Foam concrete online monitoring method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of building material monitoring, in particular to a foam concrete online monitoring method and device, computer equipment and a storage medium, and the method comprises the following steps: obtaining a foam concrete production instruction, obtaining preset foaming production process data according to the foam concrete production instruction, acquiring real-time concrete feeding end data according to the foaming process data; calculating the concrete feeding end data according to the production process data to obtain foam concrete production data; performing foaming degree judgment on the foam concrete production data to obtain a foaming degree judgment result; and performing foamed concrete finished product prediction according to the foaming degree judgment result, and generating a process data adjustment instruction according to a finished product prediction result so as to adjust the foaming process data. According to the invention, key parameters in the foam concrete production process can be accurately monitored in real time, and the production process can be monitored and regulated in real time.

Description

Technical Field

[0001] The present application relates to the technical field of building material monitoring, and in particular to a foam concrete online monitoring method, device, computer equipment and storage medium. Background Art

[0002] Foamed concrete is a lightweight and porous concrete structure formed by introducing foam into a slurry made of cementitious materials and water through specific physical or chemical methods, followed by sufficient mixing and stirring. In the entire production process of foamed concrete, it is of vital importance to accurately monitor and continuously monitor its key parameters in real time. This not only affects whether the quality of the final product can meet the standards, but also directly affects the optimization effect of the production process and the degree of improvement in production efficiency.

[0003] However, the existing monitoring methods, to a large extent, mostly carry out sampling monitoring of foam concrete finished products after the production work is completed. This offline monitoring method has many obvious defects. First, the monitoring results are often delayed and cannot provide timely and effective data support for the production process in the first place. Secondly, since it is impossible to obtain information in the production process in real time, it is impossible to timely feedback on various problems that may arise, making it difficult for potential risks in the production process to be detected and resolved in time. Finally, such a monitoring model is difficult to truly realize real-time regulation of the production process, resulting in the inability to achieve rapid and accurate optimization and improvement in the production process, which to a certain extent restricts the overall level and development potential of foam concrete production. Summary of the invention

[0004] In order to monitor the key parameters in the foam concrete production process in real time and accurately and realize real-time monitoring and regulation of the production process, the present application provides a foam concrete online monitoring method, device, computer equipment and storage medium.

[0005] The above-mentioned invention objective of the present application is achieved through the following technical solutions: A foam concrete online monitoring method, the foam concrete online monitoring method comprising: Obtaining a foamed concrete production instruction, obtaining preset foaming production process data according to the foamed concrete production instruction, and obtaining real-time concrete feed end data according to the foaming process data; Calculating the concrete feed end data according to the production process data to obtain foamed concrete production data; Performing foaming degree judgment on the foamed concrete production data to obtain a foaming degree judgment result; The foamed concrete finished product is predicted according to the foaming degree judgment result, and the process data adjustment instruction is generated according to the finished product prediction result to adjust the foaming process data.

[0006] By adopting the above technical solution, by obtaining the foam concrete production instructions, the preset foaming production process data is automatically retrieved from the stored production process database, so that the monitoring strategy can be dynamically adjusted according to the actual production needs, so that the monitoring is more adaptable to the changes under different production conditions. According to the specific production instructions, the real-time concrete feed end data is further obtained, which covers the instantaneous values ​​of various key parameters in the foam concrete feeding process, such as cement dosage, cement slurry water dosage, air dosage, foaming agent dosage and foaming water dosage. By obtaining these real-time data of the feed end, each step of the production process can be monitored with high precision, which not only provides a solid foundation for subsequent data processing, but also makes the control of the production process more refined. Next, the concrete feed end data is calculated according to the obtained production process data to obtain the foam concrete production data. This calculation process includes the specific calculation of multiple key parameters such as foam density, cement slurry dosage, wet density, etc. For example, the data such as foaming agent mass, foaming water mass and foam volume collected in real time by the sensor are input into the pre-set calculation formula, and the calculation result of foam density can be quickly obtained. Similarly, for the calculation of cement slurry dosage, the calculation is performed based on the data of cement quality and cement slurry water quality. These calculation results not only accurately reflect the actual situation of the current foamed concrete, but also provide an important basis for the subsequent judgment of the foaming degree. Subsequently, the foaming degree is judged on the obtained foamed concrete production data to obtain the foaming degree judgment result. This process compares and analyzes the obtained production data with the preset standard foaming degree parameters to determine whether the foaming degree of the current foamed concrete meets expectations. Based on the calculation results, the foaming degree judgment results are generated in real time, which can timely discover possible problems in the production process, such as whether the foam density meets the standard range, whether the foaming degree meets expectations, etc., thereby providing an accurate data basis for subsequent finished product prediction. On this basis, the finished product prediction of foamed concrete is carried out. The finished product prediction data generated according to the foaming degree judgment results can help production personnel to understand the actual situation in the current production process in a timely manner. By comparing and analyzing with historical data and ideal conditions, accurate finished product prediction results are generated. Finally, process data adjustment instructions are generated according to the finished product prediction results to adjust the foaming process data, so as to continuously optimize and improve the production process. Through real-time monitoring and data analysis, production process parameters can be adjusted according to actual conditions, so that the production process is more in line with the expected quality standards, ensuring the high quality of the final product.

[0007] In a preferred example, the present application can be further configured as follows: the step of obtaining the foamed concrete production instruction, obtaining preset foaming production process data according to the foamed concrete production instruction, and obtaining real-time concrete feed end data according to the foaming process data specifically includes: Acquire foamed concrete specification data and corresponding concrete production formula data from the production process data; Acquire the feed end type to be monitored and the detection threshold data corresponding to each feed end type to be monitored according to the concrete formula data and the foamed concrete specification data; The concrete feeding end data is acquired according to the feeding end monitoring type and the threshold data to be detected.

[0008] By adopting the above technical solution, when a foam concrete production instruction is received, the specification data of the foamed concrete and the corresponding concrete production formula data will be automatically extracted from the production process data. This process ensures that the operation of the monitoring system is based on specific production needs and expected product specifications, thereby improving the pertinence and effectiveness of the monitoring work. Next, the specific type that needs to be monitored at the feed end and its corresponding threshold data to be detected are determined based on the concrete formula data and the foamed concrete specification data. For example, if the foamed concrete under a certain formula has strict requirements on the amount of cement slurry water, the monitoring system will focus on the changes in this parameter and set a reasonable threshold range, so that it can discover and respond to problems that may affect product quality in the first place, ensuring that the production process is always under control. Then, based on the known feed end monitoring type and its threshold data to be detected, the corresponding concrete feed end data is obtained. The data at the feed end includes the actual measured values ​​of multiple key parameters such as cement usage, cement slurry water usage, etc., and is input into a specially designed calculation formula to evaluate whether the various indicators in the foam concrete production process meet the expected standards. This not only allows real-time grasp of the status changes of each production link, but also enables continuous optimization of production strategies through comparative analysis of historical data, thereby reducing the defective rate and improving production efficiency.

[0009] In a preferred example, the present application can be further configured as follows: the concrete feed end data is calculated according to the production process data to obtain the foamed concrete production data, specifically including: Obtaining a corresponding detection calculation formula according to the feed end monitoring type corresponding to the production process data; The concrete feed end data is input into the detection calculation formula to obtain the concrete production data.

[0010] By adopting the above technical scheme, the foam concrete online monitoring method can obtain the key parameter data of the feed end in real time during the production process, and calculate the specific production situation of the foam concrete by applying these data. First, when the foam concrete production instruction is received, the preset foaming production process data is automatically called to determine the required feed end monitoring type and its corresponding threshold data to be detected. According to the feed end monitoring type and the threshold data to be detected, the real-time concrete feed end data changes can be dynamically captured. Further, according to the feed end monitoring type clearly specified in the production process data, a detection calculation formula suitable for this type can be matched. For example, in the case of tracking parameters such as cement consumption, cement slurry water consumption, and air consumption during the monitoring process, the corresponding detection calculation formula will be selected to process the collected information, and the real-time concrete feed end data obtained will be substituted into these calculation formulas for comprehensive calculation, thereby realizing the effective transformation and utilization of the original monitoring data, and the entire calculation process is not limited to simple numerical superposition or comparison, but scientific calculation is performed by rationally deploying different feed end parameters, so as to obtain more accurate and reliable foam concrete production data. At the same time, it also provides a data basis for judging the degree of foaming and predicting finished products in subsequent links.

[0011] In a preferred example, the present application may be further configured as follows: the foaming degree judgment of the foamed concrete production data is performed to obtain the foaming degree judgment result, specifically including: Acquire a pre-trained finished product prediction model according to the foaming production process, and input the foamed concrete production data into the finished product prediction model; The finished product prediction model determines the foaming degree according to the foamed concrete production data to obtain the foaming degree judgment result.

[0012] By adopting the above technical solution and using a pre-trained finished product prediction model to judge the degree of foaming, the accuracy and real-time performance of data in the foam concrete production process can be significantly improved. First, a pre-trained finished product prediction model is obtained according to the foaming production process. The model is trained based on a large amount of experimental data and actual production experience, and can accurately analyze the foam concrete production data. After obtaining the foam concrete production data, it is input into the finished product prediction model. The finished product prediction model judges the degree of foaming based on the foam concrete production data to obtain the foaming degree judgment result. This process realizes the real-time evaluation of key parameters in the foam concrete production process through the precise calculation and judgment of the model. The specific application of the finished product prediction model is reflected in the following aspects: the production data input by the model includes but is not limited to key parameters such as cement dosage, cement slurry water dosage, air dosage, foaming agent dosage, foaming water dosage, and finished product slurry flow rate. These data can be collected in real time by the sensor module and obtained after processing by the data processing module; the model can complete the comprehensive analysis of these complex parameters in a very short time, and then judge the foaming degree of foamed concrete. The accuracy of the judgment result is directly related to the scientificity and effectiveness of the subsequent production process parameter adjustment; the finished product prediction model can more accurately identify abnormal situations that may occur in the production process by comparing historical data with real-time data, such as unreasonable raw material ratios, improper foaming agent addition, deviation of process control parameters, etc., so that production personnel can quickly adjust the production process; the use of the finished product prediction model can also minimize errors in the production process, avoid product quality problems caused by insufficient manual experience or misjudgment, and further improve the yield rate and overall production efficiency of foamed concrete.

[0013] In a preferred example, the present application can be further configured as follows: the foamed concrete finished product prediction is performed according to the foaming degree judgment result, and the process data adjustment instruction is generated according to the finished product prediction result to adjust the foaming process data, specifically including: Inputting the foaming production process into the finished product prediction model to obtain finished product prediction data; The foaming degree judgment result is compared with the finished product prediction result, and the finished product prediction result is generated according to the comparison result.

[0014] By adopting the above technical solution, the foaming production process data is input into the pre-trained finished product prediction model, and the model is used to comprehensively evaluate the production of foamed concrete to obtain finished product prediction data. This process is based on a large amount of historical production data and machine learning algorithms to ensure that the finished product prediction model has high accuracy and reliability; the foaming degree judgment result is compared with the finished product prediction result, and the difference between the two is compared to identify whether the current production status meets the expected target. If the foaming degree judgment result shows that the actual production situation deviates from the target, the corresponding process data adjustment instruction will be generated. These instructions usually include but are not limited to adjusting the raw material ratio, changing the amount of foaming agent added, or adjusting the water temperature, so as to correct possible problems in the production process and make the production closer to the expected target. The generation process of the adjustment instruction follows certain rules. For example, when the foaming degree is lower than the predetermined standard, the system may suggest increasing the proportion of foaming agent added, and vice versa, reducing the amount of foaming agent used. The purpose of this is to ensure product quality while improving production efficiency. In addition, through the careful analysis of the difference between the foaming degree judgment results and the finished product prediction results, the existing process can be further optimized, and the accumulated experience can also be used to update the data set for subsequent model training, forming a dynamic cycle improvement mechanism. This method not only improves the overall intelligence level of the foam concrete production line, but also greatly improves the consistency of product quality and reduces the product defect rate caused by improper manual operation, thereby achieving the high efficiency, energy saving and environmental protection goals of foam concrete production.

[0015] The second object of the invention is achieved by the following technical solutions: A foam concrete online monitoring device, the foam concrete online monitoring device comprising: A feed data acquisition module, used to acquire a foam concrete production instruction, acquire preset foaming production process data according to the foam concrete production instruction, and acquire real-time concrete feed end data according to the foaming process data; A data calculation module, used to calculate the concrete feed end data according to the production process data to obtain foamed concrete production data; The data judgment module is used to judge the foaming degree of the foamed concrete production data and obtain the foaming degree judgment result; the process parameter adjustment module is used to predict the foamed concrete finished product according to the foaming degree judgment result, and generate a process data adjustment instruction according to the finished product prediction result to adjust the foaming process data.

[0016] By adopting the above technical solution, by obtaining the foam concrete production instructions, the preset foaming production process data is automatically retrieved from the stored production process database, so that the monitoring strategy can be dynamically adjusted according to the actual production needs, so that the monitoring is more adaptable to the changes under different production conditions. According to the specific production instructions, the real-time concrete feed end data is further obtained, which covers the instantaneous values ​​of various key parameters in the foam concrete feeding process, such as cement dosage, cement slurry water dosage, air dosage, foaming agent dosage and foaming water dosage. By obtaining these real-time data of the feed end, each step of the production process can be monitored with high precision, which not only provides a solid foundation for subsequent data processing, but also makes the control of the production process more refined. Next, the concrete feed end data is calculated according to the obtained production process data to obtain the foam concrete production data. This calculation process includes the specific calculation of multiple key parameters such as foam density, cement slurry dosage, wet density, etc. For example, the data such as foaming agent mass, foaming water mass and foam volume collected in real time by the sensor are input into the pre-set calculation formula, and the calculation result of foam density can be quickly obtained. Similarly, for the calculation of cement slurry dosage, the calculation is performed based on the data of cement quality and cement slurry water quality. These calculation results not only accurately reflect the actual situation of the current foamed concrete, but also provide an important basis for the subsequent judgment of the foaming degree. Subsequently, the foaming degree is judged on the obtained foamed concrete production data to obtain the foaming degree judgment result. This process compares and analyzes the obtained production data with the preset standard foaming degree parameters to determine whether the foaming degree of the current foamed concrete meets expectations. Based on the calculation results, the foaming degree judgment results are generated in real time, which can timely discover possible problems in the production process, such as whether the foam density meets the standard range, whether the foaming degree meets expectations, etc., thereby providing an accurate data basis for subsequent finished product prediction. On this basis, the finished product prediction of foamed concrete is carried out. The finished product prediction data generated according to the foaming degree judgment results can help production personnel to understand the actual situation in the current production process in a timely manner. By comparing and analyzing with historical data and ideal conditions, accurate finished product prediction results are generated. Finally, process data adjustment instructions are generated according to the finished product prediction results to adjust the foaming process data, so as to continuously optimize and improve the production process. Through real-time monitoring and data analysis, production process parameters can be adjusted according to actual conditions, so that the production process is more in line with the expected quality standards, ensuring the high quality of the final product.

[0017] The third objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned foam concrete online monitoring method are implemented.

[0018] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned foam concrete online monitoring method are implemented.

[0019] In summary, the present application includes at least one of the following beneficial technical effects: 1. By acquiring the data of the foam concrete feeding end in real time and performing calculations, the foam concrete production data is obtained, which realizes the real-time monitoring of key parameters in the production process, solves the lag problem existing in the offline monitoring method, and improves the timeliness and accuracy of the monitoring results; 2. Through the judgment of foaming degree and prediction of finished products, problems in the production process can be discovered in time and process data adjustment instructions can be generated to achieve real-time control of foaming process data, reduce the probability of potential risks in the production process, and improve product quality stability; 3. Through high-precision sensors and efficient data acquisition and processing modules, the integrity and accuracy of monitoring data are ensured, enabling production personnel to quickly adjust production process parameters based on real-time monitoring results, optimize production processes, and improve overall production efficiency and product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is a flow chart of a foam concrete online monitoring method in one embodiment of the present application; Figure 2 This is a flow chart for implementing step S10 of the method for online monitoring of foamed concrete in one embodiment of the present application; Figure 3 This is a flowchart for implementing step S20 of the method for online monitoring of foamed concrete in one embodiment of the present application; Figure 4 This is a flowchart for implementing step S30 of the method for online monitoring of foamed concrete in one embodiment of the present application; Figure 5 This is a flowchart for implementing step S40 of the method for online monitoring of foamed concrete in one embodiment of the present application; Figure 6 This is a principle block diagram of a foam concrete online monitoring system in one embodiment of the present application; Figure 7 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The present application is further described in detail below in conjunction with the accompanying drawings.

[0022] In one embodiment, if Figure 1 As shown, the present application discloses a foam concrete online monitoring method, which specifically includes the following steps: S10: Obtaining a foamed concrete production instruction, obtaining preset foaming production process data according to the foamed concrete production instruction, and obtaining real-time concrete feed end data according to the foaming process data.

[0023] In this embodiment, the foamed concrete production instruction refers to an instruction for controlling the start-up of a corresponding foamed concrete production line.

[0024] Specifically, before the production of foam concrete is required, the pre-set concrete formula and production process are used as the production process data to trigger the foam concrete production instruction to control the feeding end of the production line, obtain the corresponding proportion of raw materials according to the concrete formula, and when obtaining each raw material at the feeding end, obtain the operation data of the feeding equipment through the corresponding sensor to obtain the concrete feeding data, wherein the specific requirements of the sensor are as follows: (1) Accuracy: The measurement accuracy of each sensor should meet the requirements for parameter monitoring accuracy in the foam concrete production process, and the error should be controlled within ±0.1%.

[0025] (2) Response time: The response time of the sensor should be less than 0.5 seconds to ensure real-time data collection.

[0026] (3) Stability: It can work stably in the harsh environment of foam concrete production (such as high humidity, strong vibration, etc.), and its performance will not be significantly reduced after working for more than 12 hours.

[0027] (4) Protection level: The protection level of the sensor should not be lower than IP65 to prevent damage to the sensor by dust, water vapor, etc.

[0028] Preferably, the data acquisition module is used to receive the data collected by the sensor and transmit it to the data processing module, and its specific requirements are as follows: (1) Sampling frequency: The sampling frequency of the data acquisition module should not be less than 80 Hz to ensure the integrity and accuracy of the data.

[0029] (2) Data transmission rate: The data transmission rate between the data acquisition module, the sensor module and the data processing module should be greater than 10Mbps to achieve fast data transmission.

[0030] (3) Compatibility: The data acquisition module should be compatible with sensors of different types and specifications to facilitate system expansion and upgrading.

[0031] S20: Calculate the concrete feed end data according to the production process data to obtain foamed concrete production data.

[0032] Specifically, after obtaining the feed end data of the production line, the feed end data is calculated according to the production indicators that need to be monitored in the production process data, such as foam density, cement slurry dosage, wet density and other parameters, and the corresponding calculation results are used as foam concrete production data.

[0033] S30: judging the foaming degree of the foamed concrete production data to obtain a foaming degree judgment result.

[0034] Specifically, after the foamed concrete production data is acquired, the foamed concrete production data is compared with the standard corresponding to the production process data, and the comparison result is used as the foaming degree judgment result.

[0035] S40: Predicting the finished product of the foamed concrete according to the foaming degree judgment result, and generating a process data adjustment instruction according to the finished product prediction result to adjust the foaming process data.

[0036] Specifically, the quality of the finished product is predicted based on the foaming degree judgment result, that is, the error between the current foam concrete production data and the standard, so as to predict the quality of the finished product produced by the currently fed raw materials as the finished product prediction result. If the finished product quality is abnormal from the finished product prediction result, the process data adjustment instruction is triggered to notify the personnel to adjust the foaming process data used to control the production line.

[0037] In this embodiment, by obtaining the foam concrete production instruction, the preset foaming production process data is automatically retrieved from the stored production process database, so that the monitoring strategy can be dynamically adjusted according to the actual production demand, so that the monitoring is more adapted to the changes under different production conditions. According to the specific production instruction, the real-time concrete feed end data is further obtained, which covers the instantaneous values ​​of various key parameters in the foam concrete feeding process, such as cement dosage, cement slurry water dosage, air dosage, foaming agent dosage and foaming water dosage. By obtaining these real-time data of the feed end, each step of the production process can be monitored with high precision, which not only provides a solid foundation for subsequent data processing, but also makes the control of the production process more refined. Next, the concrete feed end data is calculated according to the obtained production process data to obtain the foam concrete production data. This calculation process includes the specific calculation of multiple key parameters such as foam density, cement slurry dosage, wet density, etc. For example, the data such as foaming agent mass, foaming water mass and foam volume collected in real time by the sensor are input into the pre-set calculation formula, and the calculation result of foam density can be quickly obtained. Similarly, for the calculation of cement slurry dosage, the calculation is performed based on the data of cement quality and cement slurry water quality. These calculation results not only accurately reflect the actual situation of the current foamed concrete, but also provide an important basis for the subsequent judgment of the foaming degree. Subsequently, the foaming degree is judged on the obtained foamed concrete production data to obtain the foaming degree judgment result. This process compares and analyzes the obtained production data with the preset standard foaming degree parameters to determine whether the foaming degree of the current foamed concrete meets expectations. Based on the calculation results, the foaming degree judgment results are generated in real time, which can timely discover possible problems in the production process, such as whether the foam density meets the standard range, whether the foaming degree meets expectations, etc., thereby providing an accurate data basis for subsequent finished product prediction. On this basis, the finished product prediction of foamed concrete is carried out. The finished product prediction data generated according to the foaming degree judgment results can help production personnel to understand the actual situation in the current production process in a timely manner. By comparing and analyzing with historical data and ideal conditions, accurate finished product prediction results are generated. Finally, process data adjustment instructions are generated according to the finished product prediction results to adjust the foaming process data, so as to continuously optimize and improve the production process. Through real-time monitoring and data analysis, production process parameters can be adjusted according to actual conditions, so that the production process is more in line with the expected quality standards, ensuring the high quality of the final product.

[0038] In one embodiment, if Figure 2 As shown, in step S10, the foamed concrete production instruction is obtained, the preset foaming production process data is obtained according to the foamed concrete production instruction, and the real-time concrete feeding end data is obtained according to the foaming process data, which specifically includes: S11: Obtain foamed concrete specification data and corresponding concrete production formula data from the production process data.

[0039] Specifically, before generating the production process data, the specification data of the foamed concrete is generated according to the strength data of the foamed concrete, and the formula for preparing the concrete of the specification is obtained as the concrete production formula data.

[0040] S12: Acquire the feed end type to be monitored and the detection threshold data corresponding to each feed end type to be monitored according to the concrete formula data and the foamed concrete specification data.

[0041] Specifically, according to the types of raw materials included in the concrete formula data, the type of storage device storing the raw materials is obtained as the type to be monitored at the feed end; and according to the concrete formula data, the foamed concrete specification data and the concrete formula data, the ratio between each raw material is obtained, and then according to the total amount of production, the threshold data to be detected corresponding to each type to be monitored at the feed end is obtained, which is used to control the rate of conveying raw materials at the output port of each type of the feed end.

[0042] S13: Acquire concrete feed end data according to the feed end monitoring type and the threshold data to be detected.

[0043] Specifically, the concrete feeding end data is acquired according to the feeding end monitoring type and the threshold data to be detected.

[0044] In one embodiment, if Figure 3 As shown, in step S20, the concrete feed end data is calculated according to the production process data to obtain the foamed concrete production data, which specifically includes: S21: Obtain a corresponding detection calculation formula according to the corresponding feed end monitoring type in the production process data.

[0045] Specifically, according to the data type that needs to be monitored in the production process data, that is, the feed end monitoring type, the corresponding detection calculation formula is obtained, for example: (1) The calculation formula of foam density is as follows: Foam density calculation formula: Among them, ρ 泡沫 is the foam density, m 发泡剂 is the mass of foaming agent, m 发泡水 is the mass of foaming water, V 泡沫 is the foam volume.

[0046] (2) Calculation formula for cement slurry dosage: V 水泥浆体 =m 水泥 +m水泥浆水 Among them, V 水泥浆体 is the amount of cement slurry, m 水泥 is the mass of cement, m 水泥浆水 Cement slurry water quality.

[0047] (3) Calculation formula for wet density of foam concrete: Among them, ρ 湿 is the wet density of foam concrete, m 总 is the total mass of foamed concrete (including the mass of cement, cement paste, foaming agent, foaming water, foam formed by air, etc.), V 总 is the total volume of foam concrete.

[0048] S22: Input the concrete feed end data into the detection calculation formula to obtain the concrete production data.

[0049] Specifically, each concrete feed end data monitored by the sensor device is input into the corresponding parameter in the detection calculation formula, so that the result calculated by each calculation formula is used as the concrete production data.

[0050] In one embodiment, if Figure 4 As shown, in step S30, the foaming degree of the foamed concrete production data is judged to obtain the foaming degree judgment result, which specifically includes: S31: Obtain a pre-trained finished product prediction model according to the foaming production process, and input the foamed concrete production data into the finished product prediction model.

[0051] Specifically, the production of foam concrete is tested in advance according to the same production process and formula, sensors of different specifications, and sensors of the same specifications but different formulas and production processes, and the initial model is trained with the corresponding test results to obtain the finished product prediction model.

[0052] Furthermore, the foamed concrete production data is input into the finished product prediction model for calculation to obtain corresponding results.

[0053] S32: The finished product prediction model determines the foaming degree according to the foam concrete production data to obtain a foaming degree determination result.

[0054] Specifically, after the predicted result is obtained, the foaming degree of the result is judged to determine the foaming condition of the foaming agent foam, thereby obtaining the foaming degree judgment result.

[0055] In one embodiment, if Figure 5As shown, in step S40, the foamed concrete finished product is predicted according to the foaming degree judgment result, and the process data adjustment instruction is generated according to the finished product prediction result to adjust the foaming process data, which specifically includes: S41: Input the foaming production process into the finished product prediction model to obtain finished product prediction data.

[0056] Specifically, the foaming production process is input into the finished product prediction model, and a prediction is made based on the formula and production process to determine whether the result meets the corresponding production specifications. If so, the prediction result is used as the finished product prediction data.

[0057] S42: Compare the foaming degree judgment result with the finished product prediction result, and generate the finished product prediction result according to the comparison result.

[0058] Specifically, after obtaining the finished product prediction result, the foaming degree prediction result is compared with the finished product prediction result. If the comparison result is within the error range, the finished product prediction result is normal production. If not, it is necessary to adjust the foaming production process data used to control the rate of material addition at the feed end.

[0059] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0060] In one embodiment, a foam concrete online monitoring device is provided, and the foam concrete online monitoring device corresponds to the foam concrete online monitoring method in the above embodiment. Figure 6 As shown, the foam concrete online monitoring device includes a feed data acquisition module, a data calculation module, a data judgment module and a process parameter adjustment module. The detailed description of each functional module is as follows: A feed data acquisition module is used to obtain foam concrete production instructions, obtain preset foaming production process data according to the foam concrete production instructions, and obtain real-time concrete feed end data according to the foaming process data; A data calculation module is used to calculate the concrete feed end data according to the production process data to obtain the foam concrete production data; The data judgment module is used to judge the foaming degree of foam concrete production data and obtain the foaming degree judgment result; the process parameter adjustment module is used to predict the foamed concrete finished product according to the foaming degree judgment result, and generate process data adjustment instructions according to the finished product prediction result to adjust the foaming process data.

[0061] Optionally, the feed data acquisition module includes: The process data acquisition submodule is used to obtain the foamed concrete specification data and the corresponding concrete production formula data from the production process data; The monitoring type acquisition submodule is used to acquire the feed end monitoring type and the detection threshold data corresponding to each feed end monitoring type according to the concrete formula data and the foamed concrete specification data; The feed monitoring submodule is used to obtain the concrete feed end data according to the feed end monitoring type and the threshold data to be detected.

[0062] Optionally, the data calculation module includes: The formula acquisition submodule is used to obtain the corresponding detection calculation formula according to the corresponding feed end monitoring type in the production process data; The data calculation submodule is used to input the concrete feeding end data into the detection calculation formula to obtain the concrete production data.

[0063] Optionally, the data judgment module includes: The model prediction submodule is used to obtain a pre-trained finished product prediction model according to the foaming production process and input the foamed concrete production data into the finished product prediction model; The data judgment submodule is used for the finished product prediction model to judge the foaming degree according to the foam concrete production data to obtain the foaming degree judgment result.

[0064] Optionally, the process parameter adjustment module includes: The finished product prediction submodule is used to input the foaming production process into the finished product prediction model to obtain finished product prediction data; The prediction result comparison submodule is used to compare the foaming degree judgment result with the finished product prediction result, and generate the finished product prediction result according to the comparison result.

[0065] The specific definition of the foam concrete online monitoring device can be found in the above-mentioned definition of the foam concrete online monitoring method, which will not be repeated here. Each module in the above-mentioned foam concrete online monitoring device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0066] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a foam concrete online monitoring method is implemented.

[0067] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Obtaining foam concrete production instructions, obtaining preset foaming production process data according to the foam concrete production instructions, and obtaining real-time concrete feeding end data according to the foaming process data; Calculate the concrete feed end data according to the production process data to obtain the foam concrete production data; The foaming degree is judged on the foamed concrete production data to obtain the foaming degree judgment result; The foamed concrete finished product is predicted based on the foaming degree judgment result, and the process data adjustment instruction is generated based on the finished product prediction result to adjust the foaming process data.

[0068] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Obtaining foam concrete production instructions, obtaining preset foaming production process data according to the foam concrete production instructions, and obtaining real-time concrete feeding end data according to the foaming process data; Calculate the concrete feed end data according to the production process data to obtain the foam concrete production data; The foaming degree is judged on the foamed concrete production data to obtain the foaming degree judgment result; The foamed concrete finished product is predicted based on the foaming degree judgment result, and the process data adjustment instruction is generated based on the finished product prediction result to adjust the foaming process data.

[0069] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0070] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0071] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A foam concrete online monitoring method, characterized in that: The foam concrete online monitoring method comprises: Obtaining a foamed concrete production instruction, obtaining preset foaming production process data according to the foamed concrete production instruction, and obtaining real-time concrete feed end data according to the foaming process data; Calculating the concrete feed end data according to the production process data to obtain foamed concrete production data; Performing foaming degree judgment on the foamed concrete production data to obtain a foaming degree judgment result; The foamed concrete finished product is predicted according to the foaming degree judgment result, and the process data adjustment instruction is generated according to the finished product prediction result to adjust the foaming process data.

2. The foam concrete online monitoring method according to claim 1, characterized in that: The step of obtaining the foamed concrete production instruction, obtaining preset foaming production process data according to the foamed concrete production instruction, and obtaining real-time concrete feed end data according to the foaming process data, specifically includes: Acquire foamed concrete specification data and corresponding concrete production formula data from the production process data; Acquire the feed end type to be monitored and the detection threshold data corresponding to each feed end type to be monitored according to the concrete formula data and the foamed concrete specification data; The concrete feeding end data is acquired according to the feeding end monitoring type and the threshold data to be detected.

3. The foam concrete online monitoring method according to claim 2, characterized in that: The calculation of the concrete feed end data according to the production process data to obtain the foamed concrete production data specifically includes: Obtaining a corresponding detection calculation formula according to the feed end monitoring type corresponding to the production process data; The concrete feed end data is input into the detection calculation formula to obtain the concrete production data.

4. The foam concrete online monitoring method according to claim 1, characterized in that: The step of judging the foaming degree of the foamed concrete production data to obtain the foaming degree judgment result specifically includes: Acquire a pre-trained finished product prediction model according to the foaming production process, and input the foamed concrete production data into the finished product prediction model; The finished product prediction model determines the foaming degree according to the foamed concrete production data to obtain the foaming degree judgment result.

5. The foam concrete online monitoring method according to claim 4, characterized in that: The method of predicting a finished foamed concrete product according to the foaming degree judgment result and generating a process data adjustment instruction according to the finished product prediction result to adjust the foaming process data specifically includes: Inputting the foaming production process into the finished product prediction model to obtain finished product prediction data; The foaming degree judgment result is compared with the finished product prediction result, and the finished product prediction result is generated according to the comparison result.

6. A foam concrete online monitoring device, characterized in that: The foam concrete online monitoring device comprises: A feed data acquisition module, used to acquire a foam concrete production instruction, acquire preset foaming production process data according to the foam concrete production instruction, and acquire real-time concrete feed end data according to the foaming process data; A data calculation module, used to calculate the concrete feed end data according to the production process data to obtain foamed concrete production data; A data judgment module is used to judge the foaming degree of the foamed concrete production data to obtain a foaming degree judgment result; The process parameter adjustment module is used to predict the finished foamed concrete product according to the foaming degree judgment result, and generate a process data adjustment instruction according to the finished product prediction result to adjust the foaming process data.

7. The foam concrete online monitoring device according to claim 6, characterized in that: The feed data acquisition module comprises: A process data acquisition submodule, used to acquire foamed concrete specification data and corresponding concrete production formula data from the production process data; A monitoring type acquisition submodule, used for acquiring the feed end to be monitored type and the to-be-detected threshold data corresponding to each feed end to be monitored type according to the concrete formula data and the foamed concrete specification data; The feed monitoring submodule is used to obtain the concrete feed end data according to the feed end monitoring type and the threshold data to be detected.

8. The foam concrete online monitoring device according to claim 7, characterized in that: The data calculation module includes: A formula acquisition submodule, used to acquire a corresponding detection calculation formula according to the feed end to be monitored type corresponding to the production process data; The data calculation submodule is used to input the concrete feeding end data into the detection calculation formula to obtain the concrete production data.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the foam concrete online monitoring method according to any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the foam concrete online monitoring method according to any one of claims 1 to 5 are implemented.

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