Granted Patent B2

US 12,487,149 · App. 18/955,501 · Granted Dec 2, 2025

Inventors: Xiantao Peng (Zhejiang, CN); Peng Wang (Zhejiang, CN); Yibo Qiu (Zhejiang, CN); Dake Li (Zhejiang, CN); Feng Xu (Zhejiang, CN); Junliang Jin (Zhejiang, CN)

Assignee: ZHEJIANG HENGYI PETROCHEMICAL CO., LTD.

G01M99/005G05D1/2285G05D1/686G05D1/689G05D2105/28G05D2105/89

Abstract

Claims (81)

1 . A control method for drone inspection of a chemical production plant, comprising:

determining a first drone for performing a preset inspection task in a target scene, wherein the first drone is responsible for the preset inspection task of the chemical production plant;

obtaining data of a target object collected by the first drone in the target scene;

determining a state of the target object in the target scene based on the data of the target object;

outputting prompt information matching a preset state in the target scene in a case of the state represents that the target object is in the preset state of the target scene;

receiving an item demand sent by the first drone; and

dispatching a second drone for the first drone based on the item demand, so that the second drone transports a target item to an inspector corresponding to the first drone based on the item demand;

wherein the preset inspection task comprises:

in a case of the target scene belongs to an active inspection scene and the target object is a device, the preset inspection task is a routine inspection task or a sampling inspection task, wherein the routine inspection task is pre-set, and the sampling inspection task is randomly generated;

in a case of the target scene belongs to an active inspection scene and the target object is a person, the preset inspection task is a routine inspection task or a sampling inspection task;

in a case of the target scene belongs to a passive inspection scene and the target object is a device, the preset inspection task is a first dedicated inspection task, and the first dedicated inspection task is set based on an attribute of the device;

in a case of the target scene belongs to a passive inspection scene and the target object is a person, the preset inspection task is a second dedicated inspection task, and the second dedicated inspection task is generated based on a personnel requirement.

2 . The method of claim 1 , wherein the determining a first drone for performing a preset inspection task in a target scene, comprises:

in response to receiving a follow instruction forwarded by a drone, determining the drone that forwards the follow instruction as the first drone, wherein the follow instruction is an instruction sent by an inspector to the drone that sends the follow instruction and is used to instruct the drone to follow the inspector to work, and the follow instruction comprises information characterizing the preset inspection task.

3 . The method of claim 1 , wherein the determining a first drone for performing a preset inspection task in a target scene, comprises:

in response to receiving an operation requirement sent by a terminal, determining the first drone for performing the preset inspection task in the target scene for the terminal from candidate drones based on the operation requirement and state information of the candidate drones, wherein the operation requirement comprises information characterizing the preset inspection task.

4 . The method of claim 1 , wherein the determining a first drone for performing a preset inspection task in a target scene, comprises:

determining the first drone for performing the preset inspection task in the target scene from candidate drones according to state information of the candidate drones in combination with an inspection cycle.

5 . The method of claim 1 , wherein the preset state comprises a device abnormal state, and the target object comprises a target device;

wherein the outputting prompt information matching a preset state in the target scene in the case of the state represents that the target object is in the preset state of the target scene, comprises:

outputting prompt information matching the device abnormal state in the target scene in a case of the state represents that the target device is in the device abnormal state of the target scene.

6 . The method of claim 1 , wherein the preset state comprises a person abnormal state, and the target object comprises a target person;

wherein the outputting prompt information matching a preset state in the target scene in the case of the state represents that the target object is in the preset state of the target scene, comprises:

outputting prompt information matching the person abnormal state in the target scene in a case of the state represents that the target person is in the person abnormal state of the target scene.

7 . The method of claim 1 , wherein the determining a state of the target object in the target scene based on the data of the target object, comprises:

obtaining a known corresponding relationship, wherein the known corresponding relationship at least comprises a relationship between each state of the target object and corresponding interval data; and

analyzing the state corresponding to the data of the target object in the target scene based on the known corresponding relationship.

8 . The method of claim 7 , further comprising:

establishing a corresponding relationship between the data of the target object and the state of the target object in the target scene; and

updating the known corresponding relationship based on the corresponding relationship.

9 . The method of claim 1 , wherein the determining a state of the target object in the target scene based on the data of the target object, comprises:

inputting the data of the target object in the target scene into a state analysis model, wherein the state analysis model is obtained by training based on a known corresponding relationship and is used to predict the state of the target object in the target scene; and

obtaining the state of the target object in the target scene output by the state analysis model.

10 . The method of claim 9 , further comprising:

establishing a corresponding relationship between the data of the target object and the state of the target object in the target scene; and

updating the known corresponding relationship based on the corresponding relationship.

11 . The method of claim 1 , wherein the first drone is provided with a first voice recognition model, the target object comprises an inspector, and the method further comprises:

sending the item demand to a system background if the item demand of the inspector is recognized by the first voice recognition model in a case of the first drone receives voice of the inspector.

12 . The method of claim 1 , wherein the first drone is provided with a second voice recognition model, the target object comprises a target device, and the method further comprises:

inputting collected sound of the target device into the second voice recognition model in a process of performing the preset inspection task by the first drone, and sending the item demand to a system background if the item demand matching a fault of the target device is analyzed by the second voice recognition model.

13 . The method of claim 1 , further comprising:

determining an inspection path for the first drone to perform the preset inspection task; and

sending the inspection path to the first drone, so that the first drone performs the preset inspection task based on the inspection path.

14 . The method of claim 1 , wherein the target object comprises an inspector, and the method further comprises:

receiving a control instruction of the inspector sent by the first drone and an execution record of the first drone for the control instruction, wherein the control instruction is received in a process of performing the preset inspection task by the first drone, and the first drone recognizes that the inspector has control authority to send the control instruction; and

storing the control instruction of the inspector and the execution record corresponding to the control instruction.

15 . An electronic device, comprising:

at least one processor; and

a memory connected in communication with the at least one processor;

wherein the memory stores an instruction executable by the at least one processor, and the instruction, when executed by the at least one processor, enables the at least one processor to execute:

determining a first drone for performing a preset inspection task in a target scene, wherein the first drone is responsible for the preset inspection task of the chemical production plant;

obtaining data of a target object collected by the first drone in the target scene;

determining a state of the target object in the target scene based on the data of the target object;

outputting prompt information matching a preset state in the target scene in a case of the state represents that the target object is in the preset state of the target scene;

receiving an item demand sent by the first drone; and

dispatching a second drone for the first drone based on the item demand, so that the second drone transports a target item to an inspector corresponding to the first drone based on the item demand;

wherein the preset inspection task comprises:

in a case of the target scene belongs to an active inspection scene and the target object is a device, the preset inspection task is a routine inspection task or a sampling inspection task, wherein the routine inspection task is pre-set, and the sampling inspection task is randomly generated;

in a case of the target scene belongs to an active inspection scene and the target object is a person, the preset inspection task is a routine inspection task or a sampling inspection task;

in a case of the target scene belongs to a passive inspection scene and the target object is a device, the preset inspection task is a first dedicated inspection task, and the first dedicated inspection task is set based on an attribute of the device;

in a case of the target scene belongs to a passive inspection scene and the target object is a person, the preset inspection task is a second dedicated inspection task, and the second dedicated inspection task is generated based on a personnel requirement.

16 . The electronic device of claim 15 , wherein the determining a first drone for performing a preset inspection task in a target scene, comprises:

in response to receiving a follow instruction forwarded by a drone, determining the drone that forwards the follow instruction as the first drone, wherein the follow instruction is an instruction sent by an inspector to the drone that sends the follow instruction and is used to instruct the drone to follow the inspector to work, and the follow instruction comprises information characterizing the preset inspection task.

17 . The electronic device of claim 15 , wherein the determining a first drone for performing a preset inspection task in a target scene, comprises:

in response to receiving an operation requirement sent by a terminal, determining the first drone for performing the preset inspection task in the target scene for the terminal from candidate drones based on the operation requirement and state information of the candidate drones, wherein the operation requirement comprises information characterizing the preset inspection task.

18 . A non-transitory computer-readable storage medium storing a computer instruction thereon, wherein the computer instruction is used to cause a computer to execute:

determining a first drone for performing a preset inspection task in a target scene, wherein the first drone is responsible for the preset inspection task of the chemical production plant;

obtaining data of a target object collected by the first drone in the target scene;

determining a state of the target object in the target scene based on the data of the target object;

outputting prompt information matching a preset state in the target scene in a case of the state represents that the target object is in the preset state of the target scene;

receiving an item demand sent by the first drone; and

dispatching a second drone for the first drone based on the item demand, so that the second drone transports a target item to an inspector corresponding to the first drone based on the item demand;

wherein the preset inspection task comprises:

in a case of the target scene belongs to an active inspection scene and the target object is a device, the preset inspection task is a routine inspection task or a sampling inspection task, wherein the routine inspection task is pre-set, and the sampling inspection task is randomly generated;

in a case of the target scene belongs to an active inspection scene and the target object is a person, the preset inspection task is a routine inspection task or a sampling inspection task;

in a case of the target scene belongs to a passive inspection scene and the target object is a device, the preset inspection task is a first dedicated inspection task, and the first dedicated inspection task is set based on an attribute of the device;

in a case of the target scene belongs to a passive inspection scene and the target object is a person, the preset inspection task is a second dedicated inspection task, and the second dedicated inspection task is generated based on a personnel requirement.

19 . The non-transitory computer-readable storage medium of claim 18 , wherein the determining a first drone for performing a preset inspection task in a target scene, comprises:

in response to receiving a follow instruction forwarded by a drone, determining the drone that forwards the follow instruction as the first drone, wherein the follow instruction is an instruction sent by an inspector to the drone that sends the follow instruction and is used to instruct the drone to follow the inspector to work, and the follow instruction comprises information characterizing the preset inspection task.

20 . The electronic device of claim 15 , wherein the determining a first drone for performing a preset inspection task in a target scene, comprises:

determining the first drone for performing the preset inspection task in the target scene from candidate drones according to state information of the candidate drones in combination with an inspection cycle.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (26)