Elevator leveling method and system

Abstract

The application discloses an elevator leveling method and system, and relates to the technical field of elevators.The method comprises the following steps: acquiring current cage position point cloud data when a cage of an elevator enters a target area; determining a current cage position in a preset running channel map based on the current cage position point cloud data, wherein the preset running channel map is a three-dimensional map established based on point cloud data of a running channel of the elevator, and a landing sill position is marked on the preset running channel map; and judging whether the elevator is leveled in place based on the current cage position and a landing sill position corresponding to the target area in the preset running channel map.Through laser radar, a three-dimensional shaft map can be constructed, accurate positioning of the cage in the transverse direction of the shaft can be realized, the elevator leveling is more accurate, and the transverse deviation problem during parallel operation of multiple elevators can be solved.

Description

Technical Field

[0001] This application relates to the field of elevator technology, specifically to an elevator leveling method and an elevator leveling system. Background Technology

[0002] Leveling of an elevator refers to the process and state in which the elevator car reaches the same horizontal level as the floor sill when it stops at the target floor.

[0003] Existing construction hoists use a combination of encoder pulse counting and auxiliary positioning for automatic leveling. However, during hoist operation, gear slippage, gear wear, or electromagnetic interference can cause encoder pulse signal loss or repeated counting, resulting in accumulated floor positioning errors. In severe cases, this can lead to hoist cage overshooting or bottoming out accidents. Furthermore, auxiliary limit devices based on magnetic strips or laser beams are susceptible to environmental factors such as dust, oil, and strong light, causing signal drift or false triggering, and their reliability decreases significantly under harsh working conditions.

[0004] Therefore, existing construction hoists have problems with leveling accuracy. Summary of the Invention

[0005] The purpose of this application is to provide a method and system for leveling a construction hoist, in order to solve the problem that the leveling of construction hoists in the prior art is not accurate enough.

[0006] To achieve the above objectives, the first aspect of this application provides a method for leveling a lift, the method comprising:

[0007] When the hoist cage enters the target area, acquire the point cloud data of the current cage position;

[0008] Based on the current cage position point cloud data, the current cage position is determined in the preset operation channel map. The preset operation channel map is a three-dimensional map built based on the point cloud data of the elevator's operation channel. The preset operation channel map is marked with the positions of the landing door sills.

[0009] Based on the current cage position and the corresponding floor sill position of the target area in the preset operation channel map, it is determined whether the elevator is level with the floor.

[0010] In this embodiment of the application, the process of constructing the preset running channel map includes:

[0011] The point cloud data and structural data of the elevator's operating channel are obtained, and the structural data of the elevator's operating channel includes floor height information;

[0012] Based on the structural data of the elevator's operating channel, the point cloud data of the elevator's operating channel is segmented to obtain segmented point cloud data.

[0013] Based on the segmented point cloud data, a running channel map is constructed.

[0014] In this embodiment of the application, obtaining the point cloud data of the elevator's operating channel includes:

[0015] Obtain the initial point cloud data of the elevator's operating channel;

[0016] The initial point cloud data of the elevator's operating channel is preprocessed to obtain the point cloud data of the elevator's operating channel. The preprocessing includes noise reduction processing and / or motion distortion correction processing.

[0017] In this embodiment of the application, determining whether the floor leveling is in place based on the current cage position and the floor sill position corresponding to the target area in the preset operation channel map includes:

[0018] Based on the current position of the hoist cage, the position of the hoist cage floor is determined;

[0019] Calculate the horizontal offset between the location of the suspended cage floor and the location of the floor sill corresponding to the target area in the preset operation channel map to obtain the location difference value;

[0020] Based on the position difference value, it is determined whether the elevator is level with the floor.

[0021] In this embodiment of the application, determining the current cage position in a preset operation channel map based on the current cage position point cloud data includes:

[0022] Based on the current cage position point cloud data, the initial cage position information is determined in the preset operation channel map;

[0023] Acquire inertial measurement data;

[0024] Based on the inertial measurement data, the initial cage position information is corrected to obtain the current cage position.

[0025] In this embodiment of the application, the method further includes:

[0026] Acquire image data of the target area, the image data of the target area including reference plate information and cage information of the elevator on the side where the elevator stops in the target area;

[0027] Based on the position of the hoist cage in the image data and the position of the reference plate corresponding to the target area, it is determined whether the elevator is level with the floor.

[0028] In this embodiment of the application, determining whether the floor leveling is in place based on the current cage position and the floor sill position corresponding to the target area in the preset operation channel map includes:

[0029] Acquire image data of the target area, the image data of the target area including reference plate information and cage information of the elevator on the side where the elevator stops in the target area;

[0030] Based on the position of the cage in the image data and the position of the reference plate corresponding to the target area, the first offset value is calculated;

[0031] Based on the current cage position and the position of the floor sill corresponding to the target area in the preset operation channel map, the second offset value is calculated;

[0032] Based on the first offset value and the second offset value, it is determined whether the elevator is level with the floor.

[0033] In this embodiment of the application, determining whether the elevator is level with the floor based on the first offset value and the second offset value includes:

[0034] The first offset value is converted into a value in the map coordinate system to obtain the converted offset value. The map coordinate system is used to describe the coordinate system of each position in the preset running channel map.

[0035] The actual offset value is obtained by taking a weighted average of the converted offset value and the second offset value.

[0036] Based on the actual offset value, it is determined whether the elevator is level with the floor.

[0037] In this embodiment of the application, it also includes:

[0038] Real-time acquisition of illumination data for the operating channel;

[0039] Based on the illumination data of the operating channel, adjust the weights corresponding to the conversion offset value and the second offset value.

[0040] A second aspect of this application provides an elevator leveling system, including a controller and a lidar;

[0041] The lidar is used to acquire point cloud data of the current cage position when the hoist cage enters the target area, and to send the current cage position point cloud data to the controller.

[0042] The controller is used to determine the current cage position based on the current cage position point cloud data in a preset operating channel map. The preset operating channel map is a three-dimensional map built based on the point cloud data of the elevator's operating channel, and the floor sill positions are marked on the preset operating channel map. Based on the current cage position and the floor sill position corresponding to the target area in the preset operating channel map, the controller determines whether the elevator is leveled and in position.

[0043] In this embodiment, an inertial measurement unit is also included;

[0044] The inertial measurement unit is used to acquire inertial measurement data and send the inertial measurement data to the controller;

[0045] The controller is used to determine the initial cage position information in a preset operation channel map based on the current cage position point cloud data; and to correct the initial cage position information based on the inertial measurement data to obtain the current cage position.

[0046] In this embodiment of the application, a camera device is also included;

[0047] The camera device is used to acquire image data of the target area and send the image data of the target area to the controller. The image data of the target area includes the reference plate information and cage information of the elevator on the docking side of the target area.

[0048] The controller is also used to determine whether the elevator is level and in place based on the position of the cage in the image data and the position of the reference plate corresponding to the target area.

[0049] In this embodiment of the application, a camera device is also included;

[0050] The camera device is used to acquire image data of the target area and send the image data of the target area to the controller. The image data of the target area includes the reference plate information and cage information of the elevator on the docking side of the target area.

[0051] The controller is used to calculate a first offset value based on the position of the hoist cage in the image data and the position of the reference plate corresponding to the target area; calculate a second offset value based on the current position of the hoist cage and the position of the floor sill corresponding to the target area in the preset running channel map; and determine whether the elevator is level with the floor based on the first offset value and the second offset value.

[0052] In this embodiment of the application, an encoder is also included;

[0053] The encoder is used to acquire pulse signals and send the pulse signals to the controller, and the pulse signals are synchronized with the gears of the elevator;

[0054] The controller is also used to determine whether the elevator is level with the floor based on the pulse signal.

[0055] The above technical solution acquires point cloud data of the current cage position when the hoist cage enters the target area. Based on this point cloud data, the current cage position is determined in a preset operating channel map. This preset operating channel map is a 3D map built based on the point cloud data of the hoist's operating channel, and the floor sill positions are marked on the preset operating channel map. Based on the current cage position and the floor sill position corresponding to the target area in the preset operating channel map, it is determined whether the hoist has leveled the floor. Unlike traditional positioning methods that rely solely on the vertical direction (Z-axis), this solution uses lidar to construct a 3D hoistway map including X / Y / Z axes, enabling precise horizontal (X / Y-axis) positioning of the cage within the hoistway. This results in more accurate hoist leveling and can be used to solve the lateral offset problem when multiple hoists are operating in parallel.

[0056] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0057] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:

[0058] Figure 1 The illustration shows a schematic flowchart of a method for leveling a lift according to an embodiment of this application. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0060] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with relevant laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0061] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0062] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0063] Figure 1 The illustration schematically shows a flow diagram of a lift leveling method according to an embodiment of this application. Figure 1 As shown in the figure, this application provides a method for leveling a lift, which may include the following steps.

[0064] Step 210: When the hoist cage enters the target area, acquire the current point cloud data of the cage position;

[0065] In this embodiment, the aforementioned current cage position point cloud data can be obtained through lidar scanning. When the elevator enters the target area (target floor), the lidar can collect the cage point cloud data at a certain frequency to obtain the current cage position point cloud data. The lidar can be a high-precision lidar, which can be installed on the top of the cage or other easily accessible locations to collect the current cage position at a high frequency, thereby obtaining the current cage position point cloud data.

[0066] Step 230: Based on the current cage position point cloud data, determine the current cage position in the preset operation channel map. The preset operation channel map is a three-dimensional map built based on the point cloud data of the elevator's operation channel. The preset operation channel map is marked with the positions of the landing door sills.

[0067] In this embodiment, the point cloud data of the elevator's operating channel can be obtained by scanning the shaft, i.e., the elevator's operating channel, at a certain speed using a lidar when the elevator is first put into use. Specifically, a high-precision lidar can be configured and installed on the top of the hoist cage or other easily accessible data acquisition location to collect three-dimensional point cloud data of the operating channel at high frequency. This constructs a real-time three-dimensional map including buildings, floor sills, elevator guide rails, elevator standard sections, etc. Floor sill coordinates can be marked on the three-dimensional map and stored in memory to obtain the operating channel map. By matching the current hoist cage position point cloud data with the current hoist cage position point cloud data in the operating channel map, the corresponding position can be found, i.e., the current hoist cage position can be obtained.

[0068] In some embodiments, the process of constructing the preset running channel map includes:

[0069] First, the point cloud data and structural data of the elevator's operating channel are acquired. The structural data of the elevator's operating channel includes floor height information.

[0070] In this embodiment, the point cloud data of the elevator's operating channel can be obtained by scanning the operating channel with lidar. The structural data refers to the structural data of the operating channel, including known floor height information, guide rail arrangement information, etc.

[0071] Then, based on the structural data of the elevator's operating channel, the point cloud data of the elevator's operating channel is segmented to obtain segmented point cloud data;

[0072] Finally, based on the segmented point cloud data, a map of the operating channel is constructed.

[0073] In this embodiment, the point cloud data of the elevator's operating channel can be segmented according to floor height information to construct a lightweight 3D raster map. Specifically, the "dirty data" in the point cloud data can be filtered out first, then known knowledge (floor height, guide rail spacing, etc.) can be used to cut the point cloud into segments, and finally these segmented data can be organized into a "lightweight" 3D map for easy subsequent use.

[0074] By using the structural data of the elevator's operating channel, the point cloud data of the elevator's operating channel is segmented. Based on the segmented point cloud data, a more lightweight operating channel map can be constructed, which is easier to update and store.

[0075] In some embodiments, the standardized structure of the construction hoist's operating channel (fixed spacing between guide rails and floor sills) can be utilized to construct a map of the operating channel through online incremental mapping and offline template matching, thereby reducing map storage and computational load.

[0076] In some embodiments, acquiring the point cloud data of the elevator's operating channel includes:

[0077] First, the initial point cloud data of the elevator's operating channel is obtained;

[0078] In this embodiment, the aforementioned initial point cloud data may refer to the point cloud data obtained by lidar scanning, which includes noisy point clouds, interference point clouds, etc.

[0079] Then, the initial point cloud data of the elevator's operating channel is preprocessed to obtain the point cloud data of the elevator's operating channel. The preprocessing includes noise reduction processing and / or motion distortion correction processing.

[0080] In this embodiment, to obtain an accurate point cloud of the running channel, the initial point cloud data can be denoised and / or have motion distortion corrected according to the actual situation. Denoising can be achieved by using voxel grid filtering to remove noise points. Motion distortion correction can be implemented using existing technologies; for example, the FastSLAM algorithm combined with Extended Kalman Filter (EKF) can be used to correct motion distortion in the initial point cloud data, achieving real-time separation of dynamic obstacles (such as construction workers or other moving construction materials) from the static building structure.

[0081] By preprocessing the initial point cloud data, more accurate point cloud data for the operating channel can be obtained.

[0082] It should be noted that when obtaining the point cloud data of the current cage position, the above method can also be used for preprocessing to obtain accurate point cloud data of the cage position, which will not be elaborated here.

[0083] In some embodiments, determining the current cage position in a preset operation channel map based on the current cage position point cloud data includes:

[0084] First, based on the current cage position point cloud data, the initial cage position information is determined in the preset operation channel map;

[0085] Then, acquire inertial measurement data;

[0086] Finally, based on the inertial measurement data, the initial cage position information is corrected to obtain the current cage position.

[0087] In this embodiment, the above-mentioned correction may involve fusing the pose data of the lidar with the data of the inertial measurement unit through an extended Kalman filter (EKF) and adding motion constraints to obtain the current position of the cage. The inertial measurement data may be obtained in real time by arranging a high-precision inertial measurement unit on the cage. The inertial measurement unit may be a variety of sensors used to collect acceleration, angular velocity, and other data to compensate for the high-frequency vibration of the lidar during the motion.

[0088] By applying extended Kalman filtering to constrain the motion of the cage output by the lidar and the inertial measurement unit data, the high-frequency jitter of the lidar during rapid start-up and shutdown can be suppressed, which can greatly improve the accuracy and robustness of the cage state estimation.

[0089] Step 220: Based on the current cage position and the floor sill position corresponding to the target area in the preset operation channel map, determine whether the elevator is level with the floor.

[0090] In this embodiment, the determination of whether the elevator is leveled can be made by comparing the current position of the cage with the position of the landing door sill corresponding to the target area in the preset running channel map. If they are consistent, it means that the elevator is leveled. The communication system can send a PWM modulation signal to the elevator drive system to control the motor speed to achieve a gradual slow stop, thereby achieving precise automatic stopping of the cage in the running channel.

[0091] In some embodiments, determining whether the floor leveling is in place based on the current cage position and the floor sill position corresponding to the target area in the preset operation channel map includes:

[0092] First, based on the current position of the hoist cage, the position of the hoist cage floor is determined;

[0093] In this embodiment, after determining the current position of the cage, the position of the cage floor can be determined based on the structure of the cage.

[0094] Then, the horizontal offset between the position of the suspended cage floor and the position of the floor sill corresponding to the target area in the preset operation channel map is calculated to obtain the position difference value;

[0095] In this embodiment, the positions of the floor thresholds corresponding to each target area are pre-marked in the preset operation channel map. The horizontal offset can be calculated using the coordinates of these two positions to obtain the positional difference value. The aforementioned horizontal offset can be expressed as (Δx, Δy).

[0096] Finally, based on the position difference value, it is determined whether the elevator is level with the floor.

[0097] In this embodiment, the positional difference value is compared with a preset limit value. If both Δx and Δy are less than the limit value, the leveling is determined to be in place; otherwise, it is determined to be incomplete leveling. The preset limit value can be set in advance according to actual conditions.

[0098] By calculating the horizontal offset between the position of the hoist cage floor and the position of the landing sill corresponding to the target area in the preset operation channel map, it is possible to accurately determine whether the elevator is level with the floor.

[0099] In the above implementation process, when the hoist cage enters the target area, the current cage position point cloud data is acquired. Based on the current cage position point cloud data, the current cage position is determined in a preset operating channel map. The preset operating channel map is a three-dimensional map built based on the point cloud data of the hoist's operating channel, and the landing sill positions are marked on the preset operating channel map. Based on the current cage position and the landing sill position corresponding to the target area in the preset operating channel map, it is determined whether the hoist has leveled into place. Unlike traditional positioning methods that only rely on the height direction (Z-axis), by constructing a three-dimensional hoistway map including X / Y / Z axes using lidar, precise positioning of the cage in the lateral direction (X / Y axis) of the hoistway can be achieved, making the hoist leveling more accurate and solving the lateral offset problem when multiple hoists are operating in parallel.

[0100] In some embodiments, the method further includes:

[0101] First, image data of the target area is acquired, including reference plate information and cage information of the elevator on the side where the elevator stops in the target area;

[0102] In this embodiment, the image data can be obtained by deploying cameras in the cage. For example, fisheye binocular cameras can be deployed, facing the four sides of the running channel (if only the building side needs to be considered, then only the building side needs to be faced; if the running channel is a shaft, then the four sides need to be monitored). The cameras can be equipped with filters to adapt to strong light / low light environments.

[0103] Then, based on the position of the cage in the image data and the position of the reference plate corresponding to the target area, it is determined whether the elevator is leveled and in place.

[0104] In this embodiment, visual positioning reference points can be pre-set on the building walls. For example, corner features of the building's floor reference plates can be extracted using the SIFT / SURF algorithm as feature points, and then these feature points can be extracted from the image data, specifically using the ORB-SLAM2 algorithm. Then, the position and orientation of the hoisting cage relative to the reference points (X / Y / Z coordinates + pitch angle / lateral movement deviation) are calculated. In practice, stereo matching can be performed on the binocular images to obtain depth information, and the corner features of the building's floor reference plates can be extracted using the SIFT / SURF algorithm to confirm the distance between the hoisting cage and the building floors. The RANSAC algorithm can be used to remove mismatched points to further ensure accurate positioning. Then, the homography matrix is ​​calculated to achieve camera pose calculation. That is, photos of the building are taken using binocular cameras (two cameras) → a series of algorithms (SIFT / SURF feature finding, RANSAC error removal, homography matrix position calculation) are used to determine the camera's position and orientation, and also to determine the distance of objects in the photos (depth information) → used to further confirm whether the leveling operation has been positioned at the correct floor. By calculating the extrinsic matrix of the camera and the bottom plate of the hoisting cage using the homography matrix, the visual-world coordinate system calibration is completed. This allows the position of the hoisting cage in the image data to be transformed into the same coordinate system as the position of the reference plate corresponding to the target area. The positions of the two can then be compared to determine whether the elevator is level and in place.

[0105] By acquiring image data of the target area, including reference plate information and cage information of the elevator on the stopping side of the target area; based on the cage position in the image data and the reference plate position corresponding to the target area, it is determined whether the elevator is leveled and in position; visual positioning of the cage can be achieved, thereby providing multiple ways to determine whether the elevator is leveled and in position, improving the reliability of the elevator leveling and in position determination, and making it suitable for more scenarios.

[0106] In some embodiments, a weighted fusion of visual positioning results and positioning results based on the operation channel map can also be used. That is, determining whether the leveling is in place based on the current cage position and the floor sill position corresponding to the target area in the preset operation channel map includes:

[0107] First, image data of the target area is acquired, including reference plate information and cage information of the elevator on the side where the elevator stops in the target area;

[0108] In this embodiment, the acquisition process described above is the same as that in the embodiment of implementing the visual positioning cage described above, and will not be repeated here.

[0109] Then, based on the position of the cage in the image data and the position of the reference plate corresponding to the target area, the first offset value is calculated;

[0110] In this embodiment, the above-mentioned calculation of the first offset value may be achieved by transforming the position of the cage in the image data and the position of the reference plate corresponding to the target area to the same coordinate system, and then comparing the two positions to calculate the horizontal offset, which is the first offset value.

[0111] Then, based on the current cage position and the position of the floor sill corresponding to the target area in the preset operation channel map, the second offset value is calculated;

[0112] In this embodiment, the positions of the landing sills corresponding to each target area are pre-marked in the preset operation channel map. The horizontal offset can be calculated by the coordinates of the current cage position and the corresponding landing sill position, which is the second offset value.

[0113] Then, based on the first offset value and the second offset value, it is determined whether the elevator is level with the floor.

[0114] In this embodiment, the first offset value and the second offset value can be weighted and fused to determine whether the leveling is in place.

[0115] The step of determining whether the elevator is level with the floor based on the first offset value and the second offset value includes:

[0116] The first step is to convert the first offset value into a value in the map coordinate system to obtain the converted offset value. The map coordinate system is used to describe the coordinate system of each position in the preset running channel map.

[0117] The second step is to take a weighted average of the conversion offset value and the second offset value to obtain the actual offset value.

[0118] The third step is to determine whether the elevator is level with the floor based on the actual offset value.

[0119] In this embodiment, the first offset value can be converted into a value in the map coordinate system. The above conversion can be achieved using existing technology, so it will not be described in detail here. By converting, the first offset value and the second offset value are in the same coordinate system. Then, the first offset value and the second offset value are weighted and averaged. It is then determined whether the actual offset value obtained is less than the limit value. If it is less than the limit value, it means that the leveling is in place; otherwise, it means that the leveling is not in place.

[0120] The first offset value is obtained by using visual positioning of the hoist cage. Based on the current position of the hoist cage and the position of the floor threshold corresponding to the target area in the preset operation channel map, the second offset value is calculated. By weighted and fused the first offset value and the second offset value, a more accurate offset value can be obtained, which further improves the accuracy of the leveling judgment.

[0121] The following implementation examples also include:

[0122] First, the illumination data of the operating channel is acquired in real time;

[0123] In this embodiment, the illumination data can be obtained from external input or measured in real time by an illuminance sensor installed in the operating channel.

[0124] Then, based on the illumination data of the operating channel, the weights corresponding to the conversion offset value and the second offset value are adjusted.

[0125] In this embodiment, the weights can be dynamically adjusted based on sensor confidence levels (e.g., visual positioning has a weight of 0.7 when there is sufficient light, meaning the weight corresponding to the conversion offset value is 0.7; laser positioning has a weight of 0.8 when the well structure is clear, meaning the weight corresponding to the second offset value is 0.8). For example, if dust suddenly appears in the operating channel, causing the lidar echo signal to attenuate, the system automatically increases the visual positioning weight (e.g., the weight corresponding to the conversion offset value is increased from 0.7 to 0.8).

[0126] By adjusting the weights corresponding to the conversion offset value and the second offset value through the illumination data of the running channel, the weighted fusion value is made more consistent with the actual situation, and a more accurate offset value can be obtained, which further improves the accuracy of leveling and positioning judgment, and ensures positioning accuracy even in extreme environments with high dust concentration.

[0127] In some embodiments, the original encoder can be retained as a basic sensor for initial velocity estimation (reducing the start-up delay of pure vision / laser positioning). Kinematic constraints are applied by combining encoder pulse counting, and the cage's position at the next moment is predicted using Kalman filtering, ultimately outputting a smooth and reliable pose estimate. Simultaneously, a precise time protocol can be established to achieve microsecond-level time alignment between the lidar, camera, inertial measurement unit, encoder, etc., avoiding positioning jumps caused by asynchronous operation of multiple sensors.

[0128] For example: the encoder provides real-time feedback on the cage speed, the lidar collects point clouds at frequency, and the inertial measurement unit compensates for vertical vibration noise; when the Z-axis height approaches the target floor, the vision unit initiates a reference plate search and quickly locates the sill feature points through an algorithm; the fusion module outputs the cage's three-dimensional pose, calculates the horizontal offsets Δx and Δy, and determines whether the leveling threshold is met based on the horizontal offset. If it is met, a stop signal is sent; the drive system performs a slow stop, and the final actual stopping position's horizontal deviation and vertical error from the target sill are within the requirements.

[0129] LiDAR provides a high-precision static structural reference, visual positioning enables real-time pose calibration in dynamic environments, and inertial measurement units and encoders compensate for high-frequency motion noise, forming a three-level anti-interference system of "static mapping - dynamic correction - high-frequency filtering".

[0130] It should be noted that when both the lidar and vision sensors fail, the system can automatically switch to the emergency positioning mode of "encoder + inertial measurement unit", combined with preset safe docking strategies (such as docking at the nearest floor) to ensure operational safety in case of failure.

[0131] Figure 1 This is a flowchart illustrating the elevator leveling method in this embodiment. It should be understood that, although... Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0132] This embodiment provides a lift leveling system, including a controller and a lidar;

[0133] The lidar is used to acquire point cloud data of the current cage position when the hoist cage enters the target area, and to send the current cage position point cloud data to the controller.

[0134] The controller is used to determine the current cage position based on the current cage position point cloud data in a preset operating channel map. The preset operating channel map is a three-dimensional map built based on the point cloud data of the elevator's operating channel, and the floor sill positions are marked on the preset operating channel map. Based on the current cage position and the floor sill position corresponding to the target area in the preset operating channel map, the controller determines whether the elevator is leveled and in position.

[0135] In this embodiment, the lidar can be a high-precision lidar, which can be installed on the top of the cage or other easily accessible location to collect data at a high frequency, thereby obtaining point cloud data of the current cage position. The aforementioned controller can be the main controller of the cage or a separately configured controller.

[0136] When the hoist cage enters the target area, the LiDAR acquires point cloud data of the current cage position. Based on this point cloud data, the controller determines the current cage position in a preset operating channel map. This preset operating channel map is a 3D map built based on the point cloud data of the hoist's operating channel, and the floor sill positions are marked on the preset operating channel map. Based on the current cage position and the floor sill position corresponding to the target area in the preset operating channel map, the controller determines whether the hoist has leveled into place. Unlike traditional positioning methods that rely only on the vertical direction (Z-axis), the LiDAR constructs a 3D hoistway map including X / Y / Z axes, enabling precise horizontal (X / Y-axis) positioning of the cage in the hoistway. This makes the hoist leveling more accurate and can be used to solve the lateral offset problem when multiple hoists are operating in parallel.

[0137] In some embodiments, an inertial measurement unit is also included;

[0138] The inertial measurement unit is used to acquire inertial measurement data and send the inertial measurement data to the controller;

[0139] The controller is used to determine the initial cage position information in a preset operation channel map based on the current cage position point cloud data; and to correct the initial cage position information based on the inertial measurement data to obtain the current cage position.

[0140] In this embodiment, the inertial measurement unit can be a variety of sensors used to collect acceleration, angular velocity, and other data to compensate for the high-frequency vibration of the lidar during motion.

[0141] By setting up an inertial measurement unit, the high-frequency jitter of the lidar during rapid start-up and shutdown can be suppressed, which can greatly improve the accuracy and robustness of cage state estimation.

[0142] In some embodiments, a camera device is also included;

[0143] The camera device is used to acquire image data of the target area and send the image data of the target area to the controller. The image data of the target area includes the reference plate information and cage information of the elevator on the docking side of the target area.

[0144] The controller is also used to determine whether the elevator is level and in place based on the position of the cage in the image data and the position of the reference plate corresponding to the target area.

[0145] In this embodiment, the aforementioned camera device can be a camera deployed on the cage, such as a fisheye binocular camera, facing the four sides of the operating channel (if only the building side needs to be considered, then only facing the building side is sufficient; if the operating channel is a shaft, then the four sides need to be monitored). The camera can be equipped with a filter to adapt to strong light / low light environments.

[0146] By installing camera devices, visual positioning of the hoist cage can be achieved, thus providing multiple ways to determine whether the hoist is level with the floor, improving the reliability of the hoist's leveling judgment, and making it suitable for more scenarios.

[0147] In some embodiments, a camera device is also included;

[0148] The camera device is used to acquire image data of the target area and send the image data of the target area to the controller. The image data of the target area includes the reference plate information and cage information of the elevator on the docking side of the target area.

[0149] The controller is used to calculate a first offset value based on the position of the hoist cage in the image data and the position of the reference plate corresponding to the target area; calculate a second offset value based on the current position of the hoist cage and the position of the floor sill corresponding to the target area in the preset running channel map; and determine whether the elevator is level with the floor based on the first offset value and the second offset value.

[0150] By setting up a camera device, the visual positioning cage and the lidar positioning cage can be combined to obtain a more accurate offset value, further improving the accuracy of leveling and positioning judgment.

[0151] In some embodiments, an encoder is also included;

[0152] The encoder is used to acquire pulse signals and send the pulse signals to the controller, and the pulse signals are synchronized with the gears of the elevator;

[0153] The controller is also used to determine whether the elevator is level with the floor based on the pulse signal.

[0154] By setting an encoder, when the lidar fails, the encoder can feed back pulse signals to confirm the running height and achieve leveling and positioning, which increases redundancy. Combined with preset safe docking strategies (such as docking at the nearest floor), it ensures safe operation in case of failure.

[0155] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0156] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0157] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0158] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0159] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0160] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0161] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0162] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0163] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for leveling a lift, characterized in that, The method includes: When the hoist cage enters the target area, acquire the point cloud data of the current cage position; Based on the current cage position point cloud data, the current cage position is determined in the preset operation channel map. The preset operation channel map is a three-dimensional map built based on the point cloud data of the elevator's operation channel. The preset operation channel map is marked with the positions of the landing door sills. Based on the current cage position and the corresponding floor sill position of the target area in the preset operation channel map, it is determined whether the elevator is level with the floor.

2. The method according to claim 1, characterized in that, The process of constructing the preset operation channel map includes: The point cloud data and structural data of the elevator's operating channel are obtained, and the structural data of the elevator's operating channel includes floor height information; Based on the structural data of the elevator's operating channel, the point cloud data of the elevator's operating channel is segmented to obtain segmented point cloud data. Based on the segmented point cloud data, a running channel map is constructed.

3. The method according to claim 2, characterized in that, The acquisition of point cloud data of the elevator's operating channel includes: Obtain the initial point cloud data of the elevator's operating channel; The initial point cloud data of the elevator's operating channel is preprocessed to obtain the point cloud data of the elevator's operating channel. The preprocessing includes noise reduction processing and / or motion distortion correction processing.

4. The method according to claim 1, characterized in that, The step of determining whether the floor leveling is in place based on the current cage position and the corresponding floor sill position of the target area in the preset operation channel map includes: Based on the current position of the hoist cage, the position of the hoist cage floor is determined; Calculate the horizontal offset between the location of the suspended cage floor and the location of the floor sill corresponding to the target area in the preset operation channel map to obtain the location difference value; Based on the position difference value, it is determined whether the elevator is level with the floor.

5. The method according to claim 1, characterized in that, The process of determining the current cage position in a preset operation channel map based on the current cage position point cloud data includes: Based on the current cage position point cloud data, the initial cage position information is determined in the preset operation channel map; Acquire inertial measurement data; Based on the inertial measurement data, the initial cage position information is corrected to obtain the current cage position.

6. The method according to claim 1, characterized in that, The method further includes: Acquire image data of the target area, the image data of the target area including reference plate information and cage information of the elevator on the side where the elevator stops in the target area; Based on the position of the hoist cage in the image data and the position of the reference plate corresponding to the target area, it is determined whether the elevator is level with the floor.

7. The method according to claim 1, characterized in that, The step of determining whether the floor leveling is in place based on the current cage position and the corresponding floor sill position of the target area in the preset operation channel map includes: Acquire image data of the target area, the image data of the target area including reference plate information and cage information of the elevator on the side where the elevator stops in the target area; Based on the position of the cage in the image data and the position of the reference plate corresponding to the target area, the first offset value is calculated. Based on the current cage position and the position of the landing sill corresponding to the target area in the preset operation channel map, the second offset value is calculated; Based on the first offset value and the second offset value, it is determined whether the elevator is level with the floor.

8. The method according to claim 7, characterized in that, The step of determining whether the elevator is level with the floor based on the first offset value and the second offset value includes: The first offset value is converted into a value in the map coordinate system to obtain the converted offset value. The map coordinate system is used to describe the coordinate system of each position in the preset running channel map. The actual offset value is obtained by taking a weighted average of the converted offset value and the second offset value. Based on the actual offset value, it is determined whether the elevator is level with the floor.

9. The method according to claim 8, characterized in that, Also includes: Real-time acquisition of illumination data for the operating channel; Based on the illumination data of the operating channel, the weights corresponding to the conversion offset value and the second offset value are adjusted.

10. A leveling system for an elevator, characterized in that, Includes controllers and lidar; The lidar is used to acquire point cloud data of the current cage position when the hoist cage enters the target area, and to send the current cage position point cloud data to the controller. The controller is used to determine the current cage position based on the current cage position point cloud data in a preset operating channel map. The preset operating channel map is a three-dimensional map built based on the point cloud data of the elevator's operating channel, and the floor sill positions are marked on the preset operating channel map. Based on the current cage position and the floor sill position corresponding to the target area in the preset operating channel map, the controller determines whether the elevator is leveled and in position.

11. The system according to claim 10, characterized in that, It also includes an inertial measurement unit; The inertial measurement unit is used to acquire inertial measurement data and send the inertial measurement data to the controller; The controller is used to determine the initial cage position information in a preset operation channel map based on the current cage position point cloud data. Based on the inertial measurement data, the initial cage position information is corrected to obtain the current cage position.

12. The system according to claim 10, characterized in that, It also includes a camera device; The camera device is used to acquire image data of the target area and send the image data of the target area to the controller. The image data of the target area includes the reference plate information and cage information of the elevator on the docking side of the target area. The controller is also used to determine whether the elevator is level and in place based on the position of the cage in the image data and the position of the reference plate corresponding to the target area.

13. The system according to claim 10, characterized in that, It also includes a camera device; The camera device is used to acquire image data of the target area and send the image data of the target area to the controller. The image data of the target area includes the reference plate information and cage information of the elevator on the docking side of the target area. The controller is used to calculate a first offset value based on the position of the cage in the image data and the position of the reference plate corresponding to the target area; Based on the current cage position and the position of the landing sill corresponding to the target area in the preset operation channel map, the second offset value is calculated; Based on the first offset value and the second offset value, it is determined whether the elevator is level with the floor.

14. The system according to claim 10, characterized in that, It also includes encoders; The encoder is used to acquire pulse signals and send the pulse signals to the controller, and the pulse signals are synchronized with the gears of the elevator; The controller is also used to determine whether the elevator is level with the floor based on the pulse signal.

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