CN111338307A - Production management system for warp knitting workshop of intelligent knitting factory - Google Patents

Production management system for warp knitting workshop of intelligent knitting factory Download PDF

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CN111338307A
CN111338307A CN202010173317.0A CN202010173317A CN111338307A CN 111338307 A CN111338307 A CN 111338307A CN 202010173317 A CN202010173317 A CN 202010173317A CN 111338307 A CN111338307 A CN 111338307A
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warp knitting
knitting machine
vibration
server
temperature
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CN111338307B (en
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王云良
顾卫杰
庄岳辉
王志骋
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Jiangsu Dabei Intelligent Technology Co ltd
Changzhou Vocational Institute of Mechatronic Technology
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Jiangsu Dabei Intelligent Technology Co ltd
Changzhou Vocational Institute of Mechatronic Technology
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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 belongs to the technical field of intelligent knitting factory production, and particularly relates to a production management system for a warp knitting workshop of an intelligent knitting factory, which comprises the following components: the system comprises a vibration sensor node, a temperature sensor node and a server; the vibration sensor node is suitable for detecting vibration signals of the warp knitting machine and sending the vibration signals to the server; the temperature sensor is suitable for detecting temperature data of the warp knitting machine and sending the temperature data to the server; the server is suitable for generating a working strategy according to the vibration signal and the temperature data, so that the intelligent production management of the intelligent knitting factory warp knitting workshop is realized, and the production efficiency of the fine knitting workshop is maximized.

Description

Production management system for warp knitting workshop of intelligent knitting factory
Technical Field
The invention belongs to the technical field of intelligent knitting factory production, and particularly relates to a production management system for a warp knitting workshop of an intelligent knitting factory.
Background
Most of the management of the intelligent knitting factory at the present stage mainly stays in the monitoring stage of production, the level of applying data to the intelligent production management of a workshop is not reached, and the intelligent and efficient production arrangement of the workshop cannot be realized by utilizing the data.
Therefore, based on the above technical problems, a new production management system for a knitting intelligent factory warp knitting workshop needs to be designed.
Disclosure of Invention
The invention aims to provide a production management system for a warp knitting workshop of an intelligent knitting factory.
In order to solve the technical problem, the invention provides a production management system for a warp knitting workshop of an intelligent knitting factory, which comprises:
the system comprises a vibration sensor node, a temperature sensor node and a server;
the vibration sensor node is suitable for detecting vibration signals of the warp knitting machine and sending the vibration signals to the server;
the temperature sensor is suitable for detecting temperature data of the warp knitting machine and sending the temperature data to the server;
the server is adapted to generate an operating strategy based on the vibration signal and the temperature data.
Further, the vibration sensor node includes: the device comprises a vibration sensor, a signal amplification circuit, an AD conversion module circuit, a first vibration microprocessor, a second vibration microprocessor and a vibration communication unit;
the vibration sensor is suitable for detecting a vibration signal of the warp knitting machine;
vibration signals detected by the vibration sensor are amplified by the signal amplification circuit and then input into the first vibration microprocessor through the AD conversion module circuit, the first vibration microprocessor sends signals converted by the AD conversion module circuit to the second vibration microprocessor, and the second vibration microprocessor sends the signals to the server through the vibration communication unit.
Further, the temperature sensor node includes: the temperature sensor, the temperature microprocessor and the temperature communication unit;
the temperature sensor is suitable for detecting temperature data of the warp knitting machine and sending the temperature data to the temperature microprocessor;
the temperature microprocessor is adapted to send temperature data to the server via the temperature communication unit.
Further, the production management system for the warp knitting workshop of the intelligent knitting factory further comprises: the system comprises a gateway and a display module connected with the gateway;
the gateway is suitable for forwarding vibration signals sent by the vibration sensor nodes and temperature data sent by the temperature sensor nodes to the server; and
the gateway is suitable for receiving the working strategy sent by the server and displaying the working strategy through the display module.
Further, the server is adapted to generate an operating strategy based on the vibration signal and the temperature data, i.e.
The server is suitable for obtaining a vibration signal mean value according to the vibration signal;
the server is suitable for acquiring a temperature mean value through temperature data; and
the server is adapted to record the total time the warp knitting machine has been in operation.
Further, the server is adapted to establish respective vectors from the data and historical data, i.e.
Constructing a fault parameter vector and a coefficient vector of the warp knitting machine;
the historical data includes: historical vibration signal mean value, historical temperature mean value and historical total working time of the warp knitting machine;
the warp knitting machine fault parameter vector is as follows: x ═ x(1),x(2),x(3),1)；
Wherein x is(1)As the mean value of the vibration signal, x(2)Is the mean value of temperature, x(3)The total working time of the warp knitting machine;
the coefficient vector is: w ═ w (w)(1),w(2),w(3),b)；
Wherein, w(1)Is the mean coefficient of the vibration signal, w(2)Is a temperature mean coefficient, w(3)B is the offset of the total working time coefficient of the warp knitting machine.
Further, the server is adapted to build a warp knitting machine running state model from the respective vectors, i.e.
The warp knitting machine running state model comprises:
Figure BDA0002409954960000031
wherein, wTIs the transposition of w; e is a natural constant;
the loss function is then:
Figure BDA0002409954960000032
wherein m is the number of data set samples; y is a category label which indicates two states of fault and no fault, and when y is 1, it indicates fault, and when y is 0, it indicates no fault; y is(i)A category label for the ith data;
iterating the loss function to obtain the best value of w when the loss function is minimized, the iterative function is:
Figure BDA0002409954960000033
where α denotes the step size.
Further, the server is adapted to set a set rotational speed of the warp knitting machine, i.e. the set rotational speed of the warp knitting machine, in accordance with the warp knitting machine operation state model
Figure BDA0002409954960000034
Figure BDA0002409954960000035
Figure BDA0002409954960000041
Figure BDA0002409954960000042
Wherein m is0Is as in class y-0The number of the books; m is1The number of samples in the category y is 1; mu.s1The mean value of the data obtained after the projection of the fault data on the w vector axis is obtained; mu.s0The mean value of data obtained after projection of the fault-free data on the w vector axis is obtained; delta0The standard deviation of data obtained after the projection of the fault-free data on the w vector axis is obtained; delta1The standard deviation of the data obtained after the projection of the fault data on the w vector axis is obtained;
Figure BDA0002409954960000043
Figure BDA0002409954960000044
xciis the current state of the ith warp knitting machine viThe set rotating speed of the ith warp knitting machine is as follows:
when wxci≤μ0+δ0At the set rotation speed v of the warp knitting machinehI.e. vi＝vh；
When wxci≥μ1-δ1At the set rotation speed v of the warp knitting machineLI.e. vi＝vL；
When mu is0+δ0≤wxci≤μ1-δ1In the meantime, the set rotation speed of the warp knitting machine is as follows:
Figure BDA0002409954960000045
wherein v ishThe upper limit of the highest rotating speed of the warp knitting machine; v. ofLThe lowest rotating speed lower limit of the warp knitting machine;
and when wxci＞μ1-2δ1And early warning is carried out to prompt maintenance of the warp knitting machine.
Further, the server is adapted to generate an operating strategy based on the rotational speed of the warp knitting machine and constraints, i.e.
Figure BDA0002409954960000046
Wherein n is the total number of warp knitting machines; l is the total number of orders; v. ofiSetting the rotating speed of the ith warp knitting machine; t is tkiProduction hours on the ith warp knitting machine for the kth order, k ∈ [1, l]；PksSelling a unit price for the kth order; pkrThe raw material unit price for the kth order; a is the loss value/unit yield of the warp knitting machine; t is trThe total working hours for operators; prPay per hour for the operating workers;
the constraint conditions include: constraint conditions of working time of an operator, constraint conditions of total amount of each order and constraint conditions of working time of each warp knitting machine;
the constraint conditions of the working time of the operator comprise:
Figure BDA0002409954960000051
wherein d is the number of warp knitting machines for each worker;
the constraint conditions of the total amount of each order comprise:
Figure BDA0002409954960000052
Figure BDA0002409954960000053
Figure BDA0002409954960000054
wherein q is1Amount of contract order for order 1; q. q.skThe volume of contract orders for the kth order; q. q.slThe volume of contract orders for the first order; t is t1iMan-hours on the ith warp knitting machine for the 1 st order; t is tliThe labor hour for the ith order on the ith warp knitting machine;
the constraint conditions of the working time of each warp knitting machine comprise:
Figure BDA0002409954960000055
Figure BDA0002409954960000056
Figure BDA0002409954960000057
wherein, TGiTo allow maximum working time of the warp knitting machine at the i-th stage of the production planning cycle, i ∈ [1, n ]]；
The working strategy comprises the following steps: the set rotating speed of each warp knitting machine, the optimal distribution working hour and the total working hour of operators, wherein each order is produced on the corresponding warp knitting machine;
obtaining the best distribution working hours t of different orders on different warp knitting machines according to the simplex methodkiAnd total man-hours t of operatorsrAnd Z is minimized.
The invention has the beneficial effects that the invention adopts the vibration sensor node, the temperature sensor node and the server; the vibration sensor node is suitable for detecting vibration signals of the warp knitting machine and sending the vibration signals to the server; the temperature sensor is suitable for detecting temperature data of the warp knitting machine and sending the temperature data to the server; the server is suitable for generating a working strategy according to the vibration signal and the temperature data, so that the intelligent production management of the intelligent knitting factory warp knitting workshop is realized, and the production efficiency of the fine knitting workshop is maximized.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic block diagram of a knitted intelligent factory warp knitting shop production management system in accordance with the present invention;
FIG. 2 is a functional block diagram of a vibration sensor node according to the present invention;
fig. 3 is a functional block diagram of a temperature sensor node according to the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Fig. 1 is a schematic block diagram of a production management system of a knitting intelligent factory warp knitting workshop according to the invention.
As shown in fig. 1, this embodiment 1 provides a production management system for a warp knitting shop of a knitting intelligent factory, which includes: the warp knitting machine vibration detection system comprises a vibration sensor node, a temperature sensor node and a server, wherein the vibration sensor node is suitable for detecting vibration signals of the warp knitting machine and sending the vibration signals to the server; the temperature sensor is suitable for detecting temperature data of the warp knitting machine and sending the temperature data to the server; the server is suitable for generating a working strategy according to the vibration signal and the temperature data, so that the intelligent production management of the intelligent knitting factory warp knitting workshop is realized, and the production efficiency of the fine knitting workshop is maximized.
Fig. 2 is a functional block diagram of a vibration sensor node according to the present invention.
As shown in fig. 2, in the present embodiment, the vibration sensor node includes: the device comprises a vibration sensor, a signal amplification circuit, an AD conversion module circuit, a first vibration microprocessor, a second vibration microprocessor and a vibration communication unit; the first vibration microprocessor may be, but is not limited to, a DSP from TI corporation: TMS320C 6748; the second vibratory microprocessor may be, but is not limited to, CC2530 from TI, Inc.; the vibration communication unit may be, but is not limited to, a ZigBee module; the vibration sensor is suitable for detecting a vibration signal of the warp knitting machine; the vibration signal detected by the vibration sensor is amplified by the signal amplifying circuit and then is input into the first vibration microprocessor through the AD conversion module circuit, and the signal converted by the AD conversion module circuit is sent to the second vibration microprocessor by the first vibration microprocessor and is sent to the server by the second vibration microprocessor through the vibration communication unit; the server is suitable for obtaining a vibration signal mean value through the vibration signal, and the vibration signal mean value is used as one of important characteristics of training data to train and obtain the running state model of the warp knitting machine.
In this embodiment, the vibration sensor node further includes: and the SD card is electrically connected with the first vibration microprocessor and used for storing vibration signals.
Fig. 3 is a functional block diagram of a temperature sensor node according to the present invention.
As shown in fig. 3, in the present embodiment, the temperature sensor node includes: the temperature sensor, the temperature microprocessor and the temperature communication unit; the temperature microprocessor can adopt but not limited to STM32 series single-chip microcomputer; the temperature communication unit can be but is not limited to adopt a ZigBee module; the temperature sensor is suitable for detecting temperature data of the warp knitting machine and sending the temperature data to the temperature microprocessor; the temperature microprocessor is suitable for sending temperature data to the server through the temperature communication unit; the server is suitable for obtaining the temperature mean value through the temperature data.
In this embodiment, the production management system for a warp knitting shop of a knitting intelligent factory further includes: the system comprises a gateway and a display module connected with the gateway; the display module can be but is not limited to a display screen; when the vibration sensor node and the temperature sensor node are communicated by adopting the ZigBee module, the gateway can adopt a ZigBee gateway; the gateway is suitable for forwarding vibration signals sent by the vibration sensor nodes and temperature data sent by the temperature sensor nodes to the server; and the gateway is suitable for receiving the working strategy sent by the server and displaying the working strategy through the display module.
Knitting intelligent factory warp knitting workshop production management system still includes: a clock circuit and an input module; the input module may be, but is not limited to, a keyboard; the clock circuit is electrically connected with the gateway; the clock circuit can synchronize time and record the time when recording data; the input module and the display module are used for a human-computer interface to input and display information.
In this embodiment, the server is adapted to generate an operation strategy according to the vibration signal and the temperature data, that is, the server is adapted to obtain a mean value of the vibration signal according to the vibration signal; the server is suitable for acquiring a temperature mean value through temperature data; and the server is adapted to record the total time the warp knitting machine has been in operation.
In the embodiment, the server is suitable for establishing corresponding vectors according to the data and the historical data, namely establishing a warp knitting machine fault parameter vector and a coefficient vector; the historical data includes: historical vibration signal mean value, historical temperature mean value and historical total working time of the warp knitting machine; the warp knitting machine fault parameter vector is as follows: x ═ x(1),x(2),x(3)1); wherein x is(1)As the mean value of the vibration signal, x(2)Is the mean value of temperature, x(3)The total working time of the warp knitting machine; the coefficient vector is: w ═ w (w)(1),w(2),w(3)B); wherein, w(1)Is the mean coefficient of the vibration signal, w(2)Is a temperature mean coefficient, w(3)B is the offset of the total working time coefficient of the warp knitting machine.
In this embodiment, the server is adapted to build a warp knitting machine running state model from the respective vectors, i.e.
The warp knitting machine running state model comprises:
let the function be:
Figure BDA0002409954960000091
wherein, wTIs the transposition of w; e is a natural constant, is a constant in mathematics, is an infinite acyclic decimal number, is an transcendental number, and has a value of about 2.71828;
the loss function is then:
Figure BDA0002409954960000092
wherein m is the number of data set samples; y is a category label which indicates two states of fault and no fault, and when y is 1, it indicates fault, and when y is 0, it indicates no fault; y is(i)A category label for the ith data;
iterating the loss function by using a gradient descent method to obtain an optimal value of w when the loss function j (w) is minimized, wherein the iteration function is as follows:
Figure BDA0002409954960000101
α represents a step length, α is 0.1, the step length keeps moderate iteration speed, iteration is not too fast and an optimal solution can not be missed, the iteration speed is not too slow and the iteration can not be finished, an initial value w is set to be (1, 1.5, 2, 1), the above preset initial values of coefficients in the iteration are beneficial to improving the opportunity of obtaining the global optimal solution, and the repeated iteration calculation time R is 800.
In the embodiment, the server is suitable for setting the set rotating speed of the warp knitting machine according to the running state model of the warp knitting machine, namely the running state model of the warp knitting machine can be used for fault prediction, and the set rotating speed of the warp knitting machine can be obtained on the basis of the running state model of the warp knitting machine; for the working conditionThe upper limit of the set maximum rotating speed is determined as vh(ii) a For the warp knitting machine with poor working state, the lower limit of the set minimum rotating speed is determined to be vL,
Figure BDA0002409954960000102
Figure BDA0002409954960000103
Figure BDA0002409954960000104
Figure BDA0002409954960000105
Wherein m is0The number of samples of which the category y is 0; m is1The number of samples in the category y is 1; mu.s1The mean value of the data obtained after the projection of the fault data on the w vector axis is obtained; mu.s0The mean value of data obtained after projection of the fault-free data on the w vector axis is obtained; delta0The standard deviation of data obtained after the projection of the fault-free data on the w vector axis is obtained; delta1The standard deviation of the data obtained after the projection of the fault data on the w vector axis is obtained;
Figure BDA0002409954960000106
Figure BDA0002409954960000111
xciis the current state of the ith warp knitting machine viThe set rotating speed of the ith warp knitting machine is as follows:
when wxci≤μ0+δ0At the time, the set rotational speed of the warp knitting machine is v, i.e., vi＝vh；
When wxci≥μ1-δ1At the set rotation speed v of the warp knitting machineLI.e. vi＝vL；
When mu is0+δ0≤wxci≤μ1-δ1In the meantime, the set rotation speed of the warp knitting machine is as follows:
Figure BDA0002409954960000112
wherein v ishThe upper limit of the highest rotating speed of the warp knitting machine; v. ofLThe lowest rotating speed lower limit of the warp knitting machine; exp is an exponential function with e as the base;
and when wxci＞μ1-2δ1Early warning is carried out to prompt maintenance of the warp knitting machine; according to different running states of the warp knitting machines, the set rotating speed suitable for each warp knitting machine is set, so that the total loss of the warp knitting machines is reduced to the maximum extent, and the total maintenance cost of a warp knitting workshop is reduced.
In this embodiment, the server is adapted to generate an operating strategy based on the rotational speed of the warp knitting machine and constraints, i.e.
Figure BDA0002409954960000113
Wherein minZ is the minimum value of the target function Z; n is the total number of warp knitting machines; l is the total number of orders; v. ofiSet rotation speed i ∈ [1, n ] for the ith warp knitting machine]；tkiProduction hours on the ith warp knitting machine for the kth order, k ∈ [1, l]；PksSelling a unit price for the kth order; pkrThe raw material unit price for the kth order; a is the loss value/unit yield of the warp knitting machine and can be set according to experience; t is trThe total working hours for operators; prPay per hour for the operating workers; wherein t iskiAnd trFor decision variables to be found, tki≥0，tr≥0；
The constraint conditions include: constraint conditions of working time of an operator, constraint conditions of total amount of each order and constraint conditions of working time of each warp knitting machine;
the constraint conditions of the working time of the operator comprise:
Figure BDA0002409954960000121
wherein d is the number of warp knitting machines responsible for each operator, can be set according to experience and adjusted according to actual conditions, and if d is set to be 5, 6 or 7;
the constraint conditions of the total amount of each order comprise:
Figure BDA0002409954960000122
Figure BDA0002409954960000123
Figure BDA0002409954960000124
wherein q is1Amount of contract order for order 1; q. q.skThe volume of contract orders for the kth order; q. q.slThe volume of contract orders for the first order; t is t1iMan-hours on the ith warp knitting machine for the 1 st order; t is tliThe labor hour for the ith order on the ith warp knitting machine;
the constraint conditions of the working time of each warp knitting machine comprise:
Figure BDA0002409954960000125
Figure BDA0002409954960000126
Figure BDA0002409954960000127
wherein, TGiTo allow maximum working time of the warp knitting machine at the i-th stage of the production planning cycle, i ∈ [1, n ]]；
The working strategy comprises the following steps: the set rotating speed of each warp knitting machine, the optimal distribution working hour and the total working hour of operators, wherein each order is produced on the corresponding warp knitting machine; obtaining the best distribution working hours t of different orders on different warp knitting machines according to the simplex methodkiAnd total man-hours t of operatorsrMinimizing Z; solving the linear programming problem by using a simplex method, firstly finding out a basic feasible solution, and identifying the basic feasible solution to see whether the solution is the optimal solution; if not, switching to another improved basic feasible solution and then identifying; if not, the conversion is carried out again, and the conversion is carried out repeatedly according to the above steps, so that the optimal solution of the problem can be obtained through the limited conversion because the number of the basically feasible solutions is limited; according to the optimal set rotating speed which is currently set by the warp knitting machine, linear programming is carried out by combining data such as intelligent orders, sales, raw materials, human capital and the like, and the optimal distribution working hours t of different orders on different warp knitting machines is givenkiAnd total man-hours t of operatorsrThe highest production flow efficiency of the production orders of the warp knitting workshop is realized; the intelligent production management of the intelligent warp knitting workshop of the knitting factory is realized, and the production efficiency of the fine knitting workshop is maximized.
In summary, the invention uses the vibration sensor node, the temperature sensor node and the server; the vibration sensor node is suitable for detecting vibration signals of the warp knitting machine and sending the vibration signals to the server; the temperature sensor is suitable for detecting temperature data of the warp knitting machine and sending the temperature data to the server; the server is suitable for generating a working strategy according to the vibration signal and the temperature data, so that the intelligent production management of the intelligent knitting factory warp knitting workshop is realized, and the production efficiency of the fine knitting workshop is maximized.
In the embodiments provided in the present application, it should be understood that the disclosed system may be implemented in other ways. The system embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.

Claims (9)

1. The utility model provides a knitting intelligent factory warp knitting workshop production management system which characterized in that includes:
the system comprises a vibration sensor node, a temperature sensor node and a server;
the vibration sensor node is suitable for detecting vibration signals of the warp knitting machine and sending the vibration signals to the server;
the temperature sensor is suitable for detecting temperature data of the warp knitting machine and sending the temperature data to the server;
the server is adapted to generate an operating strategy based on the vibration signal and the temperature data.
2. The intelligent factory warp knitting shop production management system of claim 1,
the vibration sensor node includes: the device comprises a vibration sensor, a signal amplification circuit, an AD conversion module circuit, a first vibration microprocessor, a second vibration microprocessor and a vibration communication unit;
the vibration sensor is suitable for detecting a vibration signal of the warp knitting machine;
vibration signals detected by the vibration sensor are amplified by the signal amplification circuit and then input into the first vibration microprocessor through the AD conversion module circuit, the first vibration microprocessor sends signals converted by the AD conversion module circuit to the second vibration microprocessor, and the second vibration microprocessor sends the signals to the server through the vibration communication unit.
3. The intelligent factory warp knitting shop production management system of claim 1,
the temperature sensor node includes: the temperature sensor, the temperature microprocessor and the temperature communication unit;
the temperature sensor is suitable for detecting temperature data of the warp knitting machine and sending the temperature data to the temperature microprocessor;
the temperature microprocessor is adapted to send temperature data to the server via the temperature communication unit.
4. The intelligent factory warp knitting shop production management system of claim 1,
knitting intelligent factory warp knitting workshop production management system still includes: the system comprises a gateway and a display module connected with the gateway;
the gateway is suitable for forwarding vibration signals sent by the vibration sensor nodes and temperature data sent by the temperature sensor nodes to the server; and
the gateway is suitable for receiving the working strategy sent by the server and displaying the working strategy through the display module.
5. The intelligent factory warp knitting shop production management system of claim 1,
the server is adapted to generate an operating strategy based on the vibration signal and the temperature data, i.e.
The server is suitable for obtaining a vibration signal mean value according to the vibration signal;
the server is suitable for acquiring a temperature mean value through temperature data; and
the server is adapted to record the total time the warp knitting machine has been in operation.
6. The intelligent factory warp knitting shop production management system of claim 5,
the server is adapted to establish corresponding vectors from the data and historical data, i.e.
Constructing a fault parameter vector and a coefficient vector of the warp knitting machine;
the historical data includes: historical vibration signal mean value, historical temperature mean value and historical total working time of the warp knitting machine;
the warp knitting machine fault parameter vector is as follows: x ═ x(1),x(2),x(3),1)；
Wherein x is(1)As the mean value of the vibration signal, x(2)Is the mean value of temperature, x(3)The total working time of the warp knitting machine;
the coefficient vector is: w ═ w (w)(1),w(2),w(3),b)；
Wherein, w(1)Is the mean coefficient of the vibration signal, w(2)Is a temperature mean coefficient, w(3)B is the offset of the total working time coefficient of the warp knitting machine.
7. The intelligent factory warp knitting shop production management system of claim 6,
the server is adapted to build a model of the operating state of the warp knitting machine from the respective vectors, i.e.
The warp knitting machine running state model comprises:
Figure FDA0002409954950000021
wherein, wTIs the transposition of w; e is a natural constant;
the loss function is then:
Figure FDA0002409954950000031
wherein m is the number of data set samples; y is a category label which indicates two states of fault and no fault, and when y is 1, it indicates fault, and when y is 0, it indicates no fault; y is(i)A category label for the ith data;
iterating the loss function to obtain the best value of w when the loss function is minimized, the iterative function is:
Figure FDA0002409954950000032
where α denotes the step size.
8. The intelligent factory warp knitting shop production management system of claim 7,
the server is adapted to set a set rotational speed of the warp knitting machine according to a model of an operational state of the warp knitting machine, i.e. a set rotational speed of the warp knitting machine
Figure FDA0002409954950000033
Figure FDA0002409954950000034
Figure FDA0002409954950000035
Figure FDA0002409954950000036
Wherein m is0The number of samples of which the category y is 0; m is1The number of samples in the category y is 1; mu.s1The mean value of the data obtained after the projection of the fault data on the w vector axis is obtained; mu.s0The mean value of data obtained after projection of the fault-free data on the w vector axis is obtained; delta0The standard deviation of data obtained after the projection of the fault-free data on the w vector axis is obtained; delta1The standard deviation of the data obtained after the projection of the fault data on the w vector axis is obtained;
Figure FDA0002409954950000037
Figure FDA0002409954950000041
xciis the current state of the ith warp knitting machine viThe set rotating speed of the ith warp knitting machine is as follows:
when wxci≤μ0+δ0At the set rotation speed v of the warp knitting machinehI.e. vi＝vh；
When wxci≥μ1-δ1At the set rotation speed v of the warp knitting machineLI.e. vi＝vL；
When mu is0+δ0≤wxci≤μ1-δ1In the meantime, the set rotation speed of the warp knitting machine is as follows:
Figure FDA0002409954950000042
wherein v ishThe upper limit of the highest rotating speed of the warp knitting machine; v. ofLThe lowest rotating speed lower limit of the warp knitting machine;
and when wxci＞μ1-2δ1And early warning is carried out to prompt maintenance of the warp knitting machine.
9. The intelligent factory warp knitting shop production management system of claim 8,
the server is adapted to generate an operating strategy based on the rotational speed and constraints of the warp knitting machine, i.e.
Figure FDA0002409954950000043
Wherein n is the total number of warp knitting machines; l is the total number of orders; v. ofiSetting the rotating speed of the ith warp knitting machine; t is tkiProduction hours on the ith warp knitting machine for the kth order, k ∈ [1, l]；PksSelling a unit price for the kth order; pkrThe raw material unit price for the kth order; a is the loss value/unit yield of the warp knitting machine; t is trThe total working hours for operators; prPay per hour for the operating workers;
the constraint conditions include: constraint conditions of working time of an operator, constraint conditions of total amount of each order and constraint conditions of working time of each warp knitting machine;
the constraint conditions of the working time of the operator comprise:
Figure FDA0002409954950000044
wherein d is the number of warp knitting machines for each worker;
the constraint conditions of the total amount of each order comprise:
Figure FDA0002409954950000051
Figure FDA0002409954950000052
Figure FDA0002409954950000053
wherein q is1Amount of contract order for order 1; q. q.skThe volume of contract orders for the kth order; q. q.slThe volume of contract orders for the first order; t is t1iMan-hours on the ith warp knitting machine for the 1 st order; t is tliThe labor hour for the ith order on the ith warp knitting machine;
the constraint conditions of the working time of each warp knitting machine comprise:
Figure FDA0002409954950000054
Figure FDA0002409954950000055
Figure FDA0002409954950000056
wherein, TGiTo allow maximum working time of the warp knitting machine at the i-th stage of the production planning cycle, i ∈ [1, n ]]；
The working strategy comprises the following steps: the set rotating speed of each warp knitting machine, the optimal distribution working hour and the total working hour of operators, wherein each order is produced on the corresponding warp knitting machine;
obtaining the best distribution working hours t of different orders on different warp knitting machines according to the simplex methodkiAnd total man-hours t of operatorsrAnd Z is minimized.
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