An automatic control system for deep processing of steelmaking OG mud
By adopting an automated control system in the steelmaking OG mud deep processing system, collecting and analyzing silo and equipment parameters, building optimization models, realizing automatic batching and equipment adjustment, the problem of waste of energy during shutdown and poor timeliness of manual adjustments is solved, and production is improved Efficiency and energy utilization.
Patent Information
- Application Number
- CN202410066986.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-01-17
- Publication Date
- 2025-01-03
- Estimated Expiration
- 2044-01-17
AI Technical Summary
The problem of poor timeliness of energy waste and manual adjustments in the existing steelmaking OG mud deep processing automatic control system has led to energy waste and low production efficiency.
An automatic control system including silo unit, silo monitoring module, equipment monitoring module, batching control module and processing equipment regulation module was designed. By collecting multi-dimensional silo and equipment parameters, a batching optimization model is constructed and execution parameters are generated. , realize automated batching and equipment regulation, and reduce downtime and energy waste.
By reducing downtime and optimizing production efficiency, energy savings in deep processing of steelmaking OG mud are achieved, production automation and efficiency are improved, and time and energy consumption are reduced for manual adjustments.
Smart Images
Figure CN117991692B_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the field of energy-saving steelmaking generation, and in particular to an automatic control system for deep processing of steelmaking OG mud. Background Art
[0002] The sludge produced by the wet recovery system of steelmaking converter gas is called OG sludge, which is a major steel waste. OG sludge has a high iron content, fine particle size, high viscosity, and relatively low impurity content. It is a usable secondary resource.
[0003] Steelmaking is a high-temperature, high-pressure process that produces a large amount of smoke and exhaust gas. In order to reduce pollution to the environment, dust removal is required. Electrostatic precipitators or bag filters are generally used to remove dust in steelmaking. These devices can filter out particulate matter in the exhaust gas and convert it into dust particles. These dusts are dust ash. The main components of dust ash include iron oxide, silicate, carbon black and other impurities. Iron oxide is the most important component, and its content can reach more than half of the total weight of dust ash.
[0004] It is feasible to recycle iron-containing dust and mud as sintering raw materials. According to the different characteristics of dust and mud, sintering batching, material field mixing, mud spraying and rotary hearth furnace technology are used to treat them. Multiple methods are used simultaneously to resolve the difficulty of treatment and achieve the purpose of energy saving, emission reduction and comprehensive utilization of resources.
[0005] The OG mud from the steelmaking process that has been filtered by pressure is transported to the drying site in the pelletizing plant for drying until the moisture content is less than 15%. After mixing, it is dehydrated by drum drying and dried to a moisture content of less than 5%. The secondary dust removal ash from steelmaking is transported to the dust sludge cold briquetting raw material area by closed tank trucks and transported to the raw material warehouse by air pumps. The rolled iron oxide scale and coarse particles are transported to the silo in the cold briquetting raw material area by dump trucks. The dried OG mud and steelmaking dust removal ash, rolled iron oxide scale and coarse particles are weighed and mixed by spiral weighing machines in a certain proportion, and then enter the wheel roller to be compacted and mixed with the binder, and then enter the compactor for further compaction. Finally, it is briquetted and screened by a double-roller briquetting machine to obtain qualified pellets. The screened powder is returned to the buffer silo and pressed again. The qualified pellets enter the dryer for drying. When the moisture content of the raw balls is reduced to less than 2%, they are finished products, and then they are transported to the finished product yard by belt conveyors and sent to the steelmaking furnace charge area by cars as needed.
[0006] The binder is prepared and added by a special binder system. Except for the stacking of finished balls, drying of raw materials and entering the silo, which require manual intervention, the rest of the cold briquetting system, from iron-containing dust ash batching to mixing, ball pressing and drying, is all automatically controlled. In normal production, only equipment monitoring is required.
[0007] However, in current production, the drying step is the main power-consuming unit. It is undoubtedly a waste of energy to directly adjust the opening and closing of the equipment according to the fluctuation of raw material reserves. Each time the drying equipment is opened and closed, a large amount of energy is consumed for preheating, which will waste a lot of electricity and its own original heat energy. In addition, the cooling of the equipment after shutdown will cause the materials attached to the surface to cool down, and additional cleaning steps are required. Shutdown without maintenance is a huge waste, and manual adjustment requires manual judgment of the warehouse data, and the calculation and judgment take time, and the timeliness is poor. Summary of the invention
[0008] The present application provides an automatic control system for deep processing of steelmaking OG mud, which is used to solve the technical problems of energy waste due to shutdown and poor timeliness of manual adjustment in the existing automatic control system for deep processing of steelmaking OG mud.
[0009] In view of the above problems, the present application provides an automatic control system for deep processing of steelmaking OG mud, including a silo unit for storing different materials; a silo monitoring module for collecting multi-dimensional silo parameters inside each silo to obtain a silo monitoring parameter set; an equipment monitoring module for collecting multi-dimensional operating parameters of each processing equipment to obtain an equipment monitoring parameter set; a batching control module for constructing a batching optimization model based on the silo monitoring parameter set and the equipment monitoring parameter set, and generating batching optimization execution parameters and equipment adjustment parameters; a processing equipment control module for receiving the batching optimization execution parameters and the equipment adjustment parameters, and adjusting the batching of the silo unit according to the batching optimization execution parameters, and adjusting the processing efficiency of the processing equipment according to the equipment adjustment parameters.
[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:
[0011] The embodiment of the present application monitors the silo to understand the remaining amount of the silo, and understands the current production capacity based on equipment monitoring, builds an ingredient optimization model based on the silo monitoring parameter set and the equipment monitoring parameter set, generates ingredient optimization execution parameters and equipment adjustment parameters, and adjusts the ingredients of the silo unit based on the ingredient optimization execution parameters, and adjusts the processing efficiency of the processing equipment based on the equipment adjustment parameters, thereby reducing downtime and achieving energy saving of drying equipment by slowing down production efficiency.
[0012] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS
[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0014] Figure 1 Schematic diagram of the system equipment provided for this application. DETAILED DESCRIPTION
[0015] The present application provides an automatic control system for deep processing of steelmaking OG mud, which is used to solve the technical problem of low efficiency caused by arranging detection and stage adjustment in the existing recycled water quality regulation link.
[0016] After introducing the basic principles of the present application, the technical solutions in the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described here. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.
[0017] Embodiment 1
[0018] like Figure 1 As shown, the present application provides an automatic control system for deep processing of steelmaking OG mud, including:
[0019] Silo units for storing different materials.
[0020] The deep processing of steelmaking OG mud requires a variety of materials. According to the production capacity, the equipment continuously transports the materials in the silo to the processing equipment for deep processing and production. The silo unit can be centrally set up at a convenient unloading location according to site requirements, or set up near the processing equipment with unloading and conveying devices for transportation.
[0021] The silo unit includes: an OG mud silo for storing OG mud balls; a steelmaking dust ash gas tank for storing steelmaking dust ash; a steel rolling iron oxide silo for storing steel rolling iron oxide powder; a coarse particle silo for storing coarse particles; an adhesive batcher for storing adhesive and adding adhesive according to the batching control module.
[0022] The silo unit is equipped with different feeding and discharging equipment according to the materials stored inside it, and the materials are output according to the requirements of the batching control module. For example, due to the presence of a certain amount of water in the OG mud ball, the gravity discharge hopper is prone to clogging. A bolt feeding device should be used, and a scraping device in the silo should be used to avoid clogging. For another example, the dust removal ash is a dust material, and the feeding and discharging materials can be directly transported to the processing equipment by a pressure pipe for mixing and batching.
[0023] The silo monitoring module is used to collect multi-dimensional silo parameters inside each silo and obtain a silo monitoring parameter set.
[0024] Continuous monitoring of the silo can help us understand the current material reserve status. Continuous monitoring can accurately obtain the material change curve during the recording period and calculate the change law based on the repeatability of the material change curve, thereby providing parameters for subsequent capacity adjustment forecasts.
[0025] The silo monitoring module includes: an OG mud silo material detection component, which is used to collect the OG mud ball material parameters inside the OG mud silo to obtain an OG mud ball material parameter set; a steelmaking dust removal ash gas tank detection component, which is used to collect the steelmaking dust removal ash parameters inside the steelmaking dust removal ash gas tank to obtain a steelmaking dust removal ash parameter set; a steel rolling iron oxide silo detection component, which is used to collect the steel rolling iron oxide material parameters inside the steel rolling iron oxide silo to obtain a steel rolling iron oxide material parameter set; a coarse particle silo detection component is used to collect the coarse particle material parameters inside the coarse particle silo to obtain a coarse particle material parameter set; the OG mud ball material parameter set, the steelmaking dust removal ash parameter set, the steel rolling iron oxide material parameter set, and the coarse particle material parameter set are used as the silo monitoring parameter set.
[0026] OG mud and dust ash are the main consumable materials in production, and their supply directly determines the matching production capacity. When the production capacity exceeds the supply, the inventory will be continuously consumed. After the inventory is consumed, some equipment needs to be shut down. Each time the drying equipment is started and closed, a large amount of energy is consumed for preheating, which will waste a lot of electricity and its own original heat energy. In addition, the cooling of the equipment after shutdown will cause the cooling of the materials attached to the surface, and additional cleaning and other steps are required. Shutdown without maintenance is a huge waste.
[0027] The production capacity of OG mud and dust ash can be directly obtained based on the steel production capacity of the supply unit. In the absence of technological improvements or raw material shortages in related factories, the output of OG mud and dust ash supplied will be relatively stable. The subsequent production capacity changes can be estimated through seasonal fluctuations.
[0028] The equipment monitoring module is used to collect the multi-dimensional working parameters of each processing equipment to obtain the equipment monitoring parameter set. The equipment monitoring module includes: a wheel rolling equipment monitoring unit, which is used to collect the working parameters of the wheel rolling equipment and obtain the wheel rolling equipment monitoring parameter set; a compaction equipment monitoring unit, which is used to collect the working parameters of the compaction equipment and obtain the compaction equipment monitoring parameter set; a ball pressing equipment monitoring unit, which is used to collect the working parameters of the ball pressing equipment and obtain the ball pressing equipment monitoring parameter set; a drying equipment monitoring unit, which is used to collect the working parameters of the drying equipment and obtain the drying equipment monitoring parameter set; the wheel rolling equipment monitoring parameter set, the compaction equipment monitoring parameter set, the ball pressing equipment monitoring parameter set, and the drying equipment monitoring parameter set are used as the equipment monitoring parameter set.
[0029] The dried OG mud, steelmaking dust, steel rolling scale and coarse particles are weighed and mixed in a certain proportion through a spiral weighing machine, and then compacted and mixed with the binder in a wheel roller. The binder is prepared and added by a special binder system, and then further compacted in a compactor. Finally, it is briquette-pressed and sieved in a double-roller briquetting machine to obtain qualified pellets. The sieved powder is returned to the buffer silo and briquette-pressed again.
[0030] The qualified pellets enter the dryer for drying, and when the moisture content of the raw pellets drops below 2%, they become finished products. They are then transported to the finished product yard by a belt conveyor and, if needed, to the steelmaking furnace charge area by car.
[0031] During the production process, unified allocation of the production capacity of each device can enable each device to work together continuously.
[0032] The batching control module is used to construct a batching optimization model based on the silo monitoring parameter set and the equipment monitoring parameter set, and generate batching optimization execution parameters and equipment adjustment parameters. The batching control module includes:
[0033] A model building unit, used to build a processing efficiency optimization space according to the equipment monitoring parameter set;
[0034] The basic parameter unit is used to input past parameters and obtain a basic parameter set.
[0035] The correction unit is used to correct the basic parameter set according to the silo monitoring parameter set to obtain a corrected parameter set.
[0036] The optimization unit is used to bring the correction parameter set into the optimization space for optimization, and obtain the batching optimization execution parameters and equipment adjustment parameters.
[0037] The optimization unit comprises:
[0038] A preliminary calculation unit, used for bringing the equipment monitoring parameter set and the correction parameter set into a preliminary optimization formula for calculation to obtain a preliminary adjustment analysis coefficient;
[0039] The preliminary optimization formula is:
[0040]
[0041] Wherein, P is the material fluctuation value, t1 is the calculation start date, t2 is the calculation end date, wherein the calculation end date is the manually set feeding cycle day, α is the number of cycles to be optimized, when the calculation is performed without pre-optimization, the default value is 1, when estimating according to the basic parameter set, it is adjusted according to the estimated number, illustratively, when estimating three feeding cycles, it is manually set to 3, F(x) is the feed amount fluctuation function that fits the correction parameter set with the cycle days as the x-axis, G(x) is the capacity fluctuation function that fits the equipment monitoring parameter set with the cycle days as the x-axis, and X is the calculation cycle days;
[0042] An optimization calculation unit, used for generating an adjustment capacity parameter according to a preliminary adjustment analysis coefficient, and bringing the adjustment capacity parameter and the correction parameter set into a cyclic optimization formula for calculation;
[0043] The cycle optimization formula is:
[0044]
[0045]
[0046] Wherein, K is the measurement value, P is the material fluctuation value, t1 is the calculation start date, t2 is the calculation end date, wherein the calculation end date is the manually set feeding cycle day, α is the number of cycles to be optimized, when the calculation is performed without pre-optimization, the default value is 1, when the estimation is performed according to the basic parameter set, it is adjusted according to the estimated number, illustratively, when three feeding cycles are estimated, it is manually set to 3, F(x) is the feed volume fluctuation function that fits the correction parameter set with the cycle days as the x-axis, G(x) is the capacity fluctuation function that fits the equipment monitoring parameter set with the cycle days as the x-axis, U(x) is the optimization parameter after the capacity fluctuation function is adjusted according to the material fluctuation value with the cycle days as the x-axis, and X is the calculation cycle days;
[0047] The output judgment unit is used to set the permissible interval. When the K value does not meet the permissible interval, the current K value is brought into the optimization calculation unit as the P value for optimization again. When the K value meets the permissible interval, the optimization parameters are split into ingredient optimization parameters and equipment adjustment parameters.
[0048] The input past parameters refer to the parameters composed of the set of monitoring parameters of the silo in the past with a date set manually or in advance in the system. The subsequent feed volume is estimated by the past storage volume and feed volume change curve, thereby providing calculation parameters for the subsequent capacity adjustment.
[0049] According to the optimization formula, P can be used to infer the remaining material after the current cycle. When α is set to 1, each feeding cycle is calculated immediately, and the calculation result at this time is accurate. It is worth mentioning that when there is a business agreement or advance notice, when it is expected that the supply will fluctuate, the F(x) function should be manually corrected.
[0050] The processing equipment control module is used to receive the batching optimization execution parameters and the equipment adjustment parameters, and adjust the batching of the silo unit according to the batching optimization execution parameters, and adjust the processing efficiency of the processing equipment according to the equipment adjustment parameters.
[0051] Those skilled in the art will understand that the various digital numbers such as the first and second involved in this application are only for the convenience of description, and are not used to limit the scope of this application, nor do they indicate a sequence of precedence. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated with each other are in an "or" relationship. "At least one" refers to one or more. At least two refers to two or more. "At least one", "any one" or similar expressions refer to any combination of these items, including any combination of single items (individuals) or plural items (individuals). For example, at least one item (individual, kind) of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.
[0052] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in this application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
[0053] The steps of the method or algorithm described in this application can be directly embedded in hardware, software units executed by a processor, or a combination of the two. The software unit can be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, register, hard disk, removable disk, CD-ROM or any other form of storage medium in the art. Exemplarily, the storage medium can be connected to the processor so that the processor can read information from the storage medium and write information to the storage medium. Optionally, the storage medium can also be integrated into the processor. The processor and the storage medium can be arranged in an ASIC, and the ASIC can be arranged in a terminal. Optionally, the processor and the storage medium can also be arranged in different components in the terminal. These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are performed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0054] Although the present application has been described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the accompanying drawings are merely exemplary illustrations of the present application and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.
Claims
1. An automatic control system for deep processing of steelmaking OG mud, characterized in that: The system comprises: Silo units for storing different materials; The silo monitoring module is used to collect multi-dimensional silo parameters inside each silo and obtain a silo monitoring parameter set; The equipment monitoring module is used to collect multi-dimensional working parameters of each processing equipment and obtain a set of equipment monitoring parameters; A batching control module, used to construct a batching optimization model according to the silo monitoring parameter set and the equipment monitoring parameter set, and generate batching optimization execution parameters and equipment adjustment parameters; A processing equipment control module, used to receive the batching optimization execution parameters and the equipment adjustment parameters, and adjust the batching of the silo unit according to the batching optimization execution parameters, and adjust the processing efficiency of the processing equipment according to the equipment adjustment parameters; Wherein, the batching control module includes: A model building unit, used to build a processing efficiency optimization space according to the equipment monitoring parameter set; Basic parameter unit, used to input past parameters and obtain a basic parameter set; A correction unit, used for correcting the basic parameter set according to the silo monitoring parameter set to obtain a corrected parameter set; An optimization unit, used for bringing the correction parameter set into the optimization space for optimization, and obtaining batching optimization execution parameters and equipment adjustment parameters; Wherein, the optimization unit comprises: A preliminary calculation unit, used for bringing the equipment monitoring parameter set and the correction parameter set into a preliminary optimization formula for calculation to obtain a preliminary adjustment analysis coefficient; The preliminary optimization formula is: Wherein, P is the material fluctuation value, t1 is the calculation start date, t2 is the calculation end date, wherein the calculation end date is the manually set feeding cycle day, α is the number of cycles to be optimized, when the calculation is performed without pre-optimization, the default value is 1, when estimating according to the basic parameter set, it is adjusted according to the estimated number, illustratively, when estimating three feeding cycles, it is manually set to 3, F(x) is the feed amount fluctuation function that fits the correction parameter set with the cycle days as the x-axis, G(x) is the capacity fluctuation function that fits the equipment monitoring parameter set with the cycle days as the x-axis, and X is the calculation cycle days; An optimization calculation unit, used for generating an adjustment capacity parameter according to a preliminary adjustment analysis coefficient, and bringing the adjustment capacity parameter and the correction parameter set into a cyclic optimization formula for calculation; The cycle optimization formula is: Wherein, K is the measurement value, P is the material fluctuation value, t1 is the calculation start date, t2 is the calculation end date, wherein the calculation end date is the manually set feeding cycle day, α is the number of cycles to be optimized, when the calculation is performed without pre-optimization, the default value is 1, when the estimation is performed according to the basic parameter set, it is adjusted according to the estimated number, illustratively, when three feeding cycles are estimated, it is manually set to 3, F(x) is the feed volume fluctuation function that fits the correction parameter set with the cycle days as the x-axis, G(x) is the capacity fluctuation function that fits the equipment monitoring parameter set with the cycle days as the x-axis, U(x) is the optimization parameter after the capacity fluctuation function is adjusted according to the material fluctuation value with the cycle days as the x-axis, and X is the calculation cycle days; The output judgment unit is used to set the permissible interval. When the K value does not meet the permissible interval, the current K value is brought into the optimization calculation unit as the P value for optimization again. When the K value meets the permissible interval, the optimization parameters are split into ingredient optimization parameters and equipment adjustment parameters.
2. The automatic control system for deep processing of steelmaking OG mud according to claim 1 is characterized in that: The silo unit comprises: OG mud silo, used to store OG mud balls; Steelmaking dust ash gas tank, used to store steelmaking dust ash; Steel rolling iron oxide silo, used to store steel rolling iron oxide powder; Coarse particle silo, used to store coarse particles; The adhesive batcher is used to store adhesive and add adhesive according to the batching control module.
3. The automatic control system for deep processing of steelmaking OG mud according to claim 1 is characterized in that: The silo monitoring module comprises: OG mud silo material detection component, used to collect OG mud ball material parameters inside the OG mud silo and obtain the OG mud ball material parameter set; The steelmaking dust removal gas tank detection component is used to collect the steelmaking dust removal parameters inside the steelmaking dust removal gas tank to obtain a steelmaking dust removal parameter set; The steel rolling iron oxide silo detection component is used to collect the steel rolling iron oxide material parameters inside the steel rolling iron oxide silo to obtain the steel rolling iron oxide material parameter set; A coarse particle silo detection component is used to collect coarse particle material parameters inside the coarse particle silo to obtain a coarse particle material parameter set; The OG mud ball material parameter set, the steelmaking dust removal ash parameter set, the steel rolling iron oxide material parameter set, and the coarse particle material parameter set are used as the silo monitoring parameter set.
4. The automatic control system for deep processing of steelmaking OG mud according to claim 1 is characterized in that: The equipment monitoring module comprises: The wheel rolling equipment monitoring unit is used to collect the working parameters of the wheel rolling equipment and obtain the monitoring parameter set of the wheel rolling equipment; The compaction equipment monitoring unit is used to collect the working parameters of the compaction equipment and obtain a compaction equipment monitoring parameter set; A ball pressing equipment monitoring unit is used to collect working parameters of the ball pressing equipment and obtain a set of monitoring parameters of the ball pressing equipment; A drying equipment monitoring unit is used to collect operating parameters of the drying equipment and obtain a set of drying equipment monitoring parameters; The monitoring parameter set of the wheel rolling equipment, the monitoring parameter set of the compacting equipment, the monitoring parameter set of the ball pressing equipment, and the monitoring parameter set of the drying equipment are taken as the equipment monitoring parameter set.