Weft picking control device in a jet loom

Abstract: The weft picking control device of the jet loom, has a data input device (19) for feeding data of fabric conditions like yarn count number and/or reed width. There is further a data memory (C₁) with stored control factor data regarding weft picking conditions like weft picking commencement, fluid injection time, duration and/or end. The data are classified in a plurality of groups according to a rule of order. Depending on the fabric conditions the optimum control factor data are selected for automatically setting of the loom by a CPU and program (C₂) that is based on the interdependence of fabric conditions and control factor data.

Description: The present invention relates to a weft picking control device in a jet loom of the type wherein a weft yarn is picked or inserted into a shed by the action of a fluid jet injected by a weft picking nozzle. For weaving fabrics of high quality with a jet loom of the above type, it is important that good weft picking conditions should be established, so that each weft yarn can reach a predetermined end position in the weft picking passage, i.e. the shed, at a specified time. Control factors which influence the weft picking condition include for example the time at which weft picking operation is started and period of time during which weft transport fluid is injected from weft picking nozzle. The time of weft picking commencement is governed by the fabric width (or reed width) and the period, i.e. the duration of the injection is dependent on the thickness (or number count) and character of weft yarn to be picked. EP-A1-0.290.975 describes an automatic picking controlling method in which a plurality of jetting patterns for running modes of picked weft yarns is stored in a memory. The running condition of the inserted weft is detected during the actual picking operation and then a jetting pattern suitable for the running condition of the picked weft yarn is read from the memory. Thereafter the subnozzle groups are controlled, i.e. operated and actuated on the basis of the jetting pattern for a predetermined period of time after reading the jetting pattern. The Japanese patent application No. 62-263348 (1987) discloses a device in which a control factor, namely the period of injection, is selected on the basis of input data on fabric condition, namely the number count of weft yarn and thereby to optimize the control setting, without relying on the experience of skilled workmen. However, it generally takes a long time to find through experimenting an optimum period of injection for each different yarn number count. For this reason, in the above prior art device, yarn number counts are classified only into two groups, i.e. one group for relatively large number counts and the other for relatively small number counts, which correspond to two different groups of injection period. Therefore, the setting of the injection period in the above control device is made roughly only in such a way, that with a certain yarn number count as border line, the injection period is set longer for one group of yarn number counts and the period is set shorter for the other group of yarn number counts. Apparently, such application of the same injection period to all the yarn number counts falling in one of the two groups makes it difficult to provide for the accuracy which is necessary for achieving the desired quality of woven fabrics. Since the yarn number counts are thus classified into two groups only, it is difficult to optimize the weft picking control factor, in particular, when handling a weft yarn whose number count is close to the border line of the two groups of number counts. It is an object of the present invention, therefore, to provide a weft picking control device in a jet loom which is capable of improving the optimization of the weft picking control factors such as period of injection and time of picking commencement by utilizing the experience and knowledge of experts and skilled workmen. According to the present invention, this problem is solved by the teaching contained in the characterizing part of claim 1. The depending claims are related to particular embodiments of the invention. A control device according to the invention, is operated as follows: various fabric condition data are classified following the rule of order into a pluarlity of fabric condition data groups and various control factors are classified following the rule of order into a plurality of control factor groups and an optimum control factor can be selected for any given input data regarding the fabric condition and according to a specific relationship between the two groups and which is based on the experience and knowledge of experts and skilled workmen. This offers in so far an excellent advantage and effect that an optimum control factor can be determined easily and without the otherwise necessary, troublesome and time consuming work of producing data by experiments and trial runs of the machine. The weft number counts, as the fabric condition data, are classified into a plurality of groups, e.g. very small, small, slightly small, average, slightly large, large and very large, according to the rule of order, while the periods of injection, as the control factor, are classified similarly into a plurality of groups, e.g. very short, short, slightly short, average, slightly long, long and very long. Allotment of injection periods or varying lengths to the respective groups is made and based on the experience and knowledge of experts and workmen regarding the optimum corresponding relationship between the fabric condition data and their associated control factors. The groups of fabric condition data and the groups of control factors are correlated with each other, and the means for establishing the control factor operates to select an optimum control factor for the input data on the basis of the correlation between the fabric condition data and the control factors. This correlation, or the corresponding relationship, is established previously on the basis of the experience and knowledge of experts and workmen. The following examples of the invention are described with reference to the schematic drawings. Fig. 1 to 5 illustrate a first embodiment of the invention, and details thereof; Fig. 1 is a schematic front view showing an apparatus for weft picking; Fig. 2 (a) is a diagram showing the likelihood of weft number count of fabric condition data groups; Fig. 2 (b) is a diagram showing the likelihood of valve open period of control factor groups; Fig. 3 (a) is a diagram showing specific corresponding relationship between the yarn number count and the valve open period; Fig. 3 (b) is a diagram similar to that of Fig. 3 (a), but with the relationship shown in a discrete way; Fig. 4 (a) and (b) provide diagrams showing the condition of controlling of weft picking; Fig. 5 shows a flow chart of a program for establishing the control factor; Figs. 6 through 10 illustrate another embodiment of the present invention, of which Fig. 6 is a diagrammatic front view showing an apparatus for weft picking; Fig. 7 (a) is a diagram showing the likelihood of reed width of fabric condition data groups; Fig. 7 (b) is a diagram showing the likelihood of weft picking commencement time of control factor groups; Fig. 8 (a) is a diagram showing specific corresponding relationship between the reed width and the weft picking commencement time; Fig. 8 (b) is a diagram similar to that of Fig. 8 (a), but the relationship shown in a discrete way; Fig. 9 (a) and (b) provides diagrams showing the condition of controlling of weft picking, respectively; Fig. 10 shows a flow chart of a program for establishing the control factor. Reference numeral 1 designates a device for measuring and storing a predetermined length of weft yarn Y by winding the same on a drum of the device 1. Further there is a fabric condition data input device 13 and a control computer C as means for establishing and determining control factor. A length of weft yarn Y thus measured and stored by the device 1 is released therefrom for picking by a main weft picking nozzle 2. Weft insertion is then assisted by a plurality of aixiliary nozzles 3, 4, 5, 6, 7, 8, 9 and 10. When a weft yarn Y has been picked successfully, the yarn is detected by a weft detector 11, which is preferably a photoelectric sensor or reflection type, and the loom operation is continued accordingly. If a weft yarn Y fails to be detected by the weft detector 11, the loom operation is cause to stop. Releasing and stopping of a weft yarn from winding surface 1a of the weft measuring/storing device 1 is accomplished by a movable stop in 12a whose movement is controlled by an electromagnetic solenoid 12 which is in turn controlled by an electromagnetic solenoid 12 which is in turn controlled to be energized and deenergized by appropriate command signals from a control computer C. The control computer C operates to cause the solenoid 12 to be energized via a drive circuit 14 in response to a detection signal from a rotary encoder 13 which detection signal indicates an angle of rotation of the loom. Adjacent to the yarn winding surface 1a is disposed a weft release detector 15, preferably a photoelectric sensor of reflection type, which is adapted to detect a weft yarn Y which is being drawn and released from the yarn winding surface 1a. When the detector 15 detects a predetermined number turns of the weft yarn Y being released, the control computer C emits a command signal to deenergize the solenoid 12 so that the stop pin 12a is moved into engagement with the yarn winding surface 1a to stop the drawing and releasing of the weft yarn Y. Injection of air under pressure from the main nozzle 2 is controlled by an electromagnetically-operated valve V 0 . Similarly, injection of air under pressure from the auxiliary nozzles 3 - 10 is controlled by electro-magneticallly-operated valves V 1 , V 2 , V 3 , V 4 , V 5 , V 6 V 7 , V 8 , respectively. The valve V 0 is connected to an air supply tank 16 and the valves V 1 - V 8 to an air supply tank 17. Operation of each of the valves V 0 and V i (wherein i=1 to 8) to open and close is controlled by appropriate command signals which are transmitted by the control computer C via a drive circuit 18 in accordance with detection signals from the rotary encoder 13. The control computer C includes a central processing unit CPU, data memory C 1 and program memory C 2 . The control computer C further includes a data input device 19 connected thereot for inputting data on fabric conditions. The program memory C 2 of the control computer C stores therein a program, as shown by the flow chart in Fig. 5, for establishing control factor. The control factor in this embodiment is the period of time of air injection by each of the auxiliary nozzles 3 - 10. The period of injection α i , β i ) (wherein i=1 to 8) is indicated by the angle of rotation of the loom. The length of actual injection period by the nozzle, which can be expressed by β i - α i , is established the same for all the auxiliary nozzles. As indicated in the diagrams (a) and (b) of Fig. 4, the main nozzle 2 commences air injection a the angle α 0 and stops the injection at the angle β 0 . Each of the auxiliary nozzles 3 to 10 commences air injection at the angle α i and stops the injection at the angle β i . In the diagrams in Fig. 4, the curved line D indicates an optimum condition of weft flying and the angle of rotation T w depicts the time at which the leading end of a weft yarn Y should reach the target position. The period of air injection (α i , β i ) corresponds to the period of time x during which each of the electromagnetic valves V i is kept open, and this open period of the valves is established by the control factor establishin program shown by the flow chart of Fig. 5. Referring to the diagram (a) of Fig. 2, functions g 1 , g 2 , g 3 , g 4 , g 5 , g 6 , g 7 are established so as to correspond respectively to fabric condition data groups G 1 , G 2 , G 3 , G 4 , G 5 , G 6 m G 7 which are thus classified according to the rule of order in yarn number counts (1 - n 6 ). Each of the fabric condition data groups G j (j=1 to 7) covers a range of yarn number counts as follows: G 1 = Yarn count of very small numbers (1 to n 1 ) G 2 = Yarn count of small numbers (1 to n 2 ) G 3 = Yarn count of slightly small numbers (n 1 to n 3 ) G 4 = Yarn count of average numbers (n 2 to n 4 ) G 5 = Yarn count of slightly large numbers (n 3 to n 5 ) G 6 = Yarn count of large numbers (n 4 to n 6 ) G 7 = Yarn count of very large numbers (n 5 to n 6 ) wherein, 1 < n 1 < n 2 < n 3 < n 4 < n 5 < n 6 In the diagram (a) of Fig. 2, functions g j (j=1 to 7) indicate the likelihood of any yarn number count x of the fabric condition data group G j as a parameter of functions. For example, the likelihood of yarn number count 1 of the fabric condition data group G 1 is "1", while that of yarn number count n 1 of the same group G 1 is "0". Similarly, the likelihood of yarn number count 1 of the condition data group G 2 is "0", that of yarn number count n 1 is "1", and that of yarn number count n 2 is "0", respectively. Referring to the diagram (b) of Fig. 2, functions f 1 , f 2 , f 3 , f 4 , f 5 , f 6 , f 7 are established so as to correspond respectively to control factor groups F 1 , F 2 , F 3 , F 4 , F 5 , F 6 , F 7 which are thus classified according to the rule of order in the open period of the electromagnetic valves v i . Each of the control factor groups F j (j=1 to 7) covers a range of valve open periods as follows: F 1 = Very short valve open period (Θ 1 to Θ 2 ) F 2 = Short valve open period (Θ1 to Θ3 ) F 3 = Slightly shourt valve open period (Θ 2 to Θ 4 ) F 4 = Average valve open period (Θ 3 to Θ 5 ) F 5 = Slightly long valve open period (Θ 4 - Θ 6 ) F 6 = Long valve open period (Θ 5 to Θ 7 ) F 7 = Very long valve open period (Θ 6 to Θ 7 ) wherein, Θ 1 < Θ 2 < Θ 3 <Θ 4 < Θ 5 < Θ 6 < Θ 7 In the diagram (b) of Fig. 1, the functions f j (j=1 to 7) indicate the likelihood of any valve open period of the control factor group F j . For example, the likelihood of valve open period Θ 1 of the control factor group F 1 is "1", while that of valve open period Θ 2 of the same control factor group is "0". Similarly, the likelihood of valve open period Θ 1 of the control factor group F 2 is "0", that of valve open period Θ 2 is "1", and that of valve open period Θ 3 is "0", respectively. The condition data group G j corresponds to the control factor group F 8-j , which means that the valves V i should be kept opened for a longer period of time for fliying a weft yarn with a count of smaller number, and the classification of the control factor groups F j , or the grouping of valve open periods Θ 1 , Θ 2 , Θ 3 , Θ 4 , Θ 5 , Θ 6 , Θ 7 , is provided in light of experience and knowledge of experts and skilled workmen. Upon input of fabric condition data, or a data x on the number count of a weft yarn to be handled, through the data input device 19, the control computer C firstly determines the product-set G j ∩ G j+1 of the condition data group G j and G j+1 in which the yarn number count data x falls. The control computer C then performs calculations of the functions g j (x) and g j+1 (x) for the above condition data groups G j and G j+1 . For the sake of convenience in further explanation, in the diagram (a) of Fig. 2, functions g j and g j+1 for the parameter x are g 2 and g 3 , respectively. Then, the control computer C performs the calculations of functions f -1 8-f and f -1 8-(j+1) , which are inverse with respect to the functions f 8-j and f 8-(j+1) for the control factor groups F 8-j and F 8-(j+1) corresponding, respectively, to the above condition data groups G j and G j+1 , with g j (x) and g j+1 (x) as the parameters. Two values are obtainable from such functional calculation for each of the parameters g j (x) and g j+1T(x) . With the calculated values for the parameter g j (x) expressed as f -1 8-j [g j (x)] L and f -1 8-j [g j (x)] R , respectively, two points are determined on the function f 8-j ; namely one is the point g jL at the coordinates (g j (x), f -1 8-j [g j (x)] L and the other is the point g jR at the coordinates (g j (x), f -1 8-j [g j (x)] R ), as indicated in the diagram (b) of Fig. 2. Likewise, with the calculated values for the parameter g j+1 (x) expressed as f -1 8-(j+1) [g j+1 (x)] L and f -1 8-(j+1) [g j+1 (x)] R , respectively, two points are determined on the function f 8-(j+1) ; namely one is the point g (j+1)L at the coordinates (g j+1 (x), f -1 8-(j+1) [g j+1 (x)] L ) and the other is the point g (j+1)R at the coordinates (g j+1 (x), f -1 8-(j+1) [g j+1 (x)] R ), as indicated in the same diagram (b) of Fig. 2. Referring to the diagram (b) of Fig. 2, the area which is shaded with right-upward oblique lines is of a trapezoid shape with it top side defined by a line drawn between the points g jL and g jR , while the area shaded with right downward oblique lines is of a trapezoid shape with its top side defined by a line drawn between the points g (j+1)L and g (j+1)R . Then, the control computer C performs calculation to find the point of gravity center Q(Θ x ) of the sum-set area of the above two trapezoid shapes. The point Θ x on the abscissa corresponding to the point of grafity center Q(Θ x ) represents the component of open period for the electro-magnetic valves V i which is suitable for picking a weft yarn Y having the number count x. The relationship between the open period of valves V i and the yarn number count is indicated by a curved line E 1 in the diagram (a) of Fig. 3. As it is apparent, this curved line E 1 is influenced by the manner in which the valve open periods Θ 1 , Θ 2 , Θ 3 , Θ 4 , Θ 5 , Θ 6 , Θ 7 are grouped for classification from the experience and knowledge of experts and skilled workmen. Since such experience and knowledge used as the basis for the grouping of the above valve open periods Θ 1 , Θ 2 ,Θ 3 , Θ 4 , Θ 5 , Θ 6 , Θ 7 are very accurate, the curve line E 1 can provide an optimum valve open period for each yarn number count. On the basis of experience and knowledge of experts and skilled workmen, the grouping of Θ 1 , Θ 2 , Θ 3 , Θ 4 , Θ 5 , Θ 6 , Θ 7 can be made easily without relying on time-consuming different yarn number count. Furthermore, since data on valve open period obtainable from the experiment will cover a certain range of values, it would be troublesome to specifically select one optimum open period from a pluarlity of choices in the range. According to the above-described embodiment of the present invention, however, one optimum valve open period can be selected for any given yarn number count by the aid of a computer. The rotary encoder 13 for detecting the angle of rotation of the loom is operated in increment of Δ Θ (e.g. 2.5°). For this reason, the curve E 1 in the diagram (a) of Fig. 3 is converted into discrete function E 1 ′, as shown in the diagram (b) of Fig. 3. In the diagram (b), a dot represents a point at which a parameter of yarn number count is present; and a circle represents a point at which such parameter is absent. In the component Θ x of valve open period corresponding to the point of gravity center Q(Θ x ) in the diagram (b) of Fig. 2 is not an integral multiple of the above increment ΔΘ the control computer C performs the following calculation: Θ x = ((Θ x /Δ Θ) + 1)Δ Θ wherein, (Θ x /Δ Θ) represents an integral value with the decimal of Θ x /Δ Θ removed. When the value Θ x is an integral multiple of the increment Δ Θ, this Θ x is stored as the valve open period Θ x . The control computer C will control the operation of the valves V i during weaving operation according to the stored valve open period Θ x . Referring to Fig. 4, the length of valve open period Θ x (=β i - α i ) (in the diagram (a)) is set longer for handling a weft yarn having a count of smaller number, as compared with the length of valve open period Θ x (=β i ′ - α i ) (in the diagram (b)) for weft yarn with a count of larger number. It is to be noted that the present invention is not limited to the above-described embodiment, but it can be practiced in other way, e.g., wherein the time of weft picking commencement is set for each of different reed width dimensions, as will be described in the following with reference to Figs. 6 through 10. In the embodiment, the fabric condition data are provided by reed widths, and each of the condition data groups H jR (j=1 to 7 ) covers a range of feed widths as follows: H 1 = Very small reed width (L 1 to L 2 ) H 2 = Small reed width (L 1 to L 3 ) H 3 = Slightly small reed width (L 2 to L 4 ) H 4 = Average reed width (L 3 to L 5 ) H 5 = Slithly large reed width (L 4 to L 6 ) H 6 = Large reed width (L 5 to L 7 ) H 7 = Very large reed width (L 6 to L 7 ) wherein, L 1 < L 2 < L 3 < L 4 < L 5 < L 6 < L 7 On the other hand, each of the control factor groups K j (j=1 to 7) covers a range of weft picking commencement times as follows: K 1 = Very early commencement ime (t 1 to t 2 ) K 2 = Early commencement time (t 1 to t 3 ) K 3 = Slightly early commencement time (t 2 to t 4 ) K 4 = Average commencement time (t 3 to t 5 ) K 5 = Slightly late commencement time (t 4 to t 6 ) K 6 = Late commencement time (t 5 to t 7 ) K 7 = Very late commencement time (t 6 to t 7 ) wherein, t 1 < t 2 < t 3 < t 4 < t 5 < t 6 < t 7 Referring to Fig. 7, functions h j (j= 1 to 7) shown in the diagram (a) indicate the likelihood of any reed width y of the fabric condition data H j as a parameter of functions; and function k j shown in the diagram (b) indicate the likelihood of weft picking commencement time of the control factor groups K j . The fabric condition data groups H j and the control factor groups K j are established on the basis of experience and knowledge of expert and skilled workmen so as to correlate to each other. The grouping of the control factor groups K j , or the establishment of the individual weft picking commencement times t 1 , t 2 , t 3 , t 4 , t 5 , t 6 , t 7 , are made in ligth of the above experience and knowledge. Upon input of fabric condition dta, or data y on the reed width, through the data input device 19, the control computer C performs a series of calculations in a procedure similar to that described with reference to the first embodiment, but according to the flow chart provided in Fig. 10, which include: calculation of the functions h j (y) and h j+1 (y) in which the condition data y falls; calculation of the functions k -1 j[hj (y)] and k -1 fj+1 [h j+1 (y) ] which are inverse with respect to the above functions, respectively; calculation to find the point of gravity center Q(t y ) of sum-set area of two trapezoid shapes, i.e., one is a trapezoid shape whose top side is defined by a line connecting the point r jL at the coordinates (h j (y), k -1 j [h j (y)] L ) and the point r jR at the coordinates (h j (y), k -1 j [h j (y)] r ) and the other is a trapezoid shape whose top side is defined by a line connecting the point r (j+1)L at the coordinates (h j+1 (y)m k -1 j+1 [h j+1 (y)] L ) and the point r (j+1)R at the coordinates (h j+1 (y)m f -1 j+1 [h j+1 (y)] r ), both shown in the diagram (b) of Fig. 7; and calculation to find the weft picking commencement time T y . The weft picking commencement time T y is determined by the time at which the stop pin 12a is moved away from engagement with the weft winding surface la of the weft measuring and storing device 1, which latter time is in turn determined by the time at which the solenoid 12 is energized. The diagram (a) of Fig. 9 shows the weft picking commencement time T y for a reed with a relatively large width, while the diagram (b) of the same figure shows the weft picking commencement time T y for a reed with a relatively small width. The time of air injection (α i ′, β i ′) by the auxiliary nozzles 3 - 10 is changed in accordance with the change of weft picking commencement time T y . The relationship thus obtained between the weft picking commencement time T y and the reed widths is represented by the curved line E 2 shown in the diagram (a) of Fig. 7, and this line E 2 is determined by grouping establishment of weft picking commencement times t 1 , t 2 , t 3 , t 4 , t 5 , t 6 , t 7 from the experience and knowledge of experts and skilled workmen. Since such experience and knowledge used as the basis for the grouping of the weft picking commencement times t 1 , t 2 , t 3 , t 4 , t 5 , t 6 , t 7 are very accurate, the curved line E 2 can provide an optimum weft picking commencement time for each reed width. The curved line E 2 in the diagram (a) of Fig. 8 is converted into discrete function E 2 ′, as indicated in the diagram (b) of Fig. 8, for the same reason as in the first embodiment. According to the present invention, the fabric condition data and the control factors may be grouped in either a rougher or finder way than the abvove-described embodiments. Additionally, the fabric condition group may include other fabric conditions such as kinds of weft yarn, and the control factors may include other factors such as injection pressure of weft picking nozzle and/or running speed of the loom i.e. rpm of the loom. The weft picking control device of the jet loom, has a data input device 19 for feeding data of fabric conditions like yarn count number and/or reed width. There is further a data memory C 1 with stored control factor data regarding weft picking conditions like weft picking commencement, fluid injection time, duration and/or end. The data are classified in a plurality of groups according to a rule of order. Depending on the fabric conditions the optimum control factor data are selected for automatically setting of the loom by a CPU and program C 2 that is based on the interdependence of fabric conditions and control factor data.

Claims: Weft picking control device (C; C 1 , C 2 , CPU, 13, 14, 18, 19) in a jet loom wherein a weft yarn (Y) is picked by the action of fluid jets injected by weft picking nozzles (2, 3 - 10), said weft picking control device (C; C 1 , C 2 , CPU, 13, 14, 18, 19) comprising: means (C 1 ) for storing weft picking control factor data of at least one weft picking condition, means (19) for inputting data of at least one fabric condition that influences said weft picking control condition, and characterized by means (C1) for setting previously and storing a plurality of more than two groups of sequentially arrayed fabric condition data resulting from orderly classification of data of at least one fabric condition and a plurality of more than two groups of sequentially arrayed weft picking control factor data resulting from orderly classification of data of at least one weft picking control factor, means (C 1 , C 2 , CPU) for determining a specific group of fabric condition data from said plurality of more than two groups sequentially arrayed fabric condition data on the basis of said fabric condition data inputted by said data input means (19), determining a specific group of weft picking control factor data from said plurality of more than two groups sequentially arrayed weft picking control factor data on the basis of the likelihood of said determined specific group of fabric condition data, and determining an optimum weft picking control factor for said data of at least one fabric condition inputted by said data input means (19) on the basis of said determined specific group of weft picking control factor data. A weft picking control device (C; C 1 , C 2 , CPU, 13, 14, 18, 19) as claimed in claim 1 wherein the weft picking control factor data are controlling the time of weft picking commencement. A weft picking control device (C; C 1 , C 2 , CPU, 13, 14, 18, 19) as claimed in one of the claims 1 or 2 wherein the weft picking control factor data are or are in addition controlling the time of fluid injection time by at least one of the said weft picking nozzles (2, 3 - 10). A weft picking control device (C; C 1 , C 2 , CPU, 13, 14, 18, 19) as claimed in one of the claims 1 to 3, wherein the weft picking control factor data are or are in addition controlling the fluid pressure (16, 17) of at lest one of the said weft picking nozzles (2, 3 - 10). A weft picking control device (C; C 1 , C 2 , CPU, 13, 14, 18, 19) as claimed in one of the claims 1 to 4, wherein the weft picking control factor data are or are in addition controlling the number of picks per minute of the loom. A weft picking control device (C; C 1 , C 2 , CPU, 13, 14, 18, 19) as claimed in one of the claims 1 to 5 wherein the fabric condition data are the yarn number count of the weft yarn (Y). A weft picking control device (C; C 1 , C 2 , CPU, 13, 14, 18, 19) as claimed in one of the claims 1 to 6 wherein the fabric condition data are or are in addition the reed width of the loom.

Inventors: ARAKAWA AKIO, KATO MASAHIKO, ARAKAWA, AKIO, KATO, MASAHIKO, Arakawa, Akio, c/o KABUSHIKI KAISHA TOYODA, Kato, Masahiko, c/o KABUSHIKI KAISHA TOYODA
Applicants: TOYODA AUTOMATIC LOOM WORKS, KABUSHIKI KAISHA TOYODA JIDOSHOKKI SEISAKUSHO
Application year: 1991
Main classification: D03D47
IPC codes: D03D47, D03D51