A variable frequency control system for sand mixing in a sand mixer and its control method

Abstract

This application discloses a variable frequency control system for sand mixing in a sand mixer, relating to the field of variable frequency control. The method includes: an information retrieval module for retrieving historical sand mixing information and sand mixing order information; a sand mixing unit grouping module for grouping all sand mixing units; a first energy consumption allocation module for generating a first energy allocation strategy for all sand mixing units; a first sand mixing variable frequency control module for initially allocating sand mixing energy to the sand mixing units; an information monitoring module for monitoring the operating status of all sand mixing units; a second energy consumption allocation module for generating a second energy allocation strategy for all sand mixers; and a second sand mixing variable frequency control module for dynamically allocating sand mixing energy to all sand mixers in each sand mixing unit. This application can effectively achieve precise energy allocation for each sand mixer, improving energy utilization.

Description

Technical Field

[0001] This application relates to the field of frequency conversion control, and more particularly to a frequency conversion control system and control method for a sand mixer. Background Technology

[0002] Sand mixers, as key equipment in the casting process, ensure the uniform mixing of components in molding sand and effectively coat the sand grains with binder, thereby significantly improving the control of molding sand quality, increasing construction efficiency, and reducing project costs. To improve mixing efficiency, many factories use multiple sand mixers simultaneously. However, due to differences in their service life and the types of materials being mixed, the performance of different sand mixers inevitably varies. Allocating the same amount of energy to sand mixers with different performance characteristics and uses can lead to energy waste.

[0003] Existing technologies use PLC or DCS systems to automate the control of sand mixers. While this allows for monitoring and control of the sand mixers, it can only monitor multiple sand mixers as a whole. Furthermore, operators need to manually adjust relevant parameters and allocate energy based on the monitoring results. Therefore, it is difficult to achieve real-time control of the sand mixers and to accurately allocate energy to each sand mixer. Summary of the Invention

[0004] This application provides a variable frequency control system and control method for a sand mixer, which solves the problem that existing technologies cannot accurately allocate energy to sand mixers with different performance characteristics.

[0005] To achieve the above objectives, the embodiments of this application adopt the following technical solutions:

[0006] In a first aspect, a variable frequency control system for sand mixing in a sand mixer is provided. The system includes a sand mixing control center and a sand mixing management center, which are communicatively connected. The sand mixing control center includes a sand mixing information storage module, and the sand mixing management center includes an order management module and an equipment management module. The sand mixing control center also includes:

[0007] The information retrieval module is used to retrieve the historical sand mixing information of all sand mixing units in the sand mixing information storage module, as well as the sand mixing order information of the order management module. The historical sand mixing information includes historical sand mixing efficiency information and historical sand mixing energy consumption information.

[0008] The sand mixing unit grouping module is used to analyze the time-series change characteristics of all the sand mixing units based on the historical sand mixing efficiency information, and to divide all the sand mixing units into an abnormal sand mixing unit set and a normal sand mixing unit set based on the time-series change characteristics.

[0009] The first energy consumption allocation module is used to allocate weights to the abnormal sand mixing unit set and the normal sand mixing unit set according to the historical sand mixing efficiency information and the sand mixing order information, and generate a first energy allocation strategy for all the sand mixing units by combining the weight allocation results and the historical sand mixing energy consumption information.

[0010] The first sand mixing frequency conversion control module is used to initially allocate sand mixing energy to the sand mixing unit according to the first energy allocation strategy, and control all the sand mixing units that have completed energy allocation to execute sand mixing order tasks according to the sand mixing order information.

[0011] The information monitoring module is used to monitor the operating status of all the sand mixing units during the execution of the sand mixing order task by using multiple types of sensors pre-deployed inside all the sand mixing units, and to obtain sand mixing sensor information.

[0012] The second energy consumption allocation module is used to generate a second energy allocation strategy for all the sand mixers in each sand mixing unit based on the sand mixing sensor information.

[0013] The second sand mixing frequency conversion control module is used to dynamically allocate sand mixing energy to all the sand mixers in each sand mixing unit according to the second energy allocation strategy, and control all the sand mixers that have completed energy allocation to continue to execute the sand mixing order task according to the sand mixing order information.

[0014] Optionally, the sand mixing unit grouping module includes:

[0015] The time-series sorting submodule is used to sort the historical sand mixing efficiency information of each of the sand mixing units in time sequence to obtain the historical efficiency time series of all the sand mixing units.

[0016] The time series analysis submodule is used to fit the historical efficiency time series of each of the sand mixing units to obtain the time series variation characteristics of all the sand mixing units.

[0017] The abnormal grouping submodule is used to assign the sand mixing unit corresponding to the historical efficiency time series to the abnormal sand mixing unit set when the time series change characteristics show that the historical efficiency time series is a fluctuating series.

[0018] The normal grouping submodule is used to assign the sand mixing unit corresponding to the historical efficiency time series to the normal sand mixing unit set when the time series change characteristics show that the historical efficiency time series is a stationary series.

[0019] Optionally, the first energy consumption allocation module includes:

[0020] The first weight allocation submodule is used to calculate the number of sand mixing units in the abnormal sand mixing unit set and the normal sand mixing unit set respectively, and to initially allocate weights to the abnormal sand mixing unit set and the normal sand mixing unit set according to the number of sand mixing units, so as to obtain the abnormal weight coefficient and the normal weight coefficient.

[0021] The first information extraction submodule is used to extract the sand mixing order time limit and total sand mixing order quantity for each sand mixing unit from the sand mixing order information.

[0022] The efficiency calculation submodule is used to calculate the expected sand mixing efficiency information of each sand mixing unit based on the sand mixing order time limit and the total sand mixing order quantity corresponding to each sand mixing unit;

[0023] The second weight allocation submodule is used to combine the expected sand mixing efficiency information, the abnormal weight coefficient and the normal weight coefficient to perform weight allocation for all the sand mixing units, and obtain the sand mixing unit weight coefficient of all the sand mixing units.

[0024] The first energy consumption allocation submodule is used to generate a first energy allocation strategy for all the sand mixing units based on the weight coefficients of all the sand mixing units and the historical sand mixing energy consumption information.

[0025] Optionally, the second weight allocation submodule includes:

[0026] The difference calculation unit is used to calculate the efficiency difference between the expected sand mixing efficiency information and the historical sand mixing efficiency information when the expected sand mixing efficiency information is less than or equal to the historical sand mixing efficiency information.

[0027] The first weight allocation unit is used to allocate weights to any sand mixing unit in the abnormal sand mixing unit set according to the efficiency difference and the abnormal weight coefficient, thereby obtaining the abnormal sand mixing unit set weight coefficient for all sand mixing units in the abnormal sand mixing unit set.

[0028] The second weight allocation unit is used to allocate weights to any sand mixing unit in the set of normal sand mixing units according to the efficiency difference and the normal weight coefficient, so as to obtain the normal sand mixing unit set weight coefficient of all sand mixing units in the set of normal sand mixing units.

[0029] The weighting integration unit is used to integrate the weighting coefficients of the abnormal sand mixing unit set and the weighting coefficients of the normal sand mixing unit set to obtain the sand mixing unit weighting coefficients of all the sand mixing units.

[0030] Optionally, the second energy consumption allocation module includes:

[0031] The second information extraction submodule is used to extract the sand mixer information and sand mixing material information from the sand mixing sensor information of all the sand mixers in each of the sand mixing units.

[0032] The anomaly marking submodule is used to mark abnormal sand mixers based on the analysis of the change characteristics of the sand mixer information of all the sand mixing units, and upload the sand mixer number corresponding to the abnormal sand mixer to the equipment management module.

[0033] The third weight allocation submodule is used to, when there is an abnormal sand mixer in any of the sand mixing units, combine the sand mixer information, the sand mixing material information and the sand mixer number to allocate weight coefficients to all the sand mixers, and obtain the sand mixer weight coefficients for all the sand mixers.

[0034] The fourth weight allocation submodule is used to allocate weight coefficients to all sand mixers by combining the sand mixer information and the sand mixing material information when there are no abnormal sand mixers in all the sand mixing units, so as to obtain the sand mixer weight coefficients of all the sand mixers.

[0035] The second energy consumption allocation submodule is used to generate a second energy allocation strategy for all the sand mixers based on the weight coefficient of the sand mixer.

[0036] Optionally, the anomaly marking submodule includes:

[0037] The information extraction unit is used to extract the sand mixing vibration information and sand mixing current information from the sand mixing machine information corresponding to any sand mixer in any of the sand mixing units.

[0038] An abnormality marking unit is used to extract the vibration change characteristics of the sand mixing vibration information and the current amplitude characteristics of the sand mixing current information. When the vibration change characteristics are abnormal or the current amplitude characteristics are abnormal, the sand mixer is marked as an abnormal sand mixer.

[0039] The abnormal upload unit is used to read the sand mixer number of the abnormal sand mixer, mark the sand mixer number as the abnormal sand mixer number, and upload the abnormal sand mixer number to the equipment management module.

[0040] Optionally, the third weight allocation submodule includes:

[0041] An abnormal weight allocation unit is used to initially allocate weights to all the sand mixers in the sand mixing unit according to the sand mixer number of the sand mixer when there is an abnormal sand mixer in any of the sand mixing units, and obtain a first weight coefficient.

[0042] An information preprocessing unit is used to normalize the information of the sand mixer and the information of the sand mixing material.

[0043] The variability calculation unit is used to calculate the index variability of the sand mixer information and sand mixing material information after normalization processing, and obtain the sand mixing variability and material variability.

[0044] The conflict degree calculation unit is used to calculate the index conflict between the sand mixer information and the sand mixing material information after normalization, and obtain the sand mixing index conflict degree.

[0045] The weight calculation unit is used to calculate the weight coefficient of all the sand mixers when any of the sand mixing units has an abnormal sand mixer, by combining the first weight coefficient, sand mixing variability, material variability, and sand mixing index conflict degree, and using the sand mixer weight formula. The sand mixer weight formula is as follows:

[0046]

[0047] Where P(x) is the weighting coefficient of sand mixer X. Let be the sand mixing variability of sand mixer information i for sand mixer X. Let j be the material variability of the sand mixing material information of sand mixer x. λ represents the degree of conflict between the mixing parameters of mixing machine information i and mixing material information j of mixing machine X. x is the first weighting coefficient for sand mixer x.

[0048] Optionally, the second sand mixing frequency conversion control module further includes:

[0049] The progress upload submodule is used to upload the task progress of any of the sand mixing units to the order management module when any of the sand mixing units completes the sand mixing order task.

[0050] The dynamic adjustment submodule is used to continue to acquire the sand mixing sensor information of all the sand mixers in the sand mixing unit when any of the sand mixing units has not completed the sand mixing order task, and dynamically adjust the sand mixing energy of all the sand mixers based on the sand mixing sensor information until all the sand mixing units complete the sand mixing order task.

[0051] Secondly, this application provides a sand mixer frequency conversion control method, characterized in that it is applied to a sand mixer frequency conversion control system as described in any one of the first aspects, the method comprising the following steps:

[0052] Retrieve historical sand mixing information of all sand mixing units in the sand mixing information storage module, as well as sand mixing order information in the order management module. The historical sand mixing information includes historical sand mixing efficiency information and historical sand mixing energy consumption information.

[0053] Based on the historical sand mixing efficiency information, the time-series variation characteristics of all the sand mixing units are analyzed, and based on the time-series variation characteristics, all the sand mixing units are divided into an abnormal sand mixing unit set and a normal sand mixing unit set.

[0054] Based on the historical sand mixing efficiency information and the sand mixing order information, weights are assigned to the abnormal sand mixing unit set and the normal sand mixing unit set. Combining the weight assignment results and the historical sand mixing energy consumption information, a first energy allocation strategy is generated for all the sand mixing units.

[0055] According to the first energy allocation strategy, the sand mixing unit is initially allocated sand mixing energy, and all the sand mixing units that have completed energy allocation are controlled to execute sand mixing order tasks according to the sand mixing order information;

[0056] During the process of all the sand mixing units executing the sand mixing order task, the operating status of all the sand mixing units is monitored by multiple types of sensors pre-arranged inside all the sand mixing units, and sand mixing sensor information is obtained.

[0057] A second energy allocation strategy is generated for all the sand mixers in each sand mixing unit based on the sand mixing sensor information.

[0058] According to the second energy allocation strategy, the mixing energy is dynamically allocated to all the mixing machines in each mixing unit, and all the mixing machines that have completed the energy allocation are controlled to continue to execute the mixing order task according to the mixing order information.

[0059] Thirdly, this application provides a sand mixer frequency conversion control device, characterized in that it includes a sand mixer frequency conversion control system according to any one of the first aspects.

[0060] The above technical solution addresses the issue that sand mixers differ in model, performance, and usage time, resulting in varying energy requirements. Therefore, this invention first analyzes historical energy consumption information to categorize all sand mixers into abnormal and normal sets. Weights are then assigned to the sand mixers in each set based on their location. Combining these weights with historical energy consumption information, a first energy allocation strategy is generated for each sand mixer. Energy is then allocated according to this strategy to ensure optimal operation, maximizing energy utilization and mixing efficiency. Finally, a second energy allocation strategy is dynamically generated based on the first strategy and the operating status of each mixer, precisely allocating energy to each machine to achieve optimal production efficiency. In summary, this invention can precisely allocate energy to sand mixers with different performance characteristics, thereby achieving energy savings and increased production.

[0061] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0062] Figure 1 This is a schematic diagram of the structure of a sand mixer frequency conversion control system provided in an embodiment of this application;

[0063] Figure 2 This is a flowchart illustrating a variable frequency control method for sand mixing in a sand mixer, as provided in an embodiment of this application. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0065] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0066] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0067] Figure 1 The diagram illustrates the structure of a variable frequency control system for a sand mixer according to an embodiment of this application. Figure 1 As shown in the figure, this application provides a sand mixing frequency conversion control system for a sand mixer. The system includes a sand mixing control center and a sand mixing management center, which are communicatively connected. The sand mixing control center includes a sand mixing information storage module, and the sand mixing management center includes an order management module and an equipment management module. The sand mixing control center also includes:

[0068] The information retrieval module is used to retrieve historical sand mixing information of all sand mixing units in the sand mixing information storage module, as well as sand mixing order information in the order management module. The historical sand mixing information includes historical sand mixing efficiency information and historical sand mixing energy consumption information.

[0069] The sand mixing unit grouping module is used to analyze the time-series variation characteristics of all sand mixing units based on historical sand mixing efficiency information, and divide all sand mixing units into abnormal sand mixing unit set and normal sand mixing unit set according to the time-series variation characteristics.

[0070] The first energy consumption allocation module is used to allocate weights to the abnormal sand mixing unit set and the normal sand mixing unit set based on historical sand mixing efficiency information and sand mixing order information, and generate a first energy allocation strategy for all sand mixing units by combining the weight allocation results and historical sand mixing energy consumption information.

[0071] The first sand mixing frequency conversion control module is used to initially allocate sand mixing energy to the sand mixing unit according to the first energy allocation strategy, and control all sand mixing units that have completed energy allocation to execute sand mixing order tasks according to the sand mixing order information.

[0072] The information monitoring module is used to monitor the operating status of all sand mixing units during the execution of sand mixing order tasks by using multiple types of sensors pre-deployed inside all sand mixing units, and to obtain sand mixing sensor information.

[0073] The second energy consumption allocation module is used to generate a second energy allocation strategy for all sand mixers in each sand mixing unit based on the sand mixing sensor information.

[0074] The second sand mixing frequency conversion control module is used to dynamically allocate sand mixing energy to all sand mixers in each sand mixing unit according to the second energy allocation strategy, and control all sand mixers that have completed energy allocation to continue to execute sand mixing order tasks according to the sand mixing order information.

[0075] In this embodiment, the information retrieval module serves as the data input port for the entire system, responsible for retrieving pre-stored historical sand mixing information for all sand mixing units from the sand mixing information storage module. This process involves several technical details and implementation principles. First, the information retrieval module needs to establish a secure and reliable data connection with the sand mixing management center. This is typically achieved through an API interface or a dedicated data transmission protocol, such as RESTful API or SOAP-based web services. A sand mixing unit consists of multiple sand mixers of the same type that mix the same type of raw materials. Historical sand mixing efficiency information refers to the average sand mixing efficiency of all sand mixers in each sand mixing unit during past sand mixing operations. Historical sand mixing energy consumption information refers to the average electrical energy consumed by each sand mixing unit during past sand mixing operations. Sand mixing order information includes order type (e.g., resin sand, water glass sand, single sand, etc.), order time, and order quantity (e.g., resin sand: 100 tons, single sand: 500 tons), etc. The sand mixing information storage module is mainly used to store the amount of sand mixed, the mixing time, and the power consumption of each sand mixing unit for each sand mixing operation. The sand mixing order information is used to store customer orders and order progress.

[0076] The sand mixing unit grouping module is used to divide all sand mixing units into sets of abnormal and normal sand mixing units based on historical sand mixing efficiency information. It first extracts the timestamps of the historical sand mixing efficiency information and aligns them. Then, it sorts the historical sand mixing efficiency information by time to obtain the historical efficiency time series of all sand mixing units. A time series is a sequence of values ​​for the same statistical indicator arranged in chronological order of their occurrence. Methods such as control chart detection and Z-score outlier detection can be used to identify outliers in the historical efficiency time series to analyze its variation characteristics. Alternatively, the variance or standard deviation of the historical efficiency time series can be calculated to reflect its variation characteristics. Furthermore, methods such as Fourier transform or wavelet transform can be used to convert the historical efficiency time series from the time domain to the frequency domain for variation characteristic analysis. Based on the temporal variation characteristics of historical efficiency time series, sand mixing units exhibiting significant efficiency fluctuations are classified into an abnormal sand mixing unit set, such as a sudden decrease in the average efficiency of a sand mixing unit at a certain time point. Sand mixing units with stable efficiency changes are classified into a normal sand mixing unit set, meaning sand mixing units whose average efficiency remains at a certain level with almost no significant changes are classified into the normal sand mixing unit set. This is because if a sand mixing unit experiences a significant decrease in average sand mixing efficiency, it indicates that there are sand mixers within that unit that have malfunctioned or are severely worn.

[0077] The first energy allocation module is used to allocate power to sand mixing units that are not currently operating. The first energy allocation strategy is the power allocation strategy for each sand mixing unit, encompassing the power that each unit can be allocated, thus achieving overall power allocation for the sand mixing units. Power allocation needs to consider several factors. First, for sand mixing units that are highly likely to malfunction or experience severe wear, their power allocation ratio needs to be reduced, i.e., their weighting coefficient needs to be lowered. This is because even if more power is allocated to a malfunctioning or worn sand mixer, its sand mixing efficiency cannot be improved; it may even cause the malfunctioning sand mixer to overload, resulting in secondary damage. In severe cases, it may cause the motor windings to overheat, leading to motor burnout and even more serious consequences. Second, for sand mixing units with large order volumes and short deadlines, their weighting coefficient needs to be increased to improve the sand mixing efficiency of these units, enabling them to complete the order tasks within the specified time. Finally, the energy allocation needs to be based on historical sand mixing energy consumption information. This is because different sand mixers have different performance and therefore different loads. Blindly increasing the power of the sand mixer may lead to overload. Therefore, the final energy allocation strategy needs to be based on historical sand mixing energy consumption information and then adjusted according to the allocated weights.

[0078] The first sand mixing frequency converter control module is used to uniformly adjust the electrical energy of all sand mixers within each sand mixing unit using the frequency converter controlling each sand mixer. This adjustment is based on the first energy distribution strategy. A suitable frequency converter is selected according to the model of each sand mixer in each unit, such as a 200kW VM1000B frequency converter. The motor of the sand mixer is electrically connected to the frequency converter, and the parameters of the frequency converter are set according to the model of the sand mixer motor, such as the motor's rated power, rated voltage, rated current, minimum operating frequency, and maximum operating frequency. To enable simultaneous control of multiple sand mixing units, a PLC control system is used to control all sand mixers. The PLC control system receives the first energy allocation strategy from the first energy distribution module via its input module. The central processing unit of the PLC control system performs logical processing and calculations on the first energy allocation strategy, using pre-set control logic and algorithms to calculate the electrical energy required by each sand mixing unit. This, in turn, calculates the frequency value that needs to be adjusted. The PLC sends frequency control commands and start / stop commands to the frequency converters of the sand mixing units via its output module, guiding the frequency converters to adjust their output frequencies. This achieves control over the electrical energy distribution and operating status of the sand mixers, ensuring that the sand mixing units can utilize the allocated electrical energy to begin sand mixing operations according to the sand mixing order information. Furthermore, the sand mixing order task includes the total amount of raw materials that the sand mixing units need to mix, and the sand mixing energy mainly includes the electrical energy required by the sand mixers.

[0079] The information monitoring module utilizes various sensors installed inside the sand mixers to monitor the status of all sand mixers. These sensors include temperature sensors, vibration sensors, pressure sensors, and current sensors, which monitor parameter changes during the sand mixing process and dynamically adjust the power supply of the sand mixers based on these changes. This is because sand mixers experience temperature and pressure variations during operation, and these changes reflect the current operating status of the mixers. For example, excessively high internal temperature indicates potential overload, requiring adjustment of the input power; excessively high pressure suggests potential material blockage, necessitating a reduction in energy output; and excessive vibration amplitude or abnormal vibration frequency indicates potential malfunction or wear. Therefore, precise adjustment of the input power to each sand mixer based on its temperature, vibration, and other characteristics is necessary to ensure optimal operation for each mixer, thereby improving production efficiency, extending service life, and achieving the goals of increased production and energy savings.

[0080] The second energy allocation module generates a second energy allocation strategy for each sand mixer. This second energy allocation strategy is the power distribution strategy for each sand mixer in the sand mixer group, encompassing the electrical energy that each mixer can be allocated. Unlike the first energy allocation strategy, the second energy allocation strategy is dynamically changing. In addition to the initially generated second energy allocation strategy, if there is a significant change in the sand mixing sensor information (such as temperature, pressure, speed, vibration, etc.) inside a sand mixer, the second energy allocation module will immediately generate a third, fourth, and so on, energy allocation strategy for all sand mixers based on the changed sensor information. A significant change here refers to any one of the following information exceeding a preset threshold: temperature, speed, pressure, vibration amplitude, vibration frequency, etc. For example, if the temperature of a sand mixer exceeds a preset temperature threshold (which could be 60 degrees Celsius), the second energy allocation module will immediately regenerate a third energy allocation strategy after detecting the abnormal temperature change. By dynamically adjusting the energy distribution strategy to precisely regulate the input power of each sand mixer, it is possible to ensure that each sand mixer is in its optimal operating state. Furthermore, since the second energy distribution strategy is based on the first, it avoids overload during the dynamic energy distribution process. This is because the first energy distribution strategy has already completed an overall energy distribution based on the historical energy consumption information of each sand mixer unit. Subsequently, the sand mixers within each unit undergo a second energy distribution based on the power allocated to that unit. Although the sand mixers within a unit are of the same type, their usage time and quality control vary, necessitating a second energy distribution for each group of sand mixers. This ensures that each group of sand mixers can maintain its optimal operating state to the greatest extent possible, improving production efficiency while reducing energy waste, thus achieving energy conservation and increased production.

[0081] The second sand mixing frequency converter control module is used for energy distribution and regulation of each sand mixer. Similar to the first sand mixing frequency converter control module, it is also connected to the PCL control system, which enables precise energy distribution to each sand mixer. The PCL control system receives the second energy distribution strategy from the second energy distribution module through its input module. The central processing unit of the PCL control system performs logical processing and calculation on the second energy distribution strategy, using pre-set control logic and algorithms to calculate the electrical energy required by each sand mixer in different sand mixing units. This calculates the frequency value that needs to be adjusted. The PLC sends corresponding frequency control commands to the frequency converters of each sand mixer in all sand mixing units through its output module. After receiving the frequency control command, the motor of each sand mixer adjusts its frequency according to the command. After the frequency adjustment is completed, the sand mixer continues to perform the sand mixing task. Subsequently, the information monitoring module, the second energy distribution module, and the second sand mixing frequency converter control module continue to perform their respective tasks, continuously dynamically adjusting the frequency of each sand mixer. Dynamically allocate energy to each sand mixer until the sensor information of all sand mixers no longer changes significantly or all sand mixers have completed their sand mixing tasks.

[0082] In one embodiment, the sand mixing unit grouping module includes:

[0083] The time-series sorting submodule is used to sort the historical sand mixing efficiency information of each sand mixing unit in time sequence to obtain the historical efficiency time series of all sand mixing units.

[0084] The time series analysis submodule is used to fit the historical efficiency time series of each sand mixing unit to obtain the time series variation characteristics of all sand mixing units.

[0085] The abnormal grouping submodule is used to assign the sand mixing unit corresponding to the historical efficiency time series to the abnormal sand mixing unit set when the time series change characteristics show that the historical efficiency time series is a fluctuating series.

[0086] The normal grouping submodule is used to assign the sand mixing unit corresponding to the historical efficiency time series to the normal sand mixing unit set when the time series change characteristics show that the historical efficiency time series is a stationary series.

[0087] In this embodiment, the time-series sorting submodule is responsible for sorting the historical sand mixing efficiency information in time sequence. First, it extracts the timestamps of the historical sand mixing efficiency information and aligns them. Then, it sorts the historical sand mixing efficiency information by time to obtain the historical efficiency time series of all sand mixing units. A time series is a sequence of values ​​for the same statistical indicator arranged in chronological order of their occurrence. The variation characteristics of the historical efficiency time series can be analyzed using methods such as control chart detection and Z-score outlier detection. The variation characteristics can also be reflected by calculating the variance or standard deviation of the historical efficiency time series. Furthermore, methods such as Fourier transform or wavelet transform can be used to convert the historical efficiency time series from the time domain to the frequency domain for variation characteristic analysis.

[0088] The time series analysis submodule is used to analyze the time series variation characteristics of historical efficiency time series. Taking the analysis of historical efficiency time series variation characteristics using the Z-score model as an example, the Z-score model is first used to identify whether there are outliers in the historical efficiency time series of each sand mixing unit. Specifically, the average efficiency of each sand mixing unit at multiple different historical time points is calculated first. Based on the average efficiency, the efficiency standard deviation between the sand mixing efficiency of each sand mixing unit at different time points and the average efficiency is calculated. Based on the average efficiency and standard deviation, the Z-score of each sand mixing unit at different time points is calculated using the Z-score calculation formula, Z = (X1 - A) / B, where X1 is the sand mixing efficiency of the sand mixing unit at the first time point, A is the average efficiency, and B is the efficiency standard deviation. If the absolute value of the Z-score of the sand mixing unit at a certain time point is greater than the preset absolute value threshold, it is determined that the sand mixing unit has an anomaly at that time point. Therefore, it can be determined that the historical efficiency time series of the sand mixing unit has efficiency fluctuations, indicating that the historical efficiency time series of the sand mixing unit is a fluctuating series. If the absolute value of the Z-score of the sand mixing unit is less than or equal to the preset absolute value threshold at all time points, it indicates that there are no outliers in the sand mixing unit. Therefore, it can be determined that there is no efficiency fluctuation in the historical efficiency time series of the sand mixing unit, indicating that the historical efficiency time series of the sand mixing unit is a stationary series.

[0089] If the historical efficiency time series of a sand mixing unit is a fluctuating series, it indicates that the historical sand mixing efficiency of the unit suddenly increased or decreased at a certain time point. A sudden decrease in sand mixing efficiency suggests that a sand mixer in the unit may have been damaged or severely worn. A sudden increase in historical sand mixing efficiency may also indicate that a damaged sand mixer was used before the increase in efficiency, and at the current time point, due to fewer sand mixing orders to be processed, no damaged or worn sand mixer was used, leading to a sudden increase in the sand mixing efficiency of the unit. Therefore, the abnormal grouping submodule classifies sand mixing units that may have abnormal sand mixers into an abnormal sand mixing unit set. Similarly, if the sand mixing efficiency of a sand mixing unit remains at a relatively stable level, it indicates that the sand mixing unit is likely not equipped with abnormal sand mixers. Therefore, the normal grouping submodule classifies the sand mixing unit into a normal sand mixing unit set.

[0090] Dividing the sand mixing units into sets of abnormal and normal sand mixing units is a preliminary weighting based on the potential presence of abnormal sand mixers. This is because the energy allocation ratio for sand mixing units that may have abnormal sand mixers will be reduced in the subsequent energy allocation process. This is because simply allocating more electricity to abnormal sand mixers that may be faulty or worn will not improve their sand mixing efficiency; on the contrary, it may cause overload due to excessive electricity allocation, resulting in more serious consequences, such as overheating and further damage to the sand mixer, or reduced crushing and mixing efficiency, affecting the overall output quality. In addition, if the potential presence of abnormal sand mixers is not analyzed before the sand mixing units are put into operation, and the electricity input of sand mixing units that may have abnormal sand mixers is reduced, and electricity allocation is still performed as for normal sand mixing units, it is very likely to cause secondary damage to abnormal sand mixers, affecting sand mixing efficiency, and may even cause the motor of the sand mixer to burn out. For the reasons mentioned above, it is necessary to analyze in advance whether there is a possibility of abnormal sand mixers in each sand mixer unit before starting the sand mixer, and then perform weight allocation.

[0091] In one embodiment, the first energy consumption allocation module includes:

[0092] The first weight allocation submodule is used to calculate the number of sand mixing units in the abnormal sand mixing unit set and the normal sand mixing unit set respectively, and to initially allocate weights to the abnormal sand mixing unit set and the normal sand mixing unit set based on the number of sand mixing units, so as to obtain the abnormal weight coefficient and the normal weight coefficient.

[0093] The first information extraction submodule is used to extract the sand mixing order time limit and total sand mixing order quantity for each sand mixing unit from the sand mixing order information.

[0094] The efficiency calculation submodule is used to calculate the expected sand mixing efficiency information for each sand mixing unit based on the sand mixing order deadline and the total sand mixing order quantity corresponding to each sand mixing unit.

[0095] The second weight allocation submodule is used to combine the expected sand mixing efficiency information, abnormal weight coefficient and normal weight coefficient to allocate weights to all sand mixing units, and obtain the sand mixing unit weight coefficients of all sand mixing units.

[0096] The first energy consumption allocation submodule is used to generate the first energy allocation strategy for all sand mixing units based on the weight coefficients of all sand mixing units and historical sand mixing energy consumption information.

[0097] In this embodiment, the first weight allocation submodule is used to initially allocate weights to the abnormal sand mixing unit set and the normal sand mixing unit set. First, the number of sand mixing units in the abnormal and normal sand mixing unit sets is calculated. Then, based on the number of sand mixing units, initial weight coefficients are allocated to the abnormal and normal sand mixing unit sets. Next, the initial weight coefficient of the abnormal sand mixing unit set is reduced by a certain percentage, which can be set based on the average efficiency standard deviation of the abnormal sand mixing units in the abnormal sand mixing unit set. Then, a certain percentage of weight coefficients is added to the normal sand mixing units to obtain the abnormal weight coefficient and the normal weight coefficient. The increase and decrease percentages are the same, both based on the initial weight coefficients. The calculation steps for the average efficiency standard deviation include: first, calculating the average sand mixing efficiency of the sand mixing unit at different historical time points based on the historical sand mixing efficiency information of the sand mixing unit; then, calculating the efficiency standard deviation for each historical time point according to the standard deviation formula; and finally, calculating the average efficiency standard deviation of all historical time points to obtain the average efficiency standard deviation of the sand mixing unit. The historical time point refers to the time point when the sand mixing unit performed sand mixing operations before the current time point. For example, if there are two sand mixing units in the abnormal sand mixing unit set and three sand mixing units in the normal sand mixing unit set, then first, the abnormal sand mixing unit set and the normal sand mixing unit set are equally assigned weight coefficients of 0.4 and 0.6 respectively. Then, the weight coefficient of the abnormal sand mixing unit set is decreased, and the weight coefficient of the normal sand mixing unit set is increased. For example, if the increase and decrease ratios are 0.02, then the abnormal weight coefficient is 0.38, and the normal weight coefficient is 0.62.

[0098] The first information extraction submodule is used to extract the sand mixing order deadline and total sand mixing order quantity from the sand mixing order information. The sand mixing order deadline refers to the time limit for completing the sand mixing order, for example, single sand: 10 days to complete, resin molding sand: 15 days to complete. The total sand mixing order quantity refers to the total quantity of a certain type of order, for example, core sand: 150 tons, single sand: 200 tons. The efficiency calculation submodule divides the total sand mixing order quantity of each sand mixing unit by the sand mixing order deadline to calculate the minimum sand mixing efficiency of each sand mixing unit, i.e., the expected sand mixing efficiency information. This means that the sand mixing unit cannot fall below the expected sand mixing efficiency information in order to complete the sand mixing order task within the specified time.

[0099] The second weight allocation submodule is used to assign weights to all sand mixing units. Specifically, when the expected sand mixing efficiency is less than or equal to the historical sand mixing efficiency, the efficiency difference between the expected and historical sand mixing efficiency of each sand mixing unit is calculated. For sand mixing units whose efficiency difference is greater than a preset first difference threshold, it means that the actual sand mixing efficiency of the sand mixing unit is much greater than the minimum sand mixing efficiency. Even if a sand mixing unit fails later, there is a high probability that the sand mixing order can be completed. Therefore, it is not necessary to allocate more sand mixing energy, i.e., its weight coefficient is reduced. For sand mixing units with an efficiency difference less than the preset second difference threshold, since their actual sand mixing efficiency is very close to the minimum mixing efficiency, if a sand mixer malfunctions or suffers severe wear during the sand mixing order process, it is highly likely that the mixing order will not be completed. Therefore, more sand mixing energy needs to be allocated, i.e., its weighting coefficient needs to be increased to maximize the working efficiency of the sand mixing unit within a certain range. Here, actual sand mixing efficiency refers to historical sand mixing efficiency information, minimum sand mixing efficiency refers to expected sand mixing efficiency information, and the first difference threshold is greater than the second difference threshold. The first and second difference thresholds are set based on the assumption that one or more sand mixers will be unusable. For sand mixing units with difference thresholds between the first and second difference thresholds, no more or less energy needs to be allocated; energy allocation only needs to be based on the average weighting coefficient of its abnormal or normal weighting coefficient and according to historical sand mixing energy consumption information. Furthermore, the magnitude of the weighting coefficient reduction and increase is set based on the difference between the efficiency difference and the difference threshold.

[0100] The first energy allocation submodule is used to generate the first energy allocation strategy. The first energy allocation strategy includes the energy allocated to each sand mixing unit. The first sand mixing frequency converter control module can directly read the first energy allocation strategy and allocate energy to the sand mixers within each sand mixing unit according to the first energy allocation strategy. The generation steps of the first energy allocation strategy include: calculating the historical average total energy consumption of all sand mixing units based on the historical sand mixing energy consumption information of each sand mixing unit. The historical average total energy consumption is obtained by adding the historical sand mixing energy consumption information of all sand mixing units and dividing by the number of times the sand mixing unit has been run. The energy required by each sand mixing unit is calculated based on the historical average total energy consumption, historical sand mixing energy consumption information, and the weighting coefficient of the sand mixing unit. The formula for calculating the energy required by each sand mixing unit is L = 0.5K(X1 / J + Y1), where K is the total energy, J is the historical average total energy consumption, X1 is the historical sand mixing energy consumption information of sand mixing unit 1, and Y1 is the weighting coefficient of sand mixing unit 1. After calculating the energy required by all sand mixing units, the first energy allocation strategy is obtained by integrating the results.

[0101] In one embodiment, the second weight allocation submodule includes:

[0102] The difference calculation unit is used to calculate the efficiency difference between the expected sand mixing efficiency information and the historical sand mixing efficiency information when the expected sand mixing efficiency information is less than or equal to the historical sand mixing efficiency information.

[0103] The first weight allocation unit is used to assign weights to any sand mixing unit in the abnormal sand mixing unit set according to the efficiency difference and the abnormal weight coefficient, so as to obtain the abnormal sand mixing unit set weight coefficient of all sand mixing units in the abnormal sand mixing unit set.

[0104] The second weight allocation unit is used to allocate weights to any sand mixing unit in the normal sand mixing unit set according to the efficiency difference and the normal weight coefficient, so as to obtain the normal sand mixing unit set weight coefficient of all sand mixing units in the normal sand mixing unit set.

[0105] The weighting integration unit is used to integrate the weighting coefficients of abnormal sand mixing units and the weighting coefficients of normal sand mixing units to obtain the weighting coefficients of all sand mixing units.

[0106] In this embodiment, the difference calculation unit is used to calculate the efficiency difference. When the expected sand mixing efficiency is less than or equal to the historical sand mixing efficiency, the expected sand mixing efficiency is subtracted from the historical sand mixing efficiency of each sand mixing unit to obtain the efficiency difference. The larger the efficiency difference, the greater the probability that the sand mixing unit will complete the sand mixing order.

[0107] For sand mixing units with an efficiency difference greater than the preset first difference threshold, it indicates that their actual sand mixing efficiency is much greater than the minimum sand mixing efficiency. Even if a sand mixer subsequently fails, there is a high probability that the sand mixing order can be completed. Therefore, it is not necessary to allocate more sand mixing energy, i.e., reduce its weighting coefficient. For sand mixing units with an efficiency difference less than the preset second difference threshold, since their actual sand mixing efficiency is very close to the minimum mixing efficiency, if a sand mixer fails or suffers severe wear during the sand mixing order process, it is highly likely that the mixing order will not be completed. Therefore, it is necessary to allocate more sand mixing energy, i.e., increase its weighting coefficient, and try to improve the working efficiency of the sand mixing unit within a certain range. Here, the actual sand mixing efficiency refers to historical sand mixing efficiency information, the minimum sand mixing efficiency refers to expected sand mixing efficiency information, and the first difference threshold is greater than the second difference threshold. The first and second difference thresholds are difference thresholds set by assuming that one or more sand mixers are unusable. For sand mixing units whose difference thresholds fall between the first and second difference thresholds, no more or less energy needs to be allocated. Energy allocation should be based solely on the average weighting coefficient of their abnormal or normal weighting coefficients, and according to historical sand mixing energy consumption information. Furthermore, the magnitude of the weighting coefficient reduction and increase is set based on the difference between the efficiency difference and the difference threshold.

[0108] The first weight allocation unit is used to assign weights to the sand mixing units in the abnormal sand mixing unit set. Specifically, for all sand mixing units in the abnormal sand mixing unit set, the abnormal weight coefficient is evenly distributed to each sand mixing unit. If the efficiency difference of a sand mixing unit is greater than a first difference threshold, the first difference between its efficiency difference and the first difference threshold is calculated. If the efficiency difference of a sand mixing unit is less than a second difference threshold, the second difference between its efficiency difference and the second difference threshold is calculated. The sum of all first and second differences is calculated to obtain the sum of differences. The first difference is divided by the sum of differences, and the second difference is divided by the sum of differences to obtain the difference ratio of all sand mixing units. Based on the difference ratio, the weight coefficients of the above two types of sand mixing units are reduced or increased to obtain the abnormal sand mixing unit set weight coefficient for all sand mixing units in the abnormal sand mixing unit set.

[0109] The second weight allocation unit is used to allocate weights to the sand mixing units in the normal sand mixing unit set. Similarly, the normal weight coefficient is first evenly distributed to each sand mixing unit, the difference ratio of all sand mixing units is calculated, and the weight coefficients of the above two types of sand mixing units are reduced or increased according to the difference ratio to obtain the normal sand mixing unit set weight coefficient of all sand mixing units in the normal sand mixing unit set.

[0110] The weighting integration unit is used to integrate the weighting coefficients of abnormal sand mixing units and the weighting coefficients of normal sand mixing units to obtain the weighting coefficients of all sand mixing units.

[0111] In addition, there is another scenario: if the calculated expected mixing efficiency of the sand mixing unit is lower than the historical mixing efficiency, it means that the sand mixing unit is very likely unable to complete the sand mixing order. In this case, simply increasing energy allocation may still not be enough to complete the sand mixing order. Once this happens, the efficiency calculation submodule will immediately obtain the group number of the sand mixing unit, mark it as an abnormal group number, and upload it to the equipment management module. At the same time, it will also upload the calculated expected mixing efficiency and historical mixing efficiency to the equipment management module. The equipment management module will generate equipment shortage information based on the expected and historical mixing efficiency information. The equipment shortage information includes the number of missing equipment and the corresponding abnormal group number. After receiving the equipment shortage information, the staff of the target factory will immediately transfer any idle sand mixers of the same type to the sand mixing unit to ensure that the sand mixing unit can complete the sand mixing task.

[0112] In one embodiment, the second energy consumption allocation module includes:

[0113] The second information extraction submodule is used to extract the sand mixer information and sand mixing material information from the sand mixing sensor information of all sand mixers in each sand mixing unit.

[0114] The anomaly marking submodule is used to mark abnormal sand mixers based on the analysis of the change characteristics of the sand mixer information of all sand mixing units, and upload the sand mixer number corresponding to the abnormal sand mixer to the equipment management module.

[0115] The third weight allocation submodule is used to allocate weight coefficients to all sand mixers when there is an abnormal sand mixer in any sand mixing unit, by combining the sand mixer information, sand mixing material information and sand mixer number, so as to obtain the sand mixer weight coefficients of all sand mixers.

[0116] The fourth weight allocation submodule is used to assign weight coefficients to all sand mixers by combining the information of the sand mixers and the information of the sand mixing materials when there are no abnormal sand mixers in all sand mixing units, so as to obtain the weight coefficients of all sand mixers.

[0117] The second energy consumption allocation submodule is used to generate a second energy allocation strategy for all sand mixers based on the weight coefficient of the sand mixer.

[0118] In this embodiment, the second information extraction submodule extracts all sand mixer information and sand mixing material information. Sand mixer information includes sand mixing vibration information, sand mixing current information, and sand mixing rotation information. Sand mixing vibration information refers to the vibration amplitude and frequency of the sand mixer; sand mixing current information refers to the operating current of the sand mixer motor, reflecting the motor load; and sand mixing rotation information refers to the rotational speed of the sand mixer's main shaft. Sand mixing material information refers to the temperature and humidity of the raw materials inside the sand mixer, reflecting the condition of the raw materials within the sand mixer.

[0119] The anomaly marking submodule is used to mark abnormal sand mixers. Specifically, based on information such as the vibration amplitude, vibration frequency, and current of the sand mixers, it analyzes whether there are any abnormal sand mixers in all sand mixing units. When one or more sand mixers in all sand mixing units exhibit abnormal phenomena, the sand mixer is immediately marked as abnormal, and the pre-stored sand mixer number is read from the sand mixer's internal memory and the corresponding number is marked as an anomaly and uploaded to the equipment management module. Abnormal sand mixer phenomena include vibration amplitude exceeding a preset amplitude threshold, vibration frequency exceeding a preset frequency threshold, and motor current exceeding a preset first current threshold or falling below a preset second current threshold, where the first current threshold is greater than the second current threshold.

[0120] The third weight allocation submodule is used to assign weight coefficients to all sand mixers when there are abnormal sand mixers. Specifically, a first weight coefficient is assigned to each sand mixer based on whether it is abnormal. For abnormal sand mixers, the first weight coefficient reduces the final total weight of the abnormal sand mixer. This is to maximize the utilization of electrical energy and improve the overall efficiency of the sand mixers in the target plant. For abnormal sand mixers with malfunctions or significant wear, simply allocating more electrical energy will not improve their mixing efficiency before repair. Furthermore, some abnormal sand mixers, due to long service life and severe wear, may experience excessive friction between the rollers and bearings if they continue to operate at high loads, causing secondary damage to the sand mixer. Simultaneously, material accumulation inside the sand mixer can hinder the normal movement of the rollers, reducing crushing efficiency. Therefore, for sand mixers that have already malfunctioned, their energy allocation needs to be reduced. After obtaining the first weighting coefficient, a weight is assigned to each sand mixer based on the mixing current information, mixing rotation information, raw material temperature, raw material humidity, and the first weighting coefficient, thus obtaining the weighting coefficient of the sand mixer.

[0121] Specifically, methods such as min-max standardization, Z-score standardization, and function transformation can be used to first normalize the information of the sand mixer and the sand mixing material. Then, the normalized sand mixing variability, material variability, and sand mixing index conflict degree are calculated. Combining the first weighting coefficient, sand mixing variability, material variability, and sand mixing index conflict degree, the weighting coefficient of all sand mixers is calculated. Sand mixing variability reflects the fluctuation of sand mixer information. Taking the calculation of sand mixing rotation information variability as an example, the start of sand mixer operation is taken as the initial time node, the start of the second energy distribution strategy is taken as the cutoff time node, and the time period between the initial time node and the cutoff time node is taken as the trial operation period. First, the average rotation speed during the trial operation period is calculated based on the sand mixing rotation information. Then, the sand mixing variability of the rotation information is calculated using the variability calculation formula based on the average rotation speed.

[0122] The conflict index calculation formula is used to calculate the conflict index between information on sand mixers and information on sand mixing materials. The conflict index is used to measure the degree of correlation between information on sand mixers and information on sand mixing materials. Pearson correlation coefficient, Spearman correlation coefficient, covariance analysis and regression analysis can also be used to calculate the conflict index between information on sand mixers and information on sand mixing materials. The conflict index reflects the importance and relative influence of information by measuring the degree of correlation between information. For information that is relatively important and has a stronger relative influence, more weight needs to be assigned.

[0123] After calculating the sand mixing variability, material variability, and sand mixing index conflict degree of each sand mixer, the weight coefficient of all sand mixers is calculated using the sand mixer weight formula.

[0124] The fourth weight allocation submodule is used to calculate the mixing weight coefficient of all sand mixers when there are no abnormal sand mixers. Since there are no abnormal sand mixers, there is no need to assign a first weight coefficient. Instead, the mixing variability, material variability, and mixing index conflict degree of all sand mixers are directly calculated, and the mixing weight coefficient of all sand mixers is calculated using the sand mixer weight formula. The weight formula for sand mixers without a first weight coefficient is as follows:

[0125]

[0126] Where P(x) is the weighting coefficient of sand mixer x. Let be the sand mixing variability of sand mixer information i for sand mixer x. Let j be the material variability of the sand mixing material information of sand mixer x. The degree of conflict between the mixing index of sand mixer information i and the mixing material information j of sand mixer x is given.

[0127] The second energy allocation submodule is used to generate the second energy allocation strategy. The second energy allocation strategy is the power allocation strategy for the sand mixers in each sand mixing unit, including the power that each sand mixer can be allocated. The specific calculation method is to multiply the sand mixer's weight coefficient by the energy allocated to the corresponding sand mixing unit. Unlike the first energy allocation strategy, the second energy allocation strategy is dynamically changing. Besides the first generated second energy allocation strategy, if any abnormal change occurs inside a sand mixer, the second energy allocation module will immediately generate a third energy allocation strategy, a fourth energy allocation strategy, etc., for all sand mixers based on the changed sand mixing sensor information, until all sand mixers no longer exhibit abnormal changes or the sand mixers complete their sand mixing orders. Abnormal changes include sand mixer malfunctions, the temperature of raw materials inside the sand mixer exceeding a preset temperature threshold, etc. For example, if the temperature of a sand mixer exceeds a preset temperature threshold (which could be 60 degrees Celsius), the second energy allocation module will immediately regenerate the third energy allocation strategy after detecting the abnormal temperature change. Furthermore, the second energy allocation strategy is generated when each sand mixer reaches a preset operating time. In other words, each sand mixer undergoes energy allocation at least twice. By dynamically adjusting the energy allocation strategy to precisely regulate the input electrical energy of each sand mixer, it is possible to ensure that each sand mixer is in its optimal operating state. At the same time, since the second energy allocation strategy is based on the first energy allocation strategy, that is, the first energy allocation strategy allocates energy to each sand mixer group, each sand mixer in each sand mixer group will initially distribute the energy allocated to the group equally, and each sand mixer will operate using the equally distributed energy. This method avoids overload during the dynamic energy allocation process of the sand mixer. This is because the generation of the first energy allocation strategy has already completed an overall energy allocation based on the historical energy consumption information of each sand mixer unit. Subsequently, the sand mixers within each sand mixer unit are re-allocated energy according to the electrical energy allocated to their respective sand mixer units. This is because although the sand mixers within a sand mixer unit are of the same type, they have different usage times and different quality control standards. Therefore, a secondary energy allocation is required for each sand mixer group to ensure that each sand mixer group can maintain its optimal operating state to the greatest extent, improve production efficiency, reduce energy waste, and achieve energy saving and increased production. In addition, after the secondary energy allocation is completed, if a sand mixer malfunctions, the energy can be redistributed again, realizing the dynamic adjustment of the sand mixing energy of the sand mixer.

[0128] In one embodiment, the anomaly marking submodule includes:

[0129] The information extraction unit is used to extract the sand mixing vibration information and sand mixing current information from the sand mixing machine information of any sand mixer in any sand mixing unit.

[0130] The abnormal marking unit is used to extract the vibration change characteristics of the sand mixing vibration information and the current amplitude characteristics of the sand mixing current information. When the vibration change characteristics are abnormal or the current amplitude characteristics are abnormal, the sand mixer is marked as an abnormal sand mixer.

[0131] The abnormal upload unit is used to read the sand mixer number of the abnormal sand mixer, mark the sand mixer number as the abnormal sand mixer number, and upload the abnormal sand mixer number to the equipment management module.

[0132] The information extraction unit is used to extract sand mixing vibration information and sand mixing current information from the sand mixer information. Sand mixing vibration information refers to the vibration amplitude and frequency of the sand mixer, while sand mixing current information refers to the operating current of the sand mixer motor, reflecting the motor load. If the sand mixer exhibits abnormal changes such as vibration amplitude exceeding a preset amplitude threshold or vibration frequency exceeding a preset frequency threshold, it indicates that the sand mixer may have abnormal conditions such as misalignment between the motor shaft and rotor shaft, damaged rotor bearings, rotor imbalance, loose foundation bolts, or bent and deformed main shaft. When the sand mixer exhibits abnormal amplitude characteristics where the current exceeds a preset first current threshold or falls below a preset second current threshold, it indicates that the motor may have a short circuit in the windings or loose wiring leading to poor contact. Therefore, the occurrence of the above abnormal changes or amplitude characteristics indicates that the corresponding sand mixer may have malfunctioned and requires repair. Anomaly marking units can be used to identify abnormal sand mixers. Specifically, the serial number corresponding to the sand mixer exhibiting the aforementioned characteristics is marked as the abnormal sand mixer number. For example, an asterisk or other special symbol can be added after the abnormal sand mixer number. This abnormal sand mixer number is then uploaded to the equipment management module via the anomaly upload unit. The equipment management module generates a sand mixer maintenance task based on the abnormal sand mixer number. Subsequently, maintenance personnel at the target plant, upon receiving the sand mixer maintenance task, can identify the abnormal sand mixer based on the abnormal sand mixer number and perform maintenance on it. This method allows for the identification of abnormal sand mixers while completing sand mixing orders, and by uploading the abnormal sand mixer number, maintenance personnel can directly identify the abnormal sand mixer, significantly saving time in troubleshooting abnormal sand mixers.

[0133] In one embodiment, the third weight allocation submodule includes:

[0134] The abnormal weight allocation unit is used to initially allocate weights to all sand mixers in the sand mixing unit according to the sand mixer number when there is an abnormal sand mixer in any sand mixing unit, and obtain the first weight coefficient.

[0135] The information preprocessing unit is used to normalize the information of the sand mixer and the information of the sand mixing material;

[0136] The variability calculation unit is used to calculate the index variability of the sand mixer information and sand mixing material information after normalization, and obtain the sand mixing variability and material variability.

[0137] The conflict degree calculation unit is used to calculate the index conflict between the sand mixer information and the sand mixing material information after normalization, and obtain the sand mixing index conflict degree.

[0138] The weight calculation unit is used to calculate the weight coefficient of all sand mixers when any sand mixer in the sand mixing unit has an abnormal sand mixer. This is done by combining the first weight coefficient, sand mixing variability, material variability, and sand mixing index conflict degree, and using the sand mixer weight formula. The sand mixer weight formula is as follows:

[0139]

[0140] Where P(x) is the weighting coefficient of sand mixer x. Let be the sand mixing variability of sand mixer information i for sand mixer x. Let j be the material variability of the sand mixing material information of sand mixer x. λ represents the degree of conflict between the mixing parameters of mixing machine information i and mixing material information j for mixing machine x. x is the first weighting coefficient for sand mixer x.

[0141] In this embodiment, the abnormal weight allocation unit is used to allocate a first weight coefficient to the sand mixers. When there is an abnormal sand mixer in the sand mixing unit, the sand mixer numbers of all sand mixers are read, and it is analyzed whether the sand mixer number of each sand mixer is an abnormal sand mixer number. A weight is then allocated to each sand mixer. Specifically, each sand mixer is first assigned the same first primary weight. If the sand mixer number is an abnormal sand mixer number, a fixed weight is reduced based on the first primary weight to obtain the first weight coefficient. The fixed weight is set based on the highest electrical energy that all normal sand mixers in the sand mixing unit can carry. Specifically, the motor power, motor efficiency, rated load, and estimated running time of the sand mixers are obtained through the sand mixing information storage module and multiplied to obtain the highest electrical energy that all normal sand mixers in each sand mixing unit can carry. Then, the highest electrical energy is divided by the total electrical energy allocated to the sand mixing unit to obtain the energy coefficient. A fixed weight is set according to the magnitude of the energy coefficient, and the fixed weight must be less than or equal to the energy coefficient. This is because for a faulty or severely worn sand mixer, even allocating more electrical energy cannot improve its mixing efficiency. It may even cause the faulty mixer to overload, resulting in secondary damage. In severe cases, it may cause the motor windings to overheat, leading to motor burnout and even more serious consequences. Conversely, even a normal sand mixer should not be allocated too much electrical energy. If the allocated energy exceeds the maximum capacity of the mixer, it will also overload the normal mixer, reducing its service life.

[0142] The information preprocessing unit is used to normalize the information of the sand mixer and the sand mixing material. Methods such as min-max normalization, Z-score normalization, and function transformation can be used to normalize the information. Then, the variability calculation unit calculates the normalized sand mixing variability, material variability, and sand mixing index conflict degree. Combining the first weighting coefficient, sand mixing variability, material variability, and sand mixing index conflict degree, the weighting coefficients of all sand mixers are calculated. Sand mixing variability reflects the fluctuation of the sand mixer information. Taking the calculation of the sand mixing variability of rotation information as an example, the start of the sand mixer's operation is taken as the initial time node, and the start of the second energy distribution strategy is taken as the cutoff time node. The time period between the initial time node and the cutoff time node is taken as the trial operation period. First, the average rotation speed during the trial operation period is calculated based on the sand mixing rotation information. Then, the sand mixing variability of the rotation information is calculated using the variability calculation formula based on the average rotation speed. The variability calculation formula is as follows:

[0143]

[0144] in, Let k be the sand mixing variability of the sand mixing rotation information t in sand mixer x, M be the total number of sand mixing rotation information during the trial operation period, and k be the sand mixing rotation information t. tn For the nth sand mixing rotation information t during the trial operation period, k t This represents the average rotational speed.

[0145] The conflict degree calculation unit uses the index conflict calculation formula to calculate the index conflict between sand mixer information and sand mixing material information, and uses index conflict to measure the degree of correlation between sand mixer information and sand mixing material information. It can also use Pearson correlation coefficient, Spearman correlation coefficient, covariance analysis and regression analysis to calculate the index conflict between sand mixer information and sand mixing material information. The conflict index reflects the importance and relative influence of information by measuring the degree of correlation between information. For information that is relatively important and has a stronger relative influence, more weight needs to be assigned.

[0146]

[0147] Where, k i The value of i, representing the information of the sand mixer, during the trial operation period is k. i It is the average value of the mixed sand material information j during the trial operation period, k in This refers to the information of the sand mixer at the nth time node of the information i during the trial operation period, where k is the information of the sand mixer. jn It is the information of the mixed sand material at the nth time node of the mixed sand material information j during the trial operation period, H is the number of information groups composed of the sand mixer information and the mixed sand material information, and c is the cth information group.

[0148] After calculating the sand mixing variability, material variability, and sand mixing index conflict degree of each sand mixer, the first weight coefficient, sand mixing variability, material variability, and sand mixing index conflict degree are input into the sand mixer weight formula through the weight calculation unit to calculate the sand mixer weight coefficient of all sand mixers.

[0149] In one embodiment, the second sand mixing frequency converter control module further includes:

[0150] The progress upload submodule is used to upload the task progress of any sand mixing unit to the order management module when any sand mixing unit completes the sand mixing order task.

[0151] The dynamic adjustment submodule is used to continue to acquire the sand mixing sensor information of all sand mixers in the sand mixing unit when any sand mixing unit has not completed the sand mixing order task, and dynamically adjust the sand mixing energy of all sand mixers based on the sand mixing sensor information until all sand mixing units complete the sand mixing order task.

[0152] In this embodiment, the progress upload submodule is used to upload the order completion status of each sand mixing unit. When a sand mixing unit completes a sand mixing order, it can upload the order completion information to the order management module. Then, the order management module will automatically generate a sand mixing acceptance task. The sand mixing acceptance task includes the type of completed order, the sand mixing order deadline, and the total sand mixing order quantity. The order type includes information such as customer information, quality standards, and raw material types. After receiving the sand mixing acceptance task, the staff of the target factory will check whether the total sand mixing quantity is sufficient, whether the sand mixing meets the standards, and whether it is completed within the order deadline.

[0153] The dynamic adjustment submodule is used to continuously and dynamically adjust the mixing energy of all sand mixers. Specifically, when an abnormal change occurs inside a sand mixer, the second energy allocation module will immediately generate a third energy allocation strategy, a fourth energy allocation strategy, etc., for all sand mixers based on the changed mixing sensor information, until all sand mixers no longer exhibit abnormal changes or the sand mixers complete their mixing order tasks. Abnormal changes include sand mixer malfunctions, raw material temperatures exceeding preset thresholds, etc. This is because even a fault-free sand mixer, operating at high loads for extended periods, can lead to excessive friction of internal mechanical components, causing wear and shortening the mixer's lifespan. Therefore, once abnormal conditions such as abnormal temperature or vibration occur inside the sand mixer, energy needs to be reallocated to each mixer to ensure high-speed operation while extending its service life.

[0154] Finally, there is another scenario: if the abnormal sand mixing unit set contains one or more sand mixing units, and subsequent use of sand mixing machine sensor information fails to identify the abnormal sand mixing machine within the abnormal sand mixing unit set, it's possible that the total number of sand mixing orders for that sand mixing unit is low. Therefore, not all sand mixing machines in that sand mixing unit are operating, and thus, some idle sand mixing machines within that set may be abnormal. We can compare the group number corresponding to the abnormal sand mixing machine number with the group number of the sand mixing units in the abnormal sand mixing unit set to see if there are any matching numbers. If no matching group numbers exist, the idle sand mixing machines in the abnormal sand mixing unit set are identified, and their sand mixing machine numbers are obtained. A sand mixing machine maintenance task is generated based on the idle sand mixing machine's sand mixing machine number. Upon receiving the sand mixing machine maintenance task, maintenance personnel immediately perform maintenance on the corresponding sand mixing machine according to its sand mixing machine number and upload the maintenance results to the equipment management module.

[0155] This application also discloses a variable frequency control method for sand mixing in a sand mixer, applicable to a variable frequency control system for sand mixing in a sand mixer described in any of the above embodiments, with reference to... Figure 2 The method includes the following steps:

[0156] S101. Retrieve historical sand mixing information of all sand mixing units in the sand mixing information storage module, as well as sand mixing order information in the order management module. Historical sand mixing information includes historical sand mixing efficiency information and historical sand mixing energy consumption information.

[0157] In this embodiment, the sand mixing information storage module stores the average sand mixing efficiency information (i.e., historical sand mixing efficiency information) of each sand mixing unit over multiple sand mixing operations within a certain time period, and the average sand mixing energy consumption (i.e., historical sand mixing energy consumption information) of each sand mixing unit over multiple sand mixing operations within a certain time period. The sand mixing unit consists of multiple sand mixers of the same type that mix the same type of raw materials. The sand mixing order information includes the order type (e.g., resin sand, water glass sand, single sand, etc.), order time, and order quantity (e.g., resin sand: 100 tons, single sand: 500 tons). The sand mixing information storage module is mainly used to store the sand mixing quantity, sand mixing time, and power consumption for each sand mixing operation of each sand mixing unit. The sand mixing order information is used to store customer orders and order progress.

[0158] S102. Analyze the time-series variation characteristics of all sand mixing units based on historical sand mixing efficiency information, and divide all sand mixing units into a set of abnormal sand mixing units and a set of normal sand mixing units based on the time-series variation characteristics.

[0159] Based on historical sand mixing efficiency information, all sand mixing units are divided into sets of abnormal sand mixing units and sets of normal sand mixing units. First, the timestamps of the historical sand mixing efficiency information can be extracted and aligned. Then, the historical sand mixing efficiency information is sorted by time to obtain the historical efficiency time series of all sand mixing units. A time series is a sequence of values ​​for the same statistical indicator arranged in chronological order of their occurrence. The presence of outliers in the historical efficiency time series can be identified using methods such as control chart detection and Z-score outlier detection to analyze its variation characteristics. Alternatively, the variance or standard deviation of the historical efficiency time series can be calculated to reflect its variation characteristics. Furthermore, methods such as Fourier transform or wavelet transform can be used to convert the historical efficiency time series from the time domain to the frequency domain for variation characteristic analysis. Based on the temporal variation characteristics of historical efficiency time series, sand mixing units exhibiting significant efficiency fluctuations are classified into an abnormal sand mixing unit set, such as a sudden decrease in the average efficiency of a sand mixing unit at a certain time point. Sand mixing units with stable efficiency changes are classified into a normal sand mixing unit set, meaning sand mixing units whose average efficiency remains at a certain level with almost no significant changes are classified into the normal sand mixing unit set. This is because if a sand mixing unit experiences a significant decrease in average sand mixing efficiency, it indicates that there are sand mixers within that unit that have malfunctioned or are severely worn.

[0160] S103. Assign weights to the abnormal sand mixing unit set and the normal sand mixing unit set based on historical sand mixing efficiency information and sand mixing order information. Combine the weight allocation results and historical sand mixing energy consumption information to generate the first energy allocation strategy for all sand mixing units.

[0161] The first energy allocation strategy is the power allocation strategy for each sand mixing unit, encompassing the power that can be allocated to each unit and achieving overall power distribution for the sand mixing units. Power allocation needs to consider several factors. First, for sand mixing units that are highly likely to malfunction or experience severe wear, their power allocation ratio needs to be reduced, i.e., their weighting coefficient needs to be lowered. This is because even if more power is allocated to a malfunctioning or worn sand mixer, its sand mixing efficiency cannot be improved; it may even cause the malfunctioning mixer to overload, resulting in secondary damage. In severe cases, it may cause the motor windings to overheat, leading to motor burnout and even more serious consequences. Second, for sand mixing units with large order volumes and short deadlines, their weighting coefficient needs to be increased to improve the sand mixing efficiency of these units, enabling them to complete the order tasks within the specified time. Finally, the energy allocation needs to be based on historical sand mixing energy consumption information. This is because different sand mixers have different performance and therefore different loads. Blindly increasing the power of the sand mixer may lead to overload. Therefore, the final energy allocation strategy needs to be based on historical sand mixing energy consumption information and then adjusted according to the allocated weights.

[0162] S104. Based on the first energy allocation strategy, initially allocate sand mixing energy to the sand mixing unit, and control all sand mixing units that have completed energy allocation to execute sand mixing order tasks according to the sand mixing order information.

[0163] Select a suitable frequency converter based on the model of each sand mixing unit, such as a 200kW VM1000B frequency converter. Electrically connect the sand mixing machine motor to the frequency converter, and set the frequency converter parameters according to the model of the sand mixing machine motor, such as rated power, rated voltage, rated current, minimum operating frequency, and maximum operating frequency. To achieve simultaneous control of multiple sand mixing units, a PLC control system is used to control all sand mixing machines. The PLC control system receives the first energy allocation strategy from the first energy consumption allocation module through the input module. The central processing unit of the PLC control system performs logical processing and calculation on the first energy allocation strategy, and calculates the electrical energy required by each sand mixing unit using pre-set control logic and algorithms, thereby calculating the frequency value that needs to be adjusted. The PLC sends frequency control commands, start / stop commands, etc., to the frequency converters of the sand mixing units through the output module to guide the frequency converters to adjust the output frequency, thereby realizing the control of the electrical energy distribution and working status of the sand mixing machines, and controlling the sand mixing units to start the sand mixing operation according to the sand mixing order information using the allocated electrical energy. In addition, the sand mixing order includes the total amount of raw materials that the sand mixing unit needs to mix, and the sand mixing energy mainly includes the electricity required by the sand mixing machine.

[0164] S105. During the process of all sand mixing units performing sand mixing order tasks, the operating status of all sand mixing units is monitored by multiple types of sensors pre-deployed inside all sand mixing units to obtain sand mixing sensor information.

[0165] Multiple types of sensors, including temperature sensors, vibration sensors, pressure sensors, and current sensors, are used to monitor parameter changes in the sand mixer during the mixing process, enabling dynamic adjustment of the mixer's electrical energy based on these changes. This is because sand mixers experience temperature and pressure variations during operation, and these changes reflect the mixer's current operating status. For example, excessively high internal temperature indicates potential overload, requiring adjustment of the input electrical energy; excessively high pressure suggests potential material blockage, necessitating a reduction in energy output; and excessive vibration amplitude or abnormal vibration frequency indicates potential malfunction or wear. Therefore, precise adjustment of the input electrical energy to each sand mixer based on its temperature, vibration, and other characteristics is necessary to ensure optimal operation, thereby improving production efficiency, extending service life, and achieving the goals of increased production and energy savings.

[0166] S106. Generate a second energy distribution strategy for all sand mixers in each sand mixing unit based on the information from the sand mixing sensor.

[0167] The second energy allocation strategy is the power distribution strategy for the sand mixers in each sand mixing unit. It includes the power that each sand mixer can be allocated. Unlike the first energy allocation strategy, the second energy allocation strategy is dynamic. In addition to the first generated second energy allocation strategy, if there is a significant change in the sand mixing sensor information such as temperature, pressure, speed, and vibration inside a sand mixer, the second energy allocation module will immediately generate a third energy allocation strategy, a fourth energy allocation strategy, and so on for all sand mixers based on the changed sand mixing sensor information. Here, a significant change refers to any one of the information such as temperature, speed, pressure, vibration amplitude, and vibration frequency exceeding a preset threshold. For example, if the temperature of a sand mixer exceeds a preset temperature threshold (which could be 60 degrees Celsius), the second energy allocation module will immediately regenerate the third energy allocation strategy after detecting the abnormal temperature change. By dynamically adjusting the energy distribution strategy to precisely regulate the input power of each sand mixer, it is possible to ensure that each sand mixer is in its optimal operating state. Furthermore, since the second energy distribution strategy is based on the first, it avoids overload during the dynamic energy distribution process. This is because the first energy distribution strategy has already completed an overall energy distribution based on the historical energy consumption information of each sand mixer unit. Subsequently, the sand mixers within each unit undergo a second energy distribution based on the power allocated to that unit. Although the sand mixers within a unit are of the same type, their usage time and quality control vary, necessitating a second energy distribution for each group of sand mixers. This ensures that each group of sand mixers can maintain its optimal operating state to the greatest extent possible, improving production efficiency while reducing energy waste, thus achieving energy conservation and increased production.

[0168] S107. According to the second energy allocation strategy, dynamically allocate sand mixing energy to all sand mixers in each sand mixing unit, and control all sand mixers that have completed energy allocation to continue to execute sand mixing order tasks according to the sand mixing order information.

[0169] A PCL control system is used to achieve precise energy allocation for each sand mixer. The PCL control system receives the second energy allocation strategy from the second energy consumption allocation module through its input module. The central processing unit of the PCL control system performs logical processing and calculations on the second energy allocation strategy, using pre-set control logic and algorithms to calculate the electrical energy required by each sand mixer in different mixing units. This calculates the frequency value that needs to be adjusted, and the PLC sends corresponding frequency control commands to the frequency converters of each sand mixer in all mixing units through its output module. Upon receiving the frequency control command, the motor of each sand mixer adjusts its frequency accordingly. After the frequency adjustment is completed, the sand mixer continues to perform the sand mixing task. Subsequently, the information monitoring module, the second energy consumption allocation module, and the second sand mixing frequency converter control module continue to perform their respective tasks, dynamically adjusting the frequency of each sand mixer. Energy is dynamically allocated to each sand mixer until the sensor information of all sand mixers no longer changes significantly or all sand mixers have completed their sand mixing tasks.

[0170] This application also discloses a sand mixer frequency conversion control device, characterized in that it includes a sand mixer frequency conversion control system according to any one of the above claims.

[0171] The processor can be a central processing unit (CPU). Of course, depending on the actual use, it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc., and this application does not limit it in this regard.

[0172] The memory can be an internal storage unit of a computer device, such as a hard disk or RAM, or an external storage device, such as a plug-in hard disk, smart memory card (SMC), secure digital card (SD), or flash memory card (FC) provided on the computer device. Furthermore, the memory can be a combination of internal storage units and external storage devices of a computer device. The memory is used to store computer programs and other programs and data required by the computer device. The memory can also be used to temporarily store data that has been output or will be output. This application does not limit this.

[0173] This application also provides a machine-readable storage medium storing instructions for causing the machine to execute the above-described method for frequency conversion control of sand mixing in a sand mixer.

[0174] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0175] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0176] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0177] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0178] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0179] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0180] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0181] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0182] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A variable frequency control system for sand mixing in a sand mixer, characterized in that, The system includes a sand mixing control center and a sand mixing management center, which are communicatively connected. The sand mixing control center includes a sand mixing information storage module, and the sand mixing management center includes an order management module and an equipment management module. The sand mixing control center also includes: The information retrieval module is used to retrieve the historical sand mixing information of all sand mixing units in the sand mixing information storage module, as well as the sand mixing order information of the order management module. The historical sand mixing information includes historical sand mixing efficiency information and historical sand mixing energy consumption information. The sand mixing unit grouping module is used to analyze the time-series change characteristics of all the sand mixing units based on the historical sand mixing efficiency information, and to divide all the sand mixing units into an abnormal sand mixing unit set and a normal sand mixing unit set based on the time-series change characteristics. The first energy consumption allocation module is used to allocate weights to the abnormal sand mixing unit set and the normal sand mixing unit set according to the historical sand mixing efficiency information and the sand mixing order information, and generate a first energy allocation strategy for all the sand mixing units by combining the weight allocation results and the historical sand mixing energy consumption information. The first sand mixing frequency conversion control module is used to initially allocate sand mixing energy to the sand mixing unit according to the first energy allocation strategy, and control all the sand mixing units that have completed energy allocation to execute sand mixing order tasks according to the sand mixing order information. The information monitoring module is used to monitor the operating status of all the sand mixing units during the execution of the sand mixing order task by using multiple types of sensors pre-deployed inside all the sand mixing units, and to obtain sand mixing sensor information. The second energy consumption allocation module is used to generate a second energy allocation strategy for all the sand mixers in each sand mixing unit based on the sand mixing sensor information. The second sand mixing frequency conversion control module is used to dynamically allocate sand mixing energy to all the sand mixers in each sand mixing unit according to the second energy allocation strategy, and control all the sand mixers that have completed energy allocation to continue to execute the sand mixing order task according to the sand mixing order information.

2. The system according to claim 1, characterized in that, The sand mixing unit grouping module includes: The time-series sorting submodule is used to sort the historical sand mixing efficiency information of each of the sand mixing units in time sequence to obtain the historical efficiency time series of all the sand mixing units. The time series analysis submodule is used to fit the historical efficiency time series of each of the sand mixing units to obtain the time series variation characteristics of all the sand mixing units. The abnormal grouping submodule is used to assign the sand mixing unit corresponding to the historical efficiency time series to the abnormal sand mixing unit set when the time series change characteristics show that the historical efficiency time series is a fluctuating series. The normal grouping submodule is used to assign the sand mixing unit corresponding to the historical efficiency time series to the normal sand mixing unit set when the time series change characteristics show that the historical efficiency time series is a stationary series.

3. The system according to claim 1, characterized in that, The first energy consumption allocation module includes: The first weight allocation submodule is used to calculate the number of sand mixing units in the abnormal sand mixing unit set and the normal sand mixing unit set respectively, and to initially allocate weights to the abnormal sand mixing unit set and the normal sand mixing unit set according to the number of sand mixing units, so as to obtain the abnormal weight coefficient and the normal weight coefficient. The first information extraction submodule is used to extract the sand mixing order time limit and total sand mixing order quantity for each sand mixing unit from the sand mixing order information. The efficiency calculation submodule is used to calculate the expected sand mixing efficiency information of each sand mixing unit based on the sand mixing order time limit and the total sand mixing order quantity corresponding to each sand mixing unit; The second weight allocation submodule is used to combine the expected sand mixing efficiency information, the abnormal weight coefficient and the normal weight coefficient to perform weight allocation for all the sand mixing units, and obtain the sand mixing unit weight coefficient of all the sand mixing units. The first energy consumption allocation submodule is used to generate a first energy allocation strategy for all the sand mixing units based on the weight coefficients of all the sand mixing units and the historical sand mixing energy consumption information.

4. The system according to claim 3, characterized in that, The second weight allocation submodule includes: The difference calculation unit is used to calculate the efficiency difference between the expected sand mixing efficiency information and the historical sand mixing efficiency information when the expected sand mixing efficiency information is less than or equal to the historical sand mixing efficiency information. The first weight allocation unit is used to allocate weights to any sand mixing unit in the abnormal sand mixing unit set according to the efficiency difference and the abnormal weight coefficient, thereby obtaining the abnormal sand mixing unit set weight coefficient for all sand mixing units in the abnormal sand mixing unit set. The second weight allocation unit is used to allocate weights to any sand mixing unit in the set of normal sand mixing units according to the efficiency difference and the normal weight coefficient, so as to obtain the normal sand mixing unit set weight coefficient of all sand mixing units in the set of normal sand mixing units. The weighting integration unit is used to integrate the weighting coefficients of the abnormal sand mixing unit set and the weighting coefficients of the normal sand mixing unit set to obtain the sand mixing unit weighting coefficients of all the sand mixing units.

5. The system according to claim 1, characterized in that, The second energy consumption allocation module includes: The second information extraction submodule is used to extract the sand mixer information and sand mixing material information from the sand mixing sensor information of all the sand mixers in each of the sand mixing units. The anomaly marking submodule is used to mark abnormal sand mixers based on the analysis of the change characteristics of the sand mixer information of all the sand mixing units, and upload the sand mixer number corresponding to the abnormal sand mixer to the equipment management module. The third weight allocation submodule is used to, when there is an abnormal sand mixer in any of the sand mixing units, combine the sand mixer information, the sand mixing material information and the sand mixer number to allocate weight coefficients to all the sand mixers, and obtain the sand mixer weight coefficients for all the sand mixers. The fourth weight allocation submodule is used to allocate weight coefficients to all sand mixers by combining the sand mixer information and the sand mixing material information when there are no abnormal sand mixers in all the sand mixing units, so as to obtain the sand mixer weight coefficients of all the sand mixers. The second energy consumption allocation submodule is used to generate a second energy allocation strategy for all the sand mixers based on the weight coefficient of the sand mixer.

6. The system according to claim 5, characterized in that, The anomaly marking submodule includes: The information extraction unit is used to extract the sand mixing vibration information and sand mixing current information from the sand mixing machine information corresponding to any sand mixer in any of the sand mixing units. An abnormality marking unit is used to extract the vibration change characteristics of the sand mixing vibration information and the current amplitude characteristics of the sand mixing current information. When the vibration change characteristics are abnormal or the current amplitude characteristics are abnormal, the sand mixer is marked as an abnormal sand mixer. The abnormal upload unit is used to read the sand mixer number of the abnormal sand mixer, mark the sand mixer number as the abnormal sand mixer number, and upload the abnormal sand mixer number to the equipment management module.

7. The system according to claim 5, characterized in that, The third weight allocation submodule includes: An abnormal weight allocation unit is used to initially allocate weights to all the sand mixers in the sand mixing unit according to the sand mixer number of the sand mixer when there is an abnormal sand mixer in any of the sand mixing units, and obtain a first weight coefficient. An information preprocessing unit is used to normalize the information of the sand mixer and the information of the sand mixing material. The variability calculation unit is used to calculate the index variability of the sand mixer information and sand mixing material information after normalization processing, and obtain the sand mixing variability and material variability. The conflict degree calculation unit is used to calculate the index conflict between the sand mixer information and the sand mixing material information after normalization, and obtain the sand mixing index conflict degree. The weight calculation unit is used to calculate the weight coefficient of all the sand mixers when any of the sand mixing units has an abnormal sand mixer, by combining the first weight coefficient, sand mixing variability, material variability, and sand mixing index conflict degree, and using the sand mixer weight formula. The sand mixer weight formula is as follows: Where P(x) is the weighting coefficient of sand mixer x. Let be the sand mixing variability of sand mixer information i for sand mixer x. Let j be the material variability of the sand mixing material information of sand mixer x. λ represents the degree of conflict between the mixing parameters of mixing machine information i and mixing material information j for mixing machine x. x is the first weighting coefficient for sand mixer x.

8. The system according to claim 1, characterized in that, The second sand mixing frequency conversion control module also includes: The progress upload submodule is used to upload the task progress of any of the sand mixing units to the order management module when any of the sand mixing units completes the sand mixing order task. The dynamic adjustment submodule is used to continue to acquire the sand mixing sensor information of all the sand mixers in the sand mixing unit when any of the sand mixing units has not completed the sand mixing order task, and dynamically adjust the sand mixing energy of all the sand mixers based on the sand mixing sensor information until all the sand mixing units complete the sand mixing order task.

9. A frequency conversion control method for sand mixing in a sand mixer, characterized in that, The method, applied to a sand mixer frequency conversion control system according to any one of claims 1 to 8, comprises the following steps: Retrieve historical sand mixing information of all sand mixing units in the sand mixing information storage module, as well as sand mixing order information in the order management module. The historical sand mixing information includes historical sand mixing efficiency information and historical sand mixing energy consumption information. Based on the historical sand mixing efficiency information, the time-series variation characteristics of all the sand mixing units are analyzed, and based on the time-series variation characteristics, all the sand mixing units are divided into an abnormal sand mixing unit set and a normal sand mixing unit set. Based on the historical sand mixing efficiency information and the sand mixing order information, weights are assigned to the abnormal sand mixing unit set and the normal sand mixing unit set. Combining the weight assignment results and the historical sand mixing energy consumption information, a first energy allocation strategy is generated for all the sand mixing units. According to the first energy allocation strategy, the sand mixing unit is initially allocated sand mixing energy, and all the sand mixing units that have completed energy allocation are controlled to execute sand mixing order tasks according to the sand mixing order information; During the process of all the sand mixing units executing the sand mixing order task, the operating status of all the sand mixing units is monitored by multiple types of sensors pre-arranged inside all the sand mixing units, and sand mixing sensor information is obtained. A second energy allocation strategy is generated for all the sand mixers in each sand mixing unit based on the sand mixing sensor information. According to the second energy allocation strategy, the mixing energy is dynamically allocated to all the mixing machines in each mixing unit, and all the mixing machines that have completed the energy allocation are controlled to continue to execute the mixing order task according to the mixing order information.

10. A frequency conversion control device for sand mixing in a sand mixer, characterized in that, Including a sand mixing frequency conversion control system for a sand mixer according to any one of claims 1 to 8.

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