, build a ratio detection module for the raw materials based on the ratio, and use the ratio detection module to detect the actual ratio data of the concrete; A data acquisition module, used to configure a sensor network corresponding to the process flow of the concrete, and based on the sensor network, to collect process parameters and concrete image data of the process flow in real time; A final strength module, used to analyze the final strength of the concrete according to the process parameters and the actual mix ratio data using a trained concrete strength analysis model; a production quality analysis module, for respectively extracting workability features and uniformity features of the concrete image data, analyzing the workability of the concrete based on the workability features using a preset workability analysis algorithm, analyzing the uniformity of the concrete based on the uniformity features using a preset uniformity algorithm, and analyzing the production quality of the concrete according to the final strength, the workability and the uniformity; A process flow optimization module is used to define a multi-objective process optimization algorithm for the process flow based on the production quality, and to perform optimization control of the process flow based on the multi-objective process optimization algorithm.

2. The online monitoring and management system for the process flow of a concrete production line according to claim 1, characterized in that: Calculating the proportion of raw materials corresponding to the concrete, including: Analyzing the key materials of the raw materials, wherein the key materials include: water, cement and aggregate; Determining the water-binder ratio of the raw materials based on the production quality requirements of the concrete; Extracting the concrete density requirement of the production quality requirement, and calculating the coarse aggregate material coefficient and the fine aggregate material coefficient of the aggregate respectively based on the concrete density requirement; According to the water-cement ratio, the coarse aggregate material coefficient and the fine aggregate material coefficient, the proportion of the raw materials is calculated using the following formula: ， ， ， ， in, Indicates the proportion of ingredients. Indicates the water quality corresponding to water, represents the water-to-binder ratio, represents the cement mass corresponding to cement, Indicates the mass of aggregate corresponding to coarse aggregate, Indicates the mass of aggregate corresponding to fine aggregate, It represents the material coefficient of coarse aggregate. Indicates the fine aggregate material coefficient.

3. The online monitoring and management system for the process flow of a concrete production line according to claim 1, characterized in that: Based on the ingredient ratio, a ratio detection module for the raw materials is constructed, including: Constructing a detection module framework of the raw materials, and determining a raw material identification unit of the detection module framework according to the ingredient ratio; identifying the raw material type of the raw material according to the raw material identification unit; A weight sensor and a flow meter are configured for the detection module frame; Based on the weight sensor, determining the solid weight of the solid material corresponding to the raw material; Determining the liquid flow rate of the raw material corresponding to the liquid material according to the flow meter; Determine a ratio analysis unit of the detection module framework according to the raw material type, the solid weight and the liquid flow rate; Based on the raw material identification unit, the ratio analysis unit and the detection module framework, a ratio detection module for the raw materials is constructed.

4. The online monitoring and management system for the process flow of a concrete production line according to claim 1, characterized in that: Configuring a sensor network corresponding to the concrete process flow includes: Analyze the monitoring requirements of the process flow, and determine the sensor type and installation location of the sensor corresponding to the process flow according to the monitoring requirements; Construct the network architecture and communication protocol of the sensor, and plan the data transmission frequency and bandwidth requirements of the sensor; Constructing a communication network for the sensor according to the network architecture, the communication protocol, the data transmission frequency, and the bandwidth requirement; Based on the sensor type, the installation location and the communication network, a sensor network of the process flow is integrated.

5. The online monitoring and management system for the process flow of a concrete production line according to claim 1, characterized in that: According to the process parameters and the actual mix ratio data, using the trained concrete strength analysis model, analyzing the final strength of the concrete, including: Extracting data features of the process parameters and the actual ratio data; Extracting a linear function of the concrete strength analysis model; Calculating model parameters and errors of the concrete strength analysis model according to the data characteristics; Based on the linear function, the data features, the model parameters and the error, the ultimate strength of the concrete is calculated using the following formula: ， in, represents the final strength, represents the number of data features, Indicates Data features, Indicates The model parameters corresponding to the data features are Indicates error.

6. The online monitoring and management system for the process flow of a concrete production line according to claim 1, characterized in that: Extracting workability features and uniformity features of the concrete image data respectively, including: Extracting a concrete flow contour of the concrete image data, and calculating a flow area and a flow shape of the concrete corresponding to the concrete image data based on the concrete flow contour; Analyzing the fluidity of the concrete according to the flow area and the flow shape; Analyzing texture features of the concrete image data, and analyzing cohesion, cohesive structure, and texture uniformity of the concrete based on the texture features; analyzing brightness features of the concrete image data, and identifying moisture areas of the concrete according to the brightness features; Analyzing the water retention of the concrete according to the moisture region, and determining the workability characteristics of the concrete according to the water retention, the cohesion, the cohesion structure and the fluidity; Calculating a color histogram of the concrete image data, and analyzing the structural uniformity of the concrete based on the color histogram; Based on the texture uniformity and the structural uniformity, a uniformity characteristic of the concrete is determined.

7. The online monitoring and management system for the process flow of a concrete production line according to claim 1, characterized in that: Based on the workability characteristics, the workability of concrete is analyzed using a preset workability analysis algorithm, including: quantifying the workability characteristic to obtain a workability characteristic value; Analyzing feature correlations of the workability features, and determining feature weights of the workability features based on the feature correlations; According to the workability characteristic value and the characteristic weight, the workability of the concrete is analyzed using the workability analysis algorithm, wherein the workability analysis algorithm includes: ， in, Indicates the workability of concrete. Expressed that The exponential function of the base, represents the number of tradeability features, Indicates The corresponding trait value of the trait is Indicates The feature weights corresponding to the transmissibility features are Represents a constant.

8. The online monitoring and management system for the process flow of a concrete production line according to claim 1, characterized in that: Based on the uniformity characteristics, the uniformity of the concrete is analyzed using a preset uniformity algorithm, including: calculating a characteristic coefficient of variation and a characteristic standard deviation of the uniformity characteristic; Analyzing a coefficient of variation weight of the characteristic coefficient of variation and a standard deviation weight of the characteristic standard deviation; The uniformity of the concrete is calculated using the uniformity algorithm according to the characteristic coefficient of variation, the characteristic standard deviation, the coefficient of variation weight, and the standard deviation weight, wherein the uniformity algorithm includes: ， in, Indicates uniformity, represents the number of uniformity features, Indicates The coefficient of variation weight corresponding to the uniformity feature is Indicates The characteristic variation coefficient corresponding to the uniformity feature is Indicates The standard deviation weight corresponding to the uniformity feature, Indicates The characteristic standard deviation corresponding to the uniformity feature is Indicates the maximum value of the standard deviation of the uniformity feature. Represents the maximum value function.

9. The online monitoring and management system for the process flow of a concrete production line according to claim 1, characterized in that: Based on the production quality, a multi-objective process optimization algorithm for defining the process flow includes: Determining multiple optimization objectives of the process flow according to the production quality; Constructing an optimization algorithm framework for the process flow, and determining a multi-objective function of the optimization algorithm framework according to the multiple optimization objectives; Analyzing the decision variables of the multi-objective function and constructing constraint conditions of the decision variables; Constructing an initial optimization algorithm for the process flow according to the constraint conditions, the multi-objective function and the optimization algorithm framework; The algorithm performance of the initial optimization algorithm is analyzed, and when the algorithm performance meets a preset algorithm performance standard, the initial optimization algorithm is used as the multi-objective process optimization algorithm of the process flow.

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