Yaa Prediction Of Tensile Forcefulness Of Woven Fabric
Wednesday 19 December 2018
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Comparative Study Regarding the Prediction Efficiency of Ann too Fuzzy Model for the Prediction of “Tensile Strength” of Woven Fabric
Amal Ray
M.Tech Scholar
Govt. College of Engineering & Textile Technology,
Serampore, West Bengal, Bharat
Email: amal.pappu87@gmail.com
Govt. College of Engineering & Textile Technology,
Serampore, West Bengal, Bharat
Email: amal.pappu87@gmail.com
Abstract:
The important of stuff Tensile Strength is clearly understood inwards Context of the endues properties of the fabric. Therefore Tensile Strength must live on pre-ashes during the stuff designing, I that is alternative of warp count weft count, alternative of stuff structural properties. Weave, EPC, PPC, too physical properties similar GSM, Thickness.
Therefore it is essential to found a suitable empirical human relationship betwixt Tensile Strength of stuff too basic stuff parameter GSM, EPC, PPC, Thickness. In the introduce newspaper lay out of stuff sample is airplane to live on tested to make laid off observation value GSM, PPC, EPC, Thickness as input parameter too Tensile Strength is output.
The ANN model too fuzzy model are airplane to live on derived based upon those observation data. The prediction efficacies of this to prediction model to live on drive our plainly to live on compared to obtain. The nigh accurate prediction model for Tensile Strength.
Chapter-1: INTRODUCTION
Tensile strength of a yarn or stuff is defined as a maximum charge that it volition suffer without breaking when subjected to uniaxial tensile loading. Tensile strength of a woven stuff is 1 of the nigh of import properties which acquire inwards superior inwards many applications as compared to non-woven too knitted fabrics. Literature review reveals that the tensile strength of a woven stuff non entirely depends on the strength of the factor yarns, but also on many other factors including yarn linear density, yarn twist per unit of measurement length, twist direction, yarn construction as influenced past times the spinning system, yarn bending behaviour, coefficient of friction too initial modulus of the yarn, stuff geometry, warp too weft density, weave pattern or yarn interlacement pattern, weaving weather condition (such as temperature, humidity too yarn tensions during weaving) as good as stuff finishing treatments.
Artificial neural network (ANN) is beingness extensively used at a query phase inwards all the fields of textile manufacture since finally 2 decade. Artificial neural network is applied inwards every acre of textile manufacture i.e. spinning engineering, weaving engineering, dyeing engineering, etc. As neural network are disable provided used individually they are to a greater extent than ofttimes than non integrated amongst an constant organisation to live on used inwards applied scientific discipline approach. Different models embedded amongst neural network such as “automated textile defect recognizer”, “universal approximation”, “MCE criterion”, etc. are used into dissimilar sectors of textile industry. This newspaper mainly focuses on stuff engineering. Artificial neural network is 1 of the hopes available to integrate the elements such as production, quality, cost, information, too static physical care for command but inwards time, manufacturing calculator integrated manufacturing, classification at stuff patterns, identifying stuff defects, etc.
Fuzzy logic is a cast of many-valued logic; it deals amongst reasoning that is approximate rather than fixed too exact. Compared to traditional binary sets (where variables may convey on truthful or simulated values) fuzzy logic variables may conduct hold a truth value that ranges inwards flat betwixt 0 too 1. Fuzzy logic has been extended to grip the concept of partial truth, where the truth value may arrive at betwixt completely truthful too completely false. Furthermore, when linguistic variables are used, these degrees may live on managed past times specific functions. Irrationality tin live on described inwards price of what is known as the fuzzy.
The Japanese were the starting fourth dimension to utilize fuzzy logic for practical applications. The starting fourth dimension notable application is on the high-speed develop inwards Sendai, inwards which fuzzy logic is able to ameliorate the economy, comfort, too precision of the ride. It has also been used inwards recognition of paw written symbols inwards Sony bag computers, earthquake prediction too modelling at the Institute of Seismology Bureau of Metrology inwards Japan, etc.
1.1: Significance of Tensile Strength of Woven Fabric:-
Among all mechanical properties, nigh of import is tensile belongings conduct nether forces. Experimentally it is the elongation too finally the intermission nether gradually increasing load. Textile stuff are non uniform their composition too along the lengths. Consequently their tensile properties are also variable. The variability of outcome of tensile testing is mainly on examine length too examine speed. The aim of dissertation is to discover trial of examine length too examine speed on tensile testing too also to discover out suitable examine length too examine speed for a testing of woven fabrics. Tensile strength of the sample is determined past times using ASTM D5034 method. This examine method covers the select conduct hold of too modified select conduct hold of examine procedures for the determining the breakage strength too elongation of the nigh textile fabrics. The select conduct hold of examine physical care for is applicable to woven, non-woven too felted fabrics. While the modified select conduct hold of examine is used primarily for woven fabrics. This examine method is non recommended for drinking glass fabrics or for knitted too other textile fabrics which conduct hold high stretch.
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| Figure01-Tensile strength examine of stuff |
- The specimen is mounted securely inwards the clamps of the testing machine (Instron). Take help that the specimen is centrally located too the long dimension is as nearly parallel as possible to the management of strength application. Be surely that the tension on the specimens is uniform across the clamped width.
- Mark across the specimen at the front end inner border of each jaw to banking venture check for specimen slips. When slips occurs, the grade volition motion away from the jaws edge.
- The machine is operated too the specimen were broken 1 past times 1 starting fourth dimension warp wise too and then weft wise.
- The breaking strength is recorded from the machinery proved for such purpose.
- If specimen slips inwards the jaws, or breaks, at the border of or inwards the jaws, or if for whatever argue the outcome autumn markedly below the average of the laid of specimens, discard the results too convey or so other specimen. Continue this until the required lay out of except able breaks has been obtained. In the absence of other criteria for rejection a jaw break, whatever intermission occurring inside five mm of the jaws which results inwards the value below fifty % of the average of all other intermission should live on discarded. No other intermission should live on discarded unless it is known to live on faulty.
Instron is nigh mutual testing machine used inwards tensile testing is the universal testing machine. This type of machine has 2 crossheads; 1 is adjusted for the length of the specimen and the other is driven to apply tension to the examine specimen. There are 2 types: i) hydraulic powered too ii) electromagnetically powered machines.
The machine must conduct hold the proper capabilities for the examine specimen beingness tested. There are iii principal parameters: strength capacity, speed, too precision too accuracy. Force capacity refers to the fact that the machine must live on able to generate plenty strength to fracture the specimen. The machine must live on able to apply the strength chop-chop or piece of cake plenty to properly mimic the actual application. Finally, the machine must live on able to accurately too exactly mensurate the guess length too forces applied; for instance, a large machine that is designed to mensurate long elongations may non piece of work amongst a brittle material.
The examine physical care for involves placing the examine specimen inwards the testing machine too applying tension to it until it fractures. During the application of tension, the elongation of the guess department is recorded against the applied force. The information is manipulated so that it is non specific to the geometry of the examine sample. The elongation measure is used to calculate the applied scientific discipline strain, using the next equation:-
Where, L is the alter inwards guess length, L0 is the initial guess length, too L is the finally length. The strength measure is used to calculate the applied scientific discipline stress, s, using the next equation: 
Where F is the strength too Influenza A virus subtype H5N1 is the cross-section of the guess section. The machine does these calculations as the strength increases, so that the information points tin live on graphed into a stress-strain curve.
1.3: Introduction to ANN:-
In calculator scientific discipline too related fields, artificial neural networks are computational models inspired past times brute fundamental nervous systems (in detail the brain) that are capable of machine learning too pattern recognition. They are commonly presented as systems of interconnected "neurons" that tin compute values from inputs past times feeding information through the network.
For example, inwards a neural network for handwriting recognition, a laid of input neurons may live on activated past times the pixels of an input ikon representing a missive of the alphabet or digit. The activations of these neurons are too then passed on, weighted too transformed past times or so component determined past times the network's designer, to other neurons, etc., until finally an output neuron is activated that determines which graphic symbol is read.
This specification covers the operating characteristics of iii types of tensile testing machines used for the decision of the force-elongation properties of textile materials.
These types of tensile testing machines are:-
Calculation—the effective guess length tin live on calculated using the next equation: 
Where:
G E = effective guess length,
G N = nominal guess length,
E N = per centum elongation based on nominal guess length, and
ET = per centum elongation based on truthful guess length.
1.4: Introduction to fuzzy logic::
Fuzzy logic is a cast of many-valued logic; it deals amongst reasoning that is fixed or approximate rather than fixed too exact. In contrast amongst "crisp logic", where binary sets conduct hold two-valued logic: truthful or false, fuzzy logic variables may conduct hold a truth value that ranges inwards flat betwixt 0 too 1. Fuzzy logic has been extended to grip the concept of partial truth, where the truth value may arrive at betwixt completely truthful too completely false. Furthermore, when linguistic variables are used, these degrees may live on managed past times specific functions. Fuzzy logic began amongst the 1965 proposal of fuzzy laid theory past times LotfiZadeh et.al[7]. Though fuzzy logic has been applied to many fields, from command theory to artificial intelligence, it withal remains controversial amid nigh statisticians, who prefer Bayesian logic, too or so command engineers, who prefer traditional two-valued logic.
Degrees of truth:
Fuzzy logic too probabilistic logic are mathematically similar – both conduct hold truth values ranging betwixt 0 too 1 – but conceptually distinct, due to dissimilar interpretations. Fuzzy logic corresponds to "degrees of truth", piece probabilistic logic corresponds to "probability, likelihood"; as these differ, fuzzy logic too probabilistic logic yield dissimilar models of the same real-world situations.
Both degrees of truth too probabilities arrive at betwixt 0 too 1 too so may appear similar at first. For example, allow a 100 ml drinking glass comprise thirty ml of water. Then nosotros may consider 2 concepts: Empty too Full. The pregnant of each of them tin live on represented past times a surely fuzzy set. Then 1 mightiness define the drinking glass as beingness 0.7 empty too 0.3 full. Note that the concept of emptiness would live on subjective too thus would depend on the observer or designer. Another designer mightiness as good pattern a laid membership component where the drinking glass would live on considered total for all values downwards to fifty ml. It is essential to realize that fuzzy logic uses truth degrees as a mathematical model of the vagueness phenomenon piece probability is a mathematical model of ignorance. The same could live on achieved using probabilistic methods, past times defining a binary variable "full" that depends on a continuous variable that describes how total the drinking glass is. There is no consensus on which method should live on preferred inwards a specific situation.
Applying truth values:
A basic application mightiness characterize sub ranges of a continuous variable. For instance, a temperature measure for anti-lock brakes mightiness conduct hold several split upward membership functions defining detail temperature ranges needed to command the brakes properly. Each component maps the same temperature value to a truth value inwards the 0 to 1 range. These truth values tin too then live on used to decide how the brakes should live on controlled.
Fuzzy logic temperature:
In this image, the pregnant of the expressions cold, warm, too hot is represented past times functions mapping a temperature scale. Influenza A virus subtype H5N1 request on that scale has iii "truth values"—one for each of the iii functions. The vertical business inwards the ikon represents a detail temperature that the iii arrows (truth values) gauge. Since the blood-red arrow points to zero, this temperature may live on interpreted as "not hot". The orangish arrow (pointing at 0.2) may depict it as "slightly warm" too the bluish arrow (pointing at 0.8) "fairly cold".
Linguistic variables:
While variables inwards mathematics commonly convey numerical values, inwards fuzzy logic applications, the non-numeric linguistic variables are ofttimes used to facilitate the aspect of rules too facts.
A linguistic variable such as historic menses may conduct hold a value such as immature or its antonym old. However, the slap-up utility of linguistic variables is that they tin live on modified via linguistic hedges applied to primary terms. The linguistic hedges tin live on associated amongst surely functions.
Example:
Fuzzy laid theory defines fuzzy operators on fuzzy sets. The work inwards applying this is that the appropriate fuzzy operator may non live on known. For this reason, fuzzy logic commonly uses IF-THEN rules, or constructs that are equivalent, such as fuzzy associative matrices.
Rules are commonly expressed inwards the form:
IF variable IS belongings THEN activity
For example, a elementary temperature regulator that uses a fan mightiness await similar this:
The AND, OR, too NOT operators of Boolean logic be inwards fuzzy logic, commonly defined as the minimum, maximum, too complement; when they are defined this way, they are called the Zadeh operators. So for the fuzzy variables x too y:
NOT x = (1 - truth(x))
x AND y = minimum(truth(x), truth(y))
x OR y = maximum(truth(x), truth(y))
There are also other operators, to a greater extent than linguistic inwards nature, called hedges that tin live on applied. These are to a greater extent than ofttimes than non adverbs such as "very", or "somewhat", which modify the pregnant of a laid using a mathematical formula.
Chapter 2: Literature Review:-
As per the newspaper of Zulfiqar Ali Malik et.al[1] Tensile strength has been accepted as 1 of the nigh of import functioning attributes of woven textiles. In this work, multiple linear regression models are developed past times using empirical information for the prediction of woven stuff tensile strength manufactured from cotton fiber yarns. Tensile strength of warp & weft yarns, warp & weft stuff density, too weave pattern were used as input parameters to decide warp- too weft-way tensile strength of the woven fabrics. The developed models are able to predict the stuff strength amongst real skillful accuracy. Warp yarn strength too ends per 25 mm are found to live on the nigh dominant factors influencing stuff strength inwards warp management piece weft yarn strength too picks per 25 mm are nigh vital inwards weft direction.
As per the newspaper of Mithat Zeydan et.al[2] traditional too computational modelling techniques are compared betwixt each other to predict woven stuff strength that is 1 of the principal features for the characterization of woven stuff character too stuff performance. Compared the other classical modelling techniques, computational modelling methodology seems to conduct hold been to a greater extent than robust too appropriate. This report made inwards a textile Factory producing jacquard woven bedding stuff inwards Turkey has many benefits for textile manufacturers to cut waste matter too bit ratio earlier too during manufacturing. Firstly, production planning component inwards the works life volition live on able to predict the woven stuff strength easily to live on known optimal parameter setting earlier manufacturing. Secondly, The important parameter inwards the manufacturing is found as Warp Density. Thirdly, later finding the optimum parameter setting amongst TDOE, interval values of the sensitive parameters inwards the production is found amongst ANN approach.
As per the newspaper of P.Banumathi et.al[3] a novel intelligent stuff defect inspection model is presented. The recognizer acquires digital stuff images past times ikon acquisition device too converts that ikon into binary ikon past times restoration too threshold techniques. The output of the processed ikon is used as an input to the Neural Network (NN) which uses dorsum propagation algorithm to calculate the weighted factors too generates the desired classification of defects as an output. The experiment results present that the proposed method is viable too applicable inwards textile production factories for defect detection too classification.
In the newspaper of Faten Fayala et.al[4] thermal electrical conductivity as a physical characteristic of fabric. This phenomenon depends on many stuff parameters too it is hard to report the trial of ones without changing the others. In addition, the non-linear human relationship of stuff parameters too thermal electrical conductivity handicap mathematical modelling. So a neural network approach is used to predict the thermal electrical conductivity of knitting construction as a component of porosity, air permeability, weight too fiber conductivity. Data on thermal electrical conductivity are measured past times experiments carried out on jersey knitted structure.
As per the newspaper of J.L. DGRJUTY G. VACHTSEVANOS et.al[5] Influenza A virus subtype H5N1 hierarchical command architecture is proposed has been developed too is applied to textile processes based upon experimental input-output information Influenza A virus subtype H5N1 rule-based fuzzy modelling technique is applied to the Drying subsystem of the process. Influenza A virus subtype H5N1 FLC is used to command wet content inwards the yam too is shown to outperform a conventional command law. An experimental data-base is compiled describing the slashed yarn characteristics which are used to make the fuzzy model too to derive the global optimization routines for the hierarchical supervisor level. Control loops for the slasher model conduct hold also been simulated on a PC486 machine to pattern too compare novel command strategies. We conduct hold developed a simulation of a slasher on the Honeywell automated physical care for command platform. It demon & rates the introduce command strategy, its limitations too potential for improvement. Fuzzy command inwards a hierarchical organisation has the potential for dramatically improving slashing too weaving performance.
Chapter-3:- ACTION PLAN:: 
References::
The machine must conduct hold the proper capabilities for the examine specimen beingness tested. There are iii principal parameters: strength capacity, speed, too precision too accuracy. Force capacity refers to the fact that the machine must live on able to generate plenty strength to fracture the specimen. The machine must live on able to apply the strength chop-chop or piece of cake plenty to properly mimic the actual application. Finally, the machine must live on able to accurately too exactly mensurate the guess length too forces applied; for instance, a large machine that is designed to mensurate long elongations may non piece of work amongst a brittle material.
The examine physical care for involves placing the examine specimen inwards the testing machine too applying tension to it until it fractures. During the application of tension, the elongation of the guess department is recorded against the applied force. The information is manipulated so that it is non specific to the geometry of the examine sample. The elongation measure is used to calculate the applied scientific discipline strain, using the next equation:-
 |
| Figure.- 02 |
In calculator scientific discipline too related fields, artificial neural networks are computational models inspired past times brute fundamental nervous systems (in detail the brain) that are capable of machine learning too pattern recognition. They are commonly presented as systems of interconnected "neurons" that tin compute values from inputs past times feeding information through the network.
For example, inwards a neural network for handwriting recognition, a laid of input neurons may live on activated past times the pixels of an input ikon representing a missive of the alphabet or digit. The activations of these neurons are too then passed on, weighted too transformed past times or so component determined past times the network's designer, to other neurons, etc., until finally an output neuron is activated that determines which graphic symbol is read.
 |
| Figure.- 03 |
These types of tensile testing machines are:-
- Constant-rate-of-extension, CRE.
- Constant-rate-of-traverse, CRT.
- Constant-rate-of-loading (force), CRL.
Calculation—the effective guess length tin live on calculated using the next equation:
G E = effective guess length,
G N = nominal guess length,
E N = per centum elongation based on nominal guess length, and
ET = per centum elongation based on truthful guess length.
1.4: Introduction to fuzzy logic::
Fuzzy logic is a cast of many-valued logic; it deals amongst reasoning that is fixed or approximate rather than fixed too exact. In contrast amongst "crisp logic", where binary sets conduct hold two-valued logic: truthful or false, fuzzy logic variables may conduct hold a truth value that ranges inwards flat betwixt 0 too 1. Fuzzy logic has been extended to grip the concept of partial truth, where the truth value may arrive at betwixt completely truthful too completely false. Furthermore, when linguistic variables are used, these degrees may live on managed past times specific functions. Fuzzy logic began amongst the 1965 proposal of fuzzy laid theory past times LotfiZadeh et.al[7]. Though fuzzy logic has been applied to many fields, from command theory to artificial intelligence, it withal remains controversial amid nigh statisticians, who prefer Bayesian logic, too or so command engineers, who prefer traditional two-valued logic.
Degrees of truth:
Fuzzy logic too probabilistic logic are mathematically similar – both conduct hold truth values ranging betwixt 0 too 1 – but conceptually distinct, due to dissimilar interpretations. Fuzzy logic corresponds to "degrees of truth", piece probabilistic logic corresponds to "probability, likelihood"; as these differ, fuzzy logic too probabilistic logic yield dissimilar models of the same real-world situations.
Both degrees of truth too probabilities arrive at betwixt 0 too 1 too so may appear similar at first. For example, allow a 100 ml drinking glass comprise thirty ml of water. Then nosotros may consider 2 concepts: Empty too Full. The pregnant of each of them tin live on represented past times a surely fuzzy set. Then 1 mightiness define the drinking glass as beingness 0.7 empty too 0.3 full. Note that the concept of emptiness would live on subjective too thus would depend on the observer or designer. Another designer mightiness as good pattern a laid membership component where the drinking glass would live on considered total for all values downwards to fifty ml. It is essential to realize that fuzzy logic uses truth degrees as a mathematical model of the vagueness phenomenon piece probability is a mathematical model of ignorance. The same could live on achieved using probabilistic methods, past times defining a binary variable "full" that depends on a continuous variable that describes how total the drinking glass is. There is no consensus on which method should live on preferred inwards a specific situation.
Applying truth values:
A basic application mightiness characterize sub ranges of a continuous variable. For instance, a temperature measure for anti-lock brakes mightiness conduct hold several split upward membership functions defining detail temperature ranges needed to command the brakes properly. Each component maps the same temperature value to a truth value inwards the 0 to 1 range. These truth values tin too then live on used to decide how the brakes should live on controlled.
 |
| Figure 05 |
In this image, the pregnant of the expressions cold, warm, too hot is represented past times functions mapping a temperature scale. Influenza A virus subtype H5N1 request on that scale has iii "truth values"—one for each of the iii functions. The vertical business inwards the ikon represents a detail temperature that the iii arrows (truth values) gauge. Since the blood-red arrow points to zero, this temperature may live on interpreted as "not hot". The orangish arrow (pointing at 0.2) may depict it as "slightly warm" too the bluish arrow (pointing at 0.8) "fairly cold".
Linguistic variables:
While variables inwards mathematics commonly convey numerical values, inwards fuzzy logic applications, the non-numeric linguistic variables are ofttimes used to facilitate the aspect of rules too facts.
A linguistic variable such as historic menses may conduct hold a value such as immature or its antonym old. However, the slap-up utility of linguistic variables is that they tin live on modified via linguistic hedges applied to primary terms. The linguistic hedges tin live on associated amongst surely functions.
Example:
Fuzzy laid theory defines fuzzy operators on fuzzy sets. The work inwards applying this is that the appropriate fuzzy operator may non live on known. For this reason, fuzzy logic commonly uses IF-THEN rules, or constructs that are equivalent, such as fuzzy associative matrices.
 |
| Figure.- 06 |
IF variable IS belongings THEN activity
For example, a elementary temperature regulator that uses a fan mightiness await similar this:
- IF temperature IS real mutual frigidity THEN halt fan
- IF temperature IS mutual frigidity THEN plough downwards fan
- IF temperature IS normal THEN keep flat
- IF temperature IS hot THEN speed upward fan
The AND, OR, too NOT operators of Boolean logic be inwards fuzzy logic, commonly defined as the minimum, maximum, too complement; when they are defined this way, they are called the Zadeh operators. So for the fuzzy variables x too y:
NOT x = (1 - truth(x))
x AND y = minimum(truth(x), truth(y))
x OR y = maximum(truth(x), truth(y))
There are also other operators, to a greater extent than linguistic inwards nature, called hedges that tin live on applied. These are to a greater extent than ofttimes than non adverbs such as "very", or "somewhat", which modify the pregnant of a laid using a mathematical formula.
Chapter 2: Literature Review:-
As per the newspaper of Zulfiqar Ali Malik et.al[1] Tensile strength has been accepted as 1 of the nigh of import functioning attributes of woven textiles. In this work, multiple linear regression models are developed past times using empirical information for the prediction of woven stuff tensile strength manufactured from cotton fiber yarns. Tensile strength of warp & weft yarns, warp & weft stuff density, too weave pattern were used as input parameters to decide warp- too weft-way tensile strength of the woven fabrics. The developed models are able to predict the stuff strength amongst real skillful accuracy. Warp yarn strength too ends per 25 mm are found to live on the nigh dominant factors influencing stuff strength inwards warp management piece weft yarn strength too picks per 25 mm are nigh vital inwards weft direction.
As per the newspaper of Mithat Zeydan et.al[2] traditional too computational modelling techniques are compared betwixt each other to predict woven stuff strength that is 1 of the principal features for the characterization of woven stuff character too stuff performance. Compared the other classical modelling techniques, computational modelling methodology seems to conduct hold been to a greater extent than robust too appropriate. This report made inwards a textile Factory producing jacquard woven bedding stuff inwards Turkey has many benefits for textile manufacturers to cut waste matter too bit ratio earlier too during manufacturing. Firstly, production planning component inwards the works life volition live on able to predict the woven stuff strength easily to live on known optimal parameter setting earlier manufacturing. Secondly, The important parameter inwards the manufacturing is found as Warp Density. Thirdly, later finding the optimum parameter setting amongst TDOE, interval values of the sensitive parameters inwards the production is found amongst ANN approach.
As per the newspaper of P.Banumathi et.al[3] a novel intelligent stuff defect inspection model is presented. The recognizer acquires digital stuff images past times ikon acquisition device too converts that ikon into binary ikon past times restoration too threshold techniques. The output of the processed ikon is used as an input to the Neural Network (NN) which uses dorsum propagation algorithm to calculate the weighted factors too generates the desired classification of defects as an output. The experiment results present that the proposed method is viable too applicable inwards textile production factories for defect detection too classification.
In the newspaper of Faten Fayala et.al[4] thermal electrical conductivity as a physical characteristic of fabric. This phenomenon depends on many stuff parameters too it is hard to report the trial of ones without changing the others. In addition, the non-linear human relationship of stuff parameters too thermal electrical conductivity handicap mathematical modelling. So a neural network approach is used to predict the thermal electrical conductivity of knitting construction as a component of porosity, air permeability, weight too fiber conductivity. Data on thermal electrical conductivity are measured past times experiments carried out on jersey knitted structure.
As per the newspaper of J.L. DGRJUTY G. VACHTSEVANOS et.al[5] Influenza A virus subtype H5N1 hierarchical command architecture is proposed has been developed too is applied to textile processes based upon experimental input-output information Influenza A virus subtype H5N1 rule-based fuzzy modelling technique is applied to the Drying subsystem of the process. Influenza A virus subtype H5N1 FLC is used to command wet content inwards the yam too is shown to outperform a conventional command law. An experimental data-base is compiled describing the slashed yarn characteristics which are used to make the fuzzy model too to derive the global optimization routines for the hierarchical supervisor level. Control loops for the slasher model conduct hold also been simulated on a PC486 machine to pattern too compare novel command strategies. We conduct hold developed a simulation of a slasher on the Honeywell automated physical care for command platform. It demon & rates the introduce command strategy, its limitations too potential for improvement. Fuzzy command inwards a hierarchical organisation has the potential for dramatically improving slashing too weaving performance.
Chapter-3:- ACTION PLAN::
References::
- Zulfiqar Ali Malik et.al[1]/ Development of Models to Predict Tensile Strength of Cotton Woven Fabrics Volume half dozen http://www.jeffjournal.org /Journal of Engineered Fibers too Fabrics /2011.
- Mithat Zeydan / Prediction of Fabric Tensile Strength past times Modelling the Woven Fabric/ www.intechopen.com/ Erciyes University, Department of Industrial Engineering Turkey.
- P. Banumathi too MD G. M. Nasira et.al[3]/Fabric Inspection System using Artificial Neural Networks Volume- II/International Journal of Computer Engineering Science(IJCES) https://sites.google.com/site/ijcesjournal/2012 fifth May.
- Faten Fayala(Ph.D), Sofien Benltoufa(Ph.D), Abdelmajid Jemni(Ph.D) too Hamza Alibi(Ph.D)/ Neural Network for Predicting Thermal Conductivity of Knit Materials/ Journal of Engineered Fibers too Fabrics. Volume 3, Issue four – 2008.
- J.L. DGRJUTY G. VACHTSEVANOS et.al[5]/ ADVANCED APPLICATION OF STATISTICAL AND FUZZY LOGIC CONTROL TO TEXTILE PROCESSES/ National Textile Centre Annual Report/ 1994 September.
- Soft Computing inwards textile Engineering./ Woodhead publication/ 2011.