Optical fiber remote self-healing system anti-misoperation method, system, device and medium

Abstract

The present invention discloses a method, system, device and medium for preventing misoperation of an optical fiber remote self-healing system. The method obtains encoder feedback data and motor feedback data corresponding to an encoder and a motor respectively, and determines the motion state corresponding to a manipulator based on the encoder feedback data, the motor feedback data and the manipulator activity instruction corresponding to the manipulator. When the motion state is abnormal motion, the type of motion abnormality corresponding to the manipulator is determined according to the motor attribute data, the encoder feedback data, the motor feedback data and the manipulator activity instruction corresponding to the motor. Based on the type of motion abnormality, the corresponding abnormality handling decision is executed. By setting an encoder on the moving axis of the manipulator and combining the feedback data of the encoder and the motor, the automatic detection of abnormalities is realized, and the corresponding abnormality handling decision is automatically executed, so that the serious consequences caused by unexpected situations such as obstacles, ectopic blocking, motor failure or inaccurate displacement of the manipulator can be reduced or avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of optical fiber remote self-healing systems, and in particular to an optical fiber remote self-healing system anti-misoperation method, system, equipment and medium. Background Art

[0002] The optical fiber remote self-healing system is a device that automatically plugs and unplugs the optical fiber flange head based on a robot. The robot can realize longitudinal and lateral movement, and remotely plugs and unplugs the optical fiber flange head through the optical fiber clamp at the front end of the robot to repair the function of the optical fiber routing line, that is, remotely plugs and unplugs the optical fiber to adjust the communication line and realize self-healing of the communication line.

[0003] The existing optical fiber remote self-healing system is used to detect the connectivity of optical fibers; issue an alarm for abnormal optical fiber connection; send an optical fiber flange head replacement instruction to the media server; receive the instruction, so that the optical fiber flange head is shifted accordingly from the optical fiber connector array, and the manipulator completes the insertion, removal, and transfer of the optical fiber flange head, so that the optical fiber flange head is replaced to repair the connectivity of the optical fiber; during the period when the position of the optical fiber flange head changes, the manipulator also manages the optical fiber, that is, temporarily hooks the fiber body on the cable management frame to prevent the manipulator from breaking the fiber line.

[0004] However, the existing optical fiber remote self-healing system does not have the function of determining abnormal motion. After the manipulator is out of position, the manipulator will continue to move forcibly, causing damage to the manipulator, optical fiber connector or optical fiber flange head. Summary of the invention

[0005] The present invention provides a method, system, device and medium for preventing misoperation of an optical fiber remote self-healing system, which solves the technical problem that the existing optical fiber remote self-healing system does not have a motion abnormality judgment function, and after a manipulator is out of position, the manipulator will continue to forcibly move, causing damage to the manipulator, optical fiber connector or optical fiber flange head.

[0006] The present invention provides a method for preventing misoperation of an optical fiber remote self-healing system, which relates to a manipulator of the optical fiber remote self-healing system, wherein the manipulator is provided with an encoder and a motor, and the method comprises:

[0007] Obtaining encoder feedback data and motor feedback data corresponding to the encoder and the motor respectively;

[0008] Determine the motion state corresponding to the manipulator based on the encoder feedback data, the motor feedback data and the manipulator movement instruction corresponding to the manipulator;

[0009] When the motion state is motion abnormality, determining the motion abnormality type corresponding to the manipulator according to the motor property data corresponding to the motor, the encoder feedback data, the motor feedback data and the manipulator activity instruction;

[0010] Based on the motion abnormality type, a corresponding abnormality handling decision is executed.

[0011] Optionally, the manipulator movement instruction includes a normal range of motor data and a normal range of pulse data; the step of determining the motion state corresponding to the manipulator based on the encoder feedback data, the motor feedback data and the manipulator movement instruction corresponding to the manipulator includes:

[0012] Compare the motor feedback data with the normal range of the motor data to obtain a first comparison result;

[0013] Compare the encoder feedback data with the normal range of the pulse data to obtain a second comparison result;

[0014] When both the first comparison result and the second comparison result are hits, the motion state corresponding to the manipulator is normal motion;

[0015] When there is a mismatch between the first comparison result and the second comparison result, the motion state corresponding to the manipulator is abnormal motion.

[0016] Optionally, the step of determining the type of motion abnormality corresponding to the manipulator according to the motor property data corresponding to the motor, the encoder feedback data, the motor feedback data and the manipulator activity instruction comprises:

[0017] Obtaining optical fiber connector data corresponding to the optical fiber remote self-healing system;

[0018] Based on the manipulator movement instruction, determining the initial coordinates and target coordinates corresponding to the manipulator;

[0019] Perform path simulation based on the initial coordinates, the target coordinates and the optical fiber connector data to determine the motion path corresponding to the manipulator;

[0020] Determining theoretical operation data corresponding to the manipulator based on the motion path and motor property data corresponding to the motor;

[0021] Determining actual operation data corresponding to the manipulator based on the encoder feedback data and the motor feedback data;

[0022] Based on the theoretical operation data and the actual operation data, a motion abnormality type corresponding to the manipulator is determined.

[0023] Optionally, the step of determining theoretical operation data corresponding to the manipulator based on the motion path and motor property data corresponding to the motor includes:

[0024] Based on the motion path, determining a motion safety range corresponding to the manipulator;

[0025] Obtaining the rated speed, rotation distance, stall torque and stall current corresponding to the motor;

[0026] Determining a rated moving speed corresponding to the motor based on the rated rotation speed and the rotation distance;

[0027] Determining a theoretical motion position corresponding to the manipulator based on the motion path, the rotation distance and the rated speed;

[0028] The theoretical operation data corresponding to the manipulator are constructed by using the movement safety range, the stall torque, the stall current, the rated moving speed and the theoretical movement position.

[0029] Optionally, the step of determining actual operation data corresponding to the manipulator based on the encoder feedback data and the motor feedback data includes:

[0030] Analyze the motor feedback data to obtain the motor current, motor power and motor speed corresponding to the manipulator;

[0031] The motor power and the motor speed are used to calculate to obtain the motor torque corresponding to the manipulator;

[0032] Analyze the encoder feedback data to obtain the number of motor rotations and the rotation distance corresponding to the manipulator;

[0033] The product of the number of rotations of the motor and the rotation distance is summed with the initial position corresponding to the manipulator to obtain the actual movement position of the manipulator;

[0034] Calculate the motor speed and the motor rotation distance to obtain the motor movement speed corresponding to the manipulator;

[0035] The motor current, the motor torque, the actual motion position and the motor moving speed are used to construct actual operation data corresponding to the manipulator.

[0036] Optionally, the manipulator includes a motion mechanism, and the motion mechanism includes an X-axis, a Y-axis, and a Z-axis; the step of determining the type of motion abnormality corresponding to the manipulator according to the theoretical operation data and the actual operation data includes:

[0037] Comparing the actual operation data with the corresponding theoretical operation data respectively;

[0038] When the actual motion position is not equal to the corresponding theoretical motion position, the motion abnormality type corresponding to the manipulator is the first motion abnormality type;

[0039] When the moving speed of the motor is greater than the rated moving speed, the motion abnormality type corresponding to the manipulator is the second motion abnormality type;

[0040] When the actual motion position does not fall within the motion safety range, the motion abnormality type corresponding to the manipulator is the third motion abnormality type;

[0041] When the motor current and the motor torque corresponding to the X-axis or the Y-axis are the stall torque or the stall current, the motion abnormality type corresponding to the manipulator is the fourth motion abnormality type;

[0042] When the motor current and the motor torque corresponding to the Z-axis are the stall torque or the stall current, the motion abnormality type corresponding to the manipulator is the fifth motion abnormality type.

[0043] Optionally, the step of executing a corresponding exception handling decision based on the motion abnormality type includes:

[0044] When the motion abnormality type corresponding to the manipulator is the first motion abnormality type, executing a first abnormality handling decision;

[0045] When the motion abnormality type corresponding to the manipulator is the second motion abnormality type, executing a second abnormality handling decision;

[0046] When the motion abnormality type corresponding to the manipulator is the third motion abnormality type, executing the third abnormality handling decision;

[0047] When the motion abnormality type corresponding to the manipulator is the fourth motion abnormality type, executing the fourth abnormality handling decision;

[0048] When the motion abnormality type corresponding to the manipulator is the fifth motion abnormality type, the fifth abnormality handling decision is executed.

[0049] The present invention also provides an anti-misoperation system of an optical fiber remote self-healing system, which relates to a manipulator of the optical fiber remote self-healing system, wherein the manipulator is provided with an encoder and a motor, and the system comprises:

[0050] An encoder feedback data and motor feedback data acquisition module, used to respectively acquire encoder feedback data and motor feedback data corresponding to the encoder and the motor;

[0051] A motion state determination module, used for determining the motion state corresponding to the manipulator based on the encoder feedback data, the motor feedback data and the manipulator movement instruction corresponding to the manipulator;

[0052] A motion abnormality type determination module, used for determining the motion abnormality type corresponding to the manipulator according to the motor property data corresponding to the motor, the encoder feedback data, the motor feedback data and the manipulator activity instruction when the motion state is motion abnormality;

[0053] The exception handling decision execution module is used to execute the corresponding exception handling decision based on the motion abnormality type.

[0054] The present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of implementing any of the above-mentioned methods for preventing misoperation of an optical fiber remote self-healing system.

[0055] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed, any of the above-mentioned methods for preventing misoperation of an optical fiber remote self-healing system is implemented.

[0056] It can be seen from the above technical solutions that the present invention has the following advantages:

[0057] The present invention obtains encoder feedback data and motor feedback data corresponding to the encoder and the motor respectively, and determines the motion state corresponding to the manipulator based on the encoder feedback data, the motor feedback data and the manipulator activity instruction corresponding to the manipulator. When the motion state is abnormal motion, the motion abnormality type corresponding to the manipulator is determined according to the motor attribute data corresponding to the motor, the encoder feedback data, the motor feedback data and the manipulator activity instruction. Finally, based on the motion abnormality type, the corresponding abnormality handling decision is executed. The existing optical fiber remote self-healing system does not have the function of determining motion abnormality, and the manipulator will continue to move forcibly after the manipulator is out of position, resulting in damage to the manipulator, the optical fiber connector or the optical fiber flange head. By arranging an encoder on the moving axis of the manipulator, combining the encoder and the feedback data of the motor, automatic detection of abnormalities is achieved, and corresponding abnormality handling decisions are automatically executed, so that the serious consequences caused by unexpected situations such as obstacles, out-of-position blocking, motor failure or inaccurate displacement of the manipulator can be reduced or avoided, and the accident avoidance ability of the optical fiber remote self-healing system is significantly improved, so that the optical fiber remote self-healing system can work continuously, stably and safely. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0059] Figure 1 A flowchart of a method for preventing misoperation of an optical fiber remote self-healing system provided in Embodiment 1 of the present invention;

[0060] Figure 2 A flowchart of a method for preventing misoperation of an optical fiber remote self-healing system provided in Embodiment 2 of the present invention;

[0061] Figure 3 This is a structural block diagram of an anti-misoperation system of an optical fiber remote self-healing system provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0062] The embodiments of the present invention provide a method, system, device and medium for preventing misoperation of an optical fiber remote self-healing system, which are used to solve the technical problem that the existing optical fiber remote self-healing system does not have a motion abnormality judgment function, and the manipulator will continue to move forcibly after the manipulator is out of position, resulting in damage to the manipulator, optical fiber connector or optical fiber flange head.

[0063] In the embodiment of the present invention, the terminal is specifically a fiber remote self-healing system distributed in various places, and the fiber remote self-healing system is connected to the server through the network. The server and the server can be independent physical servers, or a server cluster or distributed system composed of multiple physical servers. The server can be a centralized processing terminal for operators, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0064] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] See also Figure 1 , which is a flow chart of the steps of a method for preventing misoperation of an optical fiber remote self-healing system provided in Example 1 of the present invention.

[0066] The present invention provides a method for preventing misoperation of an optical fiber remote self-healing system, which relates to a manipulator of the optical fiber remote self-healing system, wherein the manipulator is provided with an encoder and a motor, and the method comprises:

[0067] Step 101 : Obtain encoder feedback data and motor feedback data corresponding to the encoder and the motor respectively.

[0068] The manipulator of the optical fiber remote self-healing system specifically includes a front-end clamp that is compatible with the optical fiber flange head, and a moving mechanism that drives the front-end clamp. The moving mechanism is an XYZ-axis slide motion mechanism (or other equivalent alternative motion mechanisms of the XYZ-axis slide motion mechanism), and motors and corresponding encoders are respectively provided on the three axes of XYZ. The XYZ-axis slide motion mechanism is implemented by connecting a motor to a ball screw module (or other equivalent alternative mechanisms such as gear racks), and the encoder adopts an absolute rotary encoder, and the encoder on each axis is used in the form of a combination of multiple encoders, including at least one photoelectric encoder and a magnetoelectric encoder.

[0069] In an embodiment of the present invention, encoder feedback data and motor feedback data corresponding to the encoder and the motor are continuously received based on a preset time interval. The encoder feedback data includes data collected by the encoder corresponding to each axis of the XYZ-axis slide motion mechanism. The motor feedback data includes motion data of the motor corresponding to each axis of the XYZ-axis slide motion mechanism.

[0070] Step 102 : determining a motion state corresponding to the manipulator based on encoder feedback data, motor feedback data and a manipulator movement instruction corresponding to the manipulator.

[0071] In an embodiment of the present invention, the manipulator activity instruction includes a normal range of motor data and a normal range of pulse data. The normal range of motor data refers to the data interval that the corresponding motor feedback data should satisfy when the motor moves normally. The normal range of pulse data refers to the data interval that the encoder feedback data collected by the encoder should satisfy when the motor moves normally. The motor feedback data is hit-matched with the normal range of motor data to obtain a first comparison result, and the encoder feedback data is hit-matched with the normal range of pulse data to obtain a second comparison result. When both the first comparison result and the second comparison result are hits, the corresponding motion state of the manipulator is normal motion. When there is a miss between the first comparison result and the second comparison result, the corresponding motion state of the manipulator is abnormal motion.

[0072] Step 103: When the motion state is abnormal motion, determine the type of abnormal motion corresponding to the manipulator according to the motor property data, encoder feedback data, motor feedback data and manipulator activity instructions corresponding to the motor.

[0073] The motor attribute data includes the starting torque, rated torque, maximum torque, stall torque, rated speed, maximum speed, starting current, rated current and stall current corresponding to each axis motor.

[0074] The robot movement instruction refers to all preset data corresponding to the robot's movement, including the normal range of motor data, the normal range of pulse data, the initial coordinates and target coordinates of the fiber optic flange head, etc.

[0075] The motion abnormality type refers to the abnormality type of the motion data corresponding to the robot. The abnormality type is set to indicate which part of the robot has a problem at this time.

[0076] In an embodiment of the present invention, the optical fiber connector data corresponding to the optical fiber remote self-healing system is obtained, and the initial coordinates and target coordinates corresponding to the manipulator are determined based on the manipulator activity instructions. The path simulation is performed based on the initial coordinates, target coordinates and optical fiber connector data to determine the motion path corresponding to the manipulator, where the motion path refers to the optimal path corresponding to the manipulator's current motion. Based on the motion path and the motor attribute data corresponding to the motor, the theoretical operation data corresponding to the manipulator is determined, and based on the encoder feedback data and the motor feedback data, the actual operation data corresponding to the manipulator is determined. Finally, based on the theoretical operation data and the actual operation data, the type of motion abnormality corresponding to the manipulator is determined.

[0077] Step 104: Based on the motion abnormality type, execute a corresponding abnormality handling decision.

[0078] In an embodiment of the present invention, when the motion abnormality type corresponding to the manipulator is the first motion abnormality type, the first abnormality handling decision is executed. When the motion abnormality type corresponding to the manipulator is the second motion abnormality type, the second abnormality handling decision is executed. When the motion abnormality type corresponding to the manipulator is the third motion abnormality type, the third abnormality handling decision is executed. When the motion abnormality type corresponding to the manipulator is the fourth motion abnormality type, the fourth abnormality handling decision is executed. When the motion abnormality type corresponding to the manipulator is the fifth motion abnormality type, the fifth abnormality handling decision is executed.

[0079] In an embodiment of the present invention, the encoder feedback data and motor feedback data corresponding to the encoder and the motor are obtained respectively, and the motion state corresponding to the manipulator is determined based on the encoder feedback data, the motor feedback data and the manipulator activity instruction corresponding to the manipulator. When the motion state is abnormal motion, the type of motion abnormality corresponding to the manipulator is determined according to the motor attribute data corresponding to the motor, the encoder feedback data, the motor feedback data and the manipulator activity instruction. Finally, based on the type of motion abnormality, the corresponding abnormality handling decision is executed. The technical problem that the existing optical fiber remote self-healing system does not have the function of determining motion abnormality, and the manipulator will continue to move forcibly after the manipulator is out of position, resulting in damage to the manipulator, the optical fiber connector or the optical fiber flange head is solved. By setting an encoder on the moving axis of the manipulator, combining the feedback data of the encoder and the motor, automatic detection of abnormalities is realized, and corresponding abnormality handling decisions are automatically executed, so that the serious consequences caused by unexpected situations such as obstacles, out-of-position blocking, motor failure or inaccurate displacement of the manipulator can be reduced or avoided, and the accident avoidance ability of the optical fiber remote self-healing system is significantly improved, so that the optical fiber remote self-healing system can work continuously, stably and safely.

[0080] See also Figure 2 , Figure 2 A flowchart of the steps of a method for preventing misoperation of an optical fiber remote self-healing system provided in Embodiment 2 of the present invention.

[0081] Another method for preventing misoperation of an optical fiber remote self-healing system provided by the present invention relates to a manipulator of the optical fiber remote self-healing system, the manipulator being provided with an encoder and a motor, and the method comprising:

[0082] Step 201 : Obtain encoder feedback data and motor feedback data corresponding to the encoder and the motor respectively.

[0083] In the embodiment of the present invention, encoder feedback data and motor feedback data corresponding to encoders and motors on the X-axis, Y-axis and Z-axis corresponding to the manipulator are respectively obtained.

[0084] Step 202 : determining a motion state corresponding to the manipulator based on encoder feedback data, motor feedback data and a manipulator movement instruction corresponding to the manipulator.

[0085] Further, step 202 may include the following sub-steps S11-S14:

[0086] S11, comparing the motor feedback data with the normal range of the motor data to obtain a first comparison result.

[0087] In the embodiment of the present invention, it is determined whether the motor feedback data is within the normal range of the motor data. If so, the first comparison result is a hit; if not, the first comparison result is a miss.

[0088] S12, compare the encoder feedback data with the normal range of the pulse data to obtain a second comparison result.

[0089] In the embodiment of the present invention, it is determined whether the encoder feedback data is within the normal range of the pulse data. If so, the second comparison result is a hit; if not, the second comparison result is a miss.

[0090] S13. When both the first comparison result and the second comparison result are hits, the corresponding motion state of the robot arm is normal motion.

[0091] In the embodiment of the present invention, if both the first comparison result and the second comparison result are hits, the corresponding motion state of the manipulator is normal motion, and the manipulator continues to operate normally.

[0092] S14. When there is a mismatch between the first comparison result and the second comparison result, the corresponding motion state of the robot arm is abnormal motion.

[0093] In an embodiment of the present invention, if one of the first comparison result and the second comparison result does not match or both do not match, the motion state corresponding to the robot is motion abnormality, and then the corresponding abnormality handling decision is executed by determining the motion abnormality type corresponding to the robot.

[0094] Step 203: Obtain optical fiber connector data corresponding to the optical fiber remote self-healing system.

[0095] In an embodiment of the present invention, the optical fiber connector data includes the specific dimensions of the overall length and width of the optical fiber connector array and the numbers and distribution positions of the optical fiber connectors. The specific dimensions of the overall length and width of the optical fiber connector array corresponding to the optical fiber remote self-healing system are obtained, and the specific dimensions of the overall length and width of the optical fiber connector array corresponding to the optical fiber remote self-healing system are obtained.

[0096] Step 204: Determine the initial coordinates and target coordinates corresponding to the manipulator based on the manipulator movement instruction.

[0097] In an embodiment of the present invention, the initial coordinates and target coordinates of the optical fiber flange head corresponding to the movement of the manipulator contained in the manipulator activity instruction are obtained, and the initial coordinates and target coordinates corresponding to the manipulator are determined through the optical fiber connector data and the initial coordinates and target coordinates of the optical fiber flange head.

[0098] Step 205: Perform path simulation based on the initial coordinates, target coordinates and optical fiber connector data to determine the corresponding motion path of the manipulator.

[0099] In an embodiment of the present invention, a path simulation is performed based on the initial coordinates, target coordinates and optical fiber connector data by simulating a motion model. Based on the displacement of the X-axis, Y-axis and Z-axis of each path, the path with the shortest overall distance, the least number of manipulator turns, or the least Z-axis displacement (most likely to damage the manipulator and the optical fiber flange head) is selected as the motion path. The motion path refers to the optimal motion path, and the corresponding selection criteria can be set according to the actual situation of use to determine the optimal motion path.

[0100] Step 206: Determine theoretical operation data corresponding to the manipulator based on the motion path and the motor property data corresponding to the motor.

[0101] Further, step 206 may include the following sub-steps S21-S25:

[0102] S21. Determine the motion safety range corresponding to the robot based on the motion path.

[0103] In an embodiment of the present invention, the activity distances of the X-axis, Y-axis and Z-axis corresponding to the motion path are calculated, and the activity distances corresponding to the X-axis, Y-axis and Z-axis are set as the first safety range, the second safety range and the third safety range respectively.

[0104] S22, obtaining the rated speed, rotation distance, stall torque and stall current corresponding to the motor.

[0105] In the embodiment of the present invention, the rated speed, rotation distance, stall torque and stall current corresponding to the motors arranged on the X-axis, Y-axis and Z-axis are obtained respectively.

[0106] S23. Determine the rated moving speed corresponding to the motor based on the rated rotation speed and the rotation distance.

[0107] In the embodiment of the present invention, the product of the rated rotation speed (number of rotations per second) corresponding to each axis and the rotation distance corresponding to each rotation is calculated respectively, and the calculated product is used as the rated moving speed of the corresponding motor.

[0108] S24. Determine the theoretical motion position corresponding to the manipulator based on the motion path, rotation distance and rated rotation speed.

[0109] In the embodiment of the present invention, the initial coordinates and target coordinates corresponding to the manipulator are determined through the motion path, and the theoretical position corresponding to the manipulator is determined based on the initial coordinates, the rotation distance corresponding to the motor and the rated speed.

[0110] S25. Use the motion safety range, stall torque, stall current, rated moving speed and theoretical motion position to construct the theoretical operation data corresponding to the robot.

[0111] In the embodiment of the present invention, the motion safety range, the stall torque, the stall current, the rated moving speed and the theoretical motion position corresponding to each axis are used as the theoretical operation data corresponding to the manipulator.

[0112] Step 207: Determine actual operation data corresponding to the manipulator based on the encoder feedback data and the motor feedback data.

[0113] Further, step 207 may include the following sub-steps S31-S36:

[0114] S31. Analyze the motor feedback data to obtain the motor current, motor power and motor speed corresponding to the manipulator.

[0115] In an embodiment of the present invention, data analysis is performed on various motor feedback data, the motor current, motor power and motor speed in each motor feedback data are extracted, and all the motor current, motor power and motor speed are used as the motor current, motor power and motor speed corresponding to the manipulator.

[0116] S32, using the motor power and motor speed to calculate and obtain the motor torque corresponding to the manipulator.

[0117] The calculation formula corresponding to the motor torque is:

[0118] T=9550P / n

[0119] Among them, T is the motor torque, P is the motor power, and n is the motor speed.

[0120] In the embodiment of the present invention, the motor power and motor speed corresponding to each axis are obtained, and are respectively substituted into the above calculation formula to calculate the corresponding motor torque. The total motor torque is used as the motor torque corresponding to the manipulator.

[0121] S33, analyzing the encoder feedback data to obtain the number of motor rotations and the rotation distance corresponding to the manipulator.

[0122] In an embodiment of the present invention, the encoder feedback data is analyzed to obtain the number of motor rotations and the rotation distance corresponding to each axis, and the total number of motor rotations and the rotation distance are used as the number of motor rotations and the rotation distance corresponding to the manipulator.

[0123] S34, summing the product of the number of motor rotations and the rotation distance and the initial position corresponding to the manipulator to obtain the actual movement position of the manipulator.

[0124] In an embodiment of the present invention, the product of the number of motor rotations and the rotation distance corresponding to each axis is calculated respectively, and the corresponding product is summed with the initial position of each axis corresponding to the initial position of the manipulator to construct the actual movement position of the manipulator.

[0125] S35, calculating the motor speed and the motor rotation distance to obtain the motor moving speed corresponding to the manipulator.

[0126] In the embodiment of the present invention, the motor rotation distance refers to the distance corresponding to each rotation of the motor during the actual movement process. The multiplication value of the motor speed corresponding to each axis and the motor rotation distance is respectively used as the motor movement speed corresponding to each axis motor, and all motor movement speeds are used to construct the motor movement speed corresponding to the manipulator.

[0127] S36. Use the motor current, motor torque, actual motion position and motor moving speed to construct actual operation data corresponding to the robot.

[0128] In the embodiment of the present invention, the motor current, motor torque, actual motion position and motor moving speed corresponding to each axis are used to construct the actual operation data corresponding to the manipulator.

[0129] Step 208: Determine the motion abnormality type corresponding to the robot based on the theoretical operation data and the actual operation data.

[0130] Further, step 208 may include the following sub-steps S41-S46:

[0131] S41. Compare the actual operation data with the corresponding theoretical operation data.

[0132] In an embodiment of the present invention, the actual motion position is compared with the theoretical motion position; the motor moving speed is compared with the rated moving speed; the actual motion position is compared with the motion safety range; the motor current and the motor torque are compared with the stall torque and the stall current respectively.

[0133] S42: When the actual motion position is not equal to the corresponding theoretical motion position, the motion abnormality type corresponding to the manipulator is the first motion abnormality type.

[0134] In an embodiment of the present invention, the actual motion position corresponding to each axis is compared with the corresponding theoretical motion position. When the actual motion position of any axis is not equal to the corresponding theoretical motion position, the corresponding motion abnormality type of the manipulator at this time is the first motion abnormality type, that is, there is an abnormality in the motor movement accuracy.

[0135] S43: When the motor moving speed is greater than the rated moving speed, the motion abnormality type corresponding to the manipulator is the second motion abnormality type.

[0136] In an embodiment of the present invention, the motor movement speed corresponding to each axis is compared with the corresponding rated movement speed. When the motor movement speed of any axis is greater than the rated movement speed, the corresponding motion abnormality type of the manipulator at this time is the second motion abnormality type, namely, the motor movement speed abnormality.

[0137] S44: When the actual motion position does not fall within the motion safety range, the motion abnormality type corresponding to the manipulator is the third motion abnormality type.

[0138] In an embodiment of the present invention, the actual motion position corresponding to each axis is compared with the corresponding motion safety range. When the actual motion position of any axis is not within the motion safety range, the corresponding motion abnormality type of the manipulator at this time is the third motion abnormality type, that is, the manipulator is not within the safety range.

[0139] S45. When the motor current and the motor torque corresponding to the X-axis or the Y-axis are a stall torque or a stall current, the motion abnormality type corresponding to the manipulator is a fourth motion abnormality type.

[0140] In an embodiment of the present invention, the motor current and motor torque corresponding to the X-axis and Y-axis are compared with the corresponding stalled torque and stalled current respectively. When the motor current and motor torque corresponding to the X-axis or Y-axis are stalled torque or stalled current, the motion abnormality type corresponding to the manipulator is the fourth motion abnormality type, that is, the manipulator encounters an obstacle during the process of aligning the optical fiber connector (during the movement of the XY axis).

[0141] S46. When the motor current and the motor torque corresponding to the Z axis are a stall torque or a stall current, the motion abnormality type corresponding to the manipulator is the fifth motion abnormality type.

[0142] In an embodiment of the present invention, the motor current and motor torque corresponding to the Z-axis are compared with the corresponding stalled torque and stalled current. When the motor current and motor torque corresponding to the Z-axis are stalled torque or stalled current, the motion abnormality type corresponding to the manipulator is the fifth motion abnormality type, that is, the manipulator is out of position during the process of plugging and unplugging the optical fiber flange head (during the movement of the Z-axis).

[0143] Step 209: Based on the motion abnormality type, execute a corresponding abnormality handling decision.

[0144] Further, step 209 may include the following sub-steps S51-S55:

[0145] S51. When the motion abnormality type corresponding to the robot arm is the first motion abnormality type, execute the first abnormality handling decision.

[0146] In an embodiment of the present invention, if the motion abnormality type corresponding to the robot arm is the first motion abnormality type, that is, abnormal motor movement accuracy occurs, the first abnormality processing decision is executed, that is, an accuracy inspection alarm of the corresponding axis is issued.

[0147] S52: When the motion abnormality type corresponding to the robot arm is the second motion abnormality type, execute the second abnormality handling decision.

[0148] In the embodiment of the present invention, if the motion abnormality type corresponding to the robot arm is the second motion abnormality type, that is, the motor moving speed is abnormal, the second abnormality processing decision is executed, that is, the motor maintenance alarm of the corresponding axis is issued.

[0149] S53: When the motion abnormality type corresponding to the robot arm is the third motion abnormality type, execute the third abnormality handling decision.

[0150] In the embodiment of the present invention, if the motion abnormality type corresponding to the manipulator is the third motion abnormality type, that is, the manipulator is not within the safety range, the third abnormality handling decision is executed, that is, a manipulator reset correction instruction is issued.

[0151] S54: When the motion abnormality type corresponding to the robot arm is the fourth motion abnormality type, execute the fourth abnormality handling decision.

[0152] In an embodiment of the present invention, if the motion abnormality type corresponding to the manipulator is the fourth motion abnormality type, that is, the manipulator encounters an obstacle during the process of aligning the optical fiber connector (that is, during the XY axis movement), the fourth abnormality handling decision is executed, that is, a stop command is issued and a foreign object obstacle alarm is issued.

[0153] S55. When the motion abnormality type corresponding to the robot arm is the fifth motion abnormality type, execute the fifth abnormality handling decision.

[0154] In an embodiment of the present invention, if the motion abnormality type corresponding to the manipulator is the first motion abnormality type, that is, the manipulator is out of position during the process of plugging and unplugging the optical fiber flange head (that is, during the Z-axis movement), the fifth abnormality handling decision is executed, that is, a shutdown command is issued and an out-of-position alarm is issued.

[0155] In an embodiment of the present invention, encoder feedback data and motor feedback data corresponding to the encoder and motor are obtained respectively, and the motion state corresponding to the manipulator is determined based on the encoder feedback data, the motor feedback data and the manipulator activity instruction corresponding to the manipulator. The optical fiber connector data corresponding to the optical fiber remote self-healing system is obtained, and the initial coordinates and target coordinates corresponding to the manipulator are determined based on the manipulator activity instruction. Path simulation is performed based on the initial coordinates, the target coordinates and the optical fiber connector data to determine the motion path corresponding to the manipulator. The theoretical operation data corresponding to the manipulator is determined based on the motion path and the motor attribute data corresponding to the motor. The actual operation data corresponding to the manipulator is determined based on the encoder feedback data and the motor feedback data. The motion abnormality type corresponding to the manipulator is determined based on the theoretical operation data and the actual operation data, and the corresponding abnormality handling decision is executed based on the motion abnormality type. By adding an encoder structure to the manipulator on the optical fiber remote self-healing system, the motor and encoder on the optical fiber remote self-healing system can feedback the data on the corresponding moving axis, so as to realize real-time detection of the optical fiber remote self-healing system, and facilitate the analysis of specific abnormality types from various data. By presetting corresponding decisions for various types of exceptions, corresponding decisions can be automatically executed based on the analyzed exception types, and the optical fiber remote self-healing system can be protected at the first time. Moreover, through the method of the present invention, there is no need for operators to monitor the optical fiber remote self-healing system 24 hours a day and perform corresponding processing, so that the exception processing of the optical fiber remote self-healing system becomes timely and accurate.

[0156] See also Figure 3 , Figure 3 This is a structural block diagram of an anti-misoperation system of an optical fiber remote self-healing system provided in Embodiment 3 of the present invention.

[0157] An embodiment of the present invention provides an anti-misoperation system of an optical fiber remote self-healing system, and relates to a manipulator of the optical fiber remote self-healing system, wherein the manipulator is provided with an encoder and a motor, and the system comprises:

[0158] The encoder feedback data and motor feedback data acquisition module 301 is used to respectively acquire encoder feedback data and motor feedback data corresponding to the encoder and the motor.

[0159] The motion state determination module 302 is used to determine the motion state corresponding to the manipulator based on the encoder feedback data, the motor feedback data and the manipulator movement instruction corresponding to the manipulator.

[0160] The motion abnormality type determination module 303 is used to determine the motion abnormality type corresponding to the manipulator according to the motor property data, encoder feedback data, motor feedback data and manipulator activity instructions corresponding to the motor when the motion state is motion abnormality.

[0161] The exception handling decision execution module 304 is used to execute the corresponding exception handling decision based on the motion abnormality type.

[0162] Optionally, the manipulator movement instruction includes a normal range of motor data and a normal range of pulse data, and the motion state determination module 302 includes:

[0163] The first comparison result obtaining module is used to compare the motor feedback data with the normal range of the motor data to obtain a first comparison result.

[0164] The second comparison result obtaining module is used to compare the encoder feedback data with the normal range of the pulse data to obtain the second comparison result.

[0165] The normal motion determination module is used to determine that the motion state corresponding to the robot arm is normal motion when both the first comparison result and the second comparison result are hits.

[0166] The motion abnormality determination module is used to determine that when there is a mismatch between the first comparison result and the second comparison result, the motion state corresponding to the robot arm is motion abnormality.

[0167] Optionally, the movement abnormality type determination module 303 includes:

[0168] The optical fiber connector data acquisition module is used to obtain the optical fiber connector data corresponding to the optical fiber remote self-healing system.

[0169] The initial coordinate and target coordinate determination module is used to determine the initial coordinate and target coordinate corresponding to the manipulator based on the manipulator activity instruction.

[0170] The motion path determination module is used to perform path simulation based on the initial coordinates, target coordinates and optical fiber connector data to determine the motion path corresponding to the manipulator.

[0171] The theoretical operation data determination module is used to determine the theoretical operation data corresponding to the manipulator based on the motion path and the motor property data corresponding to the motor.

[0172] The actual operation data determination module is used to determine the actual operation data corresponding to the manipulator based on the encoder feedback data and the motor feedback data.

[0173] The motion abnormality type determination submodule is used to determine the motion abnormality type corresponding to the robot based on theoretical operation data and actual operation data.

[0174] Optionally, the theoretical operation data determination module may perform the following steps:

[0175] Based on the motion path, determine the corresponding safe range of motion of the robot;

[0176] Get the rated speed, rotation distance, stall torque and stall current corresponding to the motor;

[0177] Based on the rated speed and rotation distance, determine the rated moving speed corresponding to the motor;

[0178] Based on the motion path, rotation distance and rated speed, determine the corresponding theoretical motion position of the manipulator;

[0179] The theoretical operation data corresponding to the robot are constructed using the motion safety range, stall torque, stall current, rated moving speed and theoretical motion position.

[0180] Optionally, the actual operation data determination module may perform the following steps:

[0181] Analyze the motor feedback data to obtain the motor current, motor power and motor speed corresponding to the manipulator;

[0182] The motor power and motor speed are used for calculation to obtain the motor torque corresponding to the manipulator;

[0183] Analyze the encoder feedback data to obtain the number of motor rotations and the rotation distance corresponding to the robot;

[0184] The product of the number of motor revolutions and the rotation distance is summed with the initial position corresponding to the manipulator to obtain the actual movement position of the manipulator;

[0185] Calculate the motor speed and motor rotation distance to obtain the corresponding motor moving speed of the robot;

[0186] The motor current, motor torque, actual motion position and motor moving speed are used to construct the actual operation data corresponding to the robot.

[0187] Optionally, the manipulator includes a motion mechanism, the motion mechanism includes an X-axis, a Y-axis, and a Z-axis, and the motion abnormality type determination submodule may perform the following steps:

[0188] Compare the actual operation data with the corresponding theoretical operation data respectively;

[0189] When the actual motion position is not equal to the corresponding theoretical motion position, the motion abnormality type corresponding to the manipulator is the first motion abnormality type;

[0190] When the motor moving speed is greater than the rated moving speed, the motion abnormality type corresponding to the manipulator is the second motion abnormality type;

[0191] When the actual motion position does not fall within the motion safety range, the motion abnormality type corresponding to the manipulator is the third motion abnormality type;

[0192] When the motor current and motor torque corresponding to the X-axis or Y-axis are the stall torque or the stall current, the motion abnormality type corresponding to the manipulator is the fourth motion abnormality type;

[0193] When the motor current and the motor torque corresponding to the Z-axis are a stall torque or a stall current, the motion abnormality type corresponding to the manipulator is the fifth motion abnormality type.

[0194] Optionally, the exception handling decision execution module 304 includes:

[0195] The first exception handling decision execution module is used to execute the first exception handling decision when the motion abnormality type corresponding to the robot arm is the first motion abnormality type.

[0196] The second exception handling decision execution module is used to execute the second exception handling decision when the motion abnormality type corresponding to the robot arm is the second motion abnormality type.

[0197] The third exception handling decision execution module is used to execute the third exception handling decision when the motion abnormality type corresponding to the robot arm is the third motion abnormality type.

[0198] The fourth exception handling decision execution module is used to execute the fourth exception handling decision when the motion abnormality type corresponding to the manipulator is the fourth motion abnormality type.

[0199] The fifth exception handling decision execution module is used to execute the fifth exception handling decision when the motion abnormality type corresponding to the robot arm is the fifth motion abnormality type.

[0200] An embodiment of the present invention further provides an electronic device, comprising: a memory and a processor, wherein a computer program is stored in the memory; when the computer program is executed by the processor, the processor executes the method for preventing misoperation of an optical fiber remote self-healing system as described in any of the above embodiments.

[0201] The memory may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk or a ROM. The memory has a storage space for program codes for executing any method step in the above method. For example, the storage space for program codes may include individual program codes for implementing the various steps in the above method, respectively. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as a hard disk, a compact disk (CD), a memory card or a floppy disk. The program code may be compressed, for example, in an appropriate form. When these codes are run by a computing and processing device, the computing and processing device executes the various steps in the optical fiber remote self-healing system anti-misoperation method described above.

[0202] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for preventing misoperation of an optical fiber remote self-healing system according to any of the above embodiments is implemented.

[0203] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0204] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0205] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0206] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0207] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0208] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for preventing misoperation of an optical fiber remote self-healing system, characterized in that: A manipulator of the optical fiber remote self-healing system is provided, wherein the manipulator is provided with an encoder and a motor, and the method comprises: Obtaining encoder feedback data and motor feedback data corresponding to the encoder and the motor respectively; Determine the motion state corresponding to the manipulator based on the encoder feedback data, the motor feedback data and the manipulator movement instruction corresponding to the manipulator; When the motion state is motion abnormality, determining the motion abnormality type corresponding to the manipulator according to the motor property data corresponding to the motor, the encoder feedback data, the motor feedback data and the manipulator activity instruction; Based on the motion abnormality type, executing a corresponding abnormality handling decision; The manipulator movement instruction includes a normal range of motor data and a normal range of pulse data; the step of determining the motion state corresponding to the manipulator based on the encoder feedback data, the motor feedback data and the manipulator movement instruction corresponding to the manipulator includes: Compare the motor feedback data with the normal range of the motor data to obtain a first comparison result; Compare the encoder feedback data with the normal range of the pulse data to obtain a second comparison result; When both the first comparison result and the second comparison result are hits, the motion state corresponding to the manipulator is normal motion; When there is a mismatch between the first comparison result and the second comparison result, the motion state corresponding to the manipulator is abnormal motion.

2. The method for preventing misoperation of an optical fiber remote self-healing system according to claim 1, characterized in that: The step of determining the type of motion abnormality corresponding to the manipulator according to the motor property data corresponding to the motor, the encoder feedback data, the motor feedback data and the manipulator activity instruction comprises: Obtaining optical fiber connector data corresponding to the optical fiber remote self-healing system; Based on the manipulator movement instruction, determining the initial coordinates and target coordinates corresponding to the manipulator; Perform path simulation based on the initial coordinates, the target coordinates and the optical fiber connector data to determine the motion path corresponding to the manipulator; Determining theoretical operation data corresponding to the manipulator based on the motion path and motor property data corresponding to the motor; Determining actual operation data corresponding to the manipulator based on the encoder feedback data and the motor feedback data; Based on the theoretical operation data and the actual operation data, a motion abnormality type corresponding to the manipulator is determined.

3. The method for preventing misoperation of an optical fiber remote self-healing system according to claim 2, characterized in that: The step of determining theoretical operation data corresponding to the manipulator based on the motion path and the motor property data corresponding to the motor comprises: Based on the motion path, determining a motion safety range corresponding to the manipulator; Obtaining the rated speed, rotation distance, stall torque and stall current corresponding to the motor; Determining a rated moving speed corresponding to the motor based on the rated rotation speed and the rotation distance; Determining a theoretical motion position corresponding to the manipulator based on the motion path, the rotation distance and the rated speed; The theoretical operation data corresponding to the manipulator are constructed by using the movement safety range, the stall torque, the stall current, the rated moving speed and the theoretical movement position.

4. The method for preventing misoperation of an optical fiber remote self-healing system according to claim 3, characterized in that: The step of determining the actual operation data corresponding to the manipulator based on the encoder feedback data and the motor feedback data comprises: Analyze the motor feedback data to obtain the motor current, motor power and motor speed corresponding to the manipulator; The motor power and the motor speed are used to calculate to obtain the motor torque corresponding to the manipulator; Analyze the encoder feedback data to obtain the number of motor rotations and the motor rotation distance corresponding to the manipulator; The product of the number of revolutions of the motor and the distance of rotation of the motor is summed with the initial position corresponding to the manipulator to obtain the actual movement position of the manipulator; Calculate the motor speed and the motor rotation distance to obtain the motor movement speed corresponding to the manipulator; The motor current, the motor torque, the actual motion position and the motor moving speed are used to construct actual operation data corresponding to the manipulator.

5. The method for preventing misoperation of an optical fiber remote self-healing system according to claim 4, characterized in that: The manipulator includes a motion mechanism, and the motion mechanism includes an X-axis, a Y-axis, and a Z-axis; the step of determining the type of motion abnormality corresponding to the manipulator based on the theoretical operation data and the actual operation data includes: Comparing the actual operation data with the corresponding theoretical operation data respectively; When the actual motion position is not equal to the corresponding theoretical motion position, the motion abnormality type corresponding to the manipulator is the first motion abnormality type; When the moving speed of the motor is greater than the rated moving speed, the motion abnormality type corresponding to the manipulator is the second motion abnormality type; When the actual motion position does not fall within the motion safety range, the motion abnormality type corresponding to the manipulator is the third motion abnormality type; When the motor current and the motor torque corresponding to the X-axis or the Y-axis are the stall torque or the stall current, the motion abnormality type corresponding to the manipulator is the fourth motion abnormality type; When the motor current and the motor torque corresponding to the Z-axis are the stall torque or the stall current, the motion abnormality type corresponding to the manipulator is the fifth motion abnormality type.

6. The method for preventing misoperation of an optical fiber remote self-healing system according to claim 5, characterized in that: The step of executing a corresponding abnormality handling decision based on the motion abnormality type includes: When the motion abnormality type corresponding to the manipulator is the first motion abnormality type, executing a first abnormality handling decision; When the motion abnormality type corresponding to the manipulator is the second motion abnormality type, executing a second abnormality handling decision; When the motion abnormality type corresponding to the manipulator is the third motion abnormality type, executing the third abnormality handling decision; When the motion abnormality type corresponding to the manipulator is the fourth motion abnormality type, executing the fourth abnormality handling decision; When the motion abnormality type corresponding to the manipulator is the fifth motion abnormality type, the fifth abnormality handling decision is executed.

7. An optical fiber remote self-healing system anti-misoperation system, characterized in that: A manipulator of the optical fiber remote self-healing system is provided, wherein the manipulator is provided with an encoder and a motor, and the system comprises: An encoder feedback data and motor feedback data acquisition module, used to respectively acquire encoder feedback data and motor feedback data corresponding to the encoder and the motor; A motion state determination module, used for determining the motion state corresponding to the manipulator based on the encoder feedback data, the motor feedback data and the manipulator movement instruction corresponding to the manipulator; A motion abnormality type determination module, used for determining the motion abnormality type corresponding to the manipulator according to the motor property data corresponding to the motor, the encoder feedback data, the motor feedback data and the manipulator activity instruction when the motion state is motion abnormality; An exception handling decision execution module, used for executing a corresponding exception handling decision based on the motion abnormality type; The manipulator activity instruction includes a normal range of motor data and a normal range of pulse data; the motion state determination module includes: A first comparison result obtaining module is used to compare the motor feedback data with the normal range of the motor data to obtain a first comparison result; A second comparison result obtaining module is used to compare the encoder feedback data with the normal range of the pulse data to obtain a second comparison result; A normal motion determination module, configured to determine that the motion state corresponding to the manipulator is normal motion when both the first comparison result and the second comparison result are hits; The motion abnormality determination module is used to determine that when there is a mismatch between the first comparison result and the second comparison result, the motion state corresponding to the manipulator is a motion abnormality.

8. An electronic device, characterized in that: It comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for preventing misoperation of an optical fiber remote self-healing system as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the method for preventing misoperation of an optical fiber remote self-healing system as described in any one of claims 1 to 6 is implemented.

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