Intelligent batching system for operation of concrete mixing plant

Abstract

The invention belongs to the technical field of concrete mixing plant operation monitoring, and discloses a concrete mixing plant operation intelligent batching system which comprises a material conveying equipment setting module, a material conveying data acquisition module, a material conveying data analysis module, a material conveying equipment control module, a material bin data acquisition module, a material bin raw material analysis module and a material bin raw material supplementing module. When the air supply equipment is controlled, the control requirement of the air supply equipment is judged on the basis of the pipeline attachment content evaluation condition and the conveying flow abnormality evaluation condition, normal conveying of materials can be guaranteed, the control accuracy of the air supply equipment is improved, and the continuity of material conveying is guaranteed. According to the invention, raw material supplement demand judgment is carried out based on the residual raw material evaluation condition of each raw material and the monitoring environment evaluation condition during stock bin raw material supplement demand analysis, the raw material supplement opportunity can be accurately controlled, production coherence is ensured, the quality stability of the raw materials and products is powerfully ensured, and the overall operation efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of operation monitoring of concrete mixing plants and relates to an intelligent batching system for the operation of concrete mixing plants. Background Art

[0002] A concrete mixing plant is a factory facility specifically used for producing concrete. It proportionally batches and mixes raw materials such as cement, sand and gravel, water, and admixtures, and finally produces concrete that meets the requirements of construction work, etc. Its main function is to achieve efficient, precise, and stable production of concrete, ensure the uniform quality of concrete, and meet the strength, workability, and other requirements of different projects. The work of a concrete mixing plant usually includes multiple processes such as raw material supply, feeding, material transportation, and mixing. Among them, raw material supply and material transportation are important processes to ensure the smooth progress of the work of the concrete mixing plant. Therefore, intelligent batching analysis of the operation of a concrete mixing plant based on raw material supply and material transportation is of great significance.

[0003] In the prior art, there are also related solutions for the operation monitoring of concrete mixing plants. For example, a Chinese patent application for an automatic batching system of a concrete mixing plant with the publication number CN105690568B includes: a raw material storage system, a raw material weighing system, a mixer system, a raw material transportation system, and a control system. The raw material storage system includes three silos arranged side by side. The raw material transportation system is composed of a belt conveyor and a bucket elevator. The raw material weighing system includes three belt scales. The belt scales are located above the belt conveyor and below the openings of the silos. This automatic batching system can meet the large-scale concrete production process, accurately weigh and transport various raw materials, ensure product quality, and at the same time achieve precise control and efficient management of the concrete batching process, significantly avoiding problems such as cumbersome and disorderly procedures in the traditional production batching process, chaotic record management in the batching process, and serious waste of batching resources.

[0004] In addition, a Chinese patent application for a control method for the batching accuracy of a concrete mixing equipment with the publication number CN102658600A includes: after starting batching, entering a formula indexing calculation module, a stable value reading module, a formula target module, a batching drop recording module, and then entering the fifth step. The formula accuracy calculation module calculates the formula accuracy for each time. When the absolute value module of the batching accuracy cannot be less than or equal to the set accuracy, it returns to the first step. When the absolute value module of the batching accuracy is less than or equal to the set accuracy, it returns to the second step to record and store the stable value module of this batch. The present invention stores different drop methods according to different formulas, solves the problem that the change in the drop due to the change in the material formula leads to large fluctuations in the batching accuracy. The more the same formula is produced, the more stable the system is and the higher the accuracy. When batching different formulas, the stable value corresponding to the formula is read, thereby achieving the effect of improving the accuracy of dynamic batching.

[0005] Although the above two solutions propose some solutions for the operation monitoring of concrete mixing plants, there are still certain limitations: on the one hand, the existing technical solutions monitor the batching process and then mechanically conduct batching and transportation, lacking the control of the transportation parameters in the batching process, resulting in difficult-to-guarantee batching accuracy, affecting the product quality stability, reducing the production efficiency, and having poor adaptability to different raw materials, unable to flexibly adjust according to the characteristics of raw materials, restricting all links of production. On the other hand, when the existing technical solutions monitor the remaining raw materials in the corresponding bins of raw materials, they only analyze based on the weight of raw materials, ignoring the influence of the storage environment of raw materials. This analysis method may mix deteriorated raw materials into the production process, bringing serious quality and safety hazards, changing the original ratio applicability, and causing subsequent reactions to not proceed as planned, disrupting the entire production order. Summary of the Invention

[0006] In view of this, to solve the problems raised in the above background technology, a smart batching system for the operation of a concrete mixing plant is proposed.

[0007] The object of the present invention can be achieved through the following technical solutions: A smart batching system for the operation of a concrete mixing plant, including: a feeding equipment setting module for setting feeding equipment in a target concrete mixing plant, the feeding equipment including a plurality of feeding ports, feeding pipelines and air supply equipment, and each feeding port is connected to a different bin.

[0008] A feeding data acquisition module for monitoring the feeding equipment when the target concrete mixing plant is working, obtaining three-dimensional data of the feeding pipeline by using a three-dimensional scanning device, and simultaneously obtaining the feeding flow rate of the feeding pipeline by using a flow monitoring device.

[0009] A feeding data analysis module for analyzing the evaluation of the content of pipeline attachments in the feeding pipeline based on the three-dimensional data of the feeding pipeline, and simultaneously analyzing the evaluation of abnormal feeding flow rate in the feeding pipeline based on the feeding flow rate of the feeding pipeline.

[0010] A feeding equipment control module for judging whether feeding equipment control is required, and if so, further performing feeding control operations.

[0011] A bin data acquisition module for monitoring the corresponding bins of raw materials when the target concrete mixing plant is working, obtaining the remaining raw material weights of each raw material in real time, and simultaneously obtaining the storage environment parameters of the corresponding bins of each raw material by using temperature and humidity sensors, specifically including temperature and humidity.

[0012] The silo raw material analysis module is used to analyze the remaining raw material evaluation of each raw material based on the remaining raw material weight of each raw material, analyze the monitoring environment evaluation of the silo corresponding to each raw material based on the storage environment parameters of the silo corresponding to each raw material, and then analyze the raw material replenishment demand evaluation of each raw material.

[0013] The silo raw material replenishment module is used to judge whether each raw material needs to be replenished. If so, the raw material replenishment operation is further executed.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) When controlling the air supply equipment, the present invention judges the control demand of the air supply equipment based on the evaluation of the content of pipeline attachments and the evaluation of abnormal conveying flow rate. This analysis method can ensure the normal conveying of materials, improve the accuracy of air supply equipment control, ensure the continuity of material conveying, and reduce the risks of production delay and equipment damage caused by abnormal flow rate.

[0015] (2) When analyzing the raw material replenishment demand of the silo, the present invention judges the raw material replenishment demand based on the remaining raw material evaluation of each raw material and the monitoring environment evaluation. This analysis method can accurately control the raw material replenishment timing, ensure the continuity of production, effectively guarantee the stability of raw material and product quality, prevent the backlog and deterioration of raw materials, facilitate the optimization of inventory management and cost control, and also realize intelligent and efficient management. It can make automatic decisions by means of data, reduce human errors, closely connect the raw material replenishment and production links, and improve the overall operation efficiency. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is a schematic diagram of the connection of each module of the system of the present invention.

[0018] Figure 2 It is a schematic diagram of the equipment corresponding to an embodiment of the conveying equipment provided by the present invention.

[0019] Figure 3 It is a judgment flowchart corresponding to an embodiment of the judgment of the control demand of the conveying equipment provided by the present invention.

[0020] Figure 4 It is a judgment flowchart corresponding to an embodiment of the judgment of the raw material replenishment demand provided by the present invention.

[0021] Reference Signs: 1 - conveying pipeline, 2 - feeding port, 3 - air supply equipment. Detailed implementation mode

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0023] Please refer to Figure 1 As shown, the present invention provides an intelligent batching system for the operation of a concrete mixing plant, including a feeding equipment setting module, a feeding data acquisition module, a feeding data analysis module, a feeding equipment control module, a silo data acquisition module, a silo raw material analysis module, and a silo raw material supplement module. Among them, the feeding equipment setting module is respectively connected to the feeding data acquisition module and the silo data acquisition module, the feeding data acquisition module is connected to the feeding data analysis module, the feeding data analysis module is connected to the feeding equipment control module, the silo data acquisition module is connected to the silo raw material analysis module, and the silo raw material analysis module is connected to the silo raw material supplement module.

[0024] The feeding equipment setting module is used to set feeding equipment in the target concrete mixing plant. The feeding equipment includes a plurality of feeding ports, a feeding pipeline, and a ventilation equipment, and each feeding port is connected to a different silo.

[0025] It should be noted that the silo is used to store different raw materials. The silo is connected to the feeding port and then transported through the feeding pipeline. The feeding pipeline can transport the mixture after mixing of each raw material, and the ventilation equipment can perform ventilation operations on the feeding pipeline.

[0026] Exemplarily, the raw materials can be yellow sand, cement, and additives.

[0027] The feeding data acquisition module is used to monitor the feeding equipment when the target concrete mixing plant is working, obtain three-dimensional data of the feeding pipeline by using a three-dimensional scanning device, and simultaneously obtain the feeding flow rate of the feeding pipeline by using a flow monitoring device.

[0028] The feeding data analysis module is used to analyze the evaluation of the content of pipeline attachments on the feeding pipeline based on the three-dimensional data of the feeding pipeline, and simultaneously analyze the evaluation of abnormal feeding flow rate of the feeding pipeline based on the feeding flow rate of the feeding pipeline.

[0029] In a preferred embodiment of the present invention, to evaluate the content of pipeline attachments in the analysis of the material conveying pipeline, an evaluation index for the content of pipeline attachments in the material conveying pipeline needs to be constructed, and the specific method is as follows: Extract the three-dimensional data of the material conveying pipeline, locate the positions of each pipeline attachment in the material conveying pipeline, and then obtain the volume of each pipeline attachment. Calculate the sum to obtain the volume of the pipeline attachments in the material conveying pipeline, denoted as 。

[0030] Take the ratio of the volume of the pipeline attachments in the material conveying pipeline to the pre-set reference volume of the pipeline attachments as the independent variable of the sigmoid function for calculation, and obtain the evaluation index for the content of the pipeline attachments in the material conveying pipeline 。

[0031] It should be noted that the reasons for monitoring the pipeline attachments in the material conveying pipeline are as follows: It can ensure the smooth conveying of materials, avoid pipeline blockage and production interruption caused by the accumulation of attachments. It can also maintain the stability of product quality and prevent the attachments from mixing into the product and causing pollution. It can also extend the service life of the pipeline and related equipment, reduce equipment wear and maintenance costs. At the same time, for safety and environmental protection considerations, it can prevent potential safety hazards caused by attachments and avoid environmental pollution.

[0032] The sigmoid function compresses any real number into the interval (0,1). The output value can be directly interpreted as the probability of an event occurring, and it has good monotonicity in mathematics. When the input increases, the output strictly increases, ensuring the consistency between the weight adjustment direction and the loss reduction. When analyzing the evaluation index for the content of the pipeline attachments in the material conveying pipeline selecting the sigmoid function can accurately reflect the performance of the content of the pipeline attachments in the material conveying pipeline, and it has strong applicability.

[0033] In a preferred embodiment of the present invention, to evaluate the abnormal material conveying flow in the analysis of the material conveying pipeline, an evaluation index for the abnormal material conveying flow in the material conveying pipeline needs to be constructed, and the specific method is as follows: Extract the material conveying flow of the material conveying pipeline, denoted as 。

[0034] Extract the material conveying flow of the material conveying pipeline ,and take the ratio of the absolute deviation value between the material conveying flow and the pre-set reference material conveying flow to the permitted difference between the pre-set reference material conveying flow and the material conveying flow of the material conveying pipeline as the independent variable of the sigmoid function for calculation, and obtain the evaluation index for the abnormal material conveying flow in the material conveying pipeline 。

[0035] It should be noted that the reasons for monitoring the abnormal evaluation of the material conveying flow rate in the material conveying pipeline are as follows: It is related to production continuity, can timely detect problems such as pipeline blockage and leakage, and avoid production interruption and related adverse consequences. It helps to ensure the stable quality of products and avoid quality problems such as imbalance in the proportion of product components caused by abnormal flow rates. It is beneficial to maintaining the safe operation of equipment, giving early warnings of potential equipment failures, and extending the service life of equipment. It can also assist in optimizing energy utilization, making the energy consumption of the conveying system match the actual demand, and enhancing the overall efficiency.

[0036] The material conveying equipment control module is used to determine whether material conveying equipment control is required. If so, it further performs material conveying control operations.

[0037] In a preferred embodiment of the present invention, the specific method for determining whether material conveying equipment control is required is as follows: Extract the evaluation index of the content of pipeline attachments in the material conveying pipeline and the evaluation index of abnormal material conveying flow rate in the material conveying pipeline, and then perform a weighted summation calculation to obtain the material conveying equipment control demand index of the material conveying pipeline.

[0038] Exemplarily, the weights corresponding to the evaluation index of the content of pipeline attachments and the evaluation index of abnormal material conveying flow rate in the material conveying pipeline are .

[0039] It should be noted that when analyzing the material conveying equipment control demand index of the material conveying pipeline, the setting basis of the weights corresponding to the evaluation index of the content of pipeline attachments and the evaluation index of abnormal material conveying flow rate in the material conveying pipeline is as follows: From the perspective of the impact on equipment operation, excessive accumulation of attachments is likely to cause serious failures such as pipeline blockage, exacerbating equipment wear. In contrast, abnormal material conveying flow rates can lead to various forms of failures. The weights of the two are weighed according to different failure risks and wear degrees. In terms of the degree of interference with the production process, abnormal flow rates directly affect production continuity and product quality. Although attachments can give early warnings and be processed, once blockage occurs, it is also extremely harmful. The weights need to be allocated in combination with specific processes and product requirements. Based on the differences in predictability and intervenability, the content of attachments is relatively measurable and the intervention measures are conventional, while abnormal material conveying flow rates have many sudden factors and complex interventions. Therefore, the weights of the two are comprehensively considered to ensure that the weight setting is scientific and reasonable, and accurately guide the control of material conveying equipment.

[0040] Compare the material conveying equipment control demand index of the material conveying pipeline with the pre-set material conveying equipment control demand index threshold. If the material conveying equipment control demand index of the material conveying pipeline is greater than or equal to the material conveying equipment control demand index threshold, it is determined that material conveying equipment control is required; otherwise, it is determined that material conveying equipment control is not required.

[0041] Exemplarily, the material conveying equipment control demand index threshold is .

[0042] It should be noted that the basis for setting the control requirement index threshold of the feeding equipment is as follows: First, based on the material characteristics, materials such as cement, sand, and gravel in a concrete mixing plant have their own characteristics. Cement is powdery and prone to dust and moisture, and sand and gravel have different particle sizes and fluidities. Different materials require different air pressure and air volume conditions for stable transportation. The threshold is set based on the parameter monitoring and analysis of various materials under the best transportation state to ensure the smooth flow of materials. Second, closely following the rhythm of the production process, the production tasks of the mixing plant are diverse, and concrete of different strength grades is produced alternately. Each link of batching and mixing is closely connected. According to the production demand and batching progress in each period, sufficient air supply is ensured during a large amount of raw material transportation, and the air volume is reasonably reduced during the intermittent period. The threshold is determined according to this production law to match the rhythm.

[0043] It should be noted that when controlling the air supply equipment in the present invention, the control requirement judgment of the air supply equipment is based on the evaluation of the content of pipeline attachments and the evaluation of abnormal feeding flow. This analysis method can ensure the normal transportation of materials, improve the accuracy of air supply equipment control, ensure the continuity of material transportation, and reduce the risks of production delays and equipment damage caused by abnormal flow.

[0044] In a preferred embodiment of the present invention, the specific method for further performing the feeding control operation is as follows: Extract the evaluation index of the content of pipeline attachments of the feeding pipeline , the evaluation index of abnormal feeding flow of the feeding pipeline and the feeding flow of the feeding pipeline .

[0045] Compare the feeding flow of the feeding pipeline with the pre-set reference feeding flow. If the feeding flow of the feeding pipeline is greater than the reference feeding flow, calculate the difference between the evaluation index of the content of pipeline attachments of the feeding pipeline and the evaluation index of abnormal feeding flow of the feeding pipeline to obtain the air supply equipment wind speed correction index, and then perform a multiplication calculation with the current wind speed of the air supply equipment to obtain the air supply equipment wind speed correction amount. Add the current wind speed of the air supply equipment and the air supply equipment wind speed correction amount to calculate the corrected wind speed of the air supply equipment.

[0046] If the feeding flow of the feeding pipeline is less than the reference feeding flow, calculate the sum of the evaluation index of the content of pipeline attachments of the feeding pipeline and the evaluation index of abnormal feeding flow of the feeding pipeline to obtain the air supply equipment wind speed correction index, and then perform a multiplication calculation with the current wind speed of the air supply equipment to obtain the air supply equipment wind speed correction amount. Add the current wind speed of the air supply equipment and the air supply equipment wind speed correction amount to calculate the corrected wind speed of the air supply equipment.

[0047] Control the air supply equipment based on the analyzed corrected wind speed of the air supply equipment.

[0048] The silo data acquisition module is used to monitor the corresponding silos of raw materials during the operation of the target concrete mixing plant, obtain the remaining weights of various raw materials in real time, and at the same time use temperature and humidity sensors to obtain the storage environment parameters of the corresponding silos of various raw materials, specifically including temperature and humidity.

[0049] It should be noted that the reasons for selecting temperature and humidity as the storage environment parameters for monitoring the corresponding silos of various raw materials are as follows: On the one hand, this is directly related to the quality guarantee of raw materials. Taking cement as an example, it has strong hygroscopicity, and in a high-humidity environment, it is easy to hydrate and agglomerate, which not only destroys fluidity, hinders accurate batching, but also changes chemical properties, resulting in unqualified concrete strength. Moreover, too high a temperature will also accelerate the reaction of components in cement and affect quality. The same is true for sand and gravel raw materials. Humidity causes fluctuations in water content, interfering with the water-cement ratio and workability of concrete. On the other hand, from the perspective of the stability of the production process, the precise proportioning production of concrete relies on the stable state of raw materials. Temperature and humidity cause changes in the state of raw materials, and the accuracy of batching is affected. If not accurately controlled, the quality of concrete will be uneven, ultimately affecting the quality and safety of construction projects. Therefore, it is of great significance to monitor temperature and humidity.

[0050] It should be noted that the reasons for monitoring the remaining weights of raw materials in each silo are as follows: First, it is related to the continuity of production. The production of concrete requires continuous and stable supply of raw materials. Real-time monitoring of the remaining weights of raw materials can predict in advance whether the raw materials can support subsequent production. Once the raw materials are exhausted and production is interrupted, it will have a domino effect, resulting in hindered construction progress, idle equipment and manpower, and increased costs. Second, it helps with accurate batching. The quality of concrete depends on the accurate proportioning of various raw materials. Only by clearly knowing the remaining weights of raw materials can accurate data be provided for the batching link to ensure that concrete of different strengths and uses strictly follows the design formula and produces products with stable and reliable quality. Third, it is conducive to inventory management and cost control. It can not only avoid the backlog of raw materials, occupying funds and storage space, but also prevent the high costs brought by emergency procurement due to insufficient inventory. Reasonably monitor and plan inventory to achieve cost reduction and efficiency increase, and ensure the efficient and stable operation of the mixing plant.

[0051] The silo raw material analysis module is used to analyze the remaining raw material evaluation situation of each raw material based on the remaining raw material weights of each raw material, analyze the monitored environment evaluation situation of the corresponding silos of each raw material based on the storage environment parameters of the corresponding silos of each raw material, and then analyze the raw material replenishment demand evaluation situation of each raw material.

[0052] In a preferred embodiment of the present invention, to analyze the remaining raw material evaluation situation of each raw material, it is necessary to construct a remaining raw material evaluation index for each raw material. The specific method is as follows: Extract the remaining raw material weights of each raw material, and record them as , where represents the raw material number, , represents the quantity of the raw material.

[0053] The weight of the remaining raw materials and the relative deviation value from the reference remaining raw material weight of each raw material set in advance are used as the independent variable of the sigmoid function for calculation to obtain the remaining raw material evaluation index of each raw material .

[0054] In a preferred embodiment of the present invention, to analyze the monitoring environment evaluation of the bins corresponding to each raw material, it is necessary to construct a monitoring environment evaluation index for the bins corresponding to each raw material. The specific method is as follows: Extract the temperature and humidity of the bins corresponding to each raw material

[0055] The absolute value is taken after calculating the difference between the temperature of the bin corresponding to each raw material and the reference temperature set in advance to obtain the temperature deviation amount of the bin corresponding to each raw material, and then the ratio is calculated with the reference temperature to obtain the temperature deviation degree of the bin corresponding to each raw material, denoted as .

[0056] It should be noted that the setting basis of the reference temperature of the bins corresponding to the concrete mixing plant: On the one hand, it comes from the characteristics of the raw materials. The hydration of cement is affected by temperature. Too high a temperature accelerates setting, and too low a temperature reduces activity. Sand and gravel are prone to thermal stress when exposed to high temperatures. The reference temperature delimits the range accordingly to protect the stable performance of the raw materials. On the other hand, it closely follows the production process. The mixing and reaction of raw materials are different at different temperatures. The appropriate temperature ensures the best coordination of admixtures, cement, etc., and the work performance meets the standards. When deviating, the process and ratio are adjusted according to the reference temperature. Moreover, from the perspective of equipment operation and maintenance, extreme temperatures cause aging of conveying components, abnormal connections, and lubrication disturbances. Setting the reference temperature creates a suitable environment to reduce maintenance and extend the service life

[0057] The absolute value is taken after calculating the difference between the humidity of the bin corresponding to each raw material and the reference humidity set in advance to obtain the humidity deviation amount of the bin corresponding to each raw material, and then the ratio is calculated with the reference humidity to obtain the humidity deviation degree of the bin corresponding to each raw material, denoted as .

[0058] Using the formula to analyze and obtain the monitoring environment evaluation index of the bins corresponding to each raw material , where represents the influence weights corresponding to the temperature deviation degree and humidity deviation degree set in advance

[0059] Exemplarily .

[0060] It should be noted that in the process of analyzing the monitoring environment evaluation index of the silos corresponding to each raw material, the basis for setting the influence weights of the temperature deviation degree and the humidity deviation degree is as follows: On the one hand, based on the influence on raw material quality, cement is extremely sensitive to humidity. Humidity deviation is likely to cause it to caking, affecting the quality performance. In comparison, the influence of temperature deviation is relatively slower. The same is true for sand and gravel. Humidity deviation is related to the water content and water-cement ratio. Therefore, the weight of the humidity deviation degree is often higher. On the other hand, from the perspective of the degree of interference with the production process, humidity deviation can quickly change the physical state of raw materials, affecting the accuracy of batching and mixing. The interference of temperature deviation is relatively indirect, making the weight of the humidity deviation degree dominant. Furthermore, considering the operation and maintenance of equipment, high humidity is likely to cause equipment corrosion and damage, shortening the service life and increasing costs. Although temperature deviation has an impact, it is not as prominent as humidity. Therefore, the weight tends to the humidity deviation degree.

[0061] In a preferred embodiment of the present invention, to analyze the raw material replenishment demand evaluation of each raw material, it is necessary to construct a raw material replenishment demand evaluation index for each raw material. The specific method is as follows: Extract the remaining raw material evaluation index of each raw material and the monitoring environment evaluation index of the corresponding silo , and then use the formula to analyze and obtain the raw material replenishment demand evaluation index of each raw material .

[0062] It should be noted that the reasons for selecting the remaining raw material evaluation index and the monitoring environment evaluation index of each raw material as the influencing factors of the raw material replenishment demand evaluation index are as follows: On the one hand, the remaining raw material evaluation index can be regarded as a "barometer" to ensure the continuity of production. The operation of a concrete mixing plant depends on the sufficient supply of raw materials such as cement, sand and gravel, and admixtures. This index accurately reveals how long the raw material stock can support production. If the remaining amount of cement is only enough for half a day's use and the replenishment is not timely, production is bound to be interrupted, affecting the construction progress. Only by planning the replenishment plan in advance according to this can stable material supply be ensured. On the other hand, the monitoring environment evaluation index is closely related to the quality of raw materials. Deviations in environmental factors such as temperature and humidity have a great impact on the hydration of cement and the water content of sand and gravel, which may cause the deterioration of raw material performance and fail to meet production requirements. Taking it into consideration can promptly detect the erosion of the environment on raw materials, timely adjust the storage conditions, and provide key basis for raw material replenishment decisions, so as to ensure the efficient operation of the mixing plant through both hands.

[0063] The silo raw material replenishment module is used to judge whether each raw material needs to be replenished. If so, the raw material replenishment operation is further executed.

[0064] In a preferred embodiment of the present invention, the specific method for determining whether each raw material needs to be replenished is as follows: extract the raw material replenishment demand evaluation index of each raw material, and then compare it with the pre-set raw material replenishment demand evaluation index threshold respectively. If the raw material replenishment demand evaluation index of a certain raw material is greater than the raw material replenishment demand evaluation index threshold, it is determined that the raw material needs to be replenished; otherwise, it is determined that the raw material does not need to be replenished.

[0065] Exemplarily, the raw material replenishment demand evaluation index threshold is .

[0066] It should be noted that the setting basis of the raw material replenishment demand evaluation index threshold is as follows: on the one hand, based on production plans and continuity guarantee, the concrete mixing plant has to plan production in advance according to various construction project orders, accurately calculate the usage of each raw material at different times, and thus determine the threshold to avoid production stagnation caused by raw material shortages and ensure that the construction process is not hindered. For example, in large-scale infrastructure projects, the demand for concrete is large and concentrated. If the raw materials cannot be supplied, it will not only delay the construction period, but also cause equipment idleness, waste of manpower, and a sharp increase in costs. On the other hand, focusing on inventory management cost control, the storage characteristics of raw materials should be taken into account. For example, cement has a shelf life limit, and excessive inventory is likely to expire and become ineffective. Sand and gravel also occupy a large area, and excessive storage will only increase the warehousing cost. Therefore, the threshold should be set appropriately, which can not only prevent high-cost emergency procurement due to insufficient raw materials, but also avoid overstocking and tying up funds, maintain a reasonable inventory level, and achieve cost reduction and efficiency improvement.

[0067] It should be noted that when the present invention analyzes the raw material replenishment demand of the silo, it judges the raw material replenishment demand based on the remaining raw material evaluation situation and the monitoring environment evaluation situation of each raw material. This analysis method can accurately control the timing of raw material replenishment, ensure continuous production, effectively guarantee the stability of raw material and product quality, prevent raw material backlog and deterioration, facilitate the optimization of inventory management and cost control, and also achieve intelligent and efficient management. With the help of data, automatic decision-making can be realized, human errors can be reduced, the connection between raw material replenishment and production links can be closely connected, and the overall operation efficiency can be improved.

[0068] In a preferred embodiment of the present invention, the specific method for further performing the raw material replenishment operation is as follows: mark the raw materials determined to need to be replenished as the raw materials to be replenished.

[0069] Extract the remaining raw material weights of each raw material to be replenished, and then calculate the difference between the pre-set maximum storage capacity of the silo and the remaining raw material weights of each raw material to be replenished to obtain the replenishment quantity of each raw material to be replenished, and then perform the raw material replenishment operation.

[0070] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of the present technology can make various modifications, supplements, or use similar methods to replace the described specific embodiments, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. An intelligent batching system for the operation of a concrete mixing plant, characterized in that, Including: A feeding device is set up at the target concrete mixing plant. The feeding device includes a number of feeding ports, a feeding pipeline, and a ventilation device. Each feeding port is connected to a different silo; When the target concrete mixing plant is working, monitor the feeding device to obtain the three-dimensional data of the feeding pipeline and the feeding flow rate of the feeding pipeline; Evaluate the content of pipeline attachments based on the three-dimensional data analysis, and evaluate the abnormal feeding flow rate based on the feeding flow rate analysis; Judge whether to control the feeding device. If so, execute the feeding control operation; Monitor the silos corresponding to the raw materials to obtain the remaining raw material weights of each raw material and the storage environment parameters of the silos corresponding to each raw material; Analyze the evaluation of the remaining raw materials of each raw material based on the remaining raw material weights of each raw material, analyze the monitoring environment evaluation of the silos corresponding to each raw material based on the storage environment parameters, and analyze the evaluation of the raw material replenishment requirements of each raw material; Judge whether to replenish each raw material. If so, execute the raw material replenishment operation.

2. The intelligent batching system for the operation of a concrete mixing plant according to claim 1, wherein: The specific method for analyzing the evaluation of the content of pipeline attachments in the feeding pipeline requires constructing an evaluation index for the content of pipeline attachments in the feeding pipeline, and the specific method is as follows: Extract the three-dimensional data of the material conveying pipeline, locate the positions of the attachments on each pipeline of the material conveying pipeline, obtain the volumes of the attachments on each pipeline, and perform a summation calculation to obtain the volume of the attachments on the material conveying pipeline ; The volume of the attached object of the material conveying pipeline and the volume of the attached object of the pre-set reference pipeline are used as the independent variable of the sigmoid function for calculation to obtain the evaluation index of the content of the attached object of the material conveying pipeline .

3. The intelligent batching system for the operation of a concrete mixing plant according to claim 2, wherein: The specific method for analyzing the evaluation of abnormal feeding flow rate in the feeding pipeline requires constructing an evaluation index for abnormal feeding flow rate in the feeding pipeline, and the specific method is as follows: Extract the material conveying flow rate of the material conveying pipeline , and use the absolute deviation value between the material conveying flow rate and the preset reference material conveying flow rate and the permitted difference between the preset reference material conveying flow rate and the material conveying flow rate of the material conveying pipeline as the independent variable of the sigmoid function for calculation to obtain the evaluation index of the abnormal material conveying flow rate of the material conveying pipeline .

4. The intelligent batching system for the operation of a concrete mixing plant according to claim 3, characterized in that: The specific method for judging whether to control the feeding device is as follows: Extract the evaluation index for the content of pipeline attachments in the feeding pipeline and the evaluation index for abnormal feeding flow rate in the feeding pipeline, and then perform a weighted summation calculation to obtain the control requirement index for the feeding device of the feeding pipeline; Compare the control requirement index for the feeding device of the feeding pipeline with the pre-set threshold of the control requirement index for the feeding device. If the control requirement index for the feeding device of the feeding pipeline is greater than or equal to the threshold of the control requirement index for the feeding device, it is judged that the feeding device needs to be controlled. Otherwise, it is judged that the feeding device does not need to be controlled.

5. The intelligent batching system for the operation of a concrete mixing plant according to claim 3, characterized in that: The specific method for further executing the feeding control operation is as follows: Extract the evaluation index of the content of pipeline attachments in the material conveying pipeline , the evaluation index of abnormal material conveying flow in the material conveying pipeline and the material conveying flow of the material conveying pipeline ; Compare the feeding flow rate of the feeding pipeline with the pre-set reference feeding flow rate. If the feeding flow rate of the feeding pipeline is greater than the reference feeding flow rate, calculate the difference between the evaluation index for the content of pipeline attachments in the feeding pipeline and the evaluation index for abnormal feeding flow rate in the feeding pipeline to obtain the wind speed correction index for the ventilation device, and then perform a multiplication calculation with the current wind speed of the ventilation device to obtain the wind speed correction amount for the ventilation device. Perform a summation calculation on the current wind speed of the ventilation device and the wind speed correction amount for the ventilation device to obtain the corrected wind speed of the ventilation device; If the feeding flow rate of the feeding pipeline is less than the reference feeding flow rate, calculate the sum of the evaluation index for the content of pipeline attachments in the feeding pipeline and the evaluation index for abnormal feeding flow rate in the feeding pipeline to obtain the wind speed correction index for the ventilation device, and then perform a multiplication calculation with the current wind speed of the ventilation device to obtain the wind speed correction amount for the ventilation device. Perform a summation calculation on the current wind speed of the ventilation device and the wind speed correction amount for the ventilation device to obtain the corrected wind speed of the ventilation device; Control the ventilation device based on the analyzed corrected wind speed of the ventilation device.

6. The intelligent batching system for the operation of a concrete mixing plant according to claim 1, characterized in that: The specific method for analyzing the evaluation of the remaining raw materials of each raw material requires constructing an evaluation index for the remaining raw materials of each raw material, and the specific method is as follows: Extract the remaining raw material weights of each raw material, and record them respectively as , where represents the raw material number,[[]] , represents the quantity of the raw material; The remaining raw material weight and the reference remaining raw material weights of each pre-set raw material are used as the independent variable of the sigmoid function for calculation to obtain the remaining raw material evaluation indices of each raw material .

7. An intelligent batching system for the operation of a concrete mixing plant according to claim 6, characterized in that: To evaluate the monitoring environment of the bins corresponding to each raw material, it is necessary to construct a monitoring environment evaluation index for the bins corresponding to each raw material, and the specific method is as follows: Extract the temperature and humidity of the bins corresponding to each raw material; The absolute value is taken after calculating the difference between the temperature of each raw material corresponding silo and the pre-set reference temperature to obtain the temperature deviation of each raw material corresponding silo, and then the ratio is calculated with the reference temperature to obtain the temperature deviation degree of each raw material corresponding silo, denoted as ; After calculating the difference between the humidity of each raw material corresponding silo and the pre-set reference humidity and taking the absolute value, the humidity deviation of each raw material corresponding silo is obtained. Then, the ratio is calculated with the reference humidity to obtain the humidity deviation degree of each raw material corresponding silo, denoted as ; The monitoring environment evaluation index of the silo corresponding to each raw material is obtained by analyzing with the multi-weight fusion algorithm .

8. The intelligent batching system for the operation of a concrete mixing plant according to claim 7, characterized in that: To evaluate the raw material replenishment demand of each raw material, it is necessary to construct a raw material replenishment demand evaluation index for each raw material, and the specific method is as follows: Extract the remaining raw material evaluation index of each raw material and the monitoring environment evaluation index of the corresponding silo , and then use the fractional function formula to analyze and obtain the raw material supplement demand evaluation index of each raw material .

9. The intelligent batching system for the operation of a concrete mixing plant according to claim 8, characterized in that: The specific method for judging whether each raw material needs to be replenished is as follows: Extract the raw material replenishment demand evaluation index of each raw material, and then compare it with the pre-set threshold of the raw material replenishment demand evaluation index respectively. If the raw material replenishment demand evaluation index of a certain raw material is greater than the threshold of the raw material replenishment demand evaluation index, it is judged that the raw material needs to be replenished; otherwise, it is judged that the raw material does not need to be replenished.

10. An intelligent batching system for the operation of a concrete mixing plant according to claim 9, characterized in that: The specific method for further performing the raw material replenishment operation is as follows: Mark the raw materials that need to be replenished as the raw materials to be replenished; Extract the remaining weight of each raw material to be replenished, and then calculate the difference between the pre-set maximum storage capacity of the bin and the remaining weight of each raw material to be replenished to obtain the replenishment amount of each raw material to be replenished, and then perform the raw material replenishment operation.

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