CN108910177A - A kind of intelligent control method of bag-feeding Fully-automatic food packing machine - Google Patents
A kind of intelligent control method of bag-feeding Fully-automatic food packing machine Download PDFInfo
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- CN108910177A CN108910177A CN201810859719.9A CN201810859719A CN108910177A CN 108910177 A CN108910177 A CN 108910177A CN 201810859719 A CN201810859719 A CN 201810859719A CN 108910177 A CN108910177 A CN 108910177A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65B—MACHINES, APPARATUS OR DEVICES FOR, OR METHODS OF, PACKAGING ARTICLES OR MATERIALS; UNPACKING
- B65B57/00—Automatic control, checking, warning, or safety devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65B—MACHINES, APPARATUS OR DEVICES FOR, OR METHODS OF, PACKAGING ARTICLES OR MATERIALS; UNPACKING
- B65B37/00—Supplying or feeding fluent-solid, plastic, or liquid material, or loose masses of small articles, to be packaged
- B65B37/16—Separating measured quantities from supply
- B65B37/18—Separating measured quantities from supply by weighing
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65B—MACHINES, APPARATUS OR DEVICES FOR, OR METHODS OF, PACKAGING ARTICLES OR MATERIALS; UNPACKING
- B65B43/00—Forming, feeding, opening or setting-up containers or receptacles in association with packaging
- B65B43/42—Feeding or positioning bags, boxes, or cartons in the distended, opened, or set-up state; Feeding preformed rigid containers, e.g. tins, capsules, glass tubes, glasses, to the packaging position; Locating containers or receptacles at the filling position; Supporting containers or receptacles during the filling operation
- B65B43/52—Feeding or positioning bags, boxes, or cartons in the distended, opened, or set-up state; Feeding preformed rigid containers, e.g. tins, capsules, glass tubes, glasses, to the packaging position; Locating containers or receptacles at the filling position; Supporting containers or receptacles during the filling operation using roller-ways or endless conveyors
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Microelectronics & Electronic Packaging (AREA)
- General Preparation And Processing Of Foods (AREA)
Abstract
A kind of intelligent control method of bag-feeding Fully-automatic food packing machine, including：A. the voice confirmation method based on Dynamic Ranking Information is used, speech recognition system is established, by voice control, completes to provide the task of packaging bag to bag machine；B. food is weighed using intelligent food Weighting and Controlling System, the food of weight qualification is entered into bag encapsulation, is sent to video surveillance region；C. Image Multiscale clustering method is used, analysis is monitored to food packaging video image, rejects substandard product in time, completes the Detection task of device of full automatic packaging；D., infrared sensor is set, the workload of packing machine is counted, and according to the testing result of packaging, calculates the bad product rate of product, according to the rate of tension of the variation adjustment idler wheel of bad product rate, completes the intelligent control task of foods packing machine.This method has flexibility and stability, and can be according to current food type, and intelligence adjusts the use specification of each equipment, reliablely and stablely completes the intelligent control task of packing machine.
Description
Technical field
The present invention relates to a kind of intelligent control methods of bag-feeding Fully-automatic food packing machine, belong to artificial intelligence, calculate
Machine and automation control area.
Background technique
Demand with every profession and trade to production automation, food packaging applications have developed various automatic packaging machineries.When
Preceding bag-feeding Fully-automatic food packing machine, only realizes automated production, can not be according to the real-time feelings in production process
Condition makes intelligentized adjustment.Existing foods packing machine can not adjust mechanical equipment according to the variation of packaging product, intelligence
Production specification；Biggish error is generated for the Weighting and Controlling of food, accuracy is low；Lack dedicated product counting equipment；
Due to the presence of drawbacks described above, cause the production efficiency of packing machine low.
In view of the above-mentioned problems, the present invention is using Dynamic Ranking audio recognition method, intelligent food weigher, multiple dimensioned cluster
Analysis and infrared sensor device complete the intelligent control task of bag-feeding Fully-automatic food packing machine.
Summary of the invention
To solve the above problems, itself there is ability of regulation and control the purpose of the present invention is to provide a kind of, and stability is strong
Bag-feeding Fully-automatic food packing machine intelligent control method.
The present invention solves the problems, such as technical solution used by it, includes the following steps：
A kind of intelligent control method of bag-feeding Fully-automatic food packing machine, it is characterised in that：The method includes following
Step：
A. the voice confirmation method based on Dynamic Ranking Information is used, speech recognition system is established, it is complete by voice control
The task of packaging bag is provided to bag machine；
B. food is weighed using intelligent food Weighting and Controlling System, the food of weight qualification is entered into bag encapsulation, and pass through
Conveyer belt is sent to video surveillance region；
C. Image Multiscale clustering method is used, analysis is monitored to the video image of food packaging, and in time
Substandard product is rejected, the Detection task of device of full automatic packaging is completed；
D., infrared sensor is set, the workload of packing machine is counted, and according to the testing result of packaging, calculates product
Bad product rate completes the intelligent control task of foods packing machine according to the rate of tension of the variation adjustment idler wheel of bad product rate.
Further, the step A includes：
(1) one section of voice is obtained first, voice is parsed using Viterbi algorithm, according in speech recognition network
Keyword models, confirm voice messaging in keyword；
1. inputting the voice V={ v of one section of S frame1,v2,…,vS, this section of voice is recognized by the system as keyword, identification net
Contain T keyword models Mode={ mode in network1,mode2,…,modeT}；
2. system parses voice messaging, each frame voice messaging corresponds to a state of keyword models, crucial
The status switch of word model is determined by its internal state arrangement；
(2) according to the corresponding probability likelihood ratio score value of keyword in voice, the Dynamic Ranking point of whole section of voice is calculated
Number, and pass through the separating capacity of identification anti-keyword enhancing system；
1. assuming the s frame v in voicesIn t-th of model modetIn state be Statets, then probability likelihood ratio obtains
Score value is
Lt(vs)=logP (vs|Statets, t=1,2 ..., M) M≤T
Wherein, M indicates Number of Models when carrying out local calculation, then voice vsDescending arrangement in each model can
It is expressed as
2. the Dynamic Ranking Information score of whole section of voice is the cumulative of voice Ranking Information score in all frame levels, can indicate
For
Wherein, Lframe(s) the voice Ranking Information score in a frame level is indicated；
3. dynamic is arranged using geometric average method using most probably anti-keyword identification model is obtained like estimation technique training
In conjunction with the likelihood ratio score of anti-keyword identification model, relationship is position information score
Wherein, (0,1) θ ∈,Indicate anti-keyword Dynamic Ranking Information score；According to the sequence knot of composite score
Fruit, effectively identification voice messaging；
(4) according to the confirmation of voice and identification, the keyword in voice messaging is obtained, is controlled according to keyword and gives bag machine work
Make, bag task is given in completion.
Further, the step B includes：
(1) it establishes intelligent food Weighting and Controlling System, is arranged and the food weight that provides food and be consistent for controller first
Amount, triggering control batcher, is sent to meausring apparatus for food, then exports and feed back the information of output, be conveniently adjusted food
The setting value of product weight；
It (2) is the accuracy and rapidity that guarantee feed, system uses Discrete control method, feeding process is divided into quickly
Two stages at a slow speed；
1. running by feeding controller iteration, the deviation between target value and output valve is effectively controlled；
2. formulating tracking aim curve, the suitable time point for carrying out rate conversion is found, to improve the accurate of feed
Property；
(4) according to intelligent control and reasonable Discrete control, the weighing task of food is quickly and accurately completed, by weight
Qualified product encapsulate into bag, is sent to video surveillance region finally by transmission device.
Further, the step C includes：
(1) picture on surface of food pack and sealing in video image are analyzed according to multiple dimensioned clustering method, with number
According to the variation of luminous point, the picture structure in video is divided；
1. if with one group of data point set Data={ d1,d2,…,dM}∈Rl(M indicates data point number, and d indicates picture number
Strong point, RlRepresentation space point set) indicate detection video image, then image in space is represented by
Wherein, δ (d-di) (i=1,2 ..., M) be Dick draw generalized function, be expressed as image luminous point；
2. with the Convolution Analysis video image of the image template of different scale and Gaussian function, Gaussian function is Indicate that the peak value of Gaussian curve, c indicate that scale parameter, T indicate transposition,
Convolution relation formula is represented by
(2) change the clustering for carrying out image according to light spot dimension, result is packed according to the clustering recognition of image；
1. the variation of each luminous point has certain range scale, when dimensional variation arrives the minimum value less than variation range,
The luminous point is broken down into multiple small luminous points, conversely, then luminous point and other luminous points are warm；
2. specific step is as follows for clustering：
(a) light spot dimension is initialized, when scale is sufficiently small, each data point is a center, to generate one
Class；
(b) when cluster proceeds to the i-th step, make ci+1=(u+1) ci, the value of u passes through psychophysics according to Weber law
Means are chosen, when scale is ciWhen, if optical spot centre is center (ci), if scale is ciOptical spot centre fall in scale be ci+1
Spot dimensions in, then luminous point C (center (ci)) class be divided into luminous point C (center'(ci+1)) class in；
If luminous point is c in scale there are two (c) or moreiWhen optical spot centre, fall into same luminous point, then when luminous point ruler
Degree increases to ci+1When, these luminous points are dissolved into same class, and the process is recycled, until all data all incorporate in same class, are tied
Beam cluster；
3. identifying the packaging knot of the packaging bag according to the comparing result of image in cluster image and baling line correction procedure
Fruit；
(4) if the underproof food of packaging occur through detection sends it to corresponding transmission according to underproof reason
Band melt down remaking by conveyer belt.
Further, the step D includes：
(1) using infrared refraction, the property of reflection, the product number after packing machine work is counted；Using one
The counting circuit that kind is made of infrared emission tube and reception pipe, carries out accurate Counts under natural light；
Sensor is installed in the two sides for completing the food transmission device of packaging, conveyer belt side is the transmitting tube discharged up and down
And reception pipe, the other side are the baffles that can reflect infrared ray, complete product counting task using this device；
(2) according to the variation of bad product rate, the rate of tension of packing machine idler wheel is adjusted, the intelligent control for completing packing machine is appointed
Business；
1. bad products are counted, according to formula according to the cluster analysis result of food packagingIt calculates bad
Product rate, wherein N indicates the workload of packing machine, NumberrejIndicate substandard product number, p indicates bad product rate；
2. the threshold value of bad product rate is set, according to bad product rate compared with threshold value for the working efficiency for guaranteeing packing machine
As a result, the rate of tension of intelligent control packing machine idler wheel, improves the working efficiency of packing machine.
The beneficial effects of the invention are as follows：
In complicated and rigorous intelligent control task, the present invention can flexibly, stably accomplish regulation task, and can root
According to current food type, intelligence adjusts use the specification of each equipment, accurately the weighing of control food, packaging, detection and
Link is counted, with the good beneficial effect of high sensitivity, robustness.
Detailed description of the invention
Fig. 1 is the overall flow figure of a kind of intelligent control method of bag-feeding Fully-automatic food packing machine；
Fig. 2 is intelligent food Weighting and Controlling System schematic diagram；
Fig. 3 is food packaging detection device schematic diagram；
Fig. 4 is infrared sensor schematic diagram；
Specific embodiment
Referring to Fig.1, method of the present invention includes the following steps：
A. the voice confirmation method based on Dynamic Ranking Information is used, speech recognition system is established, it is complete by voice control
The task of packaging bag is provided to bag machine；
(1) one section of voice is obtained first, voice is parsed using Viterbi algorithm, according in speech recognition network
Keyword models, confirm voice messaging in keyword；
1. inputting the voice V={ v of one section of S frame1,v2,…,vS, this section of voice is recognized by the system as keyword, identification net
Contain T keyword models Mode={ mode in network1,mode2,…,modeT}；
2. system parses voice messaging, each frame voice messaging corresponds to a state of keyword models, crucial
The status switch of word model is determined by its internal state arrangement；
(2) according to the corresponding probability likelihood ratio score value of keyword in voice, the Dynamic Ranking point of whole section of voice is calculated
Number, and pass through the separating capacity of identification anti-keyword enhancing system；
1. assuming the s frame v in voicesIn t-th of model modetIn state be Statets, then probability likelihood ratio obtains
Score value is
Lt(vs)=logP (vs|Statets, t=1,2 ..., M) M≤T
Wherein, M indicates Number of Models when carrying out local calculation, then voice vsDescending arrangement in each model can
It is expressed as
2. the Dynamic Ranking Information score of whole section of voice is the cumulative of voice Ranking Information score in all frame levels, can indicate
For
Wherein, Lframe(s) the voice Ranking Information score in a frame level is indicated.
3. dynamic is arranged using geometric average method using most probably anti-keyword identification model is obtained like estimation technique training
In conjunction with the likelihood ratio score of anti-keyword identification model, relationship is position information score
Wherein, (0,1) θ ∈,Indicate anti-keyword Dynamic Ranking Information score；According to the sequence knot of composite score
Fruit, effectively identification voice messaging；
(3) according to the confirmation of voice and identification, the keyword in voice messaging is obtained, is controlled according to keyword and gives bag machine work
Make, bag task is given in completion；
B. food is weighed using intelligent food Weighting and Controlling System, the food of weight qualification is entered into bag encapsulation, and pass through
Conveyer belt is sent to video surveillance region；
(1) intelligent food Weighting and Controlling System as shown in Figure 2 is established, is arranged for controller first and provides food phase
The food weight of symbol, triggering control batcher, is sent to meausring apparatus for food, then exports and feed back the information of output,
It is conveniently adjusted the setting value of food weight；
It (2) is the accuracy and rapidity that guarantee feed, system uses Discrete control method, feeding process is divided into quickly
Two stages at a slow speed；
1. running by feeding controller iteration, the deviation between target value and output valve is effectively controlled；
2. formulating tracking aim curve, the suitable time point for carrying out rate conversion is found, to improve the accurate of feed
Property；
(5) according to intelligent control and reasonable Discrete control, the weighing task of food is quickly and accurately completed, by weight
Qualified product encapsulate into bag, is sent to video surveillance region finally by transmission device.
C. Image Multiscale clustering method is used, analysis is monitored to the video image of food packaging, and in time
Substandard product is rejected, the Detection task of device of full automatic packaging is completed；
(1) picture on surface of food pack and sealing in video image are analyzed according to multiple dimensioned clustering method, with number
According to the variation of luminous point, the picture structure in video is divided；
1. if with one group of data point set Data={ d1,d2,…,dM}∈Rl(M indicates data point number, and d indicates picture number
Strong point, RlRepresentation space point set) indicate detection video image, then image in space is represented by
Wherein, δ (d-di) (i=1,2 ..., M) be Dick draw generalized function, be expressed as image luminous point；
2. with the Convolution Analysis video image of the image template of different scale and Gaussian function, Gaussian function is Indicate that the peak value of Gaussian curve, c indicate that scale parameter, T indicate transposition,
Convolution relation formula is represented by
(2) change the clustering for carrying out image according to light spot dimension, result is packed according to the clustering recognition of image；
1. the variation of each luminous point has certain range scale, when dimensional variation arrives the minimum value less than variation range,
The luminous point is broken down into multiple small luminous points, conversely, then luminous point and other luminous points are warm；
2. specific step is as follows for clustering：
(a) light spot dimension is initialized, when scale is sufficiently small, each data point is a center, to generate one
Class；
(b) when cluster proceeds to the i-th step, make ci+1=(u+1) ci, the value of u passes through psychophysics according to Weber law
Means are chosen, when scale is ciWhen, if optical spot centre is center (ci), if scale is ciOptical spot centre fall in scale be ci+1
Spot dimensions in, then luminous point C (center (ci)) class be divided into luminous point C (center'(ci+1)) class in；
If luminous point is c in scale there are two (c) or moreiWhen optical spot centre, fall into same luminous point, then when luminous point ruler
Degree increases to ci+1When, these luminous points are dissolved into same class, and the process is recycled, until all data all incorporate in same class, are tied
Beam cluster；
3. identifying the packaging knot of the packaging bag according to the comparing result of image in cluster image and baling line correction procedure
Fruit；
(3) if the underproof food of packaging occur through detection sends it to corresponding transmission according to underproof reason
Band melt down remaking by conveyer belt, and transmission device is as shown below：
D., infrared sensor is set, the workload of packing machine is counted, and according to the testing result of packaging, calculates product
Bad product rate completes the intelligent control task of foods packing machine according to the rate of tension of the variation adjustment idler wheel of bad product rate.
(1) using infrared refraction, the property of reflection, the product number after packing machine work is counted；Using one
The counting circuit that kind is made of infrared emission tube and reception pipe, carries out accurate Counts under natural light；
1. installing sensor in the two sides for completing the food transmission device of packaging, conveyer belt side is the transmitting discharged up and down
Pipe and reception pipe, the other side are the baffles that can reflect infrared ray, complete product counting task using this device；
2. the working principle of infrared sensor is as shown below：
(2) according to the variation of bad product rate, the rate of tension of packing machine idler wheel is adjusted, the intelligent control for completing packing machine is appointed
Business；
1. bad products are counted, according to formula according to the cluster analysis result of food packagingIt calculates bad
Product rate, wherein N indicates the workload of packing machine, NumberrejIndicate substandard product number, p indicates bad product rate；
2. the threshold value of bad product rate is set, according to bad product rate compared with threshold value for the working efficiency for guaranteeing packing machine
As a result, the rate of tension of intelligent control packing machine idler wheel, improves the working efficiency of packing machine.
In conclusion just realizing a kind of intelligent control method of bag-feeding Fully-automatic food packing machine.Complicated and tight
In careful intelligent control task, the present invention can flexibly, stably accomplish regulation task, and can according to current food type,
Intelligence adjusts the use specification of each equipment, accurately controls weighing, packaging, detection and the statistics link of food, has sensitive
The beneficial effect that degree is high, robustness is good.
Claims (5)
1. a kind of intelligent control method of bag-feeding Fully-automatic food packing machine, it is characterised in that：The method includes following steps
Suddenly：
A. use the voice confirmation method based on Dynamic Ranking Information, establish speech recognition system, by voice control, complete to
Bag machine provides the task of packaging bag；
B. food is weighed using intelligent food Weighting and Controlling System, the food of weight qualification is entered into bag encapsulation, and pass through transmission
Band is sent to video surveillance region；
C. Image Multiscale clustering method is used, analysis is monitored to the video image of food packaging, and reject in time
Substandard product completes the Detection task of device of full automatic packaging；
D., infrared sensor is set, the workload of packing machine is counted, and according to the testing result of packaging, calculates the bad of product
Product rate completes the intelligent control task of foods packing machine according to the rate of tension of the variation adjustment idler wheel of bad product rate.
2. the intelligent control method of bag-feeding Fully-automatic food packing machine as described in claim 1, it is characterised in that：The step
Suddenly A includes：
(1) one section of voice is obtained first, voice is parsed using Viterbi algorithm, according to the pass in speech recognition network
Keyword model confirms the keyword in voice messaging；
1. inputting the voice V={ v of one section of S frame1, v2..., vS, this section of voice is recognized by the system as keyword, identifies in network
Contain T keyword models Mode={ mode1, mode2..., modeT}；
2. system parses voice messaging, each frame voice messaging corresponds to a state of keyword models, keyword mould
The status switch of type is determined by its internal state arrangement；
(2) according to the corresponding probability likelihood ratio score value of keyword in voice, the Dynamic Ranking score of whole section of voice is calculated, and
Enhance the separating capacity of system by identification anti-keyword；
1. assuming the s frame v in voicesIn t-th of model modetIn state be Statets, then probability likelihood ratio score value be
Lt(vs)=logP (vs|Statets, t=1,2 ..., M) and M≤T
Wherein, M indicates Number of Models when carrying out local calculation, then voice vsDescending arrangement in each model can indicate
For
2. the Dynamic Ranking Information score of whole section of voice is the cumulative of voice Ranking Information score in all frame levels, it is represented by
Wherein, Lframe(s) the voice Ranking Information score in a frame level is indicated；
3. Dynamic Ranking is believed using geometric average method using most probably anti-keyword identification model is obtained like estimation technique training
Score is ceased in conjunction with the likelihood ratio score of anti-keyword identification model, and relationship is
Wherein, (0,1) θ ∈,Indicate anti-keyword Dynamic Ranking Information score；According to the ranking results of composite score, have
Effect identification voice messaging；
(3) according to the confirmation of voice and identification, the keyword in voice messaging is obtained, is controlled according to keyword and is worked to bag machine,
It completes to give bag task.
3. the intelligent control method of bag-feeding Fully-automatic food packing machine as claimed in claim 2, it is characterised in that：The step
Suddenly B includes：
(1) establish intelligent food Weighting and Controlling System, first for controller be arranged with the food weight that provides food and be consistent, touch
Hair control batcher, is sent to meausring apparatus for food, then exports and feed back the information of output, be conveniently adjusted food weight
Setting value；
It (2) is the accuracy and rapidity that guarantee feed, system uses Discrete control method, feeding process is divided into quick and slow
Fast two stages；
1. running by feeding controller iteration, the deviation between target value and output valve is effectively controlled；
2. formulating tracking aim curve, the suitable time point for carrying out rate conversion is found, to improve the accuracy of feed；
(3) according to intelligent control and reasonable Discrete control, the weighing task of food is quickly and accurately completed, by weight qualification
Product carry out into bag encapsulate, be sent to video surveillance region finally by transmission device.
4. the intelligent control method of bag-feeding Fully-automatic food packing machine as claimed in claim 3, it is characterised in that：The step
Suddenly C includes：
(1) picture on surface of food pack and sealing in video image are analyzed according to multiple dimensioned clustering method, with data light
The variation of point divides the picture structure in video；
1. if with one group of data point set Data={ d1, d2..., dM}∈Rl, M expression data point number, d expression image data point,
RlRepresentation space point set indicates detection video image, then image in space is represented by
Wherein, δ (d-di) (i=1,2 ..., M) be Dick draw generalized function, be expressed as image luminous point；
2. with the Convolution Analysis video image of the image template of different scale and Gaussian function, Gaussian function isIndicate that the peak value of Gaussian curve, c indicate that scale parameter, T indicate to turn
It sets, convolution relation formula is represented by
(2) change the clustering for carrying out image according to light spot dimension, result is packed according to the clustering recognition of image；
1. the variation of each luminous point has certain range scale, when dimensional variation arrives the minimum value less than variation range, the light
Point is broken down into multiple small luminous points, conversely, then luminous point and other luminous points are warm；
2. specific step is as follows for clustering：
(a) light spot dimension is initialized, when scale is sufficiently small, each data point is a center, to generate a class；
(b) when cluster proceeds to the i-th step, make ci+1=(u+1) ci, the value of u selected according to Weber law by psychophysics means
It takes, when scale is ciWhen, if optical spot centre is center (ci), if scale is ciOptical spot centre fall in scale be ci+1Luminous point
In range, then luminous point C (center (ci)) class be divided into luminous point C (center ' (ci+1)) class in；
If luminous point is c in scale there are two (c) or moreiWhen optical spot centre, fall into same luminous point, then when light spot dimension increase
Add to ci+1When, these luminous points are dissolved into same class, and the process is recycled, until all data all incorporate in same class, are terminated poly-
Class；
3. identifying the packaging result of the packaging bag according to the comparing result of image in cluster image and baling line correction procedure；
(3) if the underproof food of packaging occur through detection sends it to corresponding conveyer belt according to underproof reason,
Melt down remaking by conveyer belt.
5. the intelligent control method of bag-feeding Fully-automatic food packing machine as claimed in claim 4, it is characterised in that：The step
Suddenly D includes：
(1) using infrared refraction, the property of reflection, the product number after packing machine work is counted；Using one kind by
The counting circuit of infrared emission tube and reception pipe composition, carries out accurate Counts under natural light；
Sensor is installed in the two sides for completing the food transmission device of packaging, conveyer belt side is the transmitting tube discharged up and down and connects
Closed tube, the other side are the baffles that can reflect infrared ray, complete product counting task using this device；
(2) according to the variation of bad product rate, the rate of tension of packing machine idler wheel is adjusted, the intelligent control task of packing machine is completed；
1. bad products are counted, according to formula according to the cluster analysis result of food packagingBad product rate is calculated,
Wherein N indicates the workload of packing machine, NumberrejIndicate substandard product number, p indicates bad product rate；
2. the threshold value of bad product rate is set for the working efficiency for guaranteeing packing machine, according to the comparison result of bad product rate and threshold value,
The rate of tension of intelligent control packing machine idler wheel, improves the working efficiency of packing machine.
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| CN114971433A (en) * | 2022-08-01 | 2022-08-30 | 中国工业互联网研究院 | Quality control method, device, equipment and storage medium based on industrial internet |
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