Intelligent control management system for energy-saving and environment-friendly materials

Abstract

The invention discloses an intelligent control management system for energy-saving and environment-friendly materials, and the system comprises a determination unit which is used for obtaining a production order, and determining a production link based on the production order; the matching unit is used for searching for existing equipment in the factory and obtaining production equipment after the existing equipment is matched with the production link; the generation unit is used for randomly selecting one of the production devices in each production link and connecting the production devices according to the production sequence to generate a plurality of production links; the screening unit is used for screening the production links based on the lowest energy consumption by adopting a sparrow search algorithm, and obtaining an optimal production link; the control unit is used for selecting production equipment for control according to the optimal production link; after the production devices matched with the production links meeting the production order are connected according to the production sequence, the multiple production links are obtained, the optimal production link can be screened from the multiple production links through the sparrow search algorithm, and when production is conducted based on the optimal production link, energy consumption can be reduced to the maximum extent, and the machining cost of a factory can be reduced.

Description

Technical Field

[0001] The present invention relates to the field of stone crushing technology, and in particular to an intelligent control and management system for energy-saving and environmentally friendly materials. Background Art

[0002] In today's society, with the large-scale development of infrastructure construction and the vigorous development of the construction industry, the demand for stone as a basic and important building material has shown a trend of continuous growth. Whether it is roadbed paving, aggregate supply in road projects, or concrete structure construction in various construction projects, they all rely on the support of a large amount of high-quality stone. The entire process of stone from mining to processing and use covers multiple links. In each link, a variety of different types of production equipment will be used, and based on different production requirements, the production equipment used will also be different. In the production process, it is necessary to control and manage the production equipment in each production link. On the one hand, it can avoid damage caused by excessive operation of the production equipment, and on the other hand, it can improve processing efficiency and reduce costs. However, at present, the control and management of production equipment in the stone production process is mostly based on the experience of the staff, and only the same link or even the same type of production equipment is regulated, and the production equipment is not combined and controlled with reference to the entire production link, resulting in increased energy consumption and increased production costs due to the selected production equipment combination. Summary of the invention

[0003] In view of this, the present invention proposes an intelligent control and management system for energy-saving and environmentally friendly materials, which can obtain the optimal production link. When the production equipment is controlled based on the optimal production link for production, energy consumption can be greatly reduced.

[0004] The technical solution of the present invention is achieved in this way:

[0005] An intelligent control and management system for energy-saving and environmentally friendly materials, comprising:

[0006] The determination unit is used to obtain the production order and determine the production link based on the production order;

[0007] The matching unit is used to find the existing equipment in the factory and obtain the production equipment after matching it with the production link;

[0008] A generation unit, used for randomly selecting one of each type of production equipment in each production link, and connecting and generating a plurality of production links according to the production sequence;

[0009] A screening unit, used for screening production links based on the lowest energy consumption by using a sparrow search algorithm, and obtaining an optimal production link;

[0010] A control unit, used to select production equipment for control according to the optimal production link;

[0011] The determination unit, matching unit, generation unit, screening unit and control unit are sequentially data-connected.

[0012] Preferably, the production process includes raw material preparation process, crushing process, screening process, mixing process, shaping process and storage process, and the raw material preparation process, crushing process, screening process, mixing process, shaping process and storage process each include several sub-processes.

[0013] Preferably, the execution steps of the determining unit include:

[0014] Step S11, obtaining a production order, and extracting the specific specifications, quantity, delivery time and delivery location of the required stones from the production order;

[0015] Step S12, standardizing the specific specifications of the required stones;

[0016] Step S13: input the standardized specific specifications, quantity, delivery time and delivery location into the trained neural network, and obtain the production links through neural network processing.

[0017] Preferably, the training steps of the neural network in step S13 are: obtaining historical production orders and corresponding production links, and taking the historical production orders and their corresponding production links as a set of data, dividing multiple sets of data into training sets and test sets, training the neural network through the training set, and using the test set to test the accuracy of the neural network.

[0018] Preferably, the execution steps of the matching unit include:

[0019] Step S21, query the factory's equipment ledger, and obtain the types and quantities of the factory's existing equipment from the equipment ledger;

[0020] Step S22: Obtain the work log of the existing equipment, perform performance evaluation on the existing equipment based on the technical parameters, production capacity, operation efficiency, and product quality stability in the work log, and eliminate the existing equipment that does not meet the performance standards;

[0021] Step S23: compare the process requirements of each production link with the existing equipment one by one, and match the production equipment corresponding to each production link.

[0022] Preferably, it also includes:

[0023] A power supply mode determination unit, used to determine the photovoltaic power generation equipment in the factory and confirm the production equipment driven by the photovoltaic power generation equipment;

[0024] The power supply mode determination unit is data-connected with the matching unit and the generation unit respectively.

[0025] Preferably, it also includes:

[0026] A distance calculation unit is used to calculate the distance between two production equipments in adjacent production links;

[0027] The distance calculation unit is data-connected with the matching unit and the generation unit respectively.

[0028] Preferably, the execution steps of the generating unit include:

[0029] Step S31, marking the production equipment driven by the photovoltaic power generation equipment among the production equipment;

[0030] Step S32, randomly selecting one of each production equipment in each production link;

[0031] Step S33: connecting the production equipment into a production chain according to the production sequence, and adjusting the length of the production chain according to the distance between the production equipment;

[0032] Step S34: Repeat steps S32-S33 to obtain several production links.

[0033] Preferably, the execution steps of the screening unit include:

[0034] Step S41, initialize the sparrow population, and determine the number of iterations as the number of production links;

[0035] Step S42: randomly select a production link and calculate the fitness value of the sparrow based on the minimum energy consumption;

[0036] Step S43, selecting another production link, calculating the fitness value and comparing it with the fitness value calculated last time, and retaining the production link with the larger fitness value;

[0037] Step S44: perform iterative calculation and output the production link with the largest fitness value as the optimal production link.

[0038] Preferably, the execution step of the screening unit further includes:

[0039] Step S45: Evaluate whether the optimal production link meets the time limit requirements of the production order. If not, eliminate the optimal production link and re-execute steps S41-S44.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] ① Production orders can be obtained by determining the unit, and then the production links for stone processing can be determined based on the production orders. The production equipment can be determined from the existing equipment in the factory based on the production links. The production of stone can be achieved by making different combinations of production equipment, and the production equipment that meets the requirements in the factory can be quickly obtained;

[0042] ②The link formed by the combination of production equipment is the production link. There are many production links. The sparrow search algorithm can be used to screen the production links and obtain the optimal production link. When the production equipment is controlled based on the optimal production link to produce stone, energy consumption can be greatly reduced and the processing cost of the factory can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 This is a schematic diagram of an energy-saving and environmentally friendly material intelligent control and management system of the present invention;

[0045] Figure 2 A diagram of the execution steps of a determination unit of an energy-saving and environmentally friendly material intelligent control and management system of the present invention;

[0046] Figure 3 This is a diagram of the execution steps of a matching unit of an energy-saving and environmentally friendly material intelligent control and management system of the present invention;

[0047] Figure 4 This is a diagram of the execution steps of a generation unit of an energy-saving and environmentally friendly material intelligent control and management system of the present invention;

[0048] Figure 5 A diagram showing the execution steps of a screening unit of an intelligent control and management system for energy-saving and environmentally friendly materials according to the present invention;

[0049] In the figure, 1. determination unit; 2. matching unit; 3. generation unit; 4. screening unit; 5. control unit; 6. power supply mode determination unit; 7. distance calculation unit. DETAILED DESCRIPTION

[0050] In order to better understand the technical content of the present invention, a specific embodiment is provided below, and the present invention is further described in conjunction with the accompanying drawings.

[0051] See also Figures 1 to 5 The present invention provides an energy-saving and environmentally friendly material intelligent control and management system, comprising:

[0052] Determining unit 1, used for obtaining a production order and determining a production link based on the production order;

[0053] Matching unit 2, used to find the existing equipment in the factory and obtain the production equipment after matching it with the production link;

[0054] A generating unit 3 is used to randomly select one of each type of production equipment in each production link, and connect and generate a plurality of production links according to the production sequence;

[0055] The screening unit 4 is used to screen the production links based on the lowest energy consumption by using the sparrow search algorithm, and obtain the optimal production link;

[0056] Control unit 5, used to select production equipment for control according to the optimal production link;

[0057] The determination unit 1, the matching unit 2, the generation unit 3, the screening unit 4 and the control unit 5 are sequentially data-connected.

[0058] An energy-saving and environmentally friendly material intelligent control and management system of the present invention is used to control the stone production process, wherein after receiving the production order, the factory analyzes the production order to determine the specific production and processing method of the stone, and then can determine the production link according to the specific production method, the production link includes raw material preparation link, crushing and processing link, screening link, mixing link, shaping link and storage link, and the raw material preparation link, crushing and processing link, screening link, mixing link, shaping link and storage link all include several sub-links, for example, the raw material preparation link includes mining, primary screening and transportation and other sub-links, the crushing and processing link includes loading and unloading, primary crushing, intermediate crushing, fine crushing and sand making and other sub-links, different sub-links correspond to different production equipment, after determining the production link to which it belongs, the matching unit 2 will search for existing equipment in the factory, not all of these existing equipment are used for production or meet the requirements of this production, so it is necessary to match the existing equipment to the equipment corresponding to the production link Adaptable equipment, the matched equipment is the production equipment, the production equipment is all the available equipment that can complete this production order, and each sub-link in each production link will have multiple equipment, and the number of each type of equipment is plural, so the production equipment in different sub-links can be combined to complete the production task, and after randomly selecting each production equipment in each sub-link, the production equipment is connected in accordance with the production sequence to form multiple production links, each production link can meet the requirements of the production order, but different production links have different energy consumption due to power consumption and equipment status issues, so the screening unit 4 can use the sparrow search algorithm to screen the production links, the screening goal is to minimize energy consumption, and finally the optimal production link can be obtained, the control unit 5 can extract the production equipment from the optimal production link, and drive the production equipment to operate to realize the production operation of stone, the selected production equipment consumes the least energy to complete the production task, and can reduce the processing cost of the factory.

[0059] Preferably, the execution steps of the determining unit 1 include:

[0060] Step S11, obtaining a production order, and extracting the specific specifications, quantity, delivery time and delivery location of the required stones from the production order;

[0061] Step S12, standardizing the specific specifications of the required stones;

[0062] Step S13: input the standardized specific specifications, quantity, delivery time and delivery location into the trained neural network, and obtain the production links through neural network processing.

[0063] The production order contains production requirements, including specific production specifications, quantity, delivery time and delivery location, etc. Different specifications and production requirements use different production links, and the specific specifications may vary in each production order. Therefore, after the specific specifications are standardized, the production requirements are input into the neural network, and the neural network processes them to obtain the production links.

[0064] Preferably, the training steps of the neural network in step S13 are: obtaining historical production orders and corresponding production links, and taking the historical production orders and their corresponding production links as a set of data, dividing multiple sets of data into training sets and test sets, training the neural network through the training set, and using the test set to test the accuracy of the neural network.

[0065] A neural network is a self-learning network that can achieve a certain purpose through training with a large amount of data. The factory can collect numerous past stone production order cases and the corresponding actual production links, and simultaneously extract the production equipment corresponding to the actual production links. The production links and production equipment are taken as a set of data, and the multiple sets of data obtained are allocated into training sets and test sets in a ratio of 7:3. The training set is used to train the neural network, and the test set can be used to test the neural network. After the test accuracy reaches the preset threshold, the training can be stopped and put into use.

[0066] Preferably, the execution steps of the matching unit 2 include:

[0067] Step S21, query the factory's equipment ledger, and obtain the types and quantities of the factory's existing equipment from the equipment ledger;

[0068] Step S22: Obtain the work log of the existing equipment, perform performance evaluation on the existing equipment based on the technical parameters, production capacity, operation efficiency, and product quality stability in the work log, and eliminate the existing equipment that does not meet the performance standards;

[0069] Step S23: compare the process requirements of each production link with the existing equipment one by one, and match the production equipment corresponding to each production link.

[0070] Check the factory's equipment management ledger to obtain detailed equipment information, including equipment name, model, specifications, purchase time, usage status, maintenance records, etc. Through the equipment ledger, you can quickly understand the types and quantities of the factory's existing production equipment, as well as the basic conditions of each equipment. At the same time, you can obtain the historical working conditions of the existing equipment from the work logs of the existing equipment. Based on the historical working conditions and some parameter data, perform performance evaluation on the existing equipment to determine whether each device can meet the needs of the current production link. For equipment that does not meet the performance standards, it can be directly eliminated in this task and not considered for use. After obtaining all available existing equipment, compare them one by one with the production links to match the production equipment of the corresponding production links.

[0071] Preferably, it also includes:

[0072] A power supply mode determination unit 6, used to determine the photovoltaic power generation equipment in the factory and confirm the production equipment driven by the photovoltaic power generation equipment;

[0073] The power supply mode determination unit 6 is data-connected with the matching unit 2 and the generation unit 3 respectively.

[0074] During the processing in the factory, some production equipment will be driven by electric energy, such as some crushing and vibration screening equipment. In order to further reduce energy consumption, photovoltaic panels will be installed in the factory to generate electricity. The electric energy converted by the photovoltaic panels will be transmitted to the production equipment for use. When calculating the energy consumption later, it is necessary to take this part of the production equipment powered by photovoltaic power generation into account. Therefore, the power supply mode determination unit 6 can determine the production equipment driven by the photovoltaic power generation equipment, mark the production equipment and transmit it to the generation unit 3.

[0075] Preferably, it also includes:

[0076] A distance calculation unit 7, used to calculate the distance between two production equipments in adjacent production links;

[0077] The distance calculation unit 7 is data-connected with the matching unit 2 and the generation unit 3 respectively.

[0078] There may be a certain distance between the production equipment in different production links, and the transportation process will also generate certain power consumption. At the same time, the transportation process between raw materials will also produce certain functions. Therefore, after calculating the distance between two production equipment in adjacent production links, they can be added to the production chain accordingly, so as to consider the distance problem when calculating energy consumption.

[0079] Preferably, the execution steps of the generating unit 3 include:

[0080] Step S31, marking the production equipment driven by the photovoltaic power generation equipment among the production equipment;

[0081] Step S32, randomly selecting one of each production equipment in each production link;

[0082] Step S33: connecting the production equipment into a production chain according to the production sequence, and adjusting the length of the production chain according to the distance between the production equipment;

[0083] Step S34: Repeat steps S32-S33 to obtain several production links.

[0084] After the generation unit 3 receives the data transmitted by the power supply mode determination unit 6, it marks the production equipment driven by the photovoltaic power generation equipment, and then randomly selects one of each production equipment in each production link, and connects them according to the production order of the stone, so as to form a production chain. The path between every two production equipment represents their distance. According to the data transmitted by the distance calculation unit 7, the length of the path between the production equipment can be adjusted. The final production chain can represent the sequential connection relationship between production equipment at different distances, and also includes production equipment driven by photovoltaic power generation equipment. After repeated processing based on the above steps, several production chains can be obtained. Each production chain can meet the needs of the production order, but the total power consumption of its production process will be different.

[0085] Preferably, the execution steps of the screening unit 4 include:

[0086] Step S41, initialize the sparrow population, and determine the number of iterations as the number of production links;

[0087] Step S42: randomly select a production link and calculate the fitness value of the sparrow based on the minimum energy consumption;

[0088] Step S43, selecting another production link, calculating the fitness value and comparing it with the fitness value calculated last time, and retaining the production link with the larger fitness value;

[0089] Step S44: perform iterative calculations and output the production link with the largest fitness value as the optimal production link;

[0090] Step S45: Evaluate whether the optimal production link meets the time limit requirements of the production order. If not, eliminate the optimal production link and re-execute steps S41-S44.

[0091] The sparrow search algorithm is used to screen all production links, and the fitness value of each production link is calculated. The calculation basis is the lowest energy consumption. After obtaining the fitness value, it is compared with the previous calculation. After multiple comparisons, the production link with the largest fitness value can be obtained and output as the optimal production link. When the stone is produced according to the production equipment in the optimal production link, the energy consumed is the lowest, which can minimize the production cost of the factory. After obtaining the optimal production link, it is necessary to determine whether the optimal production link can meet the time limit requirements of the production order under the production mode with the lowest energy consumption. If not, it is necessary to re-screen the optimal production link. At this time, the optimal production link obtained last time is eliminated, and the iterative calculation is performed again until the optimal production link meets the time limit requirements.

[0092] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent control and management system for energy-saving and environmentally friendly materials, characterized in that: include: The determination unit is used to obtain the production order and determine the production link based on the production order; The matching unit is used to find the existing equipment in the factory and obtain the production equipment after matching it with the production link; A generation unit, used for randomly selecting one of each type of production equipment in each production link, and connecting and generating a plurality of production links according to the production sequence; A screening unit, used for screening production links based on the lowest energy consumption by using a sparrow search algorithm, and obtaining an optimal production link; A control unit, used to select production equipment for control according to the optimal production link; The determination unit, matching unit, generation unit, screening unit and control unit are sequentially data-connected.

2. The energy-saving and environmentally friendly material intelligent control and management system according to claim 1 is characterized in that: The production process includes raw material preparation process, crushing process, screening process, mixing process, shaping process and storage process, and the raw material preparation process, crushing process, screening process, mixing process, shaping process and storage process each include several sub-processes.

3. The intelligent control and management system for energy-saving and environmentally friendly materials according to claim 1 is characterized in that: The execution steps of the determining unit include: Step S11, obtaining a production order, and extracting the specific specifications, quantity, delivery time and delivery location of the required stones from the production order; Step S12, standardizing the specific specifications of the required stones; Step S13: input the standardized specific specifications, quantity, delivery time and delivery location into the trained neural network, and obtain the production links through neural network processing.

4. The intelligent control and management system for energy-saving and environmentally friendly materials according to claim 3 is characterized in that: The training steps of the neural network in step S13 are: obtaining historical production orders and corresponding production links, and taking the historical production orders and their corresponding production links as a group of data, dividing multiple groups of data into training sets and test sets, training the neural network through the training set, and using the test set to test the accuracy of the neural network.

5. The energy-saving and environmentally friendly material intelligent control and management system according to claim 1 is characterized in that: The execution steps of the matching unit include: Step S21, query the factory's equipment ledger, and obtain the types and quantities of the factory's existing equipment from the equipment ledger; Step S22: Obtain the work log of the existing equipment, perform performance evaluation on the existing equipment based on the technical parameters, production capacity, operation efficiency, and product quality stability in the work log, and eliminate the existing equipment that does not meet the performance standards; Step S23: compare the process requirements of each production link with the existing equipment one by one, and match the production equipment corresponding to each production link.

6. The energy-saving and environmentally friendly material intelligent control and management system according to claim 1 is characterized in that: Also includes: A power supply mode determination unit, used to determine the photovoltaic power generation equipment in the factory and confirm the production equipment driven by the photovoltaic power generation equipment; The power supply mode determination unit is data-connected with the matching unit and the generation unit respectively.

7. The energy-saving and environmentally friendly material intelligent control and management system according to claim 6 is characterized in that: Also includes: A distance calculation unit is used to calculate the distance between two production equipments in adjacent production links; The distance calculation unit is data-connected with the matching unit and the generation unit respectively.

8. The energy-saving and environmentally friendly material intelligent control and management system according to claim 7 is characterized in that: The execution steps of the generating unit include: Step S31, marking the production equipment driven by the photovoltaic power generation equipment among the production equipment; Step S32, randomly selecting one of each production equipment in each production link; Step S33: connecting the production equipment into a production chain according to the production sequence, and adjusting the length of the production chain according to the distance between the production equipment; Step S34: Repeat steps S32-S33 to obtain several production links.

9. The intelligent control and management system for energy-saving and environmentally friendly materials according to claim 1 is characterized in that: The execution steps of the screening unit include: Step S41, initialize the sparrow population, and determine the number of iterations as the number of production links; Step S42: randomly select a production link and calculate the fitness value of the sparrow based on the minimum energy consumption; Step S43, selecting another production link, calculating the fitness value and comparing it with the fitness value calculated last time, and retaining the production link with the larger fitness value; Step S44: perform iterative calculation and output the production link with the largest fitness value as the optimal production link.

10. The intelligent control and management system for energy-saving and environmentally friendly materials according to claim 1 is characterized in that: The execution step of the screening unit also includes: Step S45: Evaluate whether the optimal production link meets the time limit requirements of the production order. If not, eliminate the optimal production link and re-execute steps S41-S44.

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