A method, device, equipment and medium for measuring the distance between a suspended platform and a lifting platform

Abstract

The present invention relates to a method, device, equipment and medium for measuring the lifting distance of a suspended platform, and belongs to the technical field of lifting and ranging. The method comprises: acquiring encoder data and laser ranging data in real time during the lifting process of the suspended platform, filtering the laser ranging data in sequence to obtain processed laser ranging data; and performing Kalman filtering on the processed laser ranging data and encoder data to obtain an optimal lifting distance. The Kalman filtering gain is adjusted according to the number of cable layers of an encoder motor acquired in real time, thereby improving the accuracy of the lifting distance.

Description

Technical Field

[0001] The present invention relates to the technical field of lifting and ranging, and in particular to a method, device, equipment and medium for lifting and ranging of a suspended platform. Background Art

[0002] The traditional measurement encoder motor drives the 1mm thick flat belt rope to rise and fall. Encoder measurement, pulse counting, position sensor and other methods are usually used to calculate the lifting distance of the rope.

[0003] Encoder measurement: Use an encoder to measure the number of times the motor rotates to calculate the distance the rope is raised or lowered. Pulse counting: Count the pulse signals generated each time the motor rotates a certain angle to determine the distance the rope is raised or lowered. Position sensor: A position sensor installed on the motor or rope monitors the position of the rope to determine the distance the rope is raised or lowered.

[0004] However, when using encoders for measurement, measurement errors occur due to accuracy issues, which will affect the accuracy of the lifting distance. When using pulse counting, rope wear will cause diameter changes, which will in turn affect the measurement accuracy of the lifting distance. When using position sensors, the environment will affect the performance of the sensor, which will in turn affect the measurement accuracy. Summary of the Invention

[0005] In view of this, it is necessary to provide a method, device, equipment and medium for measuring the lifting distance of a suspended platform to solve the technical problem of inaccurate measurement of the lifting distance when the suspended platform is lifted or lowered by a cable.

[0006] In order to solve the above problems, the present invention provides a method for measuring the distance between a suspended platform and a lifting platform, comprising:

[0007] Acquire encoder data and laser ranging data of the encoder motor during the lifting and lowering of the suspension platform in real time, filter the laser ranging data in sequence, and obtain processed laser ranging data;

[0008] Kalman filtering is performed on the processed laser ranging data and encoder data to obtain an optimal lifting distance, wherein the Kalman filtering gain is adjusted according to the number of cable layers of the encoder motor obtained in real time.

[0009] In one possible implementation, the real-time acquisition of encoder data and laser ranging data of the encoder motor during the lifting and lowering of the suspension platform includes:

[0010] The lifting and lowering of the suspension platform is controlled by an encoder motor, and encoder data is obtained in real time;

[0011] The laser ranging data is obtained in real time through the laser sensor.

[0012] In a possible implementation, the filtering process includes median filtering and sliding filtering, and the median filtering and sliding filtering processes are sequentially performed on the laser ranging data, including:

[0013] Performing median filtering on the laser ranging data to obtain first laser ranging data;

[0014] Perform sliding filtering processing on the first laser ranging data to obtain processed laser ranging data.

[0015] In a possible implementation, performing median filtering on the laser ranging data includes:

[0016] Step 1: Determine the window size;

[0017] Step 2: Select data points around the first data point in the laser ranging data according to the window size;

[0018] Step 3: sort the data points by size to obtain sorted data points;

[0019] Step 4: Select the median value of the sorted data points, and update the first data point based on the median value;

[0020] Step 5: sequentially select data points in the laser ranging data, repeat steps 2 to 4, until the last data point in the laser ranging data is selected, and obtain the first laser ranging data.

[0021] In a possible implementation, performing sliding filtering on the first laser ranging data includes:

[0022] Step 1: Determine the window size;

[0023] Step 2: determining data points within the window of the first laser ranging data according to the window size;

[0024] Step 3: Calculate the average value of the data points in the window as the filtered value;

[0025] Step 4: Move the window to the next data point and calculate the average value of the data points in the window;

[0026] Step 5: sequentially process the data points in the first laser ranging data to obtain processed laser ranging data.

[0027] In a possible implementation, performing Kalman filtering on the processed laser ranging data and encoder data to obtain an optimal lifting distance, wherein adjusting the Kalman filter gain according to the number of cable layers of the encoder motor obtained in real time, includes:

[0028] determining an actual length of the cable, and determining an encoder error based on the actual length of the cable and the encoder data;

[0029] Determining a laser error based on the actual length of the cable and the processed laser ranging data;

[0030] constructing a measurement equation based on the encoder error, the laser error, the encoder data, and the processed laser ranging data;

[0031] Obtaining a lifting speed of the suspension platform and the number of cable layers of the encoder motor, and constructing a state equation based on the lifting speed and the number of cable layers;

[0032] The lifting distance of the suspended platform is predicted based on the measurement equation and the state equation to obtain the optimal lifting distance, wherein the Kalman filter gains of the encoder and the laser ranging are dynamically adjusted based on the number of cable layers. When the number of cable layers is large, the Kalman filter gain of the laser ranging is increased, and when the number of cable layers is small, the Kalman filter gain of the laser ranging is reduced.

[0033] In a possible implementation, the calculation formula of the state equation is:

[0034] ,

[0035] ,

[0036] in, is the lifting distance at the next moment, is the lift distance at the current moment, is the lifting speed, is the time difference, is the number of cable layers at the next moment, is the number of cable layers at the current moment, is the change in the number of layers of the cable at each moment;

[0037] The calculation formula of the measurement equation is:

[0038] ,

[0039] ,

[0040] in, is the distance estimated by the encoder, is the radius corresponding to the current number of layers of the cable, is the motor rotation angle, is the encoder error, is the distance measured by laser, is the laser error.

[0041] On the other hand, the present invention also provides a suspended platform lifting and ranging device, comprising:

[0042] The data processing module is used to obtain the encoder data of the encoder motor and the laser ranging data in real time during the lifting and lowering process of the suspension platform, and filter the laser ranging data in sequence to obtain the processed laser ranging data;

[0043] The lifting distance acquisition module is used to perform Kalman filtering on the processed laser ranging data and encoder data to obtain the optimal lifting distance, wherein the Kalman filter gains of the encoder and laser ranging are adjusted according to the number of cable layers of the encoder motor obtained in real time.

[0044] On the other hand, the present invention also provides an electronic device, comprising: a processor and a memory;

[0045] The memory stores a computer-readable program executable by the processor;

[0046] When the processor executes the computer-readable program, the steps in the suspended platform lifting and ranging method as described above are implemented.

[0047] On the other hand, the present invention also provides a computer-readable storage medium, which stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the suspended platform lifting and ranging method as described above.

[0048] The beneficial effects of the present invention are as follows: laser ranging data is filtered in sequence to remove abnormal data in the data, reduce interference from the abnormal data, and improve data reliability and stability; the processed laser ranging data and encoder data are subjected to Kalman filtering, and the state is dynamically predicted and corrected through Kalman filtering, thereby providing a more accurate estimation of the lifting distance; and the Kalman filter gains of the laser ranging and encoder are dynamically adjusted according to changes in the number of cable layers of the encoder motor, thereby reducing the impact of errors and obtaining the optimal lifting distance. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A flow chart of an embodiment of the method for measuring the distance between a suspended platform and a lifting platform provided by the present invention;

[0050] Figure 2 A schematic structural diagram of an embodiment of a suspended platform lifting and distance measuring device provided by the present invention;

[0051] Figure 3 This is a schematic structural diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0052] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, and are not used to limit the scope of the present invention.

[0053] The present invention discloses a method, device, equipment and medium for measuring the distance between a suspended platform and a lifting platform, which can be used in a computer. The method, equipment or computer-readable storage medium involved in the present invention can be integrated with the above-mentioned equipment or can be relatively independent.

[0054] A specific embodiment of the present invention discloses a method for measuring the distance between the lifting and lowering of a suspended platform, which can be executed by a computer, specifically by one or more processors of the computer. Figure 1 This is a flow chart of the method for measuring the distance between the suspended platform and the lifting platform provided by the embodiment of the present invention. Figure 1 , the suspended platform lifting and ranging methods include:

[0055] S101, acquiring encoder data and laser ranging data of the encoder motor during the lifting and lowering process of the suspension platform in real time, filtering the laser ranging data in sequence, and obtaining processed laser ranging data;

[0056] S102 , performing Kalman filtering on the processed laser ranging data and encoder data to obtain an optimal lifting distance, wherein the Kalman filtering gain is adjusted according to the number of cable layers of the encoder motor obtained in real time.

[0057] Among them, the laser ranging data is processed by median filtering and sliding filtering in sequence to reduce data interference, and the state is dynamically predicted and corrected through Kalman filtering to obtain the optimal lifting distance. The optimal lifting distance is the real-time and accurate distance during the lifting process of the suspension platform. Among them, the Kalman filter gain is adjusted to reduce the impact of errors, thereby providing a more accurate state estimation value.

[0058] Compared with the prior art, the method for measuring the lifting and distance of a suspended platform provided in this embodiment obtains encoder data and laser ranging data in real time during the lifting process of the suspended platform, filters the laser ranging data in sequence to obtain processed laser ranging data, removes abnormal data in the data, reduces interference from the abnormal data, and improves data reliability and stability. Kalman filtering is performed on the processed laser ranging data and encoder data to obtain an optimal lifting distance, wherein the Kalman filter gain is adjusted according to the number of cable layers of the encoder motor obtained in real time to provide a more accurate lifting distance estimate. The Kalman filter gains of the laser ranging and encoder are dynamically adjusted according to changes in the number of cable layers to reduce the impact of errors and obtain the optimal lifting distance.

[0059] In some embodiments, in step S101, the encoding motor drives the flat belt with a thickness of 1mm to control the lifting of the suspension platform. The encoder of the encoding motor will directly feedback the motor rotation angle, and the radius will change with the superposition of the cables. The lifting of the suspension platform is controlled by the encoding motor, and the encoder data and the number of cable layers are obtained in real time. A laser sensor for upward ranging is installed at the bottom of the suspension platform. When the suspension platform is raised or lowered, the laser ranging data is obtained in real time through the laser sensor.

[0060] Obtain the encoder data and perform data correction to consider the effect of the thickness of the flat belt cable on the radius, and calculate the actual radius. The calculation formula is:

[0061] ,

[0062] in, is the actual radius, is the radius of the encoder reading, is the number of rope layers, is the thickness of the rope;

[0063] After obtaining the laser ranging data, since the data is easily interfered with, the laser ranging data is filtered in sequence to obtain the processed laser ranging data. The filtering process includes median filtering and sliding filtering. The process is as follows: performing median filtering on the laser ranging data to obtain the first laser ranging data to remove abnormal values ​​in the data, and performing sliding filtering on the first laser ranging data to obtain the processed laser ranging data to smooth the data. The specific process of the median filtering process is as follows:

[0064] Step 1. Determine the window size and select 5 as the window size;

[0065] Step 2: According to the window size, select the data points around the first data point in the laser ranging data, that is, for the first data point in the laser ranging data, take the 5 surrounding data points as the processing objects;

[0066] Step 3: Sort the 5 data points by size to obtain sorted data points;

[0067] Step 4: Determine the median value of the five sorted data points. This median value is used as the value after median filtering, that is, replace the first data point with the median value.

[0068] Step 5: sequentially select data points in the laser ranging data, repeat steps 2 to 4, and sequentially process all data points in the laser ranging data until the last data point in the laser ranging data is processed to obtain the first laser ranging data;

[0069] After obtaining the first laser ranging data, the process of performing sliding filtering on the first laser ranging data is as follows:

[0070] Step 1: Determine the window size and select 5 as the window size;

[0071] Step 2: Initialize the window and determine the data points in the window of the first laser ranging data according to the window size, that is, the data points in the window are 5 data points;

[0072] Step 3: Calculate the average value of the data points in the window as the value after smoothing filtering;

[0073] Step 4: Move the window to the next data point and calculate the average value of the data points in the window;

[0074] Step 5: Process the data points in the first laser ranging data in sequence to obtain processed laser ranging data.

[0075] In some embodiments, in step S102, the processed laser ranging data and encoder data are subjected to Kalman filtering to obtain the optimal lifting distance. First, a measurement equation and a state equation of the Kalman filter are constructed. Second, the lifting distance of the suspended platform is predicted based on the measurement equation and the state equation to obtain the optimal lifting distance.

[0076] To determine the actual length of the rope, the encoder motor reels one layer of rope each time, and updates the rope reel radius according to the change in the number of rope layers. The actual length of the rope is calculated as follows:

[0077] ,

[0078] in, is the actual length of the cable, is the initial coiling radius, is the number of rope layers;

[0079] The encoder error is determined based on the actual length of the rope and the encoder data. The encoder error is calculated as follows:

[0080] ,

[0081] in, is the encoder error, which is also the encoder measurement noise, The distance estimated by the encoder;

[0082] The laser error is determined based on the actual length of the cable and the processed laser ranging data. The calculation formula for the laser error is:

[0083] ,

[0084] in, is the laser error, that is, the laser ranging noise, which increases with the distance. is the laser ranging value;

[0085] The measurement equation is constructed based on the encoder error, laser error, encoder data, and processed laser ranging data. The calculation formula of the measurement equation is:

[0086] ,

[0087] ,

[0088] in, is the distance estimated by the encoder, is the radius corresponding to the current number of layers of the cable, is the motor rotation angle, is the encoder error, is the distance measured by laser ranging, is the laser error, is the lift distance at the current moment;

[0089] Obtain the lifting speed of the suspended platform and the number of cable layers of the encoder motor. Construct a state equation based on the lifting speed and the number of cable layers. The calculation formula of the state equation is:

[0090] ,

[0091] ,

[0092] in, is the lifting distance at the next moment, is the lift distance at the current moment, is the lifting speed, is the time difference, is the number of cable layers at the next moment, is the number of cable layers at the current moment, is the change in the number of layers of the cable at each moment;

[0093] According to the state equation, predict the state at the next moment and In each iteration, according to the change of the number of cable layers, the gains of the laser and encoder are dynamically adjusted to minimize the error and solve the optimal lifting distance. Finally, the state is updated. and , determine the Kalman filter gain of the encoder and laser ranging, the Kalman filter gain of the laser ranging is , the Kalman filter gain of the encoder is In different environments, the measurement values ​​of different sensors are different. The weight value of the sensor close to the real data should be large. The weight is the Kalman filter gain. According to the current number of cable layers, the Kalman filter gain of the encoder and laser ranging is dynamically adjusted. When it is larger, that is, when the suspension platform is at the top, it relies more on the laser ranging data. In order to reduce the influence of the error, the Kalman filter gain of the laser ranging is increased, that is, the weight of the laser ranging data is increased. When When it is small, that is, when the suspension platform is at the bottom, reduce the Kalman filter gain of the laser ranging and increase the gain of the encoder data to ensure accurate control of the descent distance. The calculation formula for the optimal lifting distance is:

[0094] ,

[0095] ,

[0096] When the suspension platform is at the top, the weight coefficients of the laser and encoder are set to 0.9 and 0.1 respectively, that is, the Kalman filter gain of the laser ranging is 0.9, and the Kalman filter gain of the encoder is 0.1. When the suspension platform is at the bottom, the weight coefficients of the laser and encoder are set to 0.1 and 0.9 respectively. Taking the initial cable radius of 3 cm, at a certain moment, the distance estimated by the motor encoder is 0.99 meters, and the laser ranging data is 1.09 meters as an example, at this time, the suspension platform is at the bottom, and calculation shows that the optimal lifting distance at this time is 1 meter.

[0097] The main function of the Kalman filter is to estimate the system state. By considering the system's dynamic model and measurement data, the system state is dynamically predicted and corrected, thereby providing a more accurate state estimate. The functions of the Kalman filter include the following aspects: State estimation. By combining the system dynamic model and observation data, the Kalman filter can estimate the current state of the system and provide the optimal estimate of the system state; Noise suppression: The Kalman filter can effectively handle noise and errors in measurements and improve the accuracy of state estimation. System control: In the control system, the Kalman filter can make corresponding adjustments and controls based on the estimated value of the system state to achieve adaptive control of the system. Prediction: By predicting the system state, the Kalman filter can detect potential system state changes in advance, which is helpful for system prediction.

[0098] In order to better implement the suspended platform lifting and ranging method in the embodiment of the present invention, based on the suspended platform lifting and ranging method, correspondingly, Figure 2 As shown, an embodiment of the present invention further provides a suspended platform lifting and distance measuring device, and the suspended platform lifting and distance measuring device 200 includes:

[0099] The data processing module 201 is used to obtain the encoder data of the encoder motor and the laser ranging data in real time during the lifting and lowering process of the suspension platform, and filter the laser ranging data in sequence to obtain the processed laser ranging data;

[0100] The lifting distance obtaining module 202 is used to perform Kalman filtering on the processed laser ranging data and encoder data to obtain the optimal lifting distance, wherein the Kalman filter gain is adjusted according to the number of cable layers of the encoder motor obtained in real time.

[0101] like Figure 3 As shown, based on the method of measuring distance by lifting a suspended platform, the present invention also provides an electronic device 300, which can be a computing device such as a mobile terminal, a desktop computer, a notebook, a PDA, or a server. The electronic device 300 includes a processor 301, a memory 302, and a display 303. Figure 3 Only some of the components of the electronic device 300 are shown, but it should be understood that implementation of all of the shown components is not required, and more or fewer components may be implemented instead.

[0102] In some embodiments, the memory 302 may be an internal storage unit of the electronic device 300, such as the hard drive or memory of the electronic device 300. In other embodiments, the memory 302 may also be an external storage device of the electronic device 300, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on the electronic device 300. Furthermore, the memory 302 may include both an internal storage unit of the electronic device 300 and an external storage device. The memory 302 is used to store application software installed on the electronic device 300 and various data, such as program code installed on the electronic device 300. The memory 302 may also be used to temporarily store data that has been output or is about to be output. In one embodiment, the memory 302 stores a suspended platform lifting and ranging program, which can be executed by the processor 301 to implement the suspended platform lifting and ranging method of various embodiments of the present invention.

[0103] In some embodiments, the processor 301 may be a central processing unit (CPU), a microprocessor, or other data processing chip, configured to execute program codes or process data stored in the memory 302, such as a method for measuring the distance between a suspended platform and a lowering platform.

[0104] In some embodiments, display 303 can be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 303 is used to display identification information for the suspended platform lifting and ranging program and to display a visual user interface. Components 301-303 of electronic device 300 communicate with each other via a system bus.

[0105] In some embodiments, when the processor 301 executes the suspension platform lifting and ranging program in the memory 302, the various steps in the suspension platform lifting and ranging method described in the above embodiments are implemented. Since the suspension platform lifting and ranging method has been described in detail above, it will not be repeated here.

[0106] Accordingly, an embodiment of the present application also provides a computer-readable storage medium, which is used to store computer-readable programs or instructions. When the program or instructions are executed by the processor, it can implement the steps or functions in the suspended platform lifting and ranging method provided in the above-mentioned method embodiments.

[0107] In summary, the method, device, equipment, and medium for measuring the lifting and distance of a suspended platform provided by the present invention obtain encoder data and laser ranging data of an encoder motor in real time during the lifting and lowering process of the suspended platform, filter the laser ranging data in sequence to obtain processed laser ranging data, and perform Kalman filtering on the processed laser ranging data and encoder data to obtain the optimal lifting distance. The Kalman filter gain is adjusted according to the number of cable layers of the encoder motor obtained in real time, thereby improving the accuracy of the lifting distance.

[0108] Those skilled in the art will appreciate that all or part of the process steps of the above-described embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, such as a magnetic disk, an optical disk, a read-only memory, or a random access memory.

[0109] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with this technical field within the technical scope disclosed by the present invention should be covered by the scope of protection of the present invention.

Claims

1. A method for measuring distance by lifting a suspended platform, characterized in that: include: Acquire encoder data and laser ranging data of the encoder motor during the lifting and lowering of the suspension platform in real time, filter the laser ranging data in sequence, and obtain processed laser ranging data; Kalman filtering is performed on the processed laser ranging data and encoder data to obtain an optimal lifting distance, wherein the Kalman filtering gain is adjusted according to the number of cable layers of the encoder motor obtained in real time.

2. The method for measuring distance by lifting a suspended platform according to claim 1, characterized in that: The real-time acquisition of encoder data of the encoder motor and laser ranging data during the lifting process of the suspension platform includes: The lifting and lowering of the suspension platform is controlled by an encoder motor, and encoder data is obtained in real time; The laser ranging data is obtained in real time through the laser sensor.

3. The method for measuring distance by lifting a suspended platform according to claim 2, characterized in that: The filtering process includes median filtering and sliding filtering, and the median filtering and sliding filtering processes are performed on the laser ranging data in sequence, including: Performing median filtering on the laser ranging data to obtain first laser ranging data; Perform sliding filtering processing on the first laser ranging data to obtain processed laser ranging data.

4. The method for measuring distance by lifting a suspended platform according to claim 3, characterized in that: The performing median filtering on the laser ranging data includes: Step 1: Determine the window size; Step 2: Select data points around the first data point in the laser ranging data according to the window size; Step 3: sort the data points by size to obtain sorted data points; Step 4: Select the median value of the sorted data points, and update the first data point based on the median value; Step 5: sequentially select data points in the laser ranging data, repeat steps 2 to 4, until the last data point in the laser ranging data is selected, and obtain the first laser ranging data.

5. The method for measuring distance by lifting a suspended platform according to claim 3, characterized in that: The performing sliding filtering on the first laser ranging data includes: Step 1: Determine the window size; Step 2: determining data points within the window of the first laser ranging data according to the window size; Step 3: Calculate the average value of the data points in the window as the filtered value; Step 4: Move the window to the next data point and calculate the average value of the data points in the window; Step 5: sequentially process the data points in the first laser ranging data to obtain processed laser ranging data.

6. The method for measuring distance by lifting a suspended platform according to claim 3, characterized in that: The Kalman filter processing is performed on the processed laser ranging data and encoder data to obtain the optimal lifting distance, wherein the Kalman filter gain is adjusted according to the number of cable layers of the encoder motor obtained in real time, including: determining an actual length of the cable, and determining an encoder error based on the actual length of the cable and the encoder data; Determining a laser error based on the actual length of the cable and the processed laser ranging data; constructing a measurement equation based on the encoder error, the laser error, the encoder data, and the processed laser ranging data; Obtaining a lifting speed of the suspension platform and the number of cable layers of the encoder motor, and constructing a state equation based on the lifting speed and the number of cable layers; The lifting distance of the suspended platform is predicted based on the measurement equation and the state equation to obtain the optimal lifting distance, wherein the Kalman filter gains of the encoder and the laser ranging are dynamically adjusted based on the number of cable layers. When the number of cable layers is large, the Kalman filter gain of the laser ranging is increased, and when the number of cable layers is small, the Kalman filter gain of the laser ranging is reduced.

7. The method for measuring distance by lifting a suspended platform according to claim 6, characterized in that: The calculation formula of the state equation is: ， ， in, is the lifting distance at the next moment, is the lift distance at the current moment, is the lifting speed, is the time difference, is the number of cable layers at the next moment, is the number of cable layers at the current moment, is the change in the number of layers of the cable at each moment; The calculation formula of the measurement equation is: ， ， in, is the distance estimated by the encoder, is the radius corresponding to the current number of layers of the cable, is the motor rotation angle, is the encoder error, is the distance measured by laser, is the laser error.

8. A suspended platform lifting and ranging device, characterized in that: include: The data processing module is used to obtain the encoder data of the encoder motor and the laser ranging data in real time during the lifting and lowering process of the suspension platform, and filter the laser ranging data in sequence to obtain the processed laser ranging data; The lifting distance acquisition module is used to perform Kalman filtering on the processed laser ranging data and encoder data to obtain the optimal lifting distance, wherein the Kalman filter gain is adjusted according to the number of cable layers of the encoder motor obtained in real time.

9. An electronic device, characterized in that: including memory and processor; The memory stores a computer-readable program executable by the processor; When the processor executes the computer-readable program, the steps of the method for measuring the lifting and distance of a suspended platform as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the suspended platform lifting and ranging method as described in any one of claims 1-7.

Images