Arc-shaped folding door with independent compartment

Abstract

The utility model relates to an arc-shaped folding door with an independent compartment, which comprises three straight wall enclosures of the compartment and a door spindle vertically mounted in the center of the top of the open side of the compartment, the door spindle is provided with at least three bearings stacked up and down, and each bearing is connected with a rotating cantilever. Each rotating cantilever is fixedly connected with the top end of an arc-shaped door leaf, a door leaf driving mechanism for driving the arc-shaped door leaves to be overlapped when the arc-shaped door leaves are opened and to be unfolded when the arc-shaped door leaves are closed is further arranged on the door shaft, and multi-line laser radars for detecting personnel entering and exiting are arranged inside and outside the compartments respectively. All the arc-shaped door leaves are driven by one central shaft to be folded, opened and closed, so that the whole structure is greatly combined, the failure rate is greatly reduced, and the door is more reliable and durable. Compared with the prior art, detection equipment is simpler, the cost is lower, the influence of the environment on laser detection is smaller, and the reliability is greatly enhanced.

Description

TECHNICAL FIELD

[0001] The utility model relates to a single room's arc folding door, which is a building component for blocking space. BACKGROUND

[0002] The existing folding door usually adopts the sliding guide rail mode, and compared with the flat opening door with a door shaft, the door leaf movement of this mode is easily blocked and jammed.

[0003] There are many applications of contactless automatic opening and closing doors, which have obvious effects in improving passing efficiency, reducing cross infection and preventing infectious diseases. The principle is to use the induction sensor installed near the passage door to sense the approach of personnel or objects, and the controller automatically controls the door to open and automatically closes the door when there is no object under the door. However, the bank cash machine isolation door and the toilet door do not have good contactless intelligent opening and closing function. On the one hand, the security / privacy particularity of the bank cash machine isolation door and the toilet door leads to the inapplicability of the conventional automatic door. On the other hand, it is difficult to realize the automatic door in this application scenario, which needs to meet the requirements of one-way automatic opening and closing and self-locking (to prevent others from entering). Especially, the toilet rotating door is particularly prone to hygiene or infectious disease problems caused by using limbs to open and lock the door. Therefore, the contactless automatic door has important application value for security doors with security and privacy requirements.

[0004] At present, there is a contactless toilet single room semi-automatic opening and closing door application, which uses limb sensors installed on the door side (one on the inside and one on the outside) to perform opening and closing operations. When entering the door, the hand needs to approach the sensing area outside the door, the door control system obtains the signal to perform the opening operation, and after the person enters, the hand needs to approach the sensing area inside the door again, the door control system obtains the signal to perform the closing operation. After the toilet is finished, the hand needs to approach the sensing area inside the door to open the door. The disadvantages of this method are as follows: the whole process needs to approach the sensing area three times, the process is complicated, and the experience is not good; the limb sensor is not friendly, which is difficult to adapt to people of different heights, and the eye recognition is not high, if someone does not recognize the prompt text above, the toilet cannot be used. How to make the structure of a single door simpler, more accurate and convenient is a problem to be solved. SUMMARY

[0005] In order to overcome the problems of the prior art, the utility model provides a single room's arc folding door. The arc folding door simplifies the complex folding door by using a rotating shaft, and the opening and closing is more smooth, and the cost is greatly reduced. The door control method uses a recognition method of laser point cloud, which is more economical and accurate than the existing Doppler radar.

[0006] The utility model discloses a purpose is realized like this: a single room's arc folding door, include: room three straight wall enclose and block, vertical installation in the room open one side top center's door shaft, door shaft setting at least three bearings of upper and lower stacking, each bearing is connected respectively rotating cantilever, each rotating cantilever is fixedly connected respectively with the top end of arc leaf, door shaft still be equipped with the door leaf drive mechanism of overlapping when driving arc leaf open, unfolding when closing, room inside and outside are provided respectively and detect the personnel's in and out multilinear laser radar.

[0007] Further, the two sides of the arc-shaped door leaf are respectively provided with push-pull bending.

[0008] Further, the door leaf drive mechanism only drives one arc-shaped door leaf, and other arc-shaped door leaves are opened or closed through the push-pull bending linkage.

[0009] Further, the rotating cantilever is a straight rod or a sector.

[0010] Further, the door shaft is provided with an absolute value angle encoder for detecting the opening degree of the door leaf.

[0011] The utility model discloses the advantages and beneficial effects are: the utility model discloses utilize one center axle to drive all arc-shaped door leaf folding open and close, make integral structure greatly combine, failure rate reduces greatly, more reliable durable. And utilize multilinear laser radar and carry out personnel detection, compare with prior art, the equipment of detection is simpler, and the cost is lower, and the influence of laser detection to environment is smaller, and the reliability greatly strengthens. BRIEF DESCRIPTION OF DRAWINGS

[0012] The utility model will be further described below in connection with the drawings and examples.

[0013] Figure 1 It is the structure plan view when the arc-shaped folding door of the utility model embodiment one closes.

[0014] Figure 2 It is the structure plan view when the arc-shaped folding door of the utility model embodiment one opens.

[0015] Figure 3 It is the elevation structure diagram of the arc-shaped folding door of the utility model embodiment one.

[0016] Figure 4 It is the flow chart of the method of the utility model embodiment six. CONCRETE IMPLEMENTATION

[0017] Embodiment one:

[0018] The utility model discloses a purpose is realized like this: a single room's arc folding door, like Figure 1 、 2As shown in Figure 3. This embodiment includes: a partition with three straight walls 1, a door hinge 2 vertically installed at the top center of the open side of the partition, the door hinge having at least three bearings 3 stacked vertically, each bearing being connected to a rotating cantilever 4, each rotating cantilever being fixedly connected to the top of an arc-shaped door leaf 5, the door hinge also having a door leaf driving mechanism for driving the arc-shaped door leaf to overlap when open and unfold when closed, and multi-line lidar for detecting personnel entering and exiting being installed inside and outside the partition.

[0019] The three straight walls of the partition are the enclosure structure of the partition. They can be made of materials such as PVC panels. Various facilities can be installed on the straight walls according to different needs, such as foldable small tables, stools, tissue boxes, etc.

[0020] The door hinge is fixed at the top, connecting a series of bearings together. The number of bearings corresponds to the number of door panels. For example, if four door panels are used, each door panel corresponds to one or two bearings, then the number of bearings is 4 or 8.

[0021] The rotating cantilever connecting the door leaf and the bearing can be a straight rod or a fan-shaped flat plate. There are four or more curved door leaves. Taking four curved door leaves as an example, the four curved door leaves are arranged opposite each other, with their upper ends fixed to the bearings of the fixed support arm by a rotatable support arm, and their lower ends suspended. The door leaf drive mechanism is fixed to the bearings, which are stacked vertically, resulting in four bearings for the four curved door leaves. The door leaf drive mechanism drives the fourth connecting bearing. Push-pull bends are provided on both sides of the four curved door leaves; driving the fourth curved door leaf can push / pull the other three curved door leaves back / out. An absolute angle encoder can be installed on the door hinge to measure the opening and closing state of the door leaves. The absolute angle encoder can be installed on the connecting bearing of the fourth curved door leaf to detect the rotation angle of the fourth curved door leaf, thereby achieving opening and closing angle control.

[0022] A door drive mechanism can drive one door leaf, which in turn drives other door leaves. Alternatively, it can drive each door leaf individually, allowing the doors to open and close in one direction or both directions.

[0023] Under the control of a multi-line lidar, the folding door panel detects the actions of person 6, including standing and entering, to open or close the folding door and prevent pedestrians from being pinched. The multi-line lidar described in this embodiment is not a single radar, but a radar system, comprising at least two radars: one inside and one outside the compartment, or two inside and two outside the compartment, forming a multi-point detection system that makes radar detection and control more precise.

[0024] The material for curved door panels can be metal or plastic.

[0025] Example 2:

[0026] This embodiment is an improvement upon Embodiment 1, and is a refinement of the embodiment regarding the curved door leaf. The curved door leaf in this embodiment has push-pull bends on both sides.

[0027] The push-pull bends on both sides of each curved door leaf hook together to create a linkage for opening and closing.

[0028] Example 3:

[0029] This embodiment is an improvement upon the above embodiment, detailing the door drive mechanism. In this embodiment, the door drive mechanism drives only one curved door leaf; other curved door leaves open or close via a push-pull and bending linkage.

[0030] The door drive mechanism only needs to drive Figure 1 The rightmost curved door can be pushed and pulled to open and close other curved doors.

[0031] Example 4:

[0032] This embodiment is an improvement upon the above embodiment, and a refinement of the rotating cantilever described in the above embodiment. The rotating cantilever described in this embodiment is a straight rod or a sector-shaped rod.

[0033] Straight rod rotating cantilever such as Figure 1 , 2 As shown.

[0034] Example 5:

[0035] This embodiment is an improvement upon the above embodiment, and a refinement of the door hinge aspect. The door hinge in this embodiment is equipped with an absolute angle encoder for detecting the door opening degree.

[0036] Absolute angle encoders, used in conjunction with multi-line lidar, are employed to detect the movement of door panels. In certain special cases, such as when people entering a compartment are carrying a large number of items, which affects the detection accuracy of the lidar beams, absolute angle encoders are used to detect the rotation angle of curved door panels, supplementing the limitations of lidar.

[0037] Example 6:

[0038] This embodiment describes a contactless door control method for the aforementioned curved folding door with a separate compartment. The purpose of the method is to achieve contactless automatic door opening and closing, without requiring the user to understand its usage beforehand or perform excessive operations.

[0039] The curved folding door of the individual cubicle described in the above embodiment is equipped with an intelligent door control multi-line LiDAR that continuously identifies whether there is a human-shaped object in front of the door. When someone stands in front of the closed individual cubicle door, the multi-line LiDAR installed on the folding door first determines whether there is someone inside the cubicle. If there is someone, the door will not open. If no one is detected inside the cubicle, and the person has been standing in front of the door for more than 1 second, the folding door of the individual cubicle will automatically open. Once the person enters the cubicle and is detected to be fully inside, the folding door will close and automatically lock, regardless of whether there is someone standing outside. When the person inside the cubicle needs to leave, they only need to approach the folding door or use a special unlocking button (either a contact button or a non-contact button) and the folding door will open automatically.

[0040] The method described in this embodiment employs a multi-line lidar to emit a massive laser point cloud into space, acquiring the spatial location information of each laser impact point in the physical space through multi-line scanning, and identifying object shapes or key feature points using the point cloud data. The laser beams of the selected lidar are safe and harmless to the human eye and do not pose privacy issues like those associated with video cameras. The steps of the method are as follows, and the process is as follows: Figure 4 As shown:

[0041] Step 1, Constructing a mathematical model of the compartment: Using laser point clouds, mathematical modeling is performed on the space inside and outside the compartment when no one is present, forming a matching and comparison model to determine whether there are objects inside or outside the compartment;

[0042] Using the rotation center of the door hinges connecting the curved door panels as the origin, a planar xy coordinate system is established. The multi-line lidar is then configured according to... Figure 2 Spatial point cloud scanning modeling is performed to obtain the xy coordinates of the partition enclosure plane. The area enclosed by ABDEC is the interior of the partition, and arc CED is the movement trajectory of the arc-shaped folding door revolving door. The rotation radius of the arc door is r, and the distance from the rear wall of the partition to the center of the semicircle is L.

[0043] Establish a spatial (elevation) xz coordinate system, such as Figure 3 As shown. The difference in the z-axis between the point cloud above a person's head and the point cloud on the ground is the height of the person's head. The z-value of the ground measured by the multi-line lidar is... The z-value at the top of the person's head The height of the human body is ;

[0044] Point cloud learning is performed on objects within an unmanned compartment to establish a matching and comparison model for determining whether an object has entered. The modeling process involves filtering objects whose x and y values ​​are located in unmanned spaces. Figure 2 The point cloud within the area enclosed by the ABDEC central fence includes point clouds falling on the ground and point clouds falling on objects (such as small tables, toilets, etc.). The point cloud is filtered according to Equation 1, and the filtered point cloud is recorded and stored, recording the coordinates of each laser point. value;

[0045] Formula 1

[0046] The point cloud data obtained by real-time scanning of the compartment is compared with the point cloud data of the compartment when it is unoccupied to determine whether an object has entered. The process includes the following sub-steps:

[0047] Sub-step 101: Use Equation 1 to obtain and filter data located in real time. Figure 2 The point cloud within the enclosure of the ABDEC compartment will Substituting the values ​​into Equation 1, we obtain Equation 2 as the point cloud selection condition within the compartment at this time. Record the coordinates of each laser point. The value is j, where j is the sequence number of the point cloud sampling points in the compartment acquired in real time; at this time, there may be people in the compartment or no one, which needs to be determined.

[0048] Formula 2

[0049] Sub-step 102 involves matching and comparing the real-time filtered point cloud with the point cloud within the unmanned room. The matching and comparison method involves finding the point cloud with a height above the z-axis for each laser point within the unmanned room. The point (valued at 0.8 meters) is based on the lowest human height. The specific method is as follows: based on the characteristics of point cloud clustering, using each laser point within the unoccupied room as the center, with a radius of... Within a circle (with a value of 0.01 meters), select points in the real-time point cloud whose z-coordinate value is greater than 0.8 meters. That is, as long as the height of the laser point within the single room is 0.8 meters greater than the matching point, and the number of such points exceeds a certain threshold. Then it is assumed that there is an object, as in Equation 3.

[0050] Formula 3

[0051] Sub-step 103 involves summing according to the conditions of Equations 2 and 3 as shown in Equation 4. If, according to Equation 4, the number N of laser points found satisfies... If the object enters the compartment, it is assumed that an object has entered; otherwise, it is assumed that there is no object in the compartment. The value of is related to the scanning density of the laser point cloud, and its magnitude should be determined according to the actual situation.

[0052] Formula 4

[0053] The principle for determining whether there are objects outside the cubicle (outside the door) is the same as that for determining whether there are objects inside the cubicle. The main difference between determining whether there are objects outside the cubicle and determining whether there are objects inside the cubicle lies in: marking out an area in front of the cubicle door that is large enough for a person to stand in. This area should be large enough for a person to stand in, along with the corresponding items. In some special situations, such as when there are accompanying persons or wheelchairs, this area needs to be expanded.

[0054] Step 2, Construct a mathematical model of human morphology: Use laser point cloud clustering analysis to mathematically model the human morphology, and determine the human matching model based on height and morphological regions.

[0055] With a human body matching model, it is possible to obtain information such as whether there is someone in front of the door, the position and shape of the human body during the process of entering the door, and the position of the human body after the door is closed.

[0056] Point cloud clustering can be divided into several cases:

[0057] Scenario 1: When a single person enters the cubicle, the point cloud is divided into point cloud distributions on the top of the head and shoulders of the single person;

[0058] The distribution of laser points falling on a standing human body (an adult or a child) is as follows: Figure 4 As shown (taking a human body standing upright under a lidar as an example), point cloud clustering can divide the data into point clouds at the top of the head, at the shoulders, and in other areas. It's easy to see that the point clouds at the top of the head and at the shoulders have significant characteristics. The point clouds at the top of the head differ from those at the shoulders in height (spatial z-coordinate) by 20-30 cm, and the height of the point clouds at the top of the head should be greater than 1.0 meter (the lower limit of human height). The point clouds at the shoulders are distributed on both sides of the point clouds at the top of the head. Clustering based on feature values ​​allows us to filter out the lidar point clouds at the top of the human head. After filtering out the point clouds at the top of the head, height measurement and position tracking can be performed. This concludes the process of human morphological data modeling.

[0059] With human body position tracking, the xy coordinates of a person in a room can be obtained, and the ability to open and close a foldable revolving door can be determined based on the coordinate position.

[0060] For human identification, under normal circumstances, it is sufficient to perform point cloud filtering on the head / shoulder feature values ​​as described above. However, there are exceptions, such as two people entering the area, a person wearing a round hat, or a person in a wheelchair. In these cases, feature values ​​need to be analyzed separately for each exception. Of course, there are other special cases, such as people wearing headscarves, people with "afro" hairstyles, etc., which are collectively considered as "other" exceptions.

[0061] Scenario 2: When two people enter the cubicle, including one adult and one child, identify the height difference between their heads and shoulders respectively;

[0062] If two people enter, such as an adult and a child, the multi-line lidar will identify both individuals and record their heights separately. and When we reach step 8 (when the two people are about to leave), the door opening method needs to be adjusted: Multi-line lidar detects that person A is close to the revolving door (their head and shoulders are both less than 0.3 meters from the revolving door), and person B is less than 0.4 meters away from A, with their head heights being approximately equal. and .

[0063] Scenario 3: When a standing person and a person in a wheelchair enter, first identify the person's head, and then identify the person's front square body, including the legs and the front footrest of the wheelchair, to determine whether it is a wheelchair.

[0064] For example, in a "compassionate restroom," if a person in a wheelchair is about to enter, the system first identifies the person's head and then identifies the front square of the person, including the legs and the front footrests of the wheelchair. The criteria for determining if it's a leg point cloud are that the height of that point cloud above the ground is greater than 0.4 meters and less than 0.8 meters. The criteria for determining if it's a footrest point cloud are that the height of that point cloud above the ground is greater than 0.1 meters and less than 0.3 meters. The distance from the footrest point cloud to the person's head is then measured. When a person in a wheelchair finishes using the restroom and is about to leave, there are two possibilities, A and B: A) the person in the wheelchair is facing the revolving door, and B) their back is to the revolving door. Determining the opening condition (Method 8) requires adjusting based on these two possibilities: A) the distance from the top of the person's head to the revolving door is less than... Meters, and there are point clouds of legs between the top of the person's head and the revolving door, B is the distance between the top of the person's head and the revolving door is less than 0.4 meters.

[0065] Case 4: Identify the characteristics of the hat, including: the shape of the hat, whether it has a brim, whether it has a rounded edge, and the distance between the rounded edge and the side wall of the compartment;

[0066] When a person wearing a hat enters the cubicle, head and shoulder features are no longer suitable for human identification; it is necessary to learn the general features of the hat. When a person is wearing a hat, the hat's characteristics include a circular crown and brim (rings), with a crown diameter of 0.15-0.2 meters, a brim ring diameter of approximately 0.3-0.5 meters, and a height difference of 0.1-0.2 meters between the crown and brim. Based on the characteristics of the crown circle, brim ring, and crown-brim height difference, the hat's point cloud data can be extracted, allowing for the measurement of the brim ring distance. And determine the location of the person. The method for determining the door opening condition (method 8) needs to be adjusted based on the width of the hat brim; the distance from the top of the person's head to the revolving door should be less than... If a person enters a cubicle wearing a hat but exits without one, the multi-line lidar automatically adjusts the door opening conditions. Specifically, if the person is not wearing a hat, the opening condition is set based on the distance between the top of their head and the revolving door being less than 0.3 meters. Similarly, if a person enters a cubicle without a hat but exits with one, the multi-line lidar automatically adjusts the door opening conditions. rice.

[0067] Case 5: Cases involving headscarves and unusual hairstyles: In addition to the four cases mentioned above, there is another case, such as people wearing headscarves or having an "afro" hairstyle. Normalization of identification conditions to determine if it is a human body: Within the compartment, there is an object between the ground and the height of the multi-line lidar. Select point A, the point with the largest z-coordinate among the laser points on the object, and let the z-coordinate value of point A be... And must meet That is, the z-value of point A is not less than 0.8 meters above the ground (the minimum height of the humanoid object is set), and then point cloud B is found in the object's laser point cloud according to the following formula.

[0068] Formula 5;

[0069] The conditions listed in Equation 5 are to find a point cloud within a certain range around point A, and the number of points in point cloud B must reach a certain scale (empirical value is no less than 20). This point cloud exhibits clustering characteristics, and the judgment method is to determine this by finding any point B in point cloud B. i It is always possible to find a point in B whose distance (projection on the xy coordinate system) is less than 0.05 meters. .

[0070] If a point cloud B that meets the conditions can be found around laser point A, then laser point A is considered to be the human body being searched for, and its coordinates are... This represents the height of the human body, and its xy coordinates represent the position of the human body.

[0071] The above are just a few examples; there are many more in reality, which require machine learning to continuously update the knowledge base.

[0072] Step 3, Door Opening Determination: If someone stands in front of a closed cubicle door for more than one second, the multi-line lidar inside the cubicle uses a human morphology mathematical model to determine whether there is someone inside the cubicle (including the judgment made when the person entered the cubicle previously, which is confirmed by scanning again). If it is confirmed that there is someone inside the cubicle, no action is taken. If it is confirmed that there is no one inside the cubicle, the door drive mechanism is activated. The door drive mechanism drives the curved door to rotate around the central bearing by controlling the drive motor to achieve automatic door opening. The angle value fed back by the rotation angle sensor configured on the central bearing is used to control the revolving door to open to the correct position.

[0073] When someone stands in front of the cubicle door (assuming the cubicle door is closed), using the various case-based judgment methods in step 2 and the results of machine learning, it is determined whether there is someone inside the cubicle. If someone is inside, the door remains closed; if no one is detected inside the cubicle, but someone is identified standing in front of the door for more than 1 second, the curved door is automatically opened. During the process of a person entering the cubicle, the body shape data of the person entering the cubicle is obtained using laser point cloud data, using the method in step 3, to measure the height of the person's head (height). ).

[0074] Step 4, determine if someone is entering the cubicle: When the cubicle is empty, the multi-line lidar inside the cubicle uses a human body shape mathematical model to confirm that there is no human-shaped object in the cubicle. At the same time, the multi-line lidar outside the cubicle is activated to scan whether there is a moving object in front of the cubicle door, and continuously identify whether the stationary object in front of the door is a human-shaped object.

[0075] This step involves identifying whether a person or object moves through the door when it is opened, in order to prevent the door from colliding with the person or object. This process requires the coordinated action of multiple LiDARs inside and outside the compartment, and the changes in their point cloud to determine whether a person or object is in motion.

[0076] Step 5: Determine if personnel have entered the compartment: Multi-line lidar inside and outside the compartment monitors the flow of personnel, whether any person or object passes through the movement trajectory of the curved door, and monitors whether there are people inside the compartment to confirm that there are people inside, thereby closing the curved folding door.

[0077] Once a person enters the compartment and is detected by the multi-line lidar to have fully entered (without any object within the door's movement trajectory), the compartment's curved folding door closes and automatically locks, regardless of whether someone is standing outside the door. If the multi-line lidar detects an object in the curved folding door's movement path during the closing process, the closing action will stop.

[0078] Step 6, Personnel Exiting the Enclosure: When a person in the enclosure needs to exit, they must stand upright close to the revolving door. Once the multi-line lidar inside the enclosure determines that the opening conditions are met, the curved folding door will open. The determination conditions include the person's head being close to their height. The head and shoulders approach the folding revolving door (the distance between the head and both shoulder points and the revolving door is less than 0.3 meters), and the dwell time is greater than 2 seconds;

[0079] Step 7, determine if people have left the cubicle: After all the people in the cubicle have left, that is, there is no one in the cubicle and no one in front of the door, the curved folding door will be automatically closed, and the system will return to Step 3 to determine whether to open the door; if there is no one in the cubicle, but there is someone in front of the cubicle door, the curved folding door will not be closed, and the system will return to Step 4 to determine whether someone is entering the cubicle.

[0080] After a person leaves the cubicle, a combination of multi-line lidar sensors inside and outside the cubicle makes a judgment: including whether the person inside the cubicle has left, whether there are people standing outside the cubicle, and whether there are people or objects moving through the curved door, thus affecting the closing of the curved door. After determining that the person inside the cubicle has left, the curved folding door is in a selection state depending on whether there is someone in front of the door, either closing the curved folding door or keeping the curved folding door open.

[0081] Finally, it should be noted that the above is only used to illustrate the technical solution of this utility model and not to limit it. Although this utility model has been described in detail with reference to the preferred arrangement, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solution of this utility model (such as the form of the partition, the form of the arc-shaped folding door, the motion drive mechanism, the sequence of steps, etc.) without departing from the spirit and scope of the technical solution of this utility model.

Claims

1. A single cubicle arc-shaped folding door characterized in that, The utility model relates to a kind of arc-shaped door and arc-shaped door drive mechanism, including: Compartment three straight walls are blocked, vertical installation in the top center of the open side of compartment door shaft, the door shaft is arranged at least three bearings of upper and lower stacking, each described bearing is respectively connected with rotating cantilever, each described rotating cantilever is respectively fixedly connected with the top end of arc-shaped door leaf, the door shaft is further provided with door leaf drive mechanism that the arc-shaped door leaf is overlapped when being driven to open, is unfolded when closing, the compartment is respectively provided with multi-line laser radar that detects personnel in and out.

2. The arc-shaped folding door according to claim 1, characterized in that Two sides of the arc-shaped door leaf are respectively provided with push-pull bending.

3. The arc-shaped folding door according to claim 2, wherein, The door leaf drive mechanism only drives one arc-shaped door leaf, and the other arc-shaped door leaves are opened or closed through push-pull bending linkage.

4. The arcuate folding door of claim 3, wherein, The rotating cantilever is a straight rod or a fan shape.

5. The arcuate folding door of claim 4, wherein, An absolute value angle encoder for detecting the opening degree of the door leaf is provided on the door shaft.

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