Industrial sewing machines have been significantly improved in recent years and especially electronic sewing control is now being introduced. This study concerns the development of a controller for an electromagnetically actuated presser foot. The controller is responsible for controlling the vertid movement of the presser foot, This is an important point since the presser foot tends to bounce at high sewing speeds, resulting in irregular seams. In this study a fuzzy logic controller was used. The reference displacement value is set up by an adaptive method in order to respect changes on the number of plies. The tested fuzzy logic controller allows a better performance of the control especially in relation with different fabrics. During this study another control strategy was considered. This control strategy combines a PI-algorithm with a fuzzy logic controller. https://vssewingmachine.in/ Yet, the controller restrids the use of new fabrics, which have not been defined in advance. This aspect will be a major point in the future development in order to recognize the fabrics during sewing and to adapt the controller adequately.
Industrial sewing machines have been improved a lot in'the recent years. Most manufactures can support a large field of applications, with machines that can perform operations with high quality and at very high speeds. Yet, some problems arise, mainly due to the constant change in materials being sewn. One important system of a sewing machine is the material feeding system. The objective of this study is the feeding system of an industrial overlock sewing machine, which is depicted in Fig. 1. The system consists of three components: a presser foot, a throat plate and a feed dog. The throat plate is a smooth surface that supports the fabric being sewn with openings for the needle and the feed dog to pass. During this movement the feed dog rises above the throat plate to engage the fabric against the underside of the presser foot before starting the advancing motion. Some of the problems in the sewing process rely in the interaction between the presser foot and the feed dog. The presser foot is responsible for guaranteeing the required pressure to control the fabric feeding and to constrain their movement during needle penetration and withdrawal. In order to study the feeding process and to control the presser foot, the sewing machine was instrumented with a LVDT (linear variable differential transformer) for measuring the vertical displacement of the presser foot, and a miniature piezoelectric force transducer to measure the (compression) farces exerted on the presser foot bar. A proportional force solenoid is used to interact with the presser foot, according to the arrangement presented in Fig. 1. Up to now, the available actuators have a quite large response time (about 50 ms step response), allowing only a stitch-by-stitch control of the maximum displacement point. Future actuators with better response times may permit the control of the whole presser-foot trajectory. Jack Sewing Machine Dealers in Chennai
The objective of this controller is to keep the displacement in admissible displacement limits, a strategy more thoroughly explained in [ 11. The controllers have been impIemented in LabView. The signals from the sensors are conditioned and acquired by an acquisition board. They are then further processed to obtain stitch-by-stitch maximum displacement values. Based on these discrete values the control algorithm computes the output for the actuator.
An adaptive method was used for all the presented controllers to set up a new reference value whenever the error or force output exceeds a defined range. The method allows adapting different fabrics and a different number of plies. The problem is that sewing defects like folds, may be incorrectly interpreted and a new reference value may be set, an undesired situation.. Therefore new techniques will be considered in the future to avoid adaptation to these sewing defects. The definition of references is being implemented by running a specific sewing test before the operation, in order to determine the reference values based on an anti-bouncing condition.
Following the research efforts undertaken by the authors in [I] und [2], this section refers to the design of a fuzzy logic controller for controiling the presser foot, presenting and discussing the results obtained during testing. 3.1. Controller design In order to define the controller parameters, some tests were carried out varying the sewing speed and the force output. The displacement of ihe presser foot was measured during these tests, for a range of sewing speeds and presser-foot forces. In Fig. 2 an example of the characterisation of two plies of an interlock fabric is depicted. In this figure it is possible to observe how the displacement varies with force and speed. In terms of controller design, and based on the result of practical sewing tests, the controller should maintain a displacement range of about 0.05" around a Qhrc #educt 5 dm pre-defined average value. The correspondent force range lies between 17.4 to 26.XN for a speed variation from 900 to 4700 stitches per minute (spm). Another interesting fact is that the sewing speed needs also to be taken into account, but seems to be less important. With the help of these graphs for the defined fabrics, the error range was defined from -0.05 to 0.05" and the force range from 17.4N to 26.8N. This force range seems to manage the defined displacement error over the used speed range. Based on these principles the Fuzzy Logic Controller was designed. Due to the preliminary studies concerning the setting of the displacement reference, it was decided to keep the adaptive method of the reference based on the error range. The Fuzzy Logic Controller uses three inputs. One of the thee inputs is the error based on the reference and the current displacement. In addition to the error, the speed and the current displacement were used as input variables to the Fuzzy Logic Controller to ensure an adaptation on the speed and on the number of plies. The control scheme is depicted in Fig. 3. With these three input variables and the force as output, the member-functions were defined (Fig, 4 to Fig. 7). In Fig. 4 the speed was defined in a range of 0 to 47OOspm. The member-functions are divided into low (0 to 2350spm), mid (0 to 4700spm) and high speed (2350 to 4700spm). In Fig. 5 the error is depicted as second antecedent. It was fixed from -0.05 to 0.05" and divided into memberfunctions of negative, zero and positive.
As the third antecedent the displacement was used, in order to differentiate between different types of fabrics as well as different number of plies to adapt the force. For this purpose, ranges were defined from 0.8 to 0.98mm for two plies of riblxl fabric, from 0.93 to 1.12" for two plies of interlock fabric, from 1.35 to 1.55" for four plies of riblxl and from 1.55 to 1.80" for four plies of interlock fabric, as the member-fimctions depicted in Fig. 6. The output force variable was fixed to a range from 17.4 to 26.8N based on the experience gained on the sewing process. The member-functions were divided into low (17.4 to 19.8N), lowmid (17.4 to.22.1N), mid .(19.8 to 24.4N), highmid (22.1 to 26.XN) and high (24.4 to 26.8N). These member-functions are presented in Fig. 7. 3.2. Test results The objective is to compare the results of the adaptive Pcontroller (already designed and implemented for this application [3]) with the results of the previously described Fuzzy Logic Controller. A PTD-controller did not show a significant improvement related to the used P-controller, therefore it was decided to continue working with a Pcontroller. The comparison between the P-controller and the Fuzzy' Logic Controller is based on different types of fabrics and a different number of plies. The P-controller was used with a gain of one. It uses practically the same adaptive reference method based on the force output, because the P-controller uses a gain of one. The parameters of the adaptive mechanisms have been chosen so that the two controllers could be compared. To achieve this, the adaptive range of the Fuzzy Logic Controller was fixed to 0.05mm or 2.9N for the P-controller. Based on this, the two controllers can be compared without adverse effects. During this test, samples of four plies of riblxl fabric and two plies on interlock fabric were used at different speeds. In Fig. 8 to Fig. 11 are depicted the displacement maximum peak (above the throat plate level), the displacement error and the force output of the controller. Fig. 8 shows the output of the Fuzzy Logic ControlIer for two plies of the interlock fabric and, in Fig. 9, the output of the P-controller. In these figures it can be seen that the error is almost zero for both controllers. To accomplish this objective, the Fuzzy Logic Controller needed to be set up exactly, in order to define the force, which minimizes the error to zero. The displacement measured is depicted as the second part of the graph. The displacement of the presser foot is increasing at the beginning when the fabric is not yet completely fed under the presser foot. The same situation appears at the end, recognizable by the decreasing displacement. The force output is depicted in the third part, being the force of the fuzzy logic controller adjusted to be higher than the one set for the P-controller. The P-controller uses, by default for knitted fabrics, 22.1N 0.3XV, corresponding to a force value suitable for all of the knitted fabrics used in this study. The Fuzzy Logic Controller, on the other hand, offers the possibility to adapt the force offset on the type of fabric, which will be recognized based on the measured displacement.
In Fig. 10 and Fig 11 are depicted the results for four plies of the riblxl fabric. The output of the Fuzzy Logic controller shows sonie humps due to the changes of the displacement error. Thercfore the Fuzzy Logic Controller needs an improvement by enlarging the error memberfunctions. The P-controller also showed good results, but also revealed a major disadvantage: the P-controller applies the maximum force when the number of plies decreases. This can be seen at the beginning and at the end of the sewing process as presented in Fig 1 1. Therefore the hzq logic controller offers more possibilities to define the force output, even for sewing without any fabric. This possibility offers adaptability for different types of fabrics and numbers of plies.
