CN115429517A - Soft scoliosis brace system based on fuzzy PID neural network - Google Patents
Soft scoliosis brace system based on fuzzy PID neural network Download PDFInfo
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- A61F5/00—Orthopaedic methods or devices for non-surgical treatment of bones or joints; Nursing devices; Anti-rape devices
- A61F5/01—Orthopaedic devices, e.g. splints, casts or braces
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Abstract
The invention discloses a soft scoliosis brace system based on a fuzzy PID neural network, which comprises: the support comprises a support main body, a monitoring assembly, a control subsystem, a self-adaptive adjusting assembly, a sliding guide rail and a back belt. The system automatically adjusts the sliding guide rail to move through the self-adaptive adjusting component, so that the length of the braces is adjusted, and the comfort of a patient when wearing the brace is improved; compared with the traditional rigid brace, the brace system improves the concealment and direct perception, further reduces the mental pressure of a wearer and reduces the occurrence of mental diseases; through the cooperation between monitoring subassembly, control subsystem, the self-adaptation regulating assembly for spinal muscle can exert accurate orthopedic torsion in the exact position in the developments, arouses the active contraction of patient's paraspinal muscle, increases muscle intensity, has improved the correction effect of brace.
Description
Technical Field
The invention relates to the technical field of spinal braces, in particular to a soft scoliosis brace system based on a fuzzy PID neural network.
Background
Juvenile idiopathic scoliosis (AIS): the common disease refers to adolescence or bone maturation (age 10-18 years), the Cobb angle on the coronal plane is more than 10 degrees, and the rotation of the vertebral body without other organic lesions accounts for about 80% of all scoliosis. Has become the 5 th most common disease of adolescents worldwide after abnormal vision, obesity, phimosis and psychosocial disorder.
The scoliosis treatment modes include non-operative treatment and operative treatment. Non-surgical treatment is generally a treatment of scoliosis at an early stage in order to prevent or correct the degree of scoliosis. Whether the scoliosis needs surgery treatment or not should be judged according to the factors of the malformation degree of the spine, the age, the body balance degree and the like of the patient in the aspect of treatment. If the patient is a teenager, non-surgical treatment should be selected. Wherein, the 20-40 degree stage of scoliosis Cobb angle mainly takes the brace wearing as the main. But there are still problems that it cannot overcome:
(1) When the Cobb angle of the spine is 20-30 degrees, when a traditional rigid brace is worn, muscles beside the spine can not actively expand and contract in equal length, iatrogenic muscular atrophy can be caused, and the malignant progress of the lateral bending Cobb angle is promoted;
(2) Some expert scholars study psychological changes before and after traditional rigid brace treatment on idiopathic scoliosis children, and as a result, the results show that 108 (80.6%) of 134 children with normal personality before traditional brace treatment have personality abnormality 1 month after brace treatment, and 19% of patients with scoliosis have real psychological disorder. Psychological diseases greatly affect the compliance and treatment effect of the treatment of children patients.
Therefore, how to solve the wearing pain point of the rigid brace by an effective method and further improve the psychological state of the patient is a problem to be solved urgently at present.
Disclosure of Invention
Therefore, the technical problem to be solved by the present invention is to overcome the defects in the prior art, and to provide a soft scoliosis brace system based on a fuzzy PID neural network.
The invention provides a soft scoliosis brace system based on a fuzzy PID neural network, which comprises: the device comprises a brace main body, a monitoring component, a control subsystem, a self-adaptive adjusting component, a sliding guide rail and a strap;
the brace main body comprises a back plate and a fixing band; the back plate is attached to the waist of a human body, the fixing belts are arranged along the waistline, and the fixing belts are used for fixing the back plate;
the monitoring component is attached to the skin of a human body and is electrically connected with the control subsystem; the monitoring assembly is used for detecting the posture of the human body and transmitting a detection signal to the control subsystem;
the control subsystem is arranged on the back plate; the output end of the control subsystem is electrically connected with the output end of the self-adaptive adjusting component; the control subsystem is used for controlling the self-adaptive adjusting component to work according to the detection signal;
the self-adaptive adjusting component is arranged on the back plate, and the output end of the self-adaptive adjusting component is connected with the sliding guide rail; the self-adaptive adjusting component is used for adjusting the sliding guide rail to move;
one end of the back belt is connected with the sliding guide rail, and the other end of the back belt is connected with the fixing belt positioned in front of the chest.
Preferably, the monitoring component comprises a gyroscope sensor, an inclination angle sensor, a distributed touch sensor and an attitude sensor; the gyroscope sensor is used for detecting the Cobb angle of the spine, the height difference of the lateral shoulder peak and the height difference of the anterior superior iliac spines on both sides; the inclination angle sensor is used for detecting the change of lordosis, kyphosis and scoliosis; the distributed tactile sensor is used for analyzing the size and the change of the spinal correction force; the posture sensor is attached to the waist and used for detecting the change of the human body acceleration signal.
Preferably, the control subsystem comprises a generalized inverse model of the multi-motor control system and a fuzzy self-adaptive PID controller; the generalized inverse model of the multi-motor control system is used for obtaining a pseudo-linear composite control system through neural network algorithm fitting; the fuzzy adaptive PID controller is used for setting the error of the pseudo linear composite control system.
Preferably, the self-adaptive adjusting assembly comprises a motor, a bevel gear commutator and a winder; the motor is connected with the output end of the control subsystem; the output shaft of the motor is connected with the input end of the bevel gear commutator; the output end of the bevel gear commutator is connected with the winder; the winder is connected with the sliding guide rail.
Preferably, the bevel gear commutator comprises a box body, a shaft base, a connecting shaft, a transmission gear and a power shaft; one side of the box body is provided with a hole; the shaft base is arranged in the box body; one end of the connecting shaft is fixed on the shaft base, and the other end of the connecting shaft is connected with the winder; the transmission gear is fixed on the periphery of the connecting shaft; one end of the power shaft is provided with a gear, the gear is meshed with the transmission gear, and one end of the power shaft, far away from the gear, penetrates through the hole and is connected with an output shaft of the motor.
Preferably, the adaptive adjustment assembly further comprises a coupler; the coupler is arranged outside the box body, and one end of the coupler is clamped with the hole; the coupling is sleeved outside the power shaft.
Preferably, the sliding guide rail comprises a guide rail base and a sliding block; the guide rail base is arranged at the end part of the strap, and a long groove is formed in the guide rail base; the sliding block is provided with a limiting hole and is arranged in the long groove; one end part of the sliding block is connected with the winder through a wire harness; the limiting holes comprise a plurality of limiting holes used for controlling the sliding distance of the sliding block.
Preferably, the two sides of the long groove are both provided with bulges, and the bulges are extended along the long axis direction of the long groove and are consistent with the long axis of the long groove in length; sliding grooves are formed in the two sides of the sliding block, extend along the long axis direction of the sliding block and are consistent with the long axis of the sliding block in length; the sliding groove is in sliding fit with the protrusion; the protrusion and the sliding groove are used for realizing sliding of the sliding block on the guide rail base.
Preferably, the harness is an adjustable harness; the back plate is a light and hard plate.
Preferably, the fixed band is soft fixed band, and the fixed band both ends tip is fixed through the magic subsides.
The technical scheme of the invention has the following advantages:
1. this system moves through self-adaptation adjusting part automatically regulated sliding guide, and then adjusts the length of braces, the comfort when having improved the patient and dressing the brace.
2. Compared with the traditional rigid brace, the brace system improves the concealment and direct perception, further reduces the mental pressure of a wearer, and reduces the occurrence of mental diseases.
3. Through the cooperation between monitoring subassembly, control subsystem, the self-adaptation regulating assembly for spinal muscle can exert accurate orthopedic torsion in the exact position in the developments, arouses the active contraction of patient's paraspinal muscle, increases muscle intensity, has improved the correction effect of brace.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a rear view of a soft scoliosis brace system based on a fuzzy PID neural network in accordance with an embodiment of the present invention;
FIG. 2 is a front view of the brace system shown in FIG. 1;
FIG. 3 is a schematic diagram of a process for obtaining a pseudo-linear composite control system in accordance with an embodiment of the present invention;
FIG. 4 is a schematic diagram of a process for constructing a control subsystem in accordance with an embodiment of the present invention
FIG. 5 is a schematic diagram of the internal structure of the adaptive tuning assembly in the practice of the present invention;
FIG. 6 is a schematic view of a sliding guide in the practice of the present invention;
FIG. 7 is a schematic view of a guide rail mount in the practice of the present invention;
FIG. 8 is a schematic diagram of a slider structure in accordance with an embodiment of the present invention.
Description of the reference numerals:
1-a brace body; 11-a back plate; 12-fixing the belt;
2-a monitoring component;
3-a control subsystem;
4-an adaptive adjustment component; 41-a motor; 42-bevel gear commutator; 421-box body; 422-shaft base; 423-connecting shaft; 424-drive gear; 425-a power shaft; 426-hole; 427-a gear; 43-a winder; 44-a coupling;
5-a sliding guide rail; 51-a guide rail mount; 511-Long groove; 512-bump; 52-a slider; 521-a limiting hole; (ii) a 522-sliding groove; 6-braces; 7-magic tape.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1 and fig. 2, the present embodiment provides a soft scoliosis brace system based on a fuzzy PID neural network, the brace system includes: the self-adaptive adjusting brace comprises a brace main body 1, a monitoring component 2, a control subsystem 3, an adaptive adjusting component 4, a sliding guide rail 5 and a back belt 6;
the brace main body 1 comprises a back plate 11 and a fixing belt 12; the back plate 11 is attached to the waist of a human body, the fixing belts 12 are arranged along the waistline, and the fixing belts 12 are used for fixing the back plate 11;
the monitoring component 2 is attached to the skin of a human body and is electrically connected with the control subsystem 3; the monitoring component 2 is used for detecting the posture of the human body and transmitting a detection signal to the control subsystem 3;
the control subsystem 3 is arranged on the back plate 11; the output end of the control subsystem 3 is electrically connected with the output end of the adaptive adjusting component 4; the control subsystem 3 is used for controlling the self-adaptive adjusting component 4 to work according to the detection signal;
the self-adaptive adjusting component 4 is arranged on the back plate 11, and the output end of the self-adaptive adjusting component 4 is connected with the sliding guide rail 5; the self-adaptive adjusting component 4 is used for adjusting the sliding guide rail 5 to move;
one end of the back belt 6 is connected with the sliding guide rail 5, and the other end is connected with a fixing belt 12 positioned in front of the chest.
Through the cooperation between monitoring subassembly, control subsystem, the self-adaptation regulating assembly for spinal muscle can exert accurate orthopedic torsion in the exact position in the developments, arouses the active contraction of patient's paraspinal muscle, increases muscle intensity, has improved the correction effect of brace.
In the present embodiment, the strap 6 is an adjustable strap; the back plate 11 is a light and hard plate; the fixing band 12 is a soft fixing band, and the end parts of the two ends of the fixing band 12 are fixed through the magic tapes 7. Compared with the traditional rigid brace, the brace system improves the concealment and direct perception, further reduces the mental pressure of a wearer, and reduces the occurrence of mental diseases.
Further, the monitoring component 2 comprises a gyroscope sensor, an inclination angle sensor, a distributed touch sensor and an attitude sensor; the gyroscope sensor is used for detecting the Cobb angle of the spine, the height difference of the lateral shoulder peak and the height difference of the anterior superior iliac spines on both sides; the inclination angle sensor is used for detecting the change of lordosis, kyphosis and scoliosis; the distributed tactile sensor is used for analyzing the size and the change of the spinal correction force; the posture sensor is attached to the waist and used for detecting the change of the human body acceleration signal.
According to the Hueter-Volkmann law, the brace conservative treatment provides a biomechanics three-point or four-point correction rule to achieve the purpose of correcting the lateral bulge. The determination of the brace model parameters is intended to collect dynamic three-dimensional kinematic data of the individual bones with a plurality of sensors (chest sensor, lumbar sensor, scapula sensor and humerus sensor) directly attached to the skin of the patient. The initial spinal information of the patient can be obtained more accurately in coordination with the exposure of the X-ray to determine the location of the point of application (Hueter-Volkmann's law, the epiphyseal pressure law, indicates that the bone growth is inhibited with increased pressure on the bone, and the bone growth is accelerated with decreased pressure on the epiphyseal, excessive pressure can inhibit epiphyseal growth, and tension on the epiphyseal can accelerate its growth).
The real-time posture data of the spine of the patient is rapidly acquired through a multi-sensor fusion technology, powerful support is provided for medical staff to call and check the data of the patient as required, and the times of the patient entering a hospital and entering X-ray examination are reduced.
Furthermore, the control subsystem 3 comprises a multi-motor control system generalized inverse model and a fuzzy self-adaptive PID controller; the generalized inverse model of the multi-motor control system is used for obtaining a pseudo-linear composite control system through neural network algorithm fitting; the fuzzy adaptive PID controller is used for setting the error of the pseudo linear composite control system. In this embodiment, the control subsystem is also equipped with a battery.
As shown in fig. 3, the fitted inverse system is realized by means of the neural network, and then the inverse system is connected in series in front of the original system, thereby forming the inverse linear control system of the two-motor neural network. The pseudo linear system constructed by the two-motor neural network inverse control is decoupled into a stable subsystem by reasonably configuring the poles of the single-input single-output subsystem in a complex plane, so that a relatively ideal pseudo linear composite control system is obtained.
In this embodiment, the reasonable configuration includes:
selecting a proper grid structure, and determining the number of input and output nodes of the used neural network;
the excitation signal is fully sampled, and data containing the whole experimental range is selected to ensure accurate training sampling;
the accuracy of the neural network off-line training is ensured, and then an inverse system of the characteristics of the two motor synchronous systems is realized.
As shown in FIG. 4, fuzzy control and traditional PID control technology are combined to form a plurality of fuzzy adaptive PID controllers, which have the characteristics of two control algorithms, based on a series of fuzzy decision rules, the system automatically adjusts PID parameters to realize the intelligent PID control of the original system, and when the two-motor neural network inverse control system changes along with input conditions and is influenced by interference factors in the operation process, the online identification of system characteristic parameters and the real-time change of control parameters are realized, so that the control system always keeps the dynamic optimal control. The two-motor neural network inverse pseudo linear control system has an open-loop stable linear transfer relationship, but the neural network has some errors when fitting an original system and is not completely linearized, so that an fuzzy self-adaptive PID controller (with a closed-loop control function) is required to be added, and a control subsystem is formed.
By combining the neural network, the fuzzy controller and the traditional PID control box, the control parameters are adjusted in real time according to the change of the motion state of the patient, so that the brace system can dynamically adjust, correct and apply force in a closed loop within short response time, and the brace system has the advantages of strong adaptability and high control precision.
In the present embodiment, the adaptive adjustment assembly 4 includes a motor 41, a bevel gear commutator 42, and a winder 43; the motor 41 is connected with the output end of the control subsystem 3; the output shaft of the motor 41 is connected with the input end of the bevel gear commutator 42; the output end of the bevel gear commutator 42 is connected with the winder 43; the wire winder 43 is connected to the slide rail 5.
Further, as shown in fig. 5, the bevel gear commutator 42 includes a box body 421, a shaft base 422, a connecting shaft 423, a transmission gear 424, a power shaft 425, and a coupling 44; one side of the box 421 is provided with a hole 426; the shaft base 422 is arranged in the box 421; one end of the connecting shaft 423 is fixed to the shaft base 422, and the opposite end thereof is connected to the winder 43; the transmission gear 424 is fixed on the periphery of the connecting shaft 423; a gear 427 is arranged at one end of the power shaft 425, the gear 427 is meshed with the transmission gear 424, and one end of the power shaft 425 far away from the gear 427 is connected with the output shaft of the motor 41 through a hole 426; the coupler 44 is arranged outside the box 421, and one end of the coupler 44 is clamped with the hole 426; coupling 44 is sleeved outside power shaft 425.
Further, as shown in fig. 6, the slide rail 5 includes a rail base 51 and a slide block 52; the back of the guide rail base 51 is fixed with the end part of the brace 6, and the front of the guide rail base 51 is provided with a long groove 511; the two sides of the long groove 511 are provided with protrusions 512, and the protrusions 512 extend along the long axis direction of the long groove 511 and have the same length as the long axis of the long groove 511, as shown in fig. 7. A limiting hole 521 is formed in the sliding block 52, and the sliding block 52 is arranged in the long groove; one end of the sliding block 52 can be connected with the winder 43 through a wire harness; the limiting holes 521 include three, and each limiting hole 521 is used for controlling the sliding distance of the sliding block 52. In addition, sliding grooves 522 are provided on both sides of the sliding block 52, and the sliding grooves 522 extend in the long axis direction of the sliding block 52 and have the same length as the long axis of the sliding block 52, as shown in fig. 8; the sliding groove 522 is in sliding fit with the protrusion 512; the sliding of the sliding block 52 on the guide rail base 51 is realized by the cooperation of the sliding groove 522 and the protrusion 512.
In this embodiment, a limiting post is inserted into the limiting hole 521, or a stop piece is installed on two radial sides of the long groove 511 to achieve the effect of controlling the sliding distance of the sliding block 52.
After the brace system is worn by a patient, the posture of the human body is detected in real time through the monitoring component 2 to obtain spine state information, the spine state information is transmitted to the motor 41 after being processed by the signal of the control subsystem 3, the motor 41 of the self-adaptive adjusting component 4 works after receiving the signal, the motor 41 rotates and can realize the rotation of the winder 43 through the coupler 44 and the bevel gear commutator 42, the winder 43 rotates to drive the sliding guide rail 5 to move, the retraction and release of braces are finally realized, and the posture of the spine is dynamically adjusted.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (10)
1. A soft scoliosis brace system based on a fuzzy PID neural network, comprising: the self-adaptive adjusting device comprises a brace main body (1), a monitoring component (2), a control subsystem (3), an adaptive adjusting component (4), a sliding guide rail (5) and a strap (6);
the brace main body (1) comprises a back plate (11) and a fixing belt (12); the back plate (11) is attached to the waist of a human body, the fixing bands (12) are arranged along the waistline, and the fixing bands (12) are used for fixing the back plate (11);
the monitoring component (2) is attached to the skin of a human body and is electrically connected with the control subsystem (3); the monitoring component (2) is used for detecting the posture of a human body and transmitting a detection signal to the control subsystem (3);
the control subsystem (3) is arranged on the back plate (11); the output end of the control subsystem (3) is electrically connected with the output end of the self-adaptive adjusting component (4); the control subsystem (3) is used for controlling the self-adaptive adjusting component (4) to work according to the detection signal;
the self-adaptive adjusting component (4) is arranged on the back plate (11), and the output end of the self-adaptive adjusting component (4) is connected with the sliding guide rail (5); the self-adaptive adjusting component (4) is used for adjusting the sliding guide rail (5) to move;
one end part of the back belt (6) is connected with the sliding guide rail (5), and the other end of the back belt is connected with the fixing belt (12) positioned in front of the chest.
2. A soft scoliosis brace system based on fuzzy PID neural network as claimed in claim 1, wherein the monitoring component (2) comprises a gyroscope sensor, an inclination sensor, a distributed touch sensor, an attitude sensor; the gyroscope sensor is used for detecting the Cobb angle of the spine, the height difference of the lateral shoulder peak and the height difference of the bilateral anterior superior iliac spines; the tilt angle sensor is used for detecting the change of lordosis, kyphosis and scoliosis; the distributed tactile sensor is used for analyzing the size and the change of the spinal correction force; the posture sensor is attached to the waist and used for detecting the change of the human body acceleration signal.
3. The soft scoliosis brace system based on fuzzy PID neural network according to claim 2, characterized in that the control subsystem (3) comprises a multi-motor control system generalized inverse model and a fuzzy adaptive PID controller; the generalized inverse model of the multi-motor control system is used for obtaining a pseudo-linear composite control system through neural network algorithm fitting; the fuzzy adaptive PID controller is used for setting the error of the pseudo linear composite control system.
4. A soft scoliosis brace system based on fuzzy PID neural network as claimed in claim 3, wherein the adaptive adjusting component (4) comprises a motor (41), a bevel gear commutator (42) and a winder (43); the motor (41) is connected with the output end of the control subsystem (3); the output shaft of the motor (41) is connected with the input end of the bevel gear commutator (42); the output end of the bevel gear commutator (42) is connected with the winder (43); the winder (43) is connected with the sliding guide rail (5).
5. The soft scoliosis brace system based on fuzzy PID neural network of claim 4, wherein the bevel gear commutator (42) comprises a box body (421), a shaft base (422), a connecting shaft (423), a transmission gear (424) and a power shaft (425); one surface of the box body (421) is provided with a hole (426); the shaft base (422) is arranged in the box body (421); one end of the connecting shaft (423) is fixed on the shaft base (422), and the other end is connected with the winder (43); the transmission gear (424) is fixed on the periphery of the connecting shaft (423); one end of the power shaft (425) is provided with a gear (427), the gear (427) is meshed with the transmission gear (424), and one end, far away from the gear (427), of the power shaft (425) penetrates through the hole (426) to be connected with an output shaft of the motor (41).
6. A soft scoliosis brace system based on fuzzy PID neural network according to claim 5, characterized by, that the adaptive adjusting component (4) further comprises a coupler (44); the coupler (44) is arranged outside the box body (421), and one end of the coupler (44) is clamped with the hole (426); the coupling (44) is sleeved outside the power shaft (425).
7. A soft scoliosis brace system based on fuzzy PID neural network according to claim 4, characterized by, that the sliding guide rail (5) comprises a guide rail base (51) and a sliding block (52); the guide rail base (51) is arranged at the end part of the strap (6), and a long groove (511) is formed in the guide rail base (51); a limiting hole (521) is formed in the sliding block (52), and the sliding block (52) is arranged in the long groove (511); one end part of the sliding block (52) is connected with the winder (43) through a wire harness; the limiting holes (521) are formed in a plurality of numbers, and the limiting holes (521) are used for controlling the sliding distance of the sliding block (52).
8. The soft scoliosis brace system based on the fuzzy PID neural network according to the claim 7, wherein the two sides of the long groove (511) are provided with protrusions (512), the protrusions (512) extend along the long axis direction of the long groove (511) and are consistent with the long axis of the long groove (511); sliding grooves (522) are formed in two sides of the sliding block (52), the sliding grooves (522) extend along the long axis direction of the sliding block (52), and the length of the sliding grooves is consistent with that of the long axis of the sliding block (52); the sliding groove (522) is in sliding fit with the protrusion (512); the protrusion (512) and the sliding groove (522) are used for realizing the sliding of the sliding block (52) on the guide rail base (51).
9. The system of claim 1, wherein the harness (6) is an adjustable harness; the back plate (11) is a light and hard plate.
10. The soft scoliosis brace system based on the fuzzy PID neural network as claimed in claim 1, wherein the fixing band (12) is a soft fixing band, and both ends of the fixing band (12) are fixed by magic tapes (7).
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116679551A (en) * | 2023-07-31 | 2023-09-01 | 欣灵电气股份有限公司 | Automatic control method of winding machine based on encoder feedback winding displacement shaft speed |
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| CN116679551B (en) * | 2023-07-31 | 2023-10-13 | 欣灵电气股份有限公司 | Automatic control method of winding machine based on encoder feedback winding displacement shaft speed |
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