CN110427004B - Intelligent management system for intelligent spinning workshop - Google Patents

Intelligent management system for intelligent spinning workshop Download PDF

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CN110427004B
CN110427004B CN201910741780.8A CN201910741780A CN110427004B CN 110427004 B CN110427004 B CN 110427004B CN 201910741780 A CN201910741780 A CN 201910741780A CN 110427004 B CN110427004 B CN 110427004B
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spinning
equipment
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CN110427004A (en
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吴海平
刘铁
桂长明
包洋
邱凯
刘航妮
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Wuhan Yudahua Textile Co ltd
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Wuhan Yudahua Textile Co ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
    • G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/32—Operator till task planning
    • G05B2219/32252—Scheduling production, machining, job shop
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The invention discloses an intelligent management system of an intelligent spinning workshop, which comprises an information monitoring system, an information processing system and an information regulation and control system. The information monitoring system is used for monitoring the data of the whole spinning workshop in real time, then the information processing system is used for processing the data in the spinning workshop to obtain the regulation and control parameters of the intelligent spinning workshop, and finally the information regulation and control system is used for regulating and controlling the operation of equipment in the intelligent spinning workshop. The intelligent management system for the intelligent spinning workshop provided by the invention realizes the automatic production and transportation control from raw materials to finished products and the online monitoring and control of the quality and the yield of the products by an information network technology, a sensor technology, a frequency conversion speed regulation technology and the like, obviously improves the quality and the production efficiency of the products, reduces the production cost, and has the advantages of modernization, scientification and standardization.

Description

Intelligent management system for intelligent spinning workshop
Technical Field
The invention belongs to the technical field of spinning, and particularly relates to an intelligent management system for an intelligent spinning workshop.
Background
The intelligent spinning workshop is based on highly automated production, transportation and storage equipment, and a spinning workshop information system can monitor the operation, production condition, production environment and the like of the workshop in real time and realize bidirectional communication, for example, the production quality is controlled in real time through an expert system, the production environment is adjusted through controlling a workshop air conditioning system, and once a fault needing manual intervention occurs, an alarm can be sent to inform workers on duty to timely deal with the problem. The spinning process design is the core content of the whole intelligent spinning production, relates to the formulation of cotton blending indexes and process parameters of each procedure of the spinning production, and determines the quality of enterprise products to a great extent by the design level.
However, the spinning process design has the characteristics of various processes, complex flow, frequent change and the like, each process of spinning has corresponding numerous process parameters, so that the information management difficulty is high, and a large amount of manpower and material resources are consumed by textile enterprises. With the development of market economy, the demands of customers on finished yarn are increasingly diversified, and the requirements on product quality are increasingly strict, which undoubtedly further aggravates the difficulty of spinning process design and product quality management. In addition, at present, cotton blending is mainly performed by a cotton blending technician according to subjective experience, the cotton blending efficiency is low, the effect is poor, an optimal cotton blending scheme is often difficult to find, raw material resources of enterprises can not be reasonably used, and the raw material cost is increased. Therefore, the traditional manual design and quality management mode is not more and more suitable for the requirements of modern spinning production, so that enterprise resources can not be reasonably configured, the product quality is difficult to guarantee, and the improvement of the production benefits of enterprises is greatly limited.
Therefore, the invention is based on the information network technology, integrates the sensor technology, the frequency conversion speed regulation and the like, constructs an intelligent spinning workshop intelligent management system, and realizes the automatic production and transportation control from raw materials to finished products and the online monitoring and control of the quality and the yield of the products by monitoring the whole spinning workshop in real time.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an intelligent management system for an intelligent spinning workshop, which comprises an information monitoring system, an information processing system and an information regulation and control system; the information processing system carries out intelligent operation of cotton distribution indexes through a cotton distribution mathematical model, the information monitoring system carries out real-time monitoring on data in the intelligent spinning workshop, and a spinning quality intelligent control model and a spinning process optimization model are constructed through the information processing system, so that the optimization of regulation and control parameters of the intelligent spinning workshop is realized, and finally the full-flow intelligent management of the intelligent spinning workshop is realized.
In order to achieve the purpose, the invention adopts the following technical scheme:
an intelligent spinning workshop intelligent management system, comprising:
the information monitoring system is used for monitoring data in the intelligent spinning workshop;
the information processing system is used for processing the data in the intelligent spinning workshop monitored by the information monitoring system to obtain the regulation and control parameters of the intelligent spinning workshop; and the combination of (a) and (b),
the information regulating and controlling system is used for regulating and controlling the operation of equipment in the intelligent spinning workshop according to the regulating and controlling parameters of the spinning workshop;
the regulation and control parameters of the spinning workshop comprise the regulation and control parameters of spinning equipment and the regulation and control parameters of air conditioning equipment;
the information regulation and control system comprises:
the spinning equipment regulating and controlling unit is used for regulating and controlling the operation of the spinning equipment according to the regulating and controlling parameters of the spinning equipment; and the combination of (a) and (b),
and the air conditioning equipment regulating and controlling unit is used for regulating and controlling the operation of the air conditioning equipment according to the regulating and controlling parameters of the air conditioning equipment.
Further, the information monitoring system includes:
the equipment operation monitoring module is used for monitoring the operation state data of the equipment;
the workshop environment monitoring module is used for monitoring environmental data in the intelligent spinning workshop;
the production quality monitoring module is used for monitoring the quality data of the product;
the production yield monitoring module is used for monitoring the yield data of the product; and the combination of (a) and (b),
and the production energy consumption monitoring module is used for monitoring the energy consumption data of production.
Further, the equipment operation monitoring module monitors and obtains operation state data of the equipment through sensors arranged at each equipment;
the workshop environment monitoring module is used for monitoring and obtaining environmental data in the intelligent spinning workshop through a temperature sensor, a humidity sensor and a dust sensor which are arranged in the spinning workshop;
the production quality monitoring module monitors and obtains the quality data of the product through a quality monitoring device arranged at each spinning process;
the production yield monitoring module monitors and obtains the yield data of the product through yield monitoring devices arranged at each spinning process;
the production energy consumption monitoring module monitors and obtains the energy consumption data of production through energy consumption monitoring devices arranged in a power supply system and a water supply system.
Furthermore, the device operation monitoring module comprises a spinning device operation monitoring unit and an air conditioning device operation monitoring unit, wherein the spinning device operation monitoring unit comprises an opening and picking device operation monitoring subunit, a cotton carding device operation monitoring subunit, a drawing device operation monitoring subunit, a roving device operation monitoring subunit, a spun yarn device operation monitoring subunit, a spooling device operation monitoring subunit and a packaging device operation monitoring subunit.
Further, the information processing system comprises a data input module, a data processing module, a data output module and a data display module which are sequentially connected, and a database module which is respectively connected with the data input module and the data output module;
the database unit is used for storing the data input by the data input module and the data output by the data output module;
the data input module is used for inputting data monitored by the information monitoring system in the intelligent spinning workshop;
the data processing module is used for processing the data input by the data input module to obtain the regulation and control parameters of the intelligent spinning workshop;
the data output module comprises two output ports which are respectively used for outputting the regulation and control parameters of the spinning workshop to the information regulation and control system and outputting the regulation and control parameters to the data display module;
and the data display module is used for displaying the regulation and control parameters of the spinning workshop.
Further, theoretical temperature and humidity control parameters of the spinning workshop with the upper limit value and the lower limit value of temperature and humidity and the environment temperature range of-5-40 ℃ and the humidity range of 0-99% are stored in the database module.
Further, theoretical temperature and humidity control parameters in the database are calculated according to the theory of flat wall heat conduction, convection heat exchange and radiation heat exchange by taking a standard temperature value and a standard humidity value in a spinning workshop as a reference; the standard temperature value and the standard humidity value are respectively the middle values of the upper limit value and the lower limit value of the temperature and the humidity.
Furthermore, the data entry module comprises an intelligent entry port and a manual entry port, the intelligent entry port is used for entering data monitored by the information monitoring system in the intelligent spinning workshop, and the manual entry port is used for manually entering data.
Further, the data processing module of the information processing system comprises:
the cotton distribution unit is used for carrying out intelligent operation of cotton distribution composition according to the required quality data of the product;
the process design unit is used for carrying out intelligent operation on the regulation and control parameters of the spinning equipment according to the cotton distribution index and the required quality data of the product; and the combination of (a) and (b),
and the environment control unit is used for carrying out intelligent operation on the regulation and control parameters of the air conditioning equipment according to the environment data.
Furthermore, the cotton distribution unit carries out intelligent operation of cotton distribution composition by constructing a cotton distribution mathematical model, and the cotton distribution mathematical model establishes a multi-target-constrained cotton distribution mathematical model by taking the minimum cost of raw cotton and the optimal index of cotton distribution as targets.
Further, the cotton matching indexes comprise a micronaire value, a maturity, an average length, a short fiber index, a breaking ratio strength and a nep index of raw cotton; the multi-target constraints comprise cotton distribution inventory constraints, total weight constraints, cotton distribution type constraints and cotton distribution index constraints.
Furthermore, the data processing module of the information processing system further comprises a process optimization unit, and the process optimization unit is used for performing optimization operation on the regulation and control parameters of the spinning equipment according to the quality data, the yield data and the energy consumption data of the product.
Furthermore, the process optimization unit takes the quality data of the product as a first investigation index, establishes a quality optimization model based on multi-process knowledge association of the spinning process, and further optimizes the spinning process by combining the yield data and the production energy consumption data on the basis.
Further, the construction method of the quality optimization model comprises the following steps:
(1) establishing quality control points in each process of the spinning process, and establishing a quality control point set;
(2) taking the breaking strength of the yarn as a key quality index, and constructing a quality loss function of each process and a quality loss function of the whole spinning process;
(3) obtaining the optimal solution of the process parameters of each corresponding quality control point when the quality loss is minimum through continuous iteration and optimization solution;
(4) on the basis of the spinning quality control point and the coupling action relationship thereof, establishing a quality optimizing objective function oriented to the spinning production process;
(5) and substituting the mass loss function of each process and the mass loss function of the whole spinning process into a mass optimizing objective function to form the mass optimizing model.
Furthermore, the data processing module of the information processing system further comprises a fault prediction unit, and the information regulation and control system further comprises a fault alarm unit; and the fault prediction unit predicts the fault of the equipment according to the running state data of the equipment and sends out a fault early warning signal in advance through the fault alarm unit.
Furthermore, the data processing module of the information processing system further comprises a fault diagnosis unit, which is used for judging whether the equipment has faults according to the running state data of the equipment; and sending out a fault warning signal through the fault alarm unit.
Further, the environment control unit comprises a coarse adjustment system and a fine adjustment system, the coarse adjustment system is used for presetting temperature and humidity control parameters in advance by acquiring environment temperature and humidity data in real time and sending a coarse adjustment indication signal to the air conditioning equipment regulation and control unit; the fine adjustment system receives the monitoring data of the temperature and humidity sensor in real time and sends a fine adjustment indicating signal to the air conditioning equipment regulation and control unit in real time according to the real-time monitoring data of the temperature and humidity.
Furthermore, the database module is also stored with position information corresponding to each sensor, each sensor corresponds to the position information of the sensor stored in the database module, and when yarn is broken or equipment fails, the data output module sends the position information of the corresponding sensor to the failure alarm unit.
Furthermore, the operation monitoring subunit of the cotton opening and picking equipment comprises a machine vision detection mechanism which is used for identifying and extracting the image characteristics of the cotton bale appearance image, the cotton grabbing machine appearance image and the environment appearance image in the cotton grabbing working range.
Further, the cotton blending composition comprises the types of raw materials, the quality data of the raw materials and the composition proportion; the required quality data of the product comprises the required data of the linear density, the fineness, the twist and the breaking strength of the yarn.
Furthermore, the quality data of the product comprises the quality data of the raw materials, the quality data of semi-finished products in each process and the quality data of finished yarns.
Further, the quality data of the raw materials comprise quality data of raw cotton and chemical fiber, the quality data of the semi-finished products in each process comprises quality data of the semi-finished products in an opening and picking process, a carding process, a drawing process and a roving process, and the quality data of finished yarns comprise finished yarn quality data in a spinning process and a winding process.
Further, the quality data of the raw cotton comprise a micronaire value, a maturity, an average length, a short fiber index, a breaking ratio strength and a nep index of the raw cotton, and the quality data of the chemical fiber comprise a chemical fiber moisture regain, a linear density, a cutting length and a breaking ratio strength; the quality data of the finished yarn comprises breaking strength, cotton nep number, fineness, twist and mass deviation value of hundred meters of the finished yarn.
Further, the operation state data of the device comprises operation state data of the spinning device and operation state data of the air conditioning device; the environmental data comprise temperature data, humidity data and air cleanliness data in the intelligent spinning workshop.
Further, the spinning equipment comprises opening and picking equipment, cotton carding equipment, drawing equipment, roving equipment, spinning equipment, spooling equipment and packaging equipment; the air conditioning equipment comprises dust removing equipment, temperature adjusting equipment and humidity adjusting equipment.
Further, the operation state data of the opening and scutching equipment comprises operation state data of the cotton grabbing equipment, the cotton mixing equipment, the cotton opening equipment and the scutching equipment; the running state data of the cotton grabbing equipment comprises the starting and stopping of the cotton grabbing equipment, the running speed and the rotating speed of a beater of the cotton grabbing equipment, and the descending stroke of the cotton grabbing equipment.
Further, the running state data of the drawing equipment comprises the speeds of a feeding roller, a drawing roller and an output roller; the running state data of the roving equipment comprises roller output speed, drafting multiple, twist, flyer rotating speed, bobbin rotating speed and keel lifting speed; the operation state data of the spinning equipment comprises spindle rotating speed, bead ring rotating speed, ring plate lifting speed, yarn guide plate lifting speed, ring plate lifting stroke, yarn guide plate lifting stroke and the like.
Furthermore, the regulation and control parameters of the spinning equipment comprise regulation and control parameters of opening and picking equipment, carding equipment, drawing equipment, roving equipment, spinning equipment, winding equipment and packaging equipment; the regulation and control parameters of the air conditioning equipment comprise regulation and control parameters of dust removal equipment, temperature regulation equipment and humidity regulation equipment.
Further, the intelligent management system of the intelligent spinning workshop comprises the following management steps:
s1, inputting required quality data of a product from a data input module of the information processing system, and calculating by the data processing module according to the required quality data of the product to obtain a cotton distribution composition;
s2, calculating by the data processing module according to the cotton blending composition and the required quality data of the product in the step S1 to obtain initial regulation and control parameters of spinning equipment of the intelligent spinning workshop;
the data processing module calculates to obtain initial regulation and control parameters of the air conditioning equipment of the intelligent spinning workshop according to the cotton distribution indexes, the required quality data of the product and the current environmental temperature and humidity data in the step S1;
s3, the data output module outputs the initial regulation and control parameters of the spinning equipment and the air conditioning equipment of the intelligent spinning workshop in the step S2 to the information regulation and control system, and the information regulation and control system regulates and controls the operation of equipment in the intelligent spinning workshop according to the initial regulation and control parameters of the spinning equipment and the air conditioning equipment of the spinning workshop;
s4, in the running process of equipment in the intelligent spinning workshop, the information monitoring system monitors data in the intelligent spinning workshop in real time and sends the monitored data to a data input module of the information processing system;
s5, calculating by a process optimization unit of the data processing module according to the data monitored in the step S4 to obtain optimized regulation and control parameters of spinning equipment of the intelligent spinning workshop;
the environment control unit of the data processing module calculates according to the data monitored in the step S4 to obtain real-time regulation and control parameters of the air conditioning equipment of the intelligent spinning workshop;
s6, the data output module outputs the optimized regulation and control parameters of the spinning equipment and the real-time regulation and control parameters of the air conditioning equipment in the intelligent spinning workshop in the step S5 to the information regulation and control system, and a spinning equipment regulation and control unit of the information regulation and control system regulates and controls the optimized operation of the spinning equipment in the intelligent spinning workshop according to the optimized regulation and control parameters of the spinning equipment in the spinning workshop;
and an air conditioning equipment regulating and controlling unit of the information regulating and controlling system regulates and controls the optimized operation of the air conditioning equipment in the intelligent spinning workshop according to the real-time regulating and controlling parameters of the spinning air conditioning equipment in the spinning workshop.
Advantageous effects
Compared with the prior art, the intelligent management system for the intelligent spinning workshop provided by the invention has the following beneficial effects:
(1) the intelligent management system is constructed based on an information network technology, a sensor technology, variable frequency speed regulation and the like are fused, an intelligent spinning workshop intelligent management system is constructed, data of the whole spinning workshop are monitored in real time through an information monitoring system, the data in the spinning workshop are processed through an information processing system to obtain regulation and control parameters of the intelligent spinning workshop, the operation of equipment in the intelligent spinning workshop is regulated and controlled through the information regulation and control system, and automatic production and transportation control from raw materials to finished products and online monitoring and control of the quality and the yield of the products are achieved.
(2) According to the invention, by constructing a cotton blending mathematical model, the most suitable raw materials can be selected from the raw material warehouse and the proportion of each raw material can be determined by taking the minimum raw cotton cost and the optimal cotton blending index as targets, and the minimization of the raw material cost is realized on the premise of ensuring that the mixed raw materials meet the established cotton blending index.
(3) The method takes the quality data of the product as a first investigation index, defines a spinning quality control point and a loss function thereof from the view point of multiple processes, further constructs a quality optimization model associated with multiple process knowledge by taking the quality loss function as a target function, and realizes the control of the spinning quality by means of an automatic process control technology; and the spinning process is further optimized and improved properly by combining the yield data and the production energy consumption data, so that the spinning quality and the production efficiency are obviously improved, and the production cost is reduced.
(4) The information monitoring system is used for monitoring the running state data, the product quality and yield data, the workshop environment data, the energy consumption data and the like of the spinning workshop in real time, and can provide the spinning workshop data to the information processing system in real time, so that the information processing system can master the production efficiency, the production quality, the workshop environment and the like of the spinning workshop at any time, and the management efficiency and the management quality are improved.
(5) According to the invention, the fault prediction unit and the fault diagnosis unit are used for carrying out fault prediction and fault diagnosis on the equipment according to the running state data of the equipment, and the fault warning unit is used for sending out the fault early warning signal and the fault warning signal, so that the product quality and yield reduction caused by the equipment fault can be prevented.
(6) According to the invention, spinning equipment or spinning units are numbered and marked, the marked position information is stored in the database module, each sensor corresponds to the position information one by one, when the equipment fails, the data output module sends the position information of the corresponding sensor to the failure alarm unit, and the failure alarm unit displays or broadcasts the position information, so that the synchronization and fixed-point detection of the equipment failure are realized, the position of the equipment which fails is conveniently found out, and the spinning efficiency and the spinning quality are improved.
(7) The environment control unit of the invention adopts an intelligent regulation and control mode combining coarse regulation and fine regulation, firstly sends a coarse regulation indicating signal to the air conditioning equipment regulation and control unit according to the theories of flat wall heat conduction, convection heat exchange and radiation heat exchange, and further sends a fine regulation indicating signal by receiving the monitoring data of the temperature and humidity sensor in the workshop in real time, thereby realizing the intelligent control of the temperature and humidity in the spinning workshop.
(8) The intelligent management system for the intelligent spinning workshop, provided by the invention, can reduce a large amount of heavy work caused by data recording, data statistics and data analysis when technical personnel manage the product quality, reduce the labor cost, simultaneously enhance the analysis and utilization of the past quality data, and realize the modernization, the scientization and the standardization of management.
Drawings
FIG. 1 is a block diagram of an intelligent management system of an intelligent spinning workshop provided by the invention;
FIG. 2 is a schematic diagram of the structure of the intelligent management system of the intelligent spinning workshop;
FIG. 3 is a block diagram of the data processing module components and functions of the information handling system;
FIG. 4 is a schematic diagram of the composition of an intelligent spinning room;
FIG. 5 is a process flow diagram of a blended yarn process;
FIG. 6 is a flow chart of intelligent management of the intelligent spinning workshop intelligent management system;
fig. 7 is a block diagram of a spinning quality control point in the intelligent quality control model.
Detailed Description
The technical solutions of the embodiments of the present invention will be described clearly and completely below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments; all other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without any inventive step, are within the scope of the present invention.
With the development of information network technology, sensor technology and variable frequency speed control technology, the production of spinning workshops has gradually developed towards automation, continuity and intellectualization. In order to further cooperate with the intelligent management of an intelligent spinning workshop so as to realize the aims of highest quality and yield of spinning products and lowest cost, the invention provides an intelligent management system of the intelligent spinning workshop, which is designed according to the following design ideas and design bases:
the spinning production process is complex, generally needs to pass through the processes of opening and picking, carding, drawing, roving, spinning and the like, the yarn with higher quality requirement also needs to pass through the combing process, and meanwhile, because the production raw materials and the quality requirements used by the pure cotton yarn and the chemical fiber blended yarn respectively have differences, different production flows are often needed in the processing.
Referring to fig. 4, the temperature and humidity have a great influence on the production efficiency and the product quality of the workshop in the actual production of the textile mill. The performance of the textile fiber material has strong sensitivity to the temperature and the humidity of air, and the phenomena of warp breakage, machine halt and the like caused by over-low temperature and humidity are increased; and the quality problems of light pulp, color difference and the like can be caused by overhigh temperature and humidity. Experiments prove that the production efficiency and the product quality of a weaving workshop can be improved by effectively controlling the temperature and the humidity. In addition, in the spinning process of a textile mill, a lot of dust, short fibers, bacteria and the like with strong adhesion can be generated to float in the air, so that the quality of textile products can be influenced, more importantly, the air is polluted, and even explosion can be caused to cause serious harm. A spinning room therefore usually contains spinning equipment and air conditioning equipment for regulating the temperature, humidity and air cleanliness of the spinning room to ensure the quality of the spinning product and the proper operation of the spinning equipment.
Wherein, the general working procedures and the action principles of the working procedures of the spinning production are as follows:
the cotton blending is the earliest work of the spinning process, mainly designs cotton blending indexes according to the required quality data of products, selects proper raw materials from a raw material warehouse and determines the proportion of the raw materials, and gives full play to the characteristics of different raw materials so as to achieve the purposes of improving the quality of spinning products, stabilizing the spinning production and reducing the spinning cost.
The opening and picking process is the first process of the spinning process and mainly completes four tasks of opening, impurity removal, mixing and uniform coiling. The opening and picking process has the characteristics of multiple machines, long process, complex processing, high technical difficulty and the like, and the quality of the process treatment is related to the processing quality of each subsequent spinning process, so that the opening and picking process is the basis of the spinning process flow.
The cotton carding process is mainly a process of ageing, carding and uniformly mixing raw material fibers, and finally, the raw sliver meeting certain specification and quality requirements is produced. The quality of the process treatment determines the separation degree of the raw material fiber bundle, and influences the drafting movement of the raw material fiber in each subsequent process.
The drawing process mainly comprises the processes of combining, drafting, mixing and forming cotton carding or combing slivers, randomly overlapping slivers with different thicknesses, and performing attenuation, repeated combination and drafting to achieve the purpose of fully mixing raw material single fibers.
The roving process mainly needs to finish three tasks of drafting, twisting and winding, firstly, a sliver is drawn and elongated to form roving through drafting, then, the roving is twisted, the strength of the roving is improved to avoid accidental elongation of winding, and finally, the twisted roving is made into a package with a certain shape through winding so as to be used in the next process.
The spinning process is the most critical process of the spinning process. The quality of the process determines the level of the whole spinning worker to a great extent, the main tasks required to be completed in the spinning process are drafting, twisting and winding, the fed roving strips are uniformly elongated and attenuated to a certain number by drafting, then appropriate twisting is carried out, and finally the spun yarns are made into packages by winding, so that the spun yarns are convenient to transport, store and subsequently reinforce.
The main task of the spooling process is to make the spun yarn produced in the spinning process into a yarn bobbin with large capacity, uniform density and good forming.
And (4) packaging, namely packaging and storing the yarn barrel formed in the spooling process.
The working principle and the function of the air conditioning equipment are as follows:
dust collecting equipment usually takes out cotton waste fibers, dust and the like generated in a spinning workshop through an exhaust fan, and separates and recovers through a subsequent separation and recovery device, so that the cleanliness of air in the workshop is kept up to the standard, the working efficiency is improved, and the service life of the equipment is prolonged.
The temperature adjusting device and the humidity adjusting device adjust the working frequency of the air supply device, the air exhaust device and the spraying device according to temperature and humidity data monitored by the temperature and humidity sensor in the workshop through the upper air supply, the lower air return and the top spraying system, and further control the air supply volume, the air exhaust volume, the spraying volume and the spraying temperature in unit time, and control over the temperature and the humidity in the workshop is achieved.
The energy consumption of the air conditioning equipment in the spinning workshop occupies a large part of the energy consumption of the spinning production, so that the intelligent management of the operation of the air conditioning equipment is also an important part of the intelligent spinning workshop management.
The intelligent spinning workshop controls the spinning equipment and the air conditioning equipment of all the processes to regularly run through a control system, so that the intelligent management of the intelligent spinning workshop is realized, and the spinning quality and efficiency are effectively controlled.
Example 1
Referring to fig. 1 and fig. 2, based on the spinning principle, the intelligent management system for the intelligent spinning workshop provided by the invention comprises:
the information monitoring system is used for monitoring data in the intelligent spinning workshop;
the information processing system is used for processing the data in the intelligent spinning workshop monitored by the information monitoring system to obtain the regulation and control parameters of the intelligent spinning workshop; and the combination of (a) and (b),
the information regulating and controlling system is used for regulating and controlling the operation of equipment in the intelligent spinning workshop according to the regulating and controlling parameters of the spinning workshop;
the regulation and control parameters of the spinning workshop comprise the regulation and control parameters of spinning equipment and the regulation and control parameters of air conditioning equipment;
the information regulation and control system comprises:
the spinning equipment regulating and controlling unit is used for regulating and controlling the operation of the spinning equipment according to the regulating and controlling parameters of the spinning equipment; and the combination of (a) and (b),
and the air conditioning equipment regulating and controlling unit is used for regulating and controlling the operation of the air conditioning equipment according to the regulating and controlling parameters of the air conditioning equipment.
Further, the spinning equipment comprises opening and picking equipment, cotton carding equipment, drawing equipment, roving equipment, spinning equipment, spooling equipment and packaging equipment; the air conditioning equipment comprises dust removing equipment, temperature adjusting equipment and humidity adjusting equipment.
The regulation and control parameters of the spinning equipment comprise regulation and control parameters of opening and picking equipment, cotton carding equipment, drawing equipment, roving equipment, spinning equipment, spooling equipment and packaging equipment; the regulation and control parameters of the air conditioning equipment comprise the regulation and control parameters of dust removal equipment, temperature regulation equipment and humidity regulation equipment.
Referring to fig. 2, the information monitoring system includes:
the equipment operation monitoring module is used for monitoring the operation state data of the equipment;
the workshop environment monitoring module is used for monitoring environmental data in the intelligent spinning workshop;
the production quality monitoring module is used for monitoring the quality data of the product;
the production yield monitoring module is used for monitoring the yield data of the product; and the combination of (a) and (b),
and the production energy consumption monitoring module is used for monitoring the energy consumption data of production.
The equipment operation monitoring module monitors and obtains operation state data of the equipment through sensors arranged at each equipment;
the workshop environment monitoring module is used for monitoring and obtaining environmental data in the intelligent spinning workshop through a temperature sensor, a humidity sensor and a dust sensor which are arranged in the spinning workshop;
the production quality monitoring module monitors and obtains the quality data of the product through a quality monitoring device arranged at each spinning process;
the production yield monitoring module monitors and obtains the yield data of the product through yield monitoring devices arranged at each spinning process;
the production energy consumption monitoring module monitors and obtains the energy consumption data of production through energy consumption monitoring devices arranged in a power supply system and a water supply system.
Further, the operation state data of the device comprises operation state data of the spinning device and operation state data of the air conditioning device; the environmental data comprise temperature data, humidity data and air cleanliness data in the intelligent spinning workshop.
Furthermore, the operation state data of the spinning equipment comprises operation state data of opening and picking equipment, cotton carding equipment, drawing equipment, roving equipment, spinning equipment, winding equipment and packaging equipment, and the operation state data of the air conditioning equipment comprises operation state data of dust removal equipment, temperature regulation equipment and humidity regulation equipment.
The running state data of the opening and scutching equipment comprises the running state data of the cotton grabbing equipment, the cotton mixing equipment, the cotton opening equipment and the scutching equipment; the running state data of the cotton grabbing equipment comprises the starting and stopping of the cotton grabbing equipment, the running speed and the rotating speed of a beater of the cotton grabbing equipment, and the descending stroke of the cotton grabbing equipment.
The running state data of the drawing equipment comprises the speeds of a feeding roller, a drawing roller and an output roller; the running state data of the roving equipment comprises roller output speed, drafting multiple, twist, flyer rotating speed, bobbin rotating speed and keel lifting speed; the operation state data of the spinning equipment comprises spindle rotating speed, bead ring rotating speed, ring plate lifting speed, yarn guide plate lifting speed, ring plate lifting stroke, yarn guide plate lifting stroke and the like.
Furthermore, the device operation monitoring module comprises a spinning device operation monitoring unit and an air conditioning device operation monitoring unit, wherein the spinning device operation monitoring unit comprises an opening and picking device operation monitoring subunit, a cotton carding device operation monitoring subunit, a drawing device operation monitoring subunit, a roving device operation monitoring subunit, a spun yarn device operation monitoring subunit, a spooling device operation monitoring subunit and a packaging device operation monitoring subunit.
Referring to fig. 2, the information processing system includes a data entry module, a data processing module, a data output module, and a data display module, which are connected in sequence, and a database module connected to the data entry module and the data output module, respectively;
the database module is used for storing the data input by the data input module and the data output by the data output module;
the data processing module is used for processing the data input by the data input module to obtain the regulation and control parameters of the intelligent spinning workshop;
the data output module comprises two output ports which are respectively used for outputting the regulation and control parameters of the spinning workshop to the information regulation and control system and outputting the regulation and control parameters to the data display module;
and the data display module is used for displaying the regulation and control parameters of the spinning workshop.
Preferably, the data entry module comprises an intelligent entry port and a manual entry port, the intelligent entry port is used for entering data monitored by the information monitoring system in the intelligent spinning workshop, and the manual entry port is used for manually entering data.
Further, the data processing module of the information processing system comprises:
the cotton distribution unit is used for carrying out intelligent operation of cotton distribution composition according to the required quality data of the product;
the process design unit is used for carrying out intelligent operation on the regulation and control parameters of the spinning equipment according to the cotton blending composition and the required quality data of the product; and the combination of (a) and (b),
and the environment control unit is used for carrying out intelligent operation on the regulation and control parameters of the air conditioning equipment according to the environment data.
Further, the environment control unit comprises a coarse adjustment system and a fine adjustment system, the coarse adjustment system is used for presetting temperature and humidity control parameters in advance by acquiring environment temperature and humidity data in real time and sending a coarse adjustment indication signal to the air conditioning equipment regulation and control unit; the fine adjustment system receives the monitoring data of the temperature and humidity sensor in real time and sends a fine adjustment indicating signal to the air conditioning equipment regulation and control unit in real time according to the real-time monitoring data of the temperature and humidity.
Furthermore, the cotton distribution unit carries out intelligent operation of cotton distribution composition by constructing a cotton distribution mathematical model, and the cotton distribution mathematical model establishes a multi-target-constrained cotton distribution mathematical model by taking the minimum cost of raw cotton and the optimal index of cotton distribution as targets.
Further, the cotton blending composition comprises the types of raw materials, the quality data of the raw materials and the composition proportion; the required quality data of the product comprises the required data of the linear density, the fineness, the twist and the breaking strength of the yarn.
Preferably, the cotton blending index comprises a micronaire value, a maturity, an average length, a staple index, a breaking ratio strength and a nep index of raw cotton; the multi-target constraints comprise cotton distribution inventory constraints, total weight constraints, cotton distribution type constraints and cotton distribution index constraints.
Preferably, the cotton distribution mathematical model establishes a multi-target-constrained cotton distribution mathematical model by taking the minimum raw cotton cost and the optimal cotton distribution index as targets, and comprises the following steps:
SA1. selection of decision variables
Selecting the consumption V of various raw cottons as decision variables of the cotton distribution mathematical model, wherein the number of the decision variables is the number m of the types of the raw cottons in the stock;
SA2. determining a cotton distribution objective function
(1) One of the goals of cotton blending is to minimize the cost of raw cotton, i.e. the sum of the raw cotton cost used in the cotton blending scheme, and the usage amount of each raw cotton in a certain cotton blending scheme is ViEach kilogram of raw cotton has a unit price of PiYuan, the calculation expression of the raw cotton cost C is shown in formula (1):
Figure BDA0002164200650000191
(2) fitting for mixingThe other cotton matching index is optimal, and the more key cotton matching indexes are six, namely, the micronaire value, the maturity, the average length, the short fiber index, the breaking ratio strength and the neps, so that the cotton matching index actually comprises six target functions optimally; the ith raw cotton index of the jth raw cotton is qjiThen the ith average quality index ZiIs represented by the formula (2):
Figure BDA0002164200650000192
optimal objective function f for various cotton blendsiIs represented by the formula (3):
fi＝|zi-bi|,i＝1,2,...,n (3)
wherein bi is the ith expected cotton blending index;
SA3 Cotton distribution restraint
(1) Cotton distribution inventory constraint
Nu consumption of ith raw cotton in cotton blending schemeiMust be less than the stock quantity mu thereofi，(νiWhen 0, it means that the raw cotton is not selected, and therefore, the stock constraint expression is also satisfied), the stock constraint expression is expressed by the formula (4):
0≤νi≤μi，i＝1,2,...,m (4)
(2) total weight constraint of cotton blend
Usage amount v of single raw cotton in cotton blending schemeiBut not limited, if the sum u of the used amount of each raw cotton is required to be consistent with the set total weight of cotton blending, the constraint expression of the total weight of cotton blending is shown as formula (5):
Figure BDA0002164200650000201
(3) cotton assortment constraint
In the spinning production, the raw cotton in stock is conveniently and quickly scheduled, the types of the raw cotton used in the cotton matching scheme are not too many, xi is the upper limit of the types, and the cotton matching type constraint expression is shown in a formula (6).
2≤Count{νi≠0}≤ξ,i＝1,2,...,m (6)
(4) Index constraint of cotton blending
The larger the index value of the average length and the breaking ratio strength in the cotton blending index is, the better the index value of the short fiber and the cotton nep is, the smaller the index value of the short fiber and the cotton nep is, and the moderate the micronaire value and the maturity index value are. The raw cotton index value is therefore classified as a blue-type constraint, namely: the quality index set of the corresponding constraint is Bmin、BmidAnd Bmax(ii) a N average cotton matching indexes in the cotton matching scheme must be in a specified range, and the lower limit of the jth cotton matching index is ljWith an upper limit of hjIf the cotton blending index constraint expression is shown as the formula (7):
Figure BDA0002164200650000202
SA4. determining a mathematical model for cotton distribution
According to steps Sa1 to Sa3, it can be determined that the cotton matching mathematical model is as shown in formula (8):
Figure BDA0002164200650000211
the cotton blending mathematical model constructed according to the method aims at the minimum cost of raw cotton and the optimal index of cotton blending, can select the most suitable raw materials from a raw material warehouse and determine the proportion of each raw material, and realizes the minimization of the cost of the raw materials on the premise of ensuring that the mixed raw materials meet the established index of cotton blending.
Furthermore, the data processing module of the information processing system further comprises a process optimization unit, and the process optimization unit is used for performing optimization operation on the regulation and control parameters of the spinning equipment according to the quality data, the yield data and the energy consumption data of the product.
The quality data of the product comprises the quality data of raw materials, the quality data of semi-finished products in each working procedure and the quality data of finished yarns.
The quality data of the raw materials comprise quality data of raw cotton and chemical fiber, the quality data of the semi-finished products in each process comprises quality data of the semi-finished products in an opening and picking process, a cotton carding process, a drawing process and a roving process, and the quality data of finished yarns comprise finished yarn quality data in a spinning process and a winding process.
Referring to fig. 5, when performing the blended yarn, the quality data of the semi-finished products in each step includes the quality data of the semi-finished products in the opening and picking step, the carding step and the combing step of the raw cotton, the quality data of the semi-finished products in the opening and picking step, the carding step and the pre-drawing step of the chemical fiber, and the quality data of the semi-finished products in the drawing and roving step.
The quality data of the raw cotton comprise a micronaire value, a maturity, an average length, a short fiber index, a breaking ratio strength and a nep index of the raw cotton, and the quality data of the chemical fiber comprise a chemical fiber moisture regain, a linear density, a cutting length and a breaking ratio strength; the quality data of the finished yarn comprises breaking strength, cotton nep number, fineness, twist and mass deviation value of hundred meters of the finished yarn.
Furthermore, the process optimization unit takes the quality data of the product as a first investigation index, establishes a quality optimization model based on multi-process knowledge association, and further optimizes the spinning process by combining the yield data and the production energy consumption data on the basis.
Further, the quality optimization model is constructed by the following method:
the construction method of the quality optimization model comprises the following steps:
(1) establishing quality control points in each process of the spinning process, and establishing a quality control point set;
(2) taking the breaking strength of the yarn as a key quality index, and constructing a quality loss function of each process and a quality loss function of the whole spinning process;
(3) obtaining the optimal solution of the process parameters of each corresponding quality control point when the quality loss is minimum through continuous iteration and optimization solution;
(4) on the basis of the spinning quality control point and the coupling action relationship thereof, establishing a quality optimizing objective function oriented to the spinning production process;
(5) and substituting the mass loss function of each process and the mass loss function of the whole spinning process into a mass optimizing objective function to form the mass optimizing model.
The specific construction method comprises the following steps:
referring to fig. 7, a multi-process quality control point block diagram for the spinning process is constructed, and the process of the spinning production process is described as set S ═ S1,S2,…SnAnd respectively establishing a quality control point set G (G) for each processi1,Gi2,…,Gij,…,GipiWhere Si denotes the ith step in the spinning process, GijThe j-th quality control points in the ith step are shown. In addition, p is countediIf the number of quality control points in the ith process is defined and m represents the number of all quality control points, then
Figure BDA0002164200650000231
I is more than 0 and less than or equal to n. At the same time, let L1(Gij) Indicates a quality control point GijCorresponding to process parameter yijLower limit of control valve, L2(Gij) Indicates a quality control point GijCorresponding to process parameter yijThe upper limit of the control valve.
Thus, for each process Si, there is a corresponding quality control point GijAnd quality output characteristic value O corresponding to quality control pointij. Thereby, for any quality control point GijIn other words, there is an actual value y of the process parameter corresponding theretoijAnd a control threshold [ L1(Gij),L2(Gij)]This means that there is a mapping relationship between the process set S, the quality control point set G, and the process parameter set Y.
On the basis, a multiple load influence factor beta which expresses influence on the breaking strength of the yarn and is expressed as shown in a formula (9) is definedij：
Figure BDA0002164200650000232
Wherein, yijAnd y'ijRespectively corresponding to the jth quality control point of the ith procedure to the actual values of the process parameters influencing the breaking strength of the yarns and the process parameter values under the condition of optimal quality in the historical process design; b is a constant related to the quality control point; n represents the number of steps.
On the basis of the formula (9), a mass loss function of the jth quality control point of the ith procedure shown in the formula (10) is defined by combining a specific process flow of spinning production, namely:
Figure BDA0002164200650000233
wherein k isijIs a coefficient, and kij＝Aij/Δ2 ijWherein, isijTolerance limits for allowable process parameters of the apparatus, AijFor process parameters outside of tolerance Δ2 ijThe yarn breaking strength loss value; beta is aijFor multiple load-influencing factors, is a characteristic quality control point GijA coupling relationship variable with its upstream quality control point; y isijAnd ytRespectively representing the actual value of the process parameter and the target value of the control threshold function in the jth quality control point of the ith procedure; cmptIs a process capability index for indicating the fluctuation state of the process quality.
On the basis of equation (10), for each step in the cotton spinning process, there is a mass loss function as shown in equation (11), namely:
Figure BDA0002164200650000241
wherein, Ci(yij) Represents the mass loss value of the jth quality control point of the ith process, and j is 1,2, … pi，fi(x) Shows the mass loss function of the i-th spinning step.
The respective process mass loss function f defined in equation (11)i(x) On the basis of (1), the whole spinning process mass loss function can be expressed as the series relation of the mass loss functions corresponding to the quality control points of each process as shown in the formula (12), namely:
Π(f1(x),f2(x),...，fj(x),...，fn(x)) (12)
the formula (12) shows that the yarn quality can be regarded as a mass loss transmission and accumulation process taking the product as a carrier, so that the spinning quality control process can be regarded as an optimization process, and the optimal solution of the process parameters of each corresponding quality control point when the quality loss is minimum is obtained through continuous iteration and optimization solution.
Therefore, on the basis of the spinning quality control points and the coupling action relationship thereof defined above, an objective function for optimizing the quality in the spinning production process is established, namely:
Figure BDA0002164200650000242
on the basis, equations (9) - (12) are substituted into equation (13), and the obtained objective function is expanded to form a quality optimization model as shown in equation (14), namely:
Figure BDA0002164200650000251
through the solution of the quality optimization model, the spinning process parameters can be optimized, and the reject ratio of the yarns is reduced. And finally, further carrying out appropriate optimization adjustment and perfection on the spinning process by combining the yield data and the production energy consumption data.
Referring to fig. 6, the management steps of the intelligent management system for the intelligent spinning workshop according to the embodiment are as follows:
s1, inputting required quality data of a product from a data input module of the information processing system, and calculating by a cotton distribution unit of the data processing module according to the required quality data of the product to obtain a cotton distribution index;
s2, calculating by a process design unit of the data processing module according to the cotton blending index in the step S1 and the required quality data of the product to obtain initial regulation and control parameters of the spinning equipment of the intelligent spinning workshop;
the rough adjusting system of the environment control unit of the data processing module calculates to obtain initial regulation and control parameters of the air conditioning equipment of the intelligent spinning workshop according to the cotton distribution indexes, the required quality data of the product and the current environment temperature and humidity data in the step S1;
s3, the data output module outputs the initial regulation and control parameters of the spinning equipment and the air conditioning equipment in the intelligent spinning workshop in the step S2 to an information regulation and control system, and the information regulation and control system regulates and controls the operation of the spinning equipment and the air conditioning equipment in the intelligent spinning workshop according to the initial regulation and control parameters of the spinning equipment and the air conditioning equipment in the spinning workshop;
s4, in the running process of equipment in the intelligent spinning workshop, the information monitoring system monitors data in the intelligent spinning workshop in real time and sends the monitored data to a data input module of the information processing system;
s5, calculating by a process optimization unit of the data processing module according to the quality data, the yield data and the energy consumption data of production monitored in the step S4 to obtain optimized regulation and control parameters of spinning equipment of the intelligent spinning workshop;
the fine adjustment system of the environment control unit of the data processing module calculates according to the temperature and humidity data monitored in the step S4 to obtain real-time regulation and control parameters of the air conditioning equipment of the intelligent spinning workshop;
s6, the data output module outputs the optimized regulation and control parameters of the spinning equipment and the real-time regulation and control parameters of the air conditioning equipment in the intelligent spinning workshop in the step S5 to the information regulation and control system, and a spinning equipment regulation and control unit of the information regulation and control system regulates and controls the optimized operation of the spinning equipment in the intelligent spinning workshop according to the optimized regulation and control parameters of the spinning equipment in the spinning workshop;
and an air conditioning equipment regulating and controlling unit of the information regulating and controlling system regulates and controls the optimized operation of the air conditioning equipment in the intelligent spinning workshop according to the real-time regulating and controlling parameters of the spinning air conditioning equipment in the spinning workshop.
Further, the method for controlling the temperature and the humidity in the spinning workshop by the environment control unit specifically comprises the following steps:
s51, taking the moment of opening all spinning equipment in the spinning workshop as the starting time, recording the starting time as 0h, acquiring weather forecast information of the next local 0-24 h period through a wireless network by the coarse adjustment system, and extracting t from the weather forecast information1，t2，…，t24The ambient temperature and humidity data at that time are recorded as T1，T2，…，T24And M1，M2，…，M24；
S52, coarse adjustment is carried out on the system calling database module and t1Time temperature and humidity T1And M1Theoretical temperature and humidity control parameters under corresponding temperature and humidity conditions are used as preset temperature and humidity control parameters, and a rough adjustment indicating signal is sent to an air conditioning equipment regulating and controlling unit;
s53, the air conditioning equipment regulating and controlling unit controls the operation of the temperature regulating equipment and the humidity regulating equipment according to the rough regulating indication signal;
s54, receiving monitoring data of the temperature and humidity sensor in the spinning workshop by the fine adjustment system at the moment, and if the monitoring data are at t1In time, the temperature and humidity in the workshop are kept within the range of 20-31 ℃ and 55% -65%, and the fine adjustment system does not send an indication signal; if at t1Within the time, if the temperature and the humidity in the workshop are kept out of the upper limit value range and the lower limit value range, the fine adjustment system sends a fine adjustment indicating signal to the air conditioning equipment regulation and control unit;
s55, repeating the steps S52-S54, and sequentially aligning t through the rough adjustment system and the fine adjustment system2，t3，…，t24The air conditioning equipment regulation and control unit sends an indication signal at any moment;
s56, when t is reached24And then, the rough adjustment system acquires weather forecast information in the next round for 0-24 h, and repeats the steps S51-S55, so that the temperature and the humidity of the spinning workshop are continuously and intelligently regulated.
Further, in step S54, the method for adjusting the trimming system specifically includes: after receiving the monitoring data of the temperature and humidity sensor, the fine adjustment system firstly judges whether the temperature and humidity are within a limited range, and if so, a new indication signal is not required to be sent; if not, the method is divided into two conditions, wherein the first condition is that the temperature and humidity are higher than the upper limit value, the required temperature and humidity regulation and control parameters are calculated according to the difference between the temperature and the upper limit value, the second condition is that the temperature and the humidity are lower than the lower limit value, and the required temperature and humidity regulation and control parameters are calculated according to the difference between the temperature and the lower limit value.
Example 2
Referring to fig. 2, compared with embodiment 1, the intelligent management system for an intelligent spinning workshop provided in embodiment 2 is different in that a data processing module of the information processing system further includes a fault prediction unit, and the information regulation and control system further includes a fault alarm unit;
and the fault prediction unit predicts the fault of the equipment according to the running state data of the equipment, sends out a fault early warning signal in advance through the fault alarm unit and actively carries out shutdown maintenance on the equipment in an early warning mode.
Furthermore, the data processing module of the information processing system further comprises a fault diagnosis unit, which is used for judging whether the equipment has faults according to the running state data of the equipment; and sending out a fault warning signal through the fault alarm unit.
Furthermore, the database module stores position information corresponding to each sensor, each sensor corresponds to the position information of the sensor stored in the database module, and when yarn is broken or equipment fails, the data output module sends the position information of the corresponding sensor to the failure alarm unit.
Furthermore, the fault alarm unit has a voice broadcast function and can synchronously broadcast the position information of the sensor.
Further, the position information of the sensor is the position information of the device monitored by the sensor. As in practical applications, the marking of sensor location information may be accomplished by location numbering and marking the devices.
The method specifically comprises the following steps: the equipment of intelligent spinning workshop is numbered and the name is marked, if drawing equipment is marked as drawing equipment 1, drawing equipment 2, drawing equipment … and drawing equipment N, the marks are stored in the database module, the marks correspond to sensors of corresponding equipment respectively, and the drawing equipment with faults can be found out quickly through displaying or broadcasting according to the numbers.
Furthermore, the roving device, the spinning device and the winding device comprise a plurality of roving units, spinning units and winding units, so that each unit can be further subjected to position numbering and marking, and the position information of the spinning device or the spinning unit with faults is displayed or broadcasted in the form of numbers.
If one spinning device comprises 100 spinning units, each spinning unit is numbered and recorded as 1,2, … and 100, corresponding numbers and names are stored in the database module and respectively correspond to the sensors in sequence, and the spinning unit with yarn breakage or fault can be quickly found out through displaying or broadcasting the numbers.
Compared with the management steps of the intelligent management system of the intelligent spinning workshop provided by the embodiment 1, the management steps are different in that the fault prediction unit and the fault diagnosis unit perform fault prediction and fault diagnosis on the equipment according to the running state data of the equipment in the running process of the equipment, and send out a fault early warning signal and a fault warning signal through the fault alarm unit, so that the reduction of product quality and yield caused by equipment faults is prevented.
Other contents of embodiment 2 are substantially the same as those of embodiment 1, and are not described again here.
Example 3
Embodiment 3 is different from embodiment 2 in that the operation monitoring subunit of the opening and picking device includes a machine vision detection mechanism, and the rest is basically the same as embodiment 1, and is not repeated herein.
The cotton grabbing process has the main effects that the cotton grabbing process is used as a first process in the opening and picking process, raw cotton and fibers are grabbed and opened, the grabbed cotton blocks are required to be as small as possible for smooth proceeding of a subsequent spinning process, and the uniformity of the grabbed cotton blocks is as high as possible. Therefore, the operation monitoring subunit of the cotton opening and picking equipment identifies and extracts the image characteristics of the cotton bale appearance image, the cotton grabbing machine appearance image and the environment appearance image in the cotton grabbing working range through the machine vision detection mechanism, processes the image characteristics to obtain corresponding processing signals, realizes accurate identification and extraction of appearance characteristics, and further improves the accuracy of operation parameter design.
The machine vision detection mechanism processes the image characteristics of the cotton bale shape image to obtain a cotton bale surface flatness distribution signal; the machine vision detection mechanism processes the image characteristics of the cotton grabbing machine shape image to obtain a cotton grabbing machine operation position and operation state signal; and the machine vision detection mechanism judges a danger factor signal in the cotton grabbing working range according to the environmental morphology image characteristics in the cotton grabbing working range.
The process optimization unit can design corresponding operation parameters aiming at different cotton bale height areas by acquiring a cotton bale surface flatness distribution signal, so that the condition that the sizes of the captured cotton blocks are different due to the fact that the cotton bales are uneven and the operation parameters are the same is prevented; the fault diagnosis unit can judge whether the bale plucker has faults or not and can give a coping scheme in time by acquiring the running position and running state signals of the bale plucker; by acquiring the image characteristics of the environment morphology in the cotton grabbing working range, the data processing module can send emergency protective measures aiming at some dangerous signals, if people or other objects are in the cotton grabbing working range, an emergency stop instruction is sent, the occurrence of operation accidents is reduced, and the damage of foreign matters to equipment is also reduced.
Furthermore, the data processing module can also judge whether the cotton bale is completely grabbed through the cotton bale shape image, if the cotton bale is completely grabbed, the data processing module sends the control parameters of stopping operation and resetting of the cotton grabbing machine to the spinning equipment control unit through the data output module, and the cotton grabbing machine continues to operate after the next batch of cotton bales are placed.
The intelligent management system of the intelligent spinning workshop is based on an information network technology, integrates a sensor technology, a variable frequency speed regulation technology and the like, monitors the data of the whole spinning workshop in real time through the information monitoring system, processes the data in the spinning workshop through the information processing system to obtain the regulation and control parameters of the intelligent spinning workshop, regulates and controls the operation of equipment in the intelligent spinning workshop through the information regulation and control system, and realizes the automatic production and transportation control from raw materials to finished products and the online monitoring and control of the quality and the yield of the products.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.

Claims (23)

1. The utility model provides an intelligence spinning workshop intelligent management system which characterized in that includes:
the information monitoring system is used for monitoring data in the intelligent spinning workshop;
the information processing system is used for processing the data in the intelligent spinning workshop monitored by the information monitoring system to obtain the regulation and control parameters of the intelligent spinning workshop; and the combination of (a) and (b),
the information regulating and controlling system is used for regulating and controlling the operation of equipment in the intelligent spinning workshop according to the regulating and controlling parameters of the spinning workshop;
the regulation and control parameters of the spinning workshop comprise the regulation and control parameters of spinning equipment and the regulation and control parameters of air conditioning equipment;
the information regulation and control system comprises: the spinning equipment regulating and controlling unit is used for regulating and controlling the operation of the spinning equipment according to the regulating and controlling parameters of the spinning equipment; the air conditioning equipment regulating and controlling unit is used for regulating and controlling the operation of the air conditioning equipment according to the regulating and controlling parameters of the air conditioning equipment;
the information processing system comprises a data input module, a data processing module, a data output module and a data display module which are sequentially connected, and a database module which is respectively connected with the data input module and the data output module;
the database module is used for storing the data input by the data input module and the data output by the data output module; the data input module is used for inputting data monitored by the information monitoring system in the intelligent spinning workshop; the data processing module is used for processing the data input by the data input module to obtain the regulation and control parameters of the intelligent spinning workshop; the data output module comprises two output ports which are respectively used for outputting the regulation and control parameters of the spinning workshop to the information regulation and control system and outputting the regulation and control parameters to the data display module; the data display module is used for displaying the regulation and control parameters of the spinning workshop;
the data processing module of the information processing system comprises:
the cotton distribution unit is used for carrying out intelligent operation of cotton distribution composition according to the required quality data of the product;
the process design unit is used for carrying out intelligent operation on the regulation and control parameters of the spinning equipment according to the cotton blending index and the required quality data of the product; the environment control unit is used for carrying out intelligent operation on the regulation and control parameters of the air conditioning equipment according to the environment data;
the environment control unit comprises a coarse adjustment system and a fine adjustment system, the coarse adjustment system is used for presetting temperature and humidity control parameters in advance by acquiring environment temperature and humidity data in real time and sending a coarse adjustment indicating signal to the air conditioning equipment regulation and control unit; the fine adjustment system receives the monitoring data of the temperature and humidity sensor in real time and sends a fine adjustment indicating signal to the air conditioning equipment regulation and control unit in real time according to the real-time monitoring data of the temperature and humidity;
the control method of the coarse adjustment system and the fine adjustment system comprises the following steps:
s51, taking the moment of opening all spinning equipment in the spinning workshop as the starting time, recording the starting time as 0h, acquiring weather forecast information of the next local 0-24 h period through a wireless network by the coarse adjustment system, and extracting t from the weather forecast information1，t2，…，t24The ambient temperature and humidity data at that time are recorded as T1，T2，…，T24And M1，M2，…，M24；
S52, coarse adjustment is carried out on the system calling database module and t1Time temperature and humidity T1And M1Theoretical temperature and humidity control parameters under corresponding temperature and humidity conditions are used as preset temperature and humidity control parameters, and a rough adjustment indicating signal is sent to an air conditioning equipment regulating and controlling unit;
s53, the air conditioning equipment regulating and controlling unit controls the operation of the temperature regulating equipment and the humidity regulating equipment according to the rough regulating indication signal;
s54, receiving monitoring data of the temperature and humidity sensor in the spinning workshop by the fine adjustment system at the moment, and if the monitoring data are at t1In time, the temperature and humidity in the workshop are kept within the range of 20-31 ℃ and 55% -65%, and the fine adjustment system does not send an indication signal; if at t1Within the time, if the temperature and the humidity in the workshop are kept out of the upper limit value range and the lower limit value range, the fine adjustment system sends a fine adjustment indicating signal to the air conditioning equipment regulation and control unit;
s55, repeating the steps S52-S54, and sequentially aligning t through the rough adjustment system and the fine adjustment system2，t3，…，t24The air conditioning equipment regulation and control unit sends an indication signal at any moment;
s56, when t is reached24And then, the rough adjustment system acquires weather forecast information in the next round for 0-24 h, and repeats the steps S51-S55, so that the temperature and the humidity of the spinning workshop are continuously and intelligently regulated.
2. The intelligent management system for the spinning workshop according to claim 1, wherein the information monitoring system comprises:
the equipment operation monitoring module is used for monitoring the operation state data of the equipment;
the workshop environment monitoring module is used for monitoring environmental data in the intelligent spinning workshop;
the production quality monitoring module is used for monitoring the quality data of the product;
the production yield monitoring module is used for monitoring the yield data of the product; and the combination of (a) and (b),
and the production energy consumption monitoring module is used for monitoring the energy consumption data of production.
3. The intelligent management system for the intelligent spinning workshop according to claim 2, wherein the equipment operation monitoring module monitors and obtains operation state data of each equipment through a sensor arranged at the equipment;
the workshop environment monitoring module is used for monitoring and obtaining environmental data in the intelligent spinning workshop through a temperature sensor, a humidity sensor and a dust sensor which are arranged in the spinning workshop;
the production quality monitoring module monitors and obtains the quality data of the product through a quality monitoring device arranged at each spinning process;
the production yield monitoring module monitors and obtains the yield data of the product through yield monitoring devices arranged at each spinning process;
the production energy consumption monitoring module monitors and obtains the energy consumption data of production through energy consumption monitoring devices arranged in a power supply system and a water supply system.
4. The intelligent management system of an intelligent spinning workshop according to claim 3, wherein the device operation monitoring module comprises a spinning device operation monitoring unit and an air conditioning device operation monitoring unit, and the spinning device operation monitoring unit comprises an opening and picking device operation monitoring subunit, a carding device operation monitoring subunit, a drawing device operation monitoring subunit, a roving device operation monitoring subunit, a spinning device operation monitoring subunit, a spooling device operation monitoring subunit and a packaging device operation monitoring subunit.
5. An intelligent management system for an intelligent spinning workshop according to claim 1, wherein theoretical temperature and humidity control parameters are stored in the database when the upper limit value and the lower limit value of the temperature and humidity in the spinning workshop and the environmental temperature range are-5-40 ℃ and the humidity range is 0-99%.
6. The intelligent management system for the intelligent spinning workshop according to claim 1, wherein the data entry module comprises an intelligent entry port and a manual entry port, the intelligent entry port is used for entering data monitored by the information monitoring system in the intelligent spinning workshop, and the manual entry port is used for manually entering data.
7. The intelligent management system of an intelligent spinning workshop, according to claim 1, characterized in that the cotton distribution unit performs intelligent operation of cotton distribution composition by constructing a cotton distribution mathematical model, and the cotton distribution mathematical model establishes a multi-target-constrained cotton distribution mathematical model with the goals of minimum raw cotton cost and optimal cotton distribution index.
8. An intelligent management system for an intelligent spinning workshop according to claim 7, wherein the cotton blending indexes comprise a micronaire value, a maturity, an average length, a short fiber index, a breaking ratio strength and a nep index of raw cotton; the multi-target constraints comprise cotton distribution inventory constraints, total weight constraints, cotton distribution type constraints and cotton distribution index constraints.
9. The intelligent management system of an intelligent spinning workshop according to claim 1, wherein the data processing module of the information processing system further comprises a process optimization unit for performing optimization operation of the regulation and control parameters of the spinning equipment according to the quality data, the yield data and the energy consumption data of the product.
10. The intelligent management system of an intelligent spinning workshop according to claim 9, wherein the process optimization unit takes the quality data of the product as a first investigation index, establishes a quality optimization model based on multi-process knowledge association of the spinning process, and further optimizes the spinning process by combining the yield data and the production energy consumption data on the basis.
11. The intelligent management system for the intelligent spinning workshop according to claim 10, wherein the quality optimization model is constructed by the following steps:
(1) establishing quality control points in each process of the spinning process, and establishing a quality control point set;
(2) taking the breaking strength of the yarn as a key quality index, and constructing a quality loss function of each process and a quality loss function of the whole spinning process;
(3) obtaining the optimal solution of the process parameters of each corresponding quality control point when the quality loss is minimum through continuous iteration and optimization solution;
(4) on the basis of the spinning quality control point and the coupling action relationship thereof, establishing a quality optimizing objective function oriented to the spinning production process;
(5) and substituting the mass loss function of each process and the mass loss function of the whole spinning process into a mass optimizing objective function to form the mass optimizing model.
12. The intelligent management system for the intelligent spinning workshop according to claim 1, wherein a data processing module of the information processing system further comprises a fault prediction unit, and the information regulation and control system further comprises a fault alarm unit; and the fault prediction unit predicts the fault of the equipment according to the running state data of the equipment and sends out a fault early warning signal in advance through the fault alarm unit.
13. The intelligent management system for the intelligent spinning workshop according to claim 12, wherein the data processing module of the information processing system further comprises a fault diagnosis unit for judging whether the equipment is in fault according to the running state data of the equipment; and sending out a fault warning signal through the fault alarm unit.
14. An intelligent management system for an intelligent spinning workshop according to claim 12, wherein the database module is further stored with position information corresponding to each sensor, each sensor corresponds to the position information of the sensor stored in the database module, and when a yarn is broken or equipment fails, the data output module sends the position information of the corresponding sensor to the failure alarm unit.
15. The intelligent management system for the intelligent spinning workshop according to claim 5, wherein theoretical temperature and humidity control parameters in the database module are calculated according to flat-wall heat conduction, convection heat exchange and radiation heat exchange theories by taking standard temperature values and standard humidity values in the spinning workshop as references; the standard temperature value and the standard humidity value are respectively the middle values of the upper limit value and the lower limit value of the temperature and the humidity.
16. An intelligent management system for an intelligent spinning workshop according to claim 4, wherein the scutching equipment operation monitoring subunit comprises a machine vision detection mechanism for identifying and extracting image characteristics of a cotton bale shape image, a cotton plucker shape image and an environment shape image in a cotton plucking working range.
17. The intelligent management system for the intelligent spinning workshop according to claim 1, wherein the cotton blending composition comprises raw material types, quality data and composition proportions of the raw materials; the required quality data of the product comprises the required data of the linear density, the fineness, the twist and the breaking strength of the yarn.
18. The intelligent management system for the spinning workshop according to claim 9, wherein the quality data of the product comprise quality data of raw materials, quality data of semi-finished products of each process and quality data of finished yarns.
19. The intelligent management system of claim 18, wherein the quality data of the raw material comprises quality data of raw cotton and chemical fiber, the quality data of the semi-finished products of the processes comprises quality data of semi-finished products of an opening picking process, a carding process, a drawing process and a roving process, and the quality data of the finished yarn comprises quality data of finished yarn of a spinning process and a winding process.
20. The intelligent management system for the intelligent spinning workshop according to the claim 19, wherein the quality data of the raw cotton comprises a micronaire value, a maturity, an average length, a short fiber index, a breaking ratio strength and a nep index of the raw cotton, and the quality data of the chemical fiber comprises a chemical fiber moisture regain, a linear density, a cutting length and a breaking ratio strength; the quality data of the finished yarn comprises breaking strength, cotton nep number, fineness, twist and mass deviation value of hundred meters of the finished yarn.
21. An intelligent management system for an intelligent spinning workshop according to claim 3, wherein the operation state data of the equipment comprises operation state data of spinning equipment and operation state data of air conditioning equipment; the environmental data comprise temperature data, humidity data and air cleanliness data in the intelligent spinning workshop.
22. The intelligent management system of the intelligent spinning workshop according to claim 1, wherein the spinning equipment comprises opening and picking equipment, carding equipment, drawing equipment, roving equipment, spinning equipment, winding equipment and packaging equipment; the air conditioning equipment comprises dust removing equipment, temperature adjusting equipment and humidity adjusting equipment.
23. An intelligent spinning workshop management system according to any one of claims 7 to 22, wherein the intelligent spinning workshop management system comprises the following steps:
s1, inputting required quality data of a product from a data input module of the information processing system, and calculating by the data processing module according to the required quality data of the product to obtain a cotton distribution composition;
s2, calculating by the data processing module according to the cotton blending composition and the required quality data of the product in the step S1 to obtain initial regulation and control parameters of spinning equipment of the intelligent spinning workshop;
the data processing module calculates to obtain initial regulation and control parameters of the air conditioning equipment of the intelligent spinning workshop according to the cotton distribution indexes, the required quality data of the product and the current environmental temperature and humidity data in the step S1;
s3, the data output module outputs the initial regulation and control parameters of the spinning equipment and the air conditioning equipment of the intelligent spinning workshop in the step S2 to the information regulation and control system, and the information regulation and control system regulates and controls the operation of equipment in the intelligent spinning workshop according to the initial regulation and control parameters of the spinning equipment and the air conditioning equipment of the spinning workshop;
s4, in the running process of equipment in the intelligent spinning workshop, the information monitoring system monitors data in the intelligent spinning workshop in real time and sends the monitored data to a data input module of the information processing system;
s5, calculating by a process optimization unit of the data processing module according to the data monitored in the step S4 to obtain optimized regulation and control parameters of spinning equipment of the intelligent spinning workshop;
the environment control unit of the data processing module calculates according to the data monitored in the step S4 to obtain real-time regulation and control parameters of the air conditioning equipment of the intelligent spinning workshop;
s6, the data output module outputs the optimized regulation and control parameters of the spinning equipment and the real-time regulation and control parameters of the air conditioning equipment in the intelligent spinning workshop in the step S5 to the information regulation and control system, and a spinning equipment regulation and control unit of the information regulation and control system regulates and controls the optimized operation of the spinning equipment in the intelligent spinning workshop according to the optimized regulation and control parameters of the spinning equipment in the spinning workshop;
and an air conditioning equipment regulating and controlling unit of the information regulating and controlling system regulates and controls the optimized operation of the air conditioning equipment in the intelligent spinning workshop according to the real-time regulating and controlling parameters of the spinning air conditioning equipment in the spinning workshop.
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