CN112947352A - Method and device for determining fault reason of unmanned equipment - Google Patents

Method and device for determining fault reason of unmanned equipment Download PDF

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Publication number
CN112947352A
CN112947352A CN201911260537.0A CN201911260537A CN112947352A CN 112947352 A CN112947352 A CN 112947352A CN 201911260537 A CN201911260537 A CN 201911260537A CN 112947352 A CN112947352 A CN 112947352A
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motor
state
abnormal
unmanned
range
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CN112947352B (en
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赵智博
王辉武
吴国易
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Guangzhou Xaircraft Technology Co Ltd
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Guangzhou Xaircraft Technology Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0208—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the configuration of the monitoring system
    • G05B23/0213—Modular or universal configuration of the monitoring system, e.g. monitoring system having modules that may be combined to build monitoring program; monitoring system that can be applied to legacy systems; adaptable monitoring system; using different communication protocols
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/24—Pc safety
    • G05B2219/24065—Real time diagnostics

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  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Testing And Monitoring For Control Systems (AREA)

Abstract

The application discloses a method and a device for determining a fault reason of unmanned equipment. Wherein, the method comprises the following steps: detecting a rotating speed value of a motor of the unmanned equipment; if the rotating speed value is detected to be within a first preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; if the actual operation attitude data is detected to be abnormal, detecting the attitude angle of the unmanned equipment to obtain a detection result; and determining the reason of the failure of the unmanned equipment according to the detection result. This application has been solved owing to adopt artifical analysis unmanned aerial vehicle's flight control log data, judges unmanned aerial vehicle's accident reason, and the great accident reason that causes of unable timely rapid analysis play unmanned aerial vehicle of task volume greatly influences customer's operating efficiency's technical problem.

Description

Method and device for determining fault reason of unmanned equipment
Technical Field
The application relates to the field of unmanned equipment, in particular to a method and a device for determining a fault reason of the unmanned equipment.
Background
In the current stage, the unmanned aerial vehicle flight accident analysis method is to manually analyze data recorded in a flight control log of the unmanned aerial vehicle through software so as to judge the reason of the failure of the unmanned aerial vehicle. The analysis method has high requirement on knowledge and skills of analysts, is low in analysis timeliness, and can cause that seventy or nearly hundreds of flight accident data often appear in busy seasons of farming and need manual processing.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a method and a device for determining failure reasons of unmanned aerial vehicle equipment, and the technical problem that due to the fact that flight control log data of an unmanned aerial vehicle are analyzed manually, accident reasons of the unmanned aerial vehicle are judged, the accident reasons of the unmanned aerial vehicle cannot be analyzed rapidly in time due to the fact that the task quantity is large, and the operation efficiency of customers is greatly influenced is solved.
According to an aspect of an embodiment of the present application, there is provided a method for determining a cause of a failure of an unmanned aerial vehicle, including: detecting a rotating speed value of a motor of the unmanned equipment; if the rotating speed value is detected to be within a first preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; if the actual operation attitude data is detected to be abnormal, detecting the attitude angle of the unmanned equipment to obtain a detection result; and determining the reason of the failure of the unmanned equipment according to the detection result.
Optionally, detecting whether the actual operation posture data of the unmanned device is abnormal includes: judging whether the actual operation attitude of the unmanned equipment is fitted with the control attitude; if the actual operation attitude is fitted with the control attitude, determining that the actual operation attitude data of the unmanned equipment is normal; and if the actual operation attitude data is not matched with the control attitude, determining that the actual operation attitude data of the unmanned equipment is abnormal.
Optionally, before detecting the attitude angle of the unmanned device, the method further comprises: determining the initial occurrence time when the actual operation attitude and the control attitude curve are not fitted; detecting whether the unmanned equipment vibrates or not at the initial occurrence moment; and under the condition that the detection result is negative, triggering to detect the attitude angle of the unmanned equipment.
Optionally, determining the cause of the failure of the unmanned aerial vehicle according to the detection result includes: and if the attitude angle is detected to be within a second preset range, determining that the reason that the unmanned equipment fails is that the unmanned equipment does not operate according to the control attitude curve due to the abnormal motor, and fitting and generating the control attitude curve by corresponding control attitude data at different moments.
Optionally, the attitude angle includes at least one of: the pitch angle of the drone, the roll angle of the drone.
Optionally, the first preset range includes: the motor control method comprises the following steps that a first preset sub-range corresponds to a state that a motor is in a restarting state; the second preset sub-range corresponds to a state that the motor is in a no-signal state; a third preset sub-range, wherein the third preset sub-range corresponds to a motor in a locked-rotor state; a fourth preset sub-range, wherein the fourth preset sub-range corresponds to a state that the motor is stopped; and the fifth preset sub-range corresponds to the state that the motor is in an idle state.
Alternatively, if the motor is detected to be in at least one of the following states: locked-rotor state, stopped state and idle state, the above-mentioned method still includes: acquiring image information when the unmanned equipment fails; and determining the reason of the failure of the unmanned equipment according to the image information.
According to another aspect of the embodiments of the present application, there is also provided a method of predicting failure of an unmanned aerial vehicle, including: detecting a rotating speed value of a motor of the unmanned equipment; if the rotating speed value is detected to be within the preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; and if the actual operation attitude data is detected to be abnormal, sending first alarm information, wherein the first alarm information is used for representing that the actual operation attitude data is abnormal due to the abnormal state of the motor.
Optionally, the preset range includes: the motor control method comprises the following steps that a first preset sub-range corresponds to a state that a motor is in a restarting state; the second preset sub-range corresponds to a state that the motor is in a no-signal state; a third preset sub-range, wherein the third preset sub-range corresponds to a motor in a locked-rotor state; a fourth preset sub-range, wherein the fourth preset sub-range corresponds to a state that the motor is stopped; and the fifth preset sub-range corresponds to the state that the motor is in an idle state.
Optionally, detecting whether the actual operation posture data of the unmanned device is abnormal further includes: and if the actual operation attitude data is detected to be normal, sending second warning information, wherein the second warning information is used for representing that the unmanned equipment is in at least one of the following states: a restart state, a no signal state, a locked rotor state, a stop state, and an idle state.
According to another aspect of the embodiments of the present application, there is also provided an apparatus for determining a cause of a failure of an unmanned aerial vehicle, including: the first detection module is used for detecting the rotating speed value of a motor of the unmanned equipment; the second detection module is used for detecting whether actual operation posture data of the unmanned equipment is abnormal or not under the condition that the rotating speed value is detected to be within the first preset range; the third detection module is used for detecting the attitude angle of the unmanned equipment under the condition of detecting that actual operation attitude data is abnormal to obtain a detection result; and the determining module is used for determining the reason of the failure of the unmanned equipment according to the detection result.
According to still another aspect of the embodiments of the present application, there is also provided an apparatus for predicting failure of an unmanned aerial vehicle, including: the fourth detection module is used for detecting the rotating speed value of the motor of the unmanned equipment; the fifth detection module is used for detecting whether the actual operation posture data of the unmanned equipment is abnormal or not under the condition that the rotating speed value is detected to be within the preset range; and the control module is used for sending first warning information under the condition that the actual operation attitude data is detected to be abnormal, wherein the first warning information is used for representing that the actual operation attitude data of the unmanned equipment is abnormal due to the abnormal state of the motor.
According to still another aspect of an embodiment of the present application, there is also provided a storage medium including a stored program, wherein the program when executed controls an apparatus on which the storage medium is located to perform the above method of determining a cause of failure of an unmanned aerial vehicle or the above method of predicting failure of an unmanned aerial vehicle.
According to yet another aspect of the embodiments of the present application, there is also provided a processor for executing a program, where the program when executed performs the above method of determining a cause of failure of an unmanned aerial device or the above method of predicting failure of an unmanned aerial device.
According to yet another aspect of the embodiments of the present application, there is also provided a computer apparatus, including a memory and a processor, wherein the memory stores a computer program; the processor, when executing the computer program, implements the above method of determining the cause of a malfunction of an unmanned aerial vehicle or the above method of predicting a malfunction of an unmanned aerial vehicle.
In the embodiment of the application, the rotating speed value of a motor of the unmanned equipment is detected; if the rotating speed value is detected to be within a first preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; if the actual operation attitude data is detected to be abnormal, detecting the attitude angle of the unmanned equipment to obtain a detection result; the mode of the reason of unmanned aerial vehicle equipment trouble takes place is confirmed according to the testing result, carry out automatic analysis to the data of unmanned aerial vehicle's flight control log record through software, judge the reason that unmanned aerial vehicle breaks down, thereby the accident reason of unmanned aerial vehicle has been realized analyzing out in time fast, the technological effect of user's operating efficiency has been improved, and then the flight control log data owing to adopt artifical analysis unmanned aerial vehicle has been solved, judge unmanned aerial vehicle's accident reason, the great accident reason that can't analyze out unmanned aerial vehicle fast in time that causes of task volume, the technical problem of very big influence customer's operating efficiency.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart of a method of determining a cause of a malfunction in an unmanned aerial vehicle according to an embodiment of the application;
FIG. 2 is a flow chart of a method of predicting failure of an unmanned aerial device according to an embodiment of the present application;
FIG. 3 is a block diagram of an apparatus for determining a cause of a malfunction of an unmanned aerial vehicle according to an embodiment of the present application;
FIG. 4 is a block diagram of an apparatus for predicting failure of an unmanned aerial device according to an embodiment of the present application;
fig. 5 is a block diagram of a computer apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present application, there is provided an embodiment of a method for determining a cause of a malfunction in an unmanned aerial vehicle, wherein the steps illustrated in the flowchart of the figure may be performed in a computer system such as a set of computer-executable instructions, and wherein although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Fig. 1 is a flowchart of a method for determining a cause of a failure of an unmanned aerial vehicle according to an embodiment of the application, as shown in fig. 1, the method including the steps of:
and step S102, detecting a rotating speed value of a motor of the unmanned equipment.
The flight control log of the unmanned aerial vehicle records all flight related data of the unmanned aerial vehicle once every a preset period of time, and one frame of data is obtained once every recording, so that the automatic analysis software analyzes the flight log by adopting a frame-by-frame analysis method from the first frame to the last frame of the log until the accident reason is analyzed.
In the control logic of the flight control system of the unmanned aerial vehicle, the flight control system changes the flight attitude of the unmanned aerial vehicle by controlling the rotating speed of each motor, then controls the attitude to change the speed of the unmanned aerial vehicle, and finally changes the position of the unmanned aerial vehicle by controlling the speed of the unmanned aerial vehicle. When the motor of the unmanned aerial vehicle is abnormal, the attitude, the speed and the position of the unmanned aerial vehicle are also connected and abnormal, so when analyzing each frame of data of the log, the relevant parameters of the motor link of the aircraft are analyzed firstly, then the relevant parameters of the attitude ring, the relevant parameters of the speed ring and finally the relevant parameters of the position ring. Step S102 first analyzes the rotation speed value of the motor of the drone described in the flight control log.
And step S104, if the rotating speed value is detected to be within the first preset range, detecting whether the actual operation posture data of the unmanned equipment is abnormal.
According to an optional embodiment of the present application, the actual operation attitude data is used to characterize attitude information of the drone during an actual flight process, including but not limited to data such as a flight direction of the drone.
And S106, if the actual operation attitude data is detected to be abnormal, detecting the attitude angle of the unmanned equipment to obtain a detection result.
And step S108, determining the reason of the failure of the unmanned equipment according to the detection result.
Through the steps, the data recorded in the flight control log of the unmanned aerial vehicle is automatically analyzed through software, and the reason that the unmanned aerial vehicle breaks down is judged, so that the accident reason of the unmanned aerial vehicle is quickly and timely analyzed, and the technical effect of the operating efficiency of a user is improved.
According to an alternative embodiment of the present application, step S106 is implemented by: judging whether the actual operation attitude of the unmanned equipment is fitted with the control attitude; if the actual operation attitude is fitted with the control attitude, determining that the actual operation attitude data of the unmanned equipment is normal; and if the actual operation posture is not matched with the pre-control posture, determining that the actual operation posture data of the unmanned equipment is abnormal.
According to an optional embodiment of the present application, the control attitude refers to a control attitude automatically generated by a control system of the unmanned aerial vehicle according to an algorithm, and the unmanned aerial vehicle operates according to the automatically generated control attitude during normal flight. Judging whether the actual operation attitude and the control attitude are fitted or not mainly comprises the following steps: and judging whether the actual pitch angle and roll angle of the unmanned aerial vehicle are fitted with the target pitch angle and target roll angle automatically generated by the control system.
Whether the actual pitch angle and the roll angle of the unmanned aerial vehicle are fitted with the target pitch angle and the target roll angle automatically generated by the control system is judged by judging whether the difference value between the actual pitch angle and the target pitch angle is within a preset range or not and whether the difference value between the actual roll angle and the target roll angle is within the preset range or not. If the difference value is within the preset range, fitting the actual pitch angle and roll angle of the unmanned aerial vehicle with the target pitch angle and target roll angle automatically generated by the control system; otherwise, no fit is made. It should be noted that the preset range is generally set to be within a range of-3.6 degrees to 3.6 degrees, wherein the value of 3.6 can be set to any number within a range of 3 to 4.
In an alternative embodiment of the present application, before performing step S106, an initial occurrence time at which the actual operation attitude does not fit the control attitude is determined; detecting whether the unmanned equipment vibrates or not at the initial occurrence moment; and under the condition that the detection result is negative, triggering to detect the attitude angle of the unmanned equipment.
The overall judgment process of the motor state comprises the following steps: the motor state refers to the state value that unmanned aerial vehicle electricity accent produced in the course of the work, and this value refers to electricity accent operating condition. In the operation process of the unmanned aerial vehicle, various faults can occur to the motor. The reason why the motor breaks down may be caused by the unmanned aerial vehicle itself (for example, the electric tuning is restarted, no signal and the like), and may also be caused by the external environment (for example, the phenomena of locked rotor, stop and the like caused by hitting an obstacle). Therefore, we need to distinguish the cause of the motor failure and the resulting effect.
When the motor breaks down due to self reasons, the flight attitude of the airplane is separated from the control attitude, the airplane can be automatically shut down when the actual attitude angle of the airplane in the air exceeds the flight control protection angle, then the airplane can touch the ground and explode, and the accelerometer does not detect the vibration of the airplane body when touching the ground. When the actual attitude angle of the aircraft in the air does not exceed the flight control protection angle and the aircraft touches down, the accelerometer of the aircraft detects a large fuselage shock during the touchdown.
When the state of the motor of the airplane is abnormal due to external environment, such as an obstacle is hit or the airplane touches the ground, the accelerometer of the airplane can detect a large fuselage vibration. Therefore, whether the accelerometer detects the self-vibration serves as a main judgment basis for judging whether the motor fault of the airplane occurs per se or is caused by the external environment.
Therefore, whether the reason for detecting the motor of the unmanned aerial vehicle to break down is caused by the motor or an external reason, whether the fuselage of the unmanned aerial vehicle shakes or not needs to be judged at the moment that the actual operation posture of the unmanned aerial vehicle does not fit with the control posture, if the fuselage of the unmanned aerial vehicle does not shake, the reason for explaining the motor to break down is caused by the motor reason, and then the posture angle of the unmanned aerial vehicle is further detected.
According to an alternative embodiment of the application, the attitude angles comprise pitch and roll angles of the drone. The pitch angle refers to the included angle between the horizontal axis of the coordinate system of the machine body and the horizontal plane. The pitch angle is positive when the X-axis of the machine body coordinate system is above the plane of the inertial coordinate system XOY, and negative otherwise. The roll represents the rotation of carrier around the axis of ordinates, and it is positive to rotate clockwise around the axis of ordinates axial, and as the name suggests, unmanned aerial vehicle's roll axis is the contained angle between unmanned aerial vehicle cross axle and the level line.
In some embodiments of the present application, step S108 is implemented by: and if the attitude angle is detected to be within a second preset range, determining that the reason that the unmanned equipment fails is that the unmanned equipment does not operate according to the control attitude curve due to the abnormal motor, and fitting and generating the control attitude curve by corresponding control attitude data at different moments.
According to an optional embodiment of the application, if the attitude angle of the unmanned aerial vehicle is detected to be greater than 48 degrees or less than-48 degrees, it is determined that the reason why the unmanned aerial vehicle breaks down is that the flight attitude of the unmanned aerial vehicle is abnormal due to the fact that the motor of the unmanned aerial vehicle is abnormal.
According to an alternative embodiment of the present application, the first preset range comprises: the motor control method comprises the following steps that a first preset sub-range corresponds to a state that a motor is in a restarting state; the second preset sub-range corresponds to a state that the motor is in a no-signal state; a third preset sub-range, wherein the third preset sub-range corresponds to a motor in a locked-rotor state; a fourth preset sub-range, wherein the fourth preset sub-range corresponds to a state that the motor is stopped; and the fifth preset sub-range corresponds to the state that the motor is in an idle state.
In specific implementation, the rotating speed value of the motor is in the range of 3xx-38xx r/s, which indicates that the motor is in a normal running state. The term "x" is used herein to mean a flag, which ranges from 0 to 9, i.e., the rotation speed of the motor is within 300-.
The first preset sub-range, the second preset sub-range, the third preset sub-range, the fourth preset sub-range and the fifth preset sub-range respectively correspond to five abnormal states of the motor, namely a restarting state, a no-signal state, a locked rotor state, a stopping state and an idling state. When the motor is in a restarting state, the corresponding rotating speed value of the motor is 19xxx (19000 and 19999 revolutions per second); when the motor is in a no-signal state, the corresponding rotating speed value of the motor is 18xxx (18000 and 18999 rpm); when the motor is in a locked-rotor state, the corresponding rotating speed value of the motor is 17xxx (17000-; when the motor is in a stop state, the corresponding rotating speed value of the motor is 0; when the motor is in an idle state, the corresponding rotating speed value of the motor is 4xxx (4000 and 4999 revolutions per second). The numerical range of the rotation speed value of the motor corresponding to the abnormal state of the five motors is only one flag bit specified artificially, and does not refer to the actual rotation speed value of the motor when the motor is in the corresponding abnormal state.
In some optional embodiments of the present application, if the motor is detected to be in at least one of the following states: in the locked-rotor state, the stopped state and the idle state, image information when the unmanned equipment fails is required to be acquired; and determining the reason of the failure of the unmanned equipment according to the image information.
The motor is in restart state and no signal state and is the electronic circuit problem, and the motor is in the stall state, and the hardware problem that stopped state or idle running state probably caused that unmanned aerial vehicle takes place to strike, motor base pine take off or oar press from both sides fracture etc. so need combine the scene photo that unmanned aerial vehicle breaks down to further judge the reason that breaks down.
Fig. 2 is a flowchart of a method of predicting failure of an unmanned aerial device according to an embodiment of the application, as shown in fig. 2, the method including:
step S202, detecting a rotating speed value of a motor of the unmanned device.
And step S204, if the rotating speed value is detected to be within the preset range, detecting whether the actual operation posture data of the unmanned equipment is abnormal.
According to an optional embodiment of the present application, the actual operation attitude data is used to characterize attitude information of the drone during an actual flight process, including but not limited to data such as a flight direction of the drone.
Step S206, if the actual operation attitude data is detected to be abnormal, first warning information is sent, and the first warning information is used for representing that the actual operation attitude data is abnormal due to the abnormal state of the motor.
The flight control log of the unmanned aerial vehicle records all flight related data of the unmanned aerial vehicle once every a preset time, and one frame of data is obtained once every recording. In the control logic of the flight control system of the unmanned aerial vehicle, the flight control system changes the flight attitude of the unmanned aerial vehicle by controlling the rotating speed of each motor, then controls the attitude to change the speed of the unmanned aerial vehicle, and finally changes the position of the unmanned aerial vehicle by controlling the speed of the unmanned aerial vehicle. When the motor of the unmanned aerial vehicle is abnormal, the attitude, the speed and the position of the unmanned aerial vehicle are also connected and abnormal, so when analyzing each frame of data of the log, the relevant parameters of the motor link of the aircraft are analyzed firstly, then the relevant parameters of the attitude ring, the relevant parameters of the speed ring and finally the relevant parameters of the position ring.
When the rotating speed value of the motor of the unmanned aerial vehicle is detected to be in an abnormal range, the motor of the unmanned aerial vehicle is in an abnormal running state. And then detecting whether the operation attitude data of the unmanned aerial vehicle is abnormal. If the actual operation attitude is fitted with the control attitude, determining that the actual operation attitude data of the unmanned equipment is normal; and if the actual operation posture is not matched with the preset control posture, determining that the actual operation posture data of the unmanned equipment is abnormal. When detecting out that there is the anomaly in unmanned aerial vehicle's actual motion gesture data, send alarm information, suggestion control unmanned aerial vehicle is returned as early as possible and navigated to avoid causing the bigger accidents of losses such as unmanned aerial vehicle crash.
According to an alternative embodiment of the present application, the preset range includes: the motor control method comprises the following steps that a first preset sub-range corresponds to a state that a motor is in a restarting state; the second preset sub-range corresponds to a state that the motor is in a no-signal state; a third preset sub-range, wherein the third preset sub-range corresponds to a motor in a locked-rotor state; a fourth preset sub-range, wherein the fourth preset sub-range corresponds to a state that the motor is stopped; and the fifth preset sub-range corresponds to the state that the motor is in an idle state.
In specific implementation, the rotating speed value of the motor is in the range of 3xx-38xx r/s, which indicates that the motor is in a normal running state. The term "x" is used herein to mean a flag, which ranges from 0 to 9, i.e., the rotation speed of the motor is within 300-.
The first preset sub-range, the second preset sub-range, the third preset sub-range, the fourth preset sub-range and the fifth preset sub-range respectively correspond to five abnormal states of the motor, namely a restarting state, a no-signal state, a locked rotor state, a stopping state and an idling state. When the motor is in a restarting state, the corresponding rotating speed value of the motor is 19xxx (19000 and 19999 revolutions per second); when the motor is in a no-signal state, the corresponding rotating speed value of the motor is 18xxx (18000 and 18999 rpm); when the motor is in a locked-rotor state, the corresponding rotating speed value of the motor is 17xxx (17000-; when the motor is in a stop state, the corresponding rotating speed value of the motor is 0; when the motor is in an idle number state, the corresponding rotating speed value of the motor is 4xxx (4000 and 4999 rpm). The numerical range of the rotation speed value of the motor corresponding to the abnormal state of the five motors is only one flag bit specified artificially, and does not refer to the actual rotation speed value of the motor when the motor is in the corresponding abnormal state.
According to an optional embodiment of the application, when step S204 is executed, if it is detected that the actual operation posture data is normal, second warning information is issued, where the second warning information is used to indicate that the unmanned equipment is in at least one of the following states: a restart state, a no signal state, a locked rotor state, a stop state, and an idle state.
If the motor of the unmanned aerial vehicle is detected to be in an abnormal operation state, but the actual operation attitude data of the unmanned aerial vehicle is normal, warning information also needs to be sent, because the operation attitude of the unmanned aerial vehicle is also in the abnormal operation state which is the same as that of the motor at the moment, for example, the motor is in a restarting operation state, the unmanned aerial vehicle can also have an operation state which is continuously restarted at the moment, a controller of the unmanned aerial vehicle is reminded to pay attention to the operation state of the motor in real time at the moment, and if the motor can be recovered to the normal operation state in a short time, the unmanned aerial; if the motor is always in the abnormal operation state of restarting within the preset time, the unmanned aerial vehicle needs to be controlled to return to the air for maintenance, if the unmanned aerial vehicle is controlled to continue to operate, the operation attitude data of the unmanned aerial vehicle, which is caused by abnormal restarting of the motor, is abnormal, and then the faults of crash and the like occur.
By the aid of the fault prediction method, the unmanned aerial vehicle can be controlled to return to the air for maintenance in time in the early stage of failure of the unmanned aerial vehicle, and faults such as crash or explosion and the like of the unmanned aerial vehicle are avoided in the operation process.
Fig. 3 is a block diagram of an apparatus for determining a cause of a malfunction of an unmanned aerial vehicle according to an embodiment of the present application, as shown in fig. 3, the apparatus including:
the first detection module 30 is used for detecting the rotating speed value of the motor of the unmanned equipment.
The flight control log of the unmanned aerial vehicle records all flight related data of the unmanned aerial vehicle once every a preset period of time, and one frame of data is obtained once every recording, so that the automatic analysis software analyzes the flight log by adopting a frame-by-frame analysis method from the first frame to the last frame of the log until the accident reason is analyzed.
In the control logic of the flight control system of the unmanned aerial vehicle, the flight control system changes the flight attitude of the unmanned aerial vehicle by controlling the rotating speed of each motor, then controls the attitude to change the speed of the unmanned aerial vehicle, and finally changes the position of the unmanned aerial vehicle by controlling the speed of the unmanned aerial vehicle. When the motor of the unmanned aerial vehicle is abnormal, the attitude, the speed and the position of the unmanned aerial vehicle are also connected and abnormal, so when analyzing each frame of data of the log, the relevant parameters of the motor link of the aircraft are analyzed firstly, then the relevant parameters of the attitude ring, the relevant parameters of the speed ring and finally the relevant parameters of the position ring. Step S102 first analyzes the rotation speed value of the motor of the drone described in the flight control log.
And the second detection module 32 is used for detecting whether the actual operation posture data of the unmanned equipment is abnormal or not under the condition that the rotating speed value is detected to be in the first preset range.
According to an optional embodiment of the present application, the actual operation attitude data is used to characterize attitude information of the drone during an actual flight process, including but not limited to data such as a flight direction of the drone.
And the third detection module 34 is configured to detect the attitude angle of the unmanned aerial vehicle device to obtain a detection result when the actual operation attitude data is detected to be abnormal.
And the determining module 36 is used for determining the reason of the failure of the unmanned equipment according to the detection result.
According to an optional embodiment of the present application, the second detecting module 32 is further configured to determine whether the actual operation posture of the unmanned aerial vehicle is fitted to the control posture; determining that actual operation attitude data of the unmanned equipment is normal under the condition that the actual operation attitude is fitted with the control attitude; and determining that the actual operation attitude data of the unmanned equipment is abnormal under the condition that the actual operation attitude is not matched with the control attitude.
According to an alternative embodiment of the present application, the apparatus is further configured to determine an initial occurrence time at which the actual operating attitude does not fit the control attitude curve; detecting whether the unmanned equipment vibrates or not at the initial occurrence moment; and under the condition that the detection result is negative, triggering to detect the attitude angle of the unmanned equipment.
In some embodiments of the present application, the determining module 36 is further configured to determine, when it is detected that the attitude angle is within the second preset range, that the cause of the malfunction of the unmanned aerial vehicle is that the unmanned aerial vehicle does not operate according to a control attitude curve due to an abnormal motor, and the control attitude curve is generated by fitting control attitude data corresponding to different times.
It should be noted that, reference may be made to the description related to the embodiment shown in fig. 1 for a preferred implementation of the embodiment shown in fig. 3, and details are not described here again.
Fig. 4 is a block diagram of an apparatus for predicting failure of an unmanned aerial vehicle according to an embodiment of the present application, as shown in fig. 4, the apparatus including:
and the fourth detection module 40 is used for detecting the rotating speed value of the motor of the unmanned equipment.
And the fifth detection module 42 is configured to detect whether actual operation posture data of the unmanned aerial vehicle is abnormal or not under the condition that the detected rotation speed value is within the preset range.
And the control module 44 is configured to send out first warning information when the actual operation posture data is detected to be abnormal, where the first warning information is used to indicate that the actual operation posture data of the unmanned aerial vehicle is abnormal due to the abnormal state of the motor.
It should be noted that, reference may be made to the description related to the embodiment shown in fig. 2 for a preferred implementation of the embodiment shown in fig. 4, and details are not described here again.
According to an embodiment of the application, a storage medium is further provided, and the storage medium comprises a stored program, and the program is used for controlling a device where the storage medium is located to execute the above method for determining the cause of the failure of the unmanned equipment or the above method for predicting the failure of the unmanned equipment.
The storage medium stores a program for executing the following functions: detecting a rotating speed value of a motor of the unmanned equipment; if the rotating speed value is detected to be within a first preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; if the actual operation attitude data is detected to be abnormal, detecting the attitude angle of the unmanned equipment to obtain a detection result; and determining the reason of the failure of the unmanned equipment according to the detection result. Or
A program that performs the following functions is stored: detecting a rotating speed value of a motor of the unmanned equipment; if the rotating speed value is detected to be within the preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; and if the actual operation attitude data is detected to be abnormal, sending first alarm information, wherein the first alarm information is used for representing that the actual operation attitude data is abnormal due to the abnormal state of the motor.
The embodiment of the application also provides a processor which is used for running the program, wherein the program runs to execute the above method for determining the cause of the failure of the unmanned equipment or the above method for predicting the failure of the unmanned equipment.
The processor is used for running a program for executing the following functions: detecting a rotating speed value of a motor of the unmanned equipment; if the rotating speed value is detected to be within a first preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; if the actual operation attitude data is detected to be abnormal, detecting the attitude angle of the unmanned equipment to obtain a detection result; and determining the reason of the failure of the unmanned equipment according to the detection result. Or
Running a program that performs the following functions: detecting a rotating speed value of a motor of the unmanned equipment; if the rotating speed value is detected to be within the preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; and if the actual operation attitude data is detected to be abnormal, sending first alarm information, wherein the first alarm information is used for representing that the actual operation attitude data is abnormal due to the abnormal state of the motor.
Fig. 5 is a block diagram of a computer apparatus according to an embodiment of the present invention. As shown in fig. 5, the computer device 50 may include: one or more processors 502 (only one shown), a memory 504, and a radio frequency module, an audio module, and a display screen.
The memory 504 stores a computer program; the processor 502, when executing the computer program, implements the above method of determining the cause of an unmanned equipment failure or the above method of predicting an unmanned equipment failure.
The processor is configured to execute a computer program that implements the following functions: detecting a rotating speed value of a motor of the unmanned equipment; if the rotating speed value is detected to be within a first preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; if the actual operation attitude data is detected to be abnormal, detecting the attitude angle of the unmanned equipment to obtain a detection result; and determining the reason of the failure of the unmanned equipment according to the detection result. Or
Running a program that performs the following functions: detecting a rotating speed value of a motor of the unmanned equipment; if the rotating speed value is detected to be within the preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not; and if the actual operation attitude data is detected to be abnormal, sending first alarm information, wherein the first alarm information is used for representing that the actual operation attitude data is abnormal due to the abnormal state of the motor.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.

Claims (15)

1. A method of determining a cause of a malfunction in an unmanned aerial vehicle, comprising:
detecting a rotating speed value of a motor of the unmanned equipment;
if the rotating speed value is detected to be within a first preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not;
if the actual operation attitude data is detected to be abnormal, detecting the attitude angle of the unmanned equipment to obtain a detection result;
and determining the reason of the failure of the unmanned equipment according to the detection result.
2. The method of claim 1, wherein detecting whether actual operational attitude data of the unmanned aerial device is abnormal comprises:
judging whether the actual operation attitude of the unmanned equipment is fitted with the control attitude;
if the actual operation posture is fitted with the control posture, determining that the actual operation posture data of the unmanned equipment is normal;
and if the actual operation posture is not matched with the control posture, determining that the actual operation posture data of the unmanned equipment is abnormal.
3. The method of claim 2, wherein prior to detecting the attitude angle of the unmanned device, the method further comprises:
determining an initial occurrence time when the actual operation attitude is not fitted with the control attitude;
detecting whether the unmanned equipment vibrates or not at the initial occurrence moment;
and under the condition that the detection result is negative, triggering and detecting the attitude angle of the unmanned equipment.
4. The method of claim 2, wherein determining a cause of the unmanned aerial device failure based on the detection comprises:
and if the attitude angle is detected to be within a second preset range, determining that the reason that the unmanned equipment fails is that the unmanned equipment does not operate according to a control attitude curve due to the fact that the motor is abnormal, wherein the control attitude curve is generated by fitting the control attitude data corresponding to different moments.
5. The method of any one of claims 1 to 3, wherein the attitude angle comprises at least one of: a pitch angle of the drone, a roll angle of the drone.
6. The method of claim 1, wherein the first preset range comprises:
a first preset sub-range, wherein the first preset sub-range corresponds to the state that the motor is in a restarting state;
a second preset sub-range, wherein the second preset sub-range corresponds to the state that the motor is in a no-signal state;
a third preset sub-range, wherein the third preset sub-range corresponds to the motor in a locked-rotor state;
a fourth preset sub-range, wherein the fourth preset sub-range corresponds to the state that the motor is stopped;
and a fifth preset sub-range, wherein the fifth preset sub-range corresponds to the state that the motor is in an idle state.
7. The method of claim 6, wherein if the motor is detected to be in at least one of: the locked-rotor state, the stopped state, and the idle state, the method further comprising:
acquiring image information when the unmanned equipment fails;
and determining the reason of the failure of the unmanned equipment according to the image information.
8. A method of predicting failure of an unmanned aerial device, comprising:
detecting a rotating speed value of a motor of the unmanned equipment;
if the rotating speed value is detected to be within a preset range, detecting whether actual operation posture data of the unmanned equipment is abnormal or not;
and if the actual operation attitude data is detected to be abnormal, sending first warning information, wherein the first warning information is used for representing that the actual operation attitude data is abnormal due to the abnormal state of the motor.
9. The method of claim 8, wherein the preset range comprises:
a first preset sub-range, wherein the first preset sub-range corresponds to the state that the motor is in a restarting state;
a second preset sub-range, wherein the second preset sub-range corresponds to the state that the motor is in a no-signal state;
a third preset sub-range, wherein the third preset sub-range corresponds to the motor in a locked-rotor state;
a fourth preset sub-range, wherein the fourth preset sub-range corresponds to the state that the motor is stopped;
and a fifth preset sub-range, wherein the fifth preset sub-range corresponds to the state that the motor is in an idle state.
10. The method of claim 9, wherein detecting whether actual operational attitude data of the unmanned aerial device is abnormal further comprises:
and if the actual operation attitude data is detected to be normal, sending second warning information, wherein the second warning information is used for representing that the unmanned equipment is in at least one of the following states: the restart state, the no signal state, the locked rotor state, the stop state, and the idle state.
11. An apparatus for determining a cause of a malfunction in an unmanned aerial vehicle, comprising:
the first detection module is used for detecting the rotating speed value of a motor of the unmanned equipment;
the second detection module is used for detecting whether actual operation attitude data of the unmanned equipment is abnormal or not under the condition that the rotating speed value is detected to be within a first preset range;
the third detection module is used for detecting the attitude angle of the unmanned equipment under the condition that the actual operation attitude data is detected to be abnormal, so as to obtain a detection result;
and the determining module is used for determining the reason of the failure of the unmanned equipment according to the detection result.
12. An apparatus for predicting failure of an unmanned aerial device, comprising:
the fourth detection module is used for detecting the rotating speed value of the motor of the unmanned equipment;
the fifth detection module is used for detecting whether the actual operation posture data of the unmanned equipment is abnormal or not under the condition that the rotating speed value is detected to be within a preset range;
and the control module is used for sending first warning information under the condition that the actual operation attitude data is detected to be abnormal, wherein the first warning information is used for representing that the actual operation attitude data of the unmanned equipment is abnormal due to the abnormal state of the motor.
13. A storage medium comprising a stored program, wherein the program is operable to control a device on which the storage medium is located to perform the method of determining a cause of failure of an unmanned aerial device of any of claims 1 to 7 or the method of predicting failure of an unmanned aerial device of any of claims 8 to 10.
14. A processor, characterized in that the processor is configured to run a program, wherein the program when run performs the method of determining a cause of a malfunction of an unmanned aerial device of any of claims 1 to 7 or the method of predicting a malfunction of an unmanned aerial device of any of claims 8 to 10.
15. A computer device comprising a memory and a processor, wherein the memory stores a computer program; the processor, when executing the computer program, implements the method of determining a cause of an unmanned aerial device fault of any of claims 1 to 7 or the method of predicting an unmanned aerial device fault of any of claims 8 to 10.
CN201911260537.0A 2019-12-10 Method and device for determining fault cause of unmanned equipment Active CN112947352B (en)

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CN107226206A (en) * 2016-03-24 2017-10-03 深圳市创翼睿翔天空科技有限公司 multi-rotor unmanned aerial vehicle safe landing system and method
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