Unmanned aerial vehicle servo system fault diagnosis method and system

Abstract

The invention belongs to the technical field of electric servo control, and relates to an unmanned aerial vehicle servo system fault diagnosis method and system. The method comprises the following steps: acquiring a position error, a control quantity and an actual position feedback value of an unmanned aerial vehicle servo system; obtaining a displacement increment according to the control quantity and a displacement change function; the in-place state mark is obtained according to the position error, so that the position state of the system can be preliminarily classified, and more intuitive information is provided for subsequent position prediction and fault diagnosis; acquiring a position predicted value according to the in-place state mark, the displacement increment and the position correction value; and diagnosing the fault type of the servo system according to the position predicted value, the actual position feedback value and the working current. By acquiring and analyzing information such as the position error, the control quantity, the actual position feedback value and the working current of the system, the fault type of the servo system can be accurately diagnosed, missing detection and false alarm of system faults can be effectively avoided, misjudgment alarm is reduced, and the accuracy and efficiency of fault diagnosis are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of electric servo control and relates to a method and system for diagnosing faults of an unmanned aerial vehicle servo system. Background Art

[0002] Servo system fault diagnosis is critical to improving the flight safety of drones. The servo system is a nonlinear system with strong electromechanical coupling, complex structure and fault correlation, which makes fault diagnosis difficult. How to quickly and effectively determine the system fault location and fault type, and reduce the false alarm rate and missed detection rate, is a major challenge faced by the research on servo system fault diagnosis methods.

[0003] The drone servo system is a position follow-up system that uses a position closed-loop control loop to achieve control stability and dynamic quality. Under normal circumstances, the actual servo position feedback value always closely follows the position set value. If any component in the servo loop (including: controller, driver, motor, mechanical transmission mechanism, position sensor, etc.) fails, the actual servo position feedback value will not follow the position set value, resulting in typical faults such as performance degradation, open loop, stall, and stop.

[0004] The existing fault diagnosis method judges the fault by comparing the error between the position given value and the feedback value, but this method faces the problem of selecting the fault threshold. If a larger fault judgment threshold is selected, the fault cannot be diagnosed in time, causing the actual position of the servo system to deviate seriously from the given value, endangering the safety of the drone; while selecting a smaller fault judgment threshold often leads to misjudgment of the fault during the servo system transition process or when the system is disturbed by noise, triggering the protection mechanism and affecting the completion of the task.

[0005] In summary, the existing servo system fault diagnosis methods have high missed detection rate and false alarm rate. Summary of the invention

[0006] The purpose of the present invention is to provide a method and system for diagnosing faults of a drone servo system, so as to solve the technical problem that the existing servo system fault diagnosis method has a high missed detection rate and false alarm rate. The present invention can effectively avoid missed detection and false alarms of system faults, reduce misjudgment alarms, and improve the accuracy and efficiency of fault diagnosis.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for diagnosing a fault in a drone servo system, comprising the following steps: Obtain the position error, control amount and actual position feedback value of the drone servo system; Obtain displacement increment according to the control amount combined with the displacement change function; Obtain the in-place status mark according to the position error; Correct the estimated position value of the previous cycle according to the in-place status mark and the actual position feedback value to obtain the position correction value; Obtain the estimated position value of the current cycle according to the in-place status mark, displacement increment and position correction value; The fault type of the servo system is diagnosed based on the actual position feedback value, operating current and the position prediction value of the current cycle.

[0008] Furthermore, the position error, control amount and actual position feedback value of the drone servo system are obtained as follows: Get the target position instruction of the servo system; Get the actual position feedback value fed back by the sensor; The position error is obtained by taking the difference between the target position command and the actual position feedback value; The control amount is obtained based on the position error.

[0009] Furthermore, the displacement increment is obtained according to the control amount combined with the displacement change function, as follows: Measuring the motion displacement increment of the servo mechanism under the continuous action of the control quantity and under different load conditions; Obtain displacement characteristic parameters according to the control amount and the motion displacement increment; The displacement increment is obtained based on the control quantity and displacement characteristic parameters combined with the displacement change function.

[0010] Furthermore, the displacement change function is dt=Uk×k, wherein dt is the displacement increment, Uk is the control amount, and k is the displacement characteristic parameter.

[0011] Furthermore, the in-place status mark is obtained according to the position error, as follows: If the position error is less than or equal to the position error threshold, the position control is in place and the in-place state mark is set to "0", otherwise the position control is not in place and the in-place state mark is set to "1".

[0012] Furthermore, the position correction value is obtained by correcting the position estimate value of the previous cycle according to the in-place status mark and the actual position feedback value, as follows: Get the actual position feedback value of the current cycle and the estimated position value of the previous cycle; If the position control is not in place, the in-place status mark is set to "1", and the position correction value is equal to the position prediction value of the previous cycle; If the position control is in place, the in-place status mark is set to "0", and the position correction value is equal to the actual position feedback value of the current cycle.

[0013] Furthermore, the position prediction value of the current cycle is obtained according to the in-place status mark, displacement increment and position correction value, as follows: If the position control is not in place and the in-place status flag is set to "1", then the predicted position value is equal to the displacement increment of the current cycle plus the position correction value; If the position control is in place and the in-place status flag is set to "0", then the predicted position value is equal to the position correction value.

[0014] Furthermore, diagnosing the fault type of the servo system according to the predicted position value, the actual position feedback value, and the working current is as follows: Obtain the position difference between the predicted position value of the previous cycle and the actual position feedback value of the current cycle; If Δs>Δsmax, |Fc|≤|Fmax|, and Imin≤Ic≤Imax, then the performance of the servo system degrades; If Δs>Δsmax, |Fc|>|Fmax|, and Imin≤Ic≤Imax, then the servo system has an open-loop fault; If Δs>Δsmax, |Fc|≤|Fmax|, and Ic>Imax, then the servo system has a stall fault; If Δs>Δsmax, |Fc|≤|Fmax|, and Ic<Imin, then the servo system has a stop fault; Otherwise, the servo system operates normally; Wherein, Δs is the position difference, Fc is the actual position feedback value of the current cycle, Δsmax is the position error threshold, Fmax is the maximum electrical stroke of the servo mechanism, Imin is the lower limit value of the normal working current, and Imax is the upper limit value of the normal working current.

[0015] Furthermore, diagnosing the fault type of the servo system according to the actual position feedback value, the working current, and the predicted position value of the current cycle, and confirming and outputting the fault type after detecting the fault continuously for 30 ms.

[0016] In a second aspect, the present invention provides a fault diagnosis system for an unmanned aerial vehicle servo system, including: A data acquisition module for acquiring the position error, the control quantity, and the actual position feedback value of the unmanned aerial vehicle servo system; A displacement increment acquisition module for acquiring the displacement increment according to the control quantity in combination with the displacement change function; An in-place status flag acquisition module for acquiring the in-place status flag according to the position error; A position correction value acquisition module for correcting the predicted position value of the previous cycle according to the in-place status flag and the actual position feedback value to obtain the position correction value; A predicted position value acquisition module for acquiring the predicted position value of the current cycle according to the in-place status flag, the displacement increment, and the position correction value; The fault type judgment module is used to diagnose the fault type of the servo system according to the actual position feedback value, the working current and the position prediction value of the current cycle.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention provides necessary data support for subsequent steps by obtaining the position error, control amount and actual position feedback value of the unmanned aerial vehicle servo system; obtaining the displacement increment according to the control amount combined with the displacement change function is helpful to understand the response of the system under the current control strategy, and provide a basis for subsequent position prediction and fault diagnosis; obtaining the in-place state mark according to the position error is helpful to preliminarily classify the position state of the system, and provide more intuitive information for subsequent position prediction and fault diagnosis; correcting the position prediction value of the previous cycle according to the in-place state mark and the actual position feedback value to obtain the position correction value, which is conducive to improving the accuracy of position prediction; obtaining the position prediction value of the current cycle according to the in-place state mark, displacement increment and position correction value; diagnosing the fault type of the servo system according to the actual position feedback value, working current and the position prediction value of the current cycle. The present invention can realize accurate diagnosis of the fault type of the servo system by obtaining and analyzing the information such as the position error, control amount, actual position feedback value and working current of the system, and can effectively avoid missed detection and false alarm of system faults, reduce misjudgment alarms, and improve the accuracy and efficiency of fault diagnosis.

[0018] 2. The present invention has only three input parameters: control quantity, position error and actual position feedback value. The parameter selection is simple, which is conducive to improving processing efficiency.

[0019] 3. The present invention uses the actual position feedback value to correct the position prediction value of the servo system mathematical model, thereby improving the accuracy of the prediction.

[0020] 4. The system of the present invention includes: a data acquisition module, a displacement increment acquisition module, an in-place status mark acquisition module, a position correction value acquisition module, a position predicted value acquisition module and a fault type judgment module. The data acquisition module is used to obtain the position error, control amount and actual position feedback value of the UAV servo system; the displacement increment acquisition module is used to obtain the displacement increment according to the control amount combined with the displacement change function; the in-place status mark acquisition module is used to obtain the in-place status mark according to the position error; the position correction value acquisition module is used to correct the position predicted value of the previous cycle according to the in-place status mark and the actual position feedback value to obtain the position correction value; the position predicted value acquisition module is used to obtain the position predicted value according to the in-place status mark, displacement increment and position correction value; the fault type judgment module is used to diagnose the fault type of the servo system according to the actual position feedback value, the working current and the position predicted value of the current cycle. The various modules cooperate with each other, which can effectively avoid missed detection and false alarms of system faults, reduce misjudgment alarms, and improve the accuracy and efficiency of fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a block diagram of the servo system fault diagnosis principle of the present invention; Figure 2 It is a functional block diagram of a servo system fault diagnosis module of the present invention; Figure 3 is a flow chart of the method of the present invention; Figure 4 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 described embodiments 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 should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first", "second", etc. in the specification of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0024] The present invention is further described in detail below in conjunction with the accompanying drawings: See also Figure 3 The present invention discloses a method for diagnosing a fault of a drone servo system, comprising the following steps: S1, obtain the position error, control amount and actual position feedback value of the drone servo system to provide necessary data support for subsequent steps; S2, obtaining the displacement increment based on the control quantity combined with the displacement change function, helps to understand the response of the system under the current control strategy and provides a basis for subsequent position prediction and fault diagnosis; S3, obtaining the in-place status mark according to the position error, helps to preliminarily classify the position status of the system and provide more intuitive information for subsequent position prediction and fault diagnosis; S4, correcting the position prediction value of the previous cycle according to the in-place status mark and the actual position feedback value to obtain a position correction value. By correcting the position prediction value of the previous cycle, it is beneficial to improve the accuracy of the position prediction; S5, obtaining the estimated position value of the current cycle according to the in-place status mark, displacement increment and position correction value; S6, diagnose the fault type of the servo system based on the actual position feedback value, working current and the position prediction value of the current cycle.

[0025] By acquiring and analyzing the system's position error, control quantity, actual position feedback value, operating current and other information, the present invention can accurately diagnose the type of servo system fault, effectively avoid missed detection of system faults and false alarms, reduce misjudgment alarms, improve the accuracy and efficiency of fault diagnosis, and help to promptly discover and eliminate potential fault hazards, thereby ensuring the normal operation and safety of the UAV servo system.

[0026] Embodiment 1: See also Figure 3 The present invention discloses a method for diagnosing a fault of a drone servo system, comprising the following steps: S1, obtain the position error, control amount and actual position feedback value of the drone servo system, as follows: Get the target position instruction of the servo system; Get the actual position feedback value fed back by the sensor; The position error is obtained by taking the difference between the target position command and the actual position feedback value; The control amount is obtained based on the position error.

[0027] S2, obtain the displacement increment according to the control amount combined with the displacement change function, as follows: Measuring the motion displacement increment of the servo mechanism under the continuous action of the control quantity and under different load conditions; Obtain displacement characteristic parameters according to the control amount and the motion displacement increment; The displacement increment is obtained based on the control quantity and displacement characteristic parameters combined with the displacement change function.

[0028] Preferably, the displacement change function is dt=Uk×k, wherein dt is the displacement increment, Uk is the control amount, and k is the displacement characteristic parameter.

[0029] S3, obtain the in-place status mark according to the position error, as follows: If the position error is less than or equal to the position error threshold, the position control is in place and the in-place state mark is set to "0", otherwise the position control is not in place and the in-place state mark is set to "1".

[0030] S4. Correct the position prediction value of the previous cycle according to the in-place status flag and the actual position feedback value to obtain the position correction value, specifically as follows: Obtain the actual position feedback value of the current cycle and the position prediction value of the previous cycle; If the position control is not in place and the in-place status flag is set to "1", the position correction value is equal to the position prediction value of the previous cycle; If the position control is in place and the in-place status flag is set to "0", the position correction value is equal to the actual position feedback value of the current cycle.

[0031] S5. Obtain the position prediction value of the current cycle according to the in-place status flag, displacement increment, and position correction value, specifically as follows: If the position control is not in place and the in-place status flag is set to "1", the position prediction value is equal to the displacement increment of the current cycle plus the position correction value; If the position control is in place and the in-place status flag is set to "0", the position prediction value is equal to the position correction value.

[0032] S6. Diagnose the fault type of the servo system according to the position prediction value, actual position feedback value, and working current, specifically as follows: Obtain the position difference between the position prediction value of the previous cycle and the actual position feedback value of the current cycle; If Δs > Δsmax, |Fc| ≤ |Fmax|, and Imin ≤ Ic ≤ Imax, the performance of the servo system decreases; If Δs > Δsmax, |Fc| > |Fmax|, and Imin ≤ Ic ≤ Imax, the servo system has an open-loop fault; If Δs > Δsmax, |Fc| ≤ |Fmax|, and Ic > Imax, the servo system has a stall fault; If Δs > Δsmax, |Fc| ≤ |Fmax|, and Ic < Imin, the servo system has a stop fault; Otherwise, the servo system operates normally; Where Δs is the position difference, Fc is the actual position feedback value of the current cycle, Δsmax is the position error threshold, Fmax is the maximum electrical stroke of the servo mechanism, Imin is the lower limit value of the normal working current, and Imax is the upper limit value of the normal working current.

[0033] Preferably, the formula for obtaining the position difference between the position prediction value of the previous cycle and the actual position feedback value of the current cycle is: Δs = |Fc - pd'|; Where Δs is the position difference, Fc is the actual position feedback value of the current cycle, and pd' is the position prediction value of the previous cycle.

[0034] Preferably, the fault type is confirmed and output when the fault is detected for 30 ms.

[0035] The purpose of the present invention is to solve the problems of high missed detection rate and false alarm rate faced by UAV servo system fault diagnosis. A fault diagnosis method based on mathematical model is proposed, and an analytical model of servo system motion characteristics is established. Faults are diagnosed by comparing the difference between the model's estimated position and the actual position of the servo system, as well as parameters such as the current control quantity and the working current of the servo system.

[0036] The servo system fault diagnosis method proposed in the present invention establishes a position analysis model of the system according to the error between the servo system position command and the actual feedback, the control quantity and the position following characteristic of the servo system, and diagnoses whether there are performance degradation, open loop, stall, jam and other faults in the servo system during operation by comparing the difference between the model prediction value and the actual position and then combining the actual position and working current.

[0037] The servo system mathematical model proposed in the present invention is a linear model, which has only three input parameters: control quantity, position error, and actual position, and has the advantages of simple model and parameter selection; the actual position is used to correct the position predicted by the servo system mathematical model, thereby improving the accuracy of the prediction; the missed detection rate and false alarm rate of the servo system fault diagnosis method can be reduced by 10%; the software is easy to implement and has strong real-time performance, which effectively reduces the maintenance and detection time of the servo system and improves the detection efficiency; it has certain versatility and can be applied to other servo systems by simply modifying certain parameters.

[0038] Embodiment 2: This embodiment discloses a method for diagnosing a fault in a drone servo system, which is as follows: See also Figure 1 The UAV servo system consists of a control driver, a servo motor, a mechanical transmission mechanism, a position sensor, etc. The control driver receives the target position command of the servo system and collects the actual position information fed back by the sensor. It calculates the output control quantity based on the error between the two to drive the motor to rotate, and transmits it to the servo mechanism output shaft through the reduction mechanism to realize the closed-loop position control of the servo system.

[0039] The servo system fault diagnosis module operates redundantly with the actual servo system. In each sampling cycle, the servo mathematical model submodule predicts the motion position of the servo system in the next cycle based on the current position error (Ec), control quantity (Uc) and actual position feedback value (Fc) and other working conditions. The model monitoring fault judgment submodule judges the fault type (Ft) based on the error between the actual position and the predicted position of the servo system and the system working current (Ic), and issues a fault warning signal.

[0040] See also Figure 2The servo system fault diagnosis module outputs the fault type based on the current position error, control quantity, actual position feedback value, and working current of the servo mechanism through data sampling and holding, position fitting, in-place state detection, position correction, position estimation, and fault judgment functional submodules, indicating whether the servo system has performance degradation, open loop, stall, or stall faults. The interface data of the servo system fault diagnosis module are shown in Table 1.

[0041] It should be noted that the position error is hereinafter referred to as Ec, the control amount is hereinafter referred to as Uc, the actual position feedback value is hereinafter referred to as Fc, the working current is hereinafter referred to as Ic; the fault type is hereinafter referred to as Ft; Table 1. Servo system fault diagnosis module interface data description:

[0042] like Figure 2 As shown, it is a functional block diagram of the internal function of the servo system fault diagnosis module. The function of the fault diagnosis module does not need to add additional hardware circuits to assist completion, and is completely realized by the method of the present invention. Under the existing hardware resource configuration conditions, the fault diagnosis module can accurately and quickly determine the fault. The specific implementation method is described as follows.

[0043] Fault diagnosis module composition: The servo system fault diagnosis module is composed of software functional sub-modules such as data sampling and holding, position fitting, in-place status detection, position correction, position estimation, and fault judgment.

[0044] The fault diagnosis module has 4 data input interfaces and 1 data output interface. The 4 input data include: current position error (Ec), control quantity (Uc), actual position feedback value (Fc), working current (Ic); 1 output data is the fault type (Ft), there are 4 types of fault types: performance degradation, open loop, stall, and stop.

[0045] Data sampling and holding submodule: The data sampling and holding submodule is responsible for periodically reading the control quantity (Uc), position error (Ec), and actual position feedback value (Fc) and saving them as discrete quantities for storage, thereby obtaining discrete control quantity (Uk), discrete position error (Ek), and discrete actual position feedback value (Fk). The general sampling period can be between a few ms and tens of ms. The sampling period of this system is 5ms.

[0046] It should be noted that Uk is the abbreviation of discrete control quantity, Ek is the abbreviation of discrete position error, and Fk is the abbreviation of discrete actual position feedback value.

[0047] Position fitting submodule: The position fitting submodule first fits the displacement characteristic parameter k according to the measured data of the servo system operation, and then calculates the output displacement increment dt by the displacement change function dt=Uk×k. The physical meaning of this expression is: under the action of the discrete control quantity Uk, the displacement increment of the servo mechanism within the sampling period is dt. Under the same control input, the fitted position of the servo mechanism should be close to the actual output position of the servo mechanism.

[0048] Characteristic parameter k fitting calculation method: Under different load conditions, measure the servo mechanism movement displacement increment (dt) after the discrete control quantity (Uk) lasts for 5ms, and calculate the displacement characteristic parameter (k) according to k=dt / Uk, where dt is the displacement increment and Uk is the discrete control quantity. By fitting and calculating a large amount of measured data, the displacement characteristic parameter finally obtained is the ratio of the servo mechanism movement displacement to the maximum PWM duty cycle. In this system, k=0.1 / 7272.

[0049] Among them, dt is the abbreviation of displacement increment, and k is the abbreviation of displacement characteristic parameter.

[0050] In-place status detection submodule: The in-place state detection submodule gives the in-place state mark (pst) according to the size of the position error (Ek). If the position error (Ek) is within the position error threshold (Sth), that is, |Ek|≤Sth, the position control is considered to be in place, and the in-place state mark (pst) is set to "0". Otherwise, the control is not in place, and the in-place state mark (pst) is set to "1". The position error threshold (Sth) is the steady-state control accuracy of the servo mechanism, and this system takes 0.1 mm.

[0051] It should be noted that pst is the abbreviation of in-place status mark, and Sth is the abbreviation of position error threshold.

[0052] Position correction submodule: The position correction submodule uses the actual position feedback value (Fk) to correct the position prediction value (pd) in time according to the in-place status mark (pst) to obtain the position correction value (pc). If the servo mechanism has reached the control accuracy range, that is, the in-place status mark (pst) is "0", the discrete actual position feedback value (Fk) of the current cycle replaces the position prediction value (pd') of the previous cycle to obtain the correction value pc=Fk; otherwise, when the in-place status mark (pst) is "1", the position prediction value is not corrected, and the correction value is equal to the position prediction value, that is, pc=pd.

[0053] Among them, pc is the abbreviation for position correction value, and pd is the abbreviation for position prediction value.

[0054] Position estimation submodule: The position estimation submodule calculates the predicted position value (pd) based on the in-place status mark (pst), displacement increment (dt), and position correction value (pc). If the servo mechanism is in the motion process state and the in-place status mark (pst) is "1", the predicted position value pd=dt+pc; if the servo mechanism is already in the in-place state and the in-place status mark (pst) is "0", the predicted position value pd=pc. Since pc=Fk, the predicted position value is equal to the actual position feedback value of the current cycle.

[0055] Fault judgment submodule: The fault judgment submodule calculates the difference between the position prediction value of the previous cycle and the actual position feedback value of the current cycle, and then diagnoses whether the servo system has performance degradation, open loop, stall, or other faults based on the actual position feedback value and working current of the servo system. The steps for judging the type of servo system fault are as follows: Calculate the absolute value of the difference between the position prediction value of the previous cycle and the actual position feedback value of the current cycle. The absolute value of the difference between the position prediction value of the previous cycle and the actual position feedback value of the current cycle is the position difference (Δs), Δs=|Fc-pd'|, Δs is the position difference, Fc is the actual position feedback value, in the above formula, it specifically refers to the actual position feedback value of the current cycle, and pd' is the position prediction value of the previous cycle; Determine whether the position difference Δs exceeds the position error threshold Δsmax. The position error threshold (Δsmax) of this system is 1 mm, and Δsmax is the abbreviation of the position error threshold; Determine whether the actual position feedback value (Fc) exceeds the maximum electrical stroke (Fmax) of the servo mechanism. Fmax is the abbreviation of the maximum electrical stroke of the servo mechanism. In this system, Fmax is ±30 mm. Determine whether the working current (Ic) is within the normal working current range, that is, Imin≤Ic≤Imax. In this system, Imin is 0.5A and Imax is 4A. Imin is the lower limit of the normal working current, Imax is the upper limit of the normal working current, and Ic is the working current. Diagnose the fault and give the fault type. The criteria are as follows: If Δs>Δsmax, |Fc|≤|Fmax| and Imin≤Ic≤Imax, the servo system performance is degraded and the fault type Ft is set to "1"; If Δs>Δsmax, |Fc|>|Fmax| and Imin≤Ic≤Imax, then the servo system has an open-loop fault and the fault type Ft is set to "2"; If Δs>Δsmax, |Fc|≤|Fmax| and Ic>Imax, then the servo system is stuck and the fault type Ft is set to "3"; If Δs > Δsmax, |Fc| ≤ |Fmax| and Ic < Imin, then the servo system stops due to a fault, and the fault type Ft is set to "4"; In other cases, the servo system operates normally without faults, and the fault type Ft is set to "0".

[0056] To prevent misjudgment of faults, during the fault diagnosis process of the method of the present invention, it is required to continuously detect 6 beats, that is, to confirm and output the fault type only when a fault is detected continuously for 30 ms.

[0057] Based on the above method, the present invention also discloses a fault diagnosis system for an unmanned aerial vehicle servo system. Refer to Figure 4 , including: A data acquisition module, which is used to acquire the position error, control amount, and actual position feedback value of the unmanned aerial vehicle servo system; A displacement increment acquisition module, which is used to acquire the displacement increment according to the control amount in combination with the displacement change function; An in-place state flag acquisition module, which is used to acquire the in-place state flag according to the position error; A position correction value acquisition module, which is used to correct the position prediction value of the previous cycle according to the in-place state flag and the actual position feedback value to obtain the position correction value; A position prediction value acquisition module, which is used to acquire the position prediction value according to the in-place state flag, displacement increment, and position correction value; A fault type judgment module, which is used to diagnose the fault type of the servo system according to the actual position feedback value, working current, and position prediction value of the current cycle.

[0058] Each module of the system of the present invention cooperates with each other, can effectively avoid missing detection and false alarms of system faults, reduce misjudgment alarms, and improve the accuracy and efficiency of fault diagnosis.

[0059] The above content is only to illustrate the technical idea of the present invention, and the protection scope of the present invention cannot be limited thereby. Any changes made on the basis of the technical solution according to the technical idea proposed by the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for diagnosing a fault in a drone servo system, characterized in that: The following steps are involved: Obtain the position error, control amount and actual position feedback value of the drone servo system; Obtain displacement increment according to the control amount combined with the displacement change function; Obtain the in-place status mark according to the position error; Correct the estimated position value of the previous cycle according to the in-place status mark and the actual position feedback value to obtain the position correction value; Obtain the estimated position value of the current cycle according to the in-place status mark, displacement increment and position correction value; The fault type of the servo system is diagnosed based on the actual position feedback value, operating current and the position prediction value of the current cycle.

2. The method for diagnosing a fault in a drone servo system according to claim 1, characterized in that: The position error, control amount and actual position feedback value of the drone servo system are obtained as follows: Get the target position instruction of the servo system; Get the actual position feedback value fed back by the sensor; The position error is obtained by taking the difference between the target position command and the actual position feedback value; The control amount is obtained based on the position error.

3. The method for diagnosing a fault in a drone servo system according to claim 1, characterized in that: The displacement increment is obtained according to the control amount combined with the displacement change function, specifically as follows: Measuring the motion displacement increment of the servo mechanism under the continuous action of the control quantity and under different load conditions; Obtain displacement characteristic parameters according to the control amount and the motion displacement increment; The displacement increment is obtained based on the control quantity and displacement characteristic parameters combined with the displacement change function.

4. The method for diagnosing a fault in a drone servo system according to claim 3, characterized in that: The displacement change function is dt=Uk×k, wherein dt is the displacement increment, Uk is the control amount, and k is the displacement characteristic parameter.

5. The method for diagnosing a fault in a drone servo system according to claim 1, characterized in that: The in-place status mark is obtained according to the position error, as follows: If the position error is less than or equal to the position error threshold, the position control is in place and the in-place state mark is set to "0", otherwise the position control is not in place and the in-place state mark is set to "1".

6. The method for diagnosing a fault in a drone servo system according to claim 5, characterized in that: The position correction value is obtained by correcting the position estimate value of the previous cycle according to the in-place status mark and the actual position feedback value, as follows: Get the actual position feedback value of the current cycle and the estimated position value of the previous cycle; If the position control is not in place, the in-place status mark is set to "1", and the position correction value is equal to the position prediction value of the previous cycle; If the position control is in place, the in-place status mark is set to "0", and the position correction value is equal to the actual position feedback value of the current cycle.

7. The method for diagnosing a fault in a drone servo system according to claim 5, characterized in that: The position estimation value of the current cycle is obtained according to the in-place status mark, displacement increment and position correction value, as follows: If the position control is not in place, the in-place status mark is set to "1", and the position prediction value is equal to the displacement increment of the current cycle plus the position correction value; If the position control is in place, the in-place status mark is set to "0", and the position prediction value is equal to the position correction value.

8. The method for diagnosing a fault in a drone servo system according to claim 1, characterized in that: The fault type of the servo system diagnosed according to the position prediction value, the actual position feedback value and the working current is as follows: Get the position difference between the predicted position value of the previous cycle and the actual position feedback value of the current cycle; If Δs>Δsmax, |Fc|≤|Fmax| and Imin≤Ic≤Imax, the servo system performance degrades; If Δs>Δsmax, |Fc|>|Fmax| and Imin≤Ic≤Imax, the servo system has an open-loop fault; If Δs>Δsmax, |Fc|≤|Fmax| and Ic>Imax, the servo system is stuck; If Δs > Δsmax, |Fc| ≤ |Fmax|, and Ic < Imin, then there is a servo system stall fault; Otherwise, the servo system operates normally; where Δs is the position difference, Fc is the actual position feedback value of the current cycle, Δsmax is the position error threshold, Fmax is the maximum electrical stroke of the servo mechanism, Imin is the lower limit value of the normal operating current, and Imax is the upper limit value of the normal operating current.

9. The method for diagnosing a fault in a drone servo system according to claim 8, characterized in that: Diagnose the fault type of the servo system based on the actual position feedback value, operating current, and the position prediction value of the current cycle, and confirm and output the fault type after detecting the fault continuously for 30 ms.

10. A UAV servo system fault diagnosis system, characterized in that: Including: A data acquisition module for acquiring the position error, control quantity, and actual position feedback value of the UAV servo system; A displacement increment acquisition module for acquiring the displacement increment according to the control quantity in combination with the displacement change function; An in-place status flag acquisition module for acquiring the in-place status flag according to the position error; A position correction value acquisition module for correcting the position prediction value of the previous cycle according to the in-place status flag and the actual position feedback value to obtain the position correction value; A position prediction value acquisition module for acquiring the position prediction value of the current cycle according to the in-place status flag, displacement increment, and position correction value; A fault type judgment module for diagnosing the fault type of the servo system based on the actual position feedback value, operating current, and the position prediction value of the current cycle.

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