CN114325379B - Method and system for determining motor rotor position fault sign - Google Patents
Method and system for determining motor rotor position fault sign Download PDFInfo
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- CN114325379B CN114325379B CN202110786390.XA CN202110786390A CN114325379B CN 114325379 B CN114325379 B CN 114325379B CN 202110786390 A CN202110786390 A CN 202110786390A CN 114325379 B CN114325379 B CN 114325379B
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Abstract
The application belongs to the technical field of aviation motor control, and particularly relates to a motor rotor position fault sign determining method and system. The method comprises the steps of respectively obtaining motor electric angular velocity signals at k-1 moment and k moment and motor rotor position phase angle signals; acquiring three-phase current of a motor at the moment k, and converting the three-phase current into a dq axis component of the motor current; determining an electromagnetic torque prediction increment of the motor at the moment k; determining the minimum value and the maximum value of the predicted increment of the electric angular speed of the motor at the moment k-1; determining a minimum value and a maximum value of a motor rotor position phase angle increment at the time k-1; taking the minimum value and the maximum value of the predicted increment of the motor electric angular velocity at the moment k-1 as a first limiting range; and taking the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k-1 as a second limiting range to jointly determine the motor rotor position fault zone bit at the moment k. The fault-tolerant control of the motor is realized, and the safe and reliable operation of a motor control system can be ensured.
Description
Technical Field
The application belongs to the technical field of aviation motor control, and particularly relates to a motor rotor position fault sign determining method and system.
Background
Along with the gradual maturity of the motor position-free control technology, the motor position-free algorithm is more and more widely applied, and the position-free algorithm can save the cost of a sensor in a motor control system, but is often matched with the position-free algorithm in some occasions with high safety and reliability. When the motor position sensor has small faults, the system can continue to stably run, when the motor position sensor has large faults and even fails, the system cannot stably run, and the system breaks down, so that the system needs to be quickly switched to a position-free control algorithm, in the switching process, the fault state of the position sensor is identified to be the key that the system is reliably switched to the position-free algorithm, fault-tolerant control is realized, and the safe and reliable running of the motor control system is ensured. In addition, motor load characteristics cause motor dynamic fluctuation and irregular interference of electromagnetic noise on signals, and the fault identification of the position signals is also very difficult.
At present, fault diagnosis strategies are mainly divided into two methods, namely hardware and software. The hardware-based method diagnosis is to add extra hardware, has the advantages of quick detection response, higher reliability and the like, but the method has higher requirements on space and installation environment, needs redundancy and increases the system cost, and is not easy to realize a hardware interface circuit. Software-based diagnostic algorithms are more advantageous and are currently the focus of research. Software-based fault diagnosis algorithms are mainly divided into three types, namely a model-based method, a signal-based method and a knowledge-based method.
The model fault diagnosis method is to construct a state observer, estimate a system state variable, compare the estimated value with the measured value, and determine the fault position and cause. The method has good real-time performance, but needs to consider the robustness of system parameters, and the optimal diagnosis capability is realized by integrating the system state. The signal fault diagnosis method is to input and output signals through a measuring system, analyze the change rule of data, generally analyze the characteristics of amplitude, frequency spectrum and the like of the signals, and determine that the system has faults if the signals deviate from the rule. Compared with the model fault diagnosis method, the signal fault diagnosis method does not depend on the model and parameters of the system, but has a large operation amount due to the adoption of Fourier analysis, principal component analysis, wavelet transformation method and the like, and is not applied to a real-time system. Whereas knowledge-based methods typically conduct fault diagnosis intelligently through intelligent algorithms. However, the logical rational construction of knowledge learning base and the complexity of intelligent algorithm limit its industrial application.
At present, for a motor rotor position fault identification technology, the diagnosis and fault-tolerant control research of a permanent magnet synchronous motor position sensor (Tian Shuai, beijing university of transportation, 6 months in 2020) is carried out on the rotor position angle after the fault in differential processing to obtain different frequency angular velocity components after the fault; the angular velocity component is used as a fault characteristic quantity, the fault characteristic quantity is extracted by using a discrete Fourier transform DFT amplitude extraction algorithm, a fault characteristic quantity threshold is set to respond to different types of faults, but the algorithm is complex, the threshold divided according to fault types is more, and engineering implementation is difficult. In "study of servo fault tolerance control under position sensor failure" (Gao Yuwen, university of electronics and technology, 2014), sliding mode control and position sensor failure detection are combined, and the rotational speed is estimated by a sliding mode algorithm, but when the actual rotational speed deviates from the estimated rotational speed, the position sensor failure is recognized. However, the article suffers from the following disadvantages: the accuracy of the sliding mode control algorithm itself, as well as the interference of the position signals, are not considered in this document, and the set threshold is difficult, which easily causes identification errors. The method for estimating the faults of the multiple sensors under the feedback of the two-phase current measurement is designed in the control system of the direct-drive permanent magnet synchronous wind driven generator (Yang Zhimin, chongqing university, 2019) so as to realize the simultaneous positioning of the faults of the multiple sensors under the current and rotating speed measurement. The observer design method based on parameter-dependent fault estimation is provided, and the faults of a mechanical disturbance, a current sensor and a rotating speed sensor in a system can be estimated simultaneously. However, the speed fault estimation still depends on the current sensor, and when the current sensor is interfered or even fails, the speed fault estimation is affected, in addition, due to the adoption of the observer design, the state parameters of the system affect the accuracy of the fault estimation, and meanwhile, the calculation amount of the algorithm is also larger. The chinese patent publication No. CN106998164B provides a fault diagnosis and fault-tolerant control system and method for a permanent magnet synchronous motor, which introduces a fault diagnosis and fault-tolerant control system and method for a permanent magnet synchronous motor, wherein an estimated rotor speed and resistance are sent to a decision unit based on a Model Reference Adaptive System (MRAS) observer for motor speed and resistance identification, so as to identify whether a motor position sensor fails, an armature winding element is open-circuited and an inter-turn short-circuited, but the accuracy of an algorithm depends on the accuracy of the estimated speed and a set threshold value, and the algorithm does not consider the interference of load and noise.
Disclosure of Invention
In order to solve the technical problems, the application provides a method and a system for determining a rotor position fault sign of a motor, which aim at solving the problems that an existing rotor position fault identification method is large in operation amount and complex in algorithm, and does not consider the influence of load characteristics on fault identification and the influence of noise interference on position signal fault identification.
The first aspect of the present application provides a method for determining a position fault flag of a rotor of an electric machine, which mainly includes: s1, respectively acquiring motor electric angular velocity signals at the moment k-1 and the moment k, and respectively acquiring motor rotor position phase angle signals at the moment k-1 and the moment k, wherein the moment k-1 and the moment k are respectively two sampling points in time sequence; s2, acquiring three-phase current of the motor at the moment k, and converting the three-phase current into a dq axis component of the motor current; s3, determining an electromagnetic torque prediction increment of the motor at the moment k; s4, determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k based on the ratio coefficient of the maximum noise of the motor angular velocity and the electric angular velocity, and further determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k-1; s5, determining the minimum value and the maximum value of the increment of the motor rotor position phase angle at the moment k based on the ratio coefficient of the maximum noise of the motor phase angle and the phase angle, and further determining the minimum value and the maximum value of the increment of the motor rotor position phase angle at the moment k-1; s6, taking the minimum value and the maximum value of the motor angular velocity prediction increment at the moment k-1 in the step S4 as a first limit range, and determining a first fault if the motor angular velocity signal increment at the moment k exceeds the first limit range; and similarly, taking the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k-1 in the step S5 as a second limit range, if the motor electric angular velocity signal increment at the moment k exceeds the second limit range, determining a second fault, and jointly determining a motor rotor position fault zone bit by the first fault and the second fault.
Preferably, step S3 includes: s31, determining an electromagnetic torque predicted value at the moment k; step S32, delaying the electromagnetic torque predicted value at the moment k by one motor inverter controller ADC sampling time, thereby obtaining a fixed electromagnetic torque predicted value at the moment k-1; and step S33, determining the electromagnetic torque prediction increment of the motor at the time k according to the electromagnetic torque prediction value at the time k and the fixed electromagnetic torque prediction value at the time k-1.
Preferably, step S31 includes: step S311, obtaining the pole pair number parameter p of the motor n Motor flux linkage parameter ψ f D-axis inductance parameter L d And q-axis inductance parameter L q The method comprises the steps of carrying out a first treatment on the surface of the Step S312, determining the electromagnetic torque predicted value T at the k time e (k)：
Wherein I is d (k),I q (k) The motor current dq axis component determined for step S2.
Preferably, step S4 further comprises: step S41, determining the increment of the motor electric angular velocity signal at the moment k according to the motor electric angular velocity signal at the moment k-1; step S42, determining the maximum motor angular velocity prediction increment at the moment k and the minimum motor angular velocity prediction increment at the moment k based on the ratio coefficient of the maximum noise of the motor angular velocity and the electric angular velocity and the motor angular velocity signal increment at the moment k; step S43, delaying the maximum motor electric angular velocity prediction increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the maximum motor electric angular velocity prediction increment at the k-1 moment, and similarly delaying the minimum motor electric angular velocity prediction increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the minimum motor electric angular velocity prediction increment at the k-1 moment.
Preferably, step S42 further includes: step S421, obtaining the pole pair number parameter p of the motor n The motor moment of inertia parameter J, the motor damping coefficient parameter D and the motor maximum load torque T Lmax Ratio coefficient eta of maximum noise of motor electric angular velocity and electric angular velocity ω Minimum fluctuation limit value delta of motor electric angular velocity ωmin ADC sampling time T of motor inverter controller s The method comprises the steps of carrying out a first treatment on the surface of the Step S422, determining the maximum motor electric angular velocity prediction increment delta omega at the moment k emmax (k) And the minimum electromechanical angular velocity prediction increment delta omega at time k emmin (k) Comprising the following steps:
wherein Δω em (k) The electromechanical angular velocity signal delta, omega at time k determined for step S41 em (k) The electromechanical angular velocity signal at time k determined for step S1.
Preferably, step S5 further includes: step S51, determining the motor rotor position phase angle increment at the moment k according to the motor rotor position phase angle signal at the moment k-1; step S52, determining the maximum motor rotor position phase angle increment at the moment k and the minimum motor rotor position phase angle increment at the moment k based on the ratio coefficient of the maximum noise of the motor phase angle and the phase angle, the motor rotor position phase angle increment at the moment k and the minimum value and the maximum value of the motor electric angular velocity prediction increment at the moment k-1; step S53, delaying the maximum motor rotor position phase angle increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the maximum motor rotor position phase angle increment at the k-1 moment, and similarly delaying the minimum motor rotor position phase angle increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the minimum motor rotor position phase angle increment at the k-1 moment.
Preferably, step S51 further comprises: step S511, obtaining the ratio coefficient eta of the maximum noise of the motor phase angle and the phase angle θ Minimum fluctuation limit value delta of motor phase angle θmin The method comprises the steps of carrying out a first treatment on the surface of the Step S512, calculating the motor rotor position phase angle increment delta theta at the moment k em (k) The calculation formula is as follows:
where pi is the circumference ratio.
Preferably, step S52 further includes: step S521, obtaining the ratio coefficient eta of the maximum noise of the motor phase angle and the phase angle θ Minimum fluctuation limit value delta of motor phase angle θmin The method comprises the steps of carrying out a first treatment on the surface of the Step S522, determining the maximum motor rotor position phase angle increment delta theta at k time emmax (k) And minimum motor rotation at time kSub-position phase angle delta theta emmin (k) Comprising the following steps:
wherein Δω emm ( a k x -1) predicting the increment, Δω, for the maximum electromechanical angular velocity at time k-1 emmin (k-1) is the minimum electromechanical angular velocity prediction increment, ω, at time k-1 em (k) The electromechanical angular velocity signal at time k determined for step S1.
Preferably, in step S6, when the first fault occurs, a first fault flag bit is set to 1, and when the second fault occurs, a second fault flag bit is set to 1, and the first fault flag bit and the second fault flag bit determine a fault flag bit of the rotor position of the motor through and operation.
A second aspect of the present application provides a motor rotor position fault flag determination system, comprising: the electric angular velocity and phase angle acquisition module is used for respectively acquiring electric angular velocity signals of the motor at the moment k-1 and the moment k and position phase angle signals of the motor rotor at the moment k-1 and the moment k, wherein the moment k-1 and the moment k are respectively two sampling points in time sequence; the dq axis component acquisition module is used for acquiring three-phase current of the motor at the moment k and converting the three-phase current into a dq axis component of the motor current; the electromagnetic torque prediction increment calculation module is used for determining the electromagnetic torque prediction increment of the motor at the moment k; the first range calculation module is used for determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k based on the ratio coefficient of the maximum noise of the motor angular velocity to the motor angular velocity, and further determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k-1; the second range calculation module is used for determining the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k based on the ratio coefficient of the maximum noise of the motor phase angle and the phase angle, and further determining the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k-1; the fault zone bit determining module is used for taking the minimum value and the maximum value of the motor electric angular velocity prediction increment at the moment k-1 in the first range calculating module as a first limiting range, and determining a first fault if the motor electric angular velocity signal increment at the moment k exceeds the first limiting range; and similarly, taking the minimum value and the maximum value of the motor rotor position phase angle increment at the k-1 moment in the second range calculation module as a second limit range, if the motor electric angular velocity signal increment at the k moment exceeds the second limit range, determining a second fault, and jointly determining a motor rotor position fault zone bit by the first fault and the second fault.
According to the synchronous motor provided with the position sensor, through the data characteristics of the position signals and the rotor external characteristics of the synchronous motor, the noise and the load margin are considered, the operation area of the rotor position signals is predicted according to the model prediction method, whether the rotor position signals are in a reasonable operation area is judged in real time, the rotor position fault identification function is realized, and the method has the following advantages:
1. the control method does not need to estimate the actual rotation speed, has weak coupling with other algorithms, and reduces estimation errors and coupling errors;
2. the control method has small operand and is suitable for a real-time motor system;
3. the control method only depends on the position sensor data of two periods, does not depend on long-term historical data, and occupies small data storage;
4. the control method has strong real-time performance and high precision, and can judge the occurrence of the fault in the first period of the occurrence of the fault;
5. according to the control method, the noise and the load margin are considered, so that the hierarchical control of the noise can be realized, the influence of the noise on a system is evaluated, and meanwhile, the fluctuation caused by the load characteristic does not influence the accuracy of an algorithm;
6. the control method is simpler and more practical in engineering application, is convenient to be applied to switching from a motor with position algorithm to a motor without position algorithm, and realizes fault-tolerant control, thereby ensuring the key of safe and reliable operation of a motor control system.
7. The control method can eliminate the influence of boundary value mutation caused by phase angle modular operation and noise interference on a fault identification algorithm.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of a method of determining a motor rotor position fault signature of the present application.
Fig. 2 is a structural diagram of a motor system according to an embodiment of the present application.
Fig. 3 is a diagram of motor electrical angular velocity signals, motor rotor position phase angle signals, and motor rotor position fault flags when an electrical angular velocity fault occurs in a rotor position in an embodiment of the present invention.
Fig. 4 is a waveform of a motor rotor position phase angle delta area at a time when an electrical angular velocity fault occurs at a rotor position according to an embodiment of the present invention.
Fig. 5 is a waveform of an increment region and an enlarged waveform of an electric angular velocity signal of a motor at a time when an electric angular velocity fault occurs in a rotor position according to an embodiment of the present invention.
FIG. 6 is a graph of motor electrical angular velocity signals, motor rotor position phase angle signals, and motor rotor position fault signature when a phase angle fault occurs to a rotor position in an embodiment of the present invention.
Fig. 7 is a waveform of a motor rotor position phase angle delta area and an amplified waveform at a time when a phase angle fault occurs in a rotor position according to an embodiment of the present invention.
Fig. 8 is a waveform of an electric angular velocity signal increment region of the motor at the moment when the electric angular velocity fault occurs at the rotor position according to the embodiment of the present invention.
Fig. 9 is a bitmap of motor electrical angular velocity signals, motor electrical angular velocity noise signals, and motor rotor position failure flags when motor electrical angular velocity noise exceeds a standard in an embodiment of the present invention.
Fig. 10 shows waveforms of increment regions and amplified waveforms of the motor electric angular velocity signal at the moment when the motor electric angular velocity noise exceeds the standard.
FIG. 11 is a diagram of rotor position phase angle noise signal, motor rotor position phase angle signal, motor rotor position fault signature when rotor position phase angle noise exceeds standard in an embodiment of the invention.
Fig. 12 is a waveform of a motor rotor position phase angle delta area and an amplified waveform at a time when rotor position phase angle noise exceeds a standard in accordance with an embodiment of the present invention.
Fig. 13 is a graph of torque, motor rotor position phase angle signal, motor rotor position fault signature for a load torque bump of 16N according to an embodiment of the present invention.
Fig. 14 is a graph of motor electrical angular velocity signal delta area waveform at time and motor rotor position phase angle delta area waveform at time when load torque is ramped up by 16N in accordance with an embodiment of the present invention.
Detailed Description
For the purposes, technical solutions and advantages of the present application, the following describes the technical solutions in the embodiments of the present application in more detail with reference to the drawings in the embodiments of the present application. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, of the embodiments of the present application. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application. All other embodiments, based on the embodiments herein, which would be apparent to one of ordinary skill in the art without undue burden are within the scope of the present application. Embodiments of the present application will be described in detail below with reference to the accompanying drawings.
The first aspect of the present application provides a method for determining a position fault flag of a rotor of an electric machine, as shown in fig. 1, mainly including:
and S1, respectively acquiring electric angular speed signals of the motor at the moment k-1 and the moment k, and respectively acquiring position phase angle signals of the rotor of the motor at the moment k-1 and the moment k, wherein the moment k-1 and the moment k are respectively two sampling points in time sequence.
The motor system structure of the present application is shown in fig. 2, where the parameters obtained or set in advance include:
motor pole pair number parameter p n Motor flux linkage parameter ψ f D-axis inductance parameter L d And q-axis inductance parameter L q The motor moment of inertia parameter J, the motor damping coefficient parameter D and the motor maximum load torque T Lmax Ratio coefficient of maximum noise of motor electric angular velocity and electric angular velocityη ω Ratio coefficient eta of maximum noise of motor phase angle and phase angle θ Minimum fluctuation limit value delta of motor electric angular velocity ωmin And motor phase angle minimum fluctuation limit value delta θmin Wherein the d-axis is the intersecting axis, the q-axis is the straight axis, and eta ω ∈[0,+∞)，η θ ∈[0,+∞)。
The application samples and processes the motor electric angular velocity signal omega em And motor rotor position phase angle signal θ em Setting sampling time as ADC sampling time T of motor inverter controller s And recording the motor electric angular velocity signal { omega ] obtained by sampling twice in time sequence em (k-1),ω em (k) Sum motor rotor position phase angle signal θ em (k-1),θ em (k)}；
Wherein omega em (k-1) is the electromechanical angular velocity signal, ω, at time k-1 em (k) For dynamo-electric angular velocity signal at time k, θ em (k-1) Motor rotor position phase angle Signal at time k-1, θ em (k) Motor rotor position phase angle signal at time k.
Step S2, sampling three-phase current I of motor at k time a (k),I b (k),I c (k) And obtaining a dq axis component I of the motor current at the moment k through a current coordinate transformation equation d (k),I q (k)。
And S3, determining an electromagnetic torque prediction increment of the motor at the moment k.
In some alternative embodiments, step S3 includes:
step S31, determining an electromagnetic torque predicted value at time k, and step S31 includes: step S311, obtaining the pole pair number parameter p of the motor n Motor flux linkage parameter ψ f D-axis inductance parameter L d And q-axis inductance parameter L q The method comprises the steps of carrying out a first treatment on the surface of the Step S312, determining the electromagnetic torque predicted value T at the k time e (k)：
Wherein I is d (k),I q (k) The motor current dq axis component determined for step S2.
And step S32, delaying the electromagnetic torque predicted value at the moment k by one motor inverter controller ADC sampling time, so as to obtain the fixed electromagnetic torque predicted value at the moment k-1.
In this step, an electromagnetic torque predictive value T at time k-1 is calculated e (k-1) whose calculation formula is:
T e (k-1)＝Delay Ts [T e (k)]；
wherein Delay Ts [T e (k)]To delay the electromagnetic torque predicted value at k time by one motor inverter controller ADC sampling time T s 。
And step S33, determining the electromagnetic torque prediction increment of the motor at the time k according to the electromagnetic torque prediction value at the time k and the fixed electromagnetic torque prediction value at the time k-1.
In this step, an electromagnetic torque prediction increment Δt at the time k is calculated e (k) The calculation formula is as follows:
ΔT e (k)＝T e (k)-T e (k-1)。
and S4, determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k based on the ratio coefficient of the maximum noise of the motor angular velocity to the electric angular velocity, and further determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k-1.
In some alternative embodiments, step S4 further comprises:
and S41, determining the increment of the electromechanical angular velocity signal at the moment k according to the electromechanical angular velocity signal at the moment k-1.
In this step, the electromechanical angular velocity signal increment Δω at time k is calculated em (k) The calculation formula is as follows:
Δω em (k)＝ω em (k)-ω em (k-1)。
step S42, based on the ratio coefficient of the maximum noise of the motor angular velocity and the electrical angular velocity and the motor angular velocity signal increment at the time k, the maximum motor angular velocity prediction increment at the time k and the minimum motor angular velocity prediction increment at the time k are determined.
In some alternative embodiments, step S42 further comprises:
step S421, obtaining the pole pair number parameter p of the motor n The motor moment of inertia parameter J, the motor damping coefficient parameter D and the motor maximum load torque T Lmax Ratio coefficient eta of maximum noise of motor electric angular velocity and electric angular velocity ω Minimum fluctuation limit value delta of motor electric angular velocity ωmin ADC sampling time T of motor inverter controller s ；
Step S422, determining the maximum motor electric angular velocity prediction increment delta omega at the moment k emmax (k) And the minimum electromechanical angular velocity prediction increment delta omega at time k emmin (k) Comprising the following steps:
wherein Δω em (k) The electromechanical angular velocity signal delta, omega at time k determined for step S41 em (k) The electromechanical angular velocity signal at time k determined for step S1.
In step S422, max { a, b } is a mathematical operator for the maximum value of the values a and b, and |c| is a mathematical operator for the absolute value of the value c.
Step S43, delaying the maximum motor electric angular velocity prediction increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the maximum motor electric angular velocity prediction increment at the k-1 moment, and similarly delaying the minimum motor electric angular velocity prediction increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the minimum motor electric angular velocity prediction increment at the k-1 moment.
In this step, the maximum electromechanical angular velocity prediction increment Deltaomega at time k-1 is calculated emmax (k-1) and a minimum electromechanical angular velocity prediction increment Δω at time k-1 emmin (k-1) whose calculation formula is:
wherein Delay Ts [Δω emmax (k)]To maximize the motor power at time kAngular velocity prediction increment Δω emmax (k) Delay one motor inverter controller ADC sampling time T s ，Delay Ts [Δω emmin (k)]Predicting an increment Δω for a minimum electromechanical angular velocity at time k emmin (k) Delay one motor inverter controller ADC sampling time T s 。
And S5, determining the minimum value and the maximum value of the increment of the motor rotor position phase angle at the moment k based on the ratio coefficient of the maximum noise of the motor phase angle and the phase angle, and further determining the minimum value and the maximum value of the increment of the motor rotor position phase angle at the moment k-1.
In some alternative embodiments, step S5 further comprises:
and S51, determining the motor rotor position phase angle increment at the moment k according to the motor rotor position phase angle signal at the moment k-1.
The step S51 further comprises a step S511 of obtaining a ratio coefficient eta of the maximum noise of the motor phase angle and the phase angle θ Minimum fluctuation limit value delta of motor phase angle θmin The method comprises the steps of carrying out a first treatment on the surface of the Step S512, calculating the motor rotor position phase angle increment delta theta at the moment k em (k) The calculation formula is as follows:
where pi is the circumference ratio.
Step S52, determining the maximum motor rotor position phase angle increment at the moment k and the minimum motor rotor position phase angle increment at the moment k based on the ratio coefficient of the maximum noise of the motor phase angle and the phase angle, the motor rotor position phase angle increment at the moment k and the minimum value and the maximum value of the motor electric angular velocity prediction increment at the moment k-1.
The step S52 further comprises a step S521 of obtaining a ratio coefficient eta of the maximum noise of the motor phase angle to the phase angle θ Minimum fluctuation limit value delta of motor phase angle θmin The method comprises the steps of carrying out a first treatment on the surface of the Step S522, determining the maximum motor rotor position phase angle increment delta theta at k time emmax (k) And the minimum motor rotor position phase angle delta theta at time k emmin (k) Comprising the following steps:
wherein Δω emm ( a k x -1) predicting the increment, Δω, for the maximum electromechanical angular velocity at time k-1 emmin (k-1) is the minimum electromechanical angular velocity prediction increment, ω, at time k-1 em (k) The electromechanical angular velocity signal at time k determined for step S1.
Step S53, delaying the maximum motor rotor position phase angle increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the maximum motor rotor position phase angle increment at the k-1 moment, and similarly delaying the minimum motor rotor position phase angle increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the minimum motor rotor position phase angle increment at the k-1 moment.
In this step, the maximum motor rotor position phase angle delta theta at time k-1 is calculated emmax (k-1) and a minimum motor rotor position phase angle delta theta at time k-1 emmin (k-1) whose calculation formula is:
wherein Delay Ts [Δθ emmax (k)]To increase the maximum motor rotor position phase angle delta theta at time k-1 emmax (k-1) delaying the sampling time T of the ADC of the motor inverter controller s ，Delay Ts [Δθ emmin (k)]To increase the minimum motor rotor position phase angle delta theta at time k-1 emmin (k-1) delaying the sampling time T of the ADC of the motor inverter controller s 。
S6, taking the minimum value and the maximum value of the motor angular velocity prediction increment at the moment k-1 in the step S4 as a first limit range, and determining a first fault if the motor angular velocity signal increment at the moment k exceeds the first limit range; and similarly, taking the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k-1 in the step S5 as a second limit range, if the motor electric angular velocity signal increment at the moment k exceeds the second limit range, determining a second fault, and jointly determining a motor rotor position fault zone bit by the first fault and the second fault.
In some optional embodiments, in step S6, when the first fault is generated, a first fault flag is set to 1, when the second fault is generated, a second fault flag is set to 1, and a motor rotor position fault flag is determined by and operation of the first fault flag and the second fault flag, where in this embodiment, a motor rotor position fault flag is calculated by a model predictive value estimation method fault The calculation formula of (2) is as follows:
flag fault ＝flag ω &flag θ
wherein, the liquid crystal display device comprises a liquid crystal display device,
and operator.
A second aspect of the present application provides a motor rotor position fault flag determining system corresponding to the above method, mainly including: the electric angular velocity and phase angle acquisition module is used for respectively acquiring electric angular velocity signals of the motor at the moment k-1 and the moment k and position phase angle signals of the motor rotor at the moment k-1 and the moment k, wherein the moment k-1 and the moment k are respectively two sampling points in time sequence; the dq axis component acquisition module is used for acquiring three-phase current of the motor at the moment k and converting the three-phase current into a dq axis component of the motor current; the electromagnetic torque prediction increment calculation module is used for determining the electromagnetic torque prediction increment of the motor at the moment k; the first range calculation module is used for determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k based on the ratio coefficient of the maximum noise of the motor angular velocity to the motor angular velocity, and further determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k-1; the second range calculation module is used for determining the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k based on the ratio coefficient of the maximum noise of the motor phase angle and the phase angle, and further determining the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k-1; the fault zone bit determining module is used for taking the minimum value and the maximum value of the motor electric angular velocity prediction increment at the moment k-1 in the first range calculating module as a first limiting range, and determining a first fault if the motor electric angular velocity signal increment at the moment k exceeds the first limiting range; and similarly, taking the minimum value and the maximum value of the motor rotor position phase angle increment at the k-1 moment in the second range calculation module as a second limit range, if the motor electric angular velocity signal increment at the k moment exceeds the second limit range, determining a second fault, and jointly determining a motor rotor position fault zone bit by the first fault and the second fault.
Fig. 3 to 5 are simulation waveforms when an electrical angular velocity fault occurs in the rotor position of the permanent magnet synchronous motor, the motor controller operates a motor rotor position fault identification method based on model prediction, and at 0.5s, the electrical angular velocity signal of the motor is cut off.
Fig. 3 is a diagram showing the motor electrical angular velocity signal, the motor rotor position phase angle signal, and the motor rotor position fault flag bitmap when the motor rotor position fails, the motor electrical angular velocity signal is cut off at 0.5s, the value drops to 0, the motor rotor position phase angle signal does not change significantly, the invention immediately identifies the motor rotor position fault, and marks the motor rotor position fault at 1.
Fig. 4 is a waveform of a motor rotor position phase angle increment region at a time k when an electric angular velocity fault occurs in a rotor position according to an embodiment of the present invention, wherein an intermediate region between a maximum motor rotor position phase angle increment at a time k-1 and a minimum motor rotor position phase angle increment at a time k-1 is a reasonable operation region of the motor rotor position phase angle increment at the time k, and the motor rotor position phase angle increment at the time k does not exceed a limit region all the time.
Fig. 5 is a waveform of a motor electric angular velocity signal increment region and an amplified waveform at a time k when an electric angular velocity fault occurs in a rotor position according to an embodiment of the present invention, wherein an intermediate region between a maximum motor electric angular velocity increment at a time k-1 and a minimum motor electric angular velocity increment at a time k-1 is a reasonable operation region of the motor electric angular velocity signal increment at a time k, and after a fault occurs in 0.5s, the motor electric angular velocity signal increment at a time k is lower than a motor electric angular velocity prediction increment at a time k-1, and exceeds a limit region.
Fig. 6 to 8 are simulation waveforms when a phase angle fault occurs in the rotor position of the permanent magnet synchronous motor, the motor controller operates a motor rotor position fault identification method based on model prediction, and the rotor position phase angle signal is cut off at 0.6 s.
Fig. 6 is a diagram of the motor electrical angular velocity signal, the motor rotor position phase angle signal, and the motor rotor position fault flag bitmap when the rotor position of the embodiment of the invention has a phase angle fault, the rotor position phase angle signal is cut off at 0.6s, the value suddenly drops to 0, the motor electrical angular velocity signal has no obvious change, the invention immediately identifies the motor rotor position fault, and marks the motor rotor position fault at 1.
FIG. 7 is a waveform of a motor rotor position phase angle increment region and an amplified waveform at a time k when a phase angle fault occurs in a rotor position according to an embodiment of the present invention, wherein an intermediate region between a maximum motor rotor position phase angle increment at a time k-1 and a minimum motor rotor position phase angle increment at a time k-1 is a reasonable operation region of the motor rotor position phase angle increment at the time k, and after a 0.6s fault occurs, a motor electrical angular velocity signal increment at the time k is lower than a motor electrical angular velocity prediction increment at the time k-1, and exceeds a limit region.
Fig. 8 is a waveform of a motor electric angular velocity signal increment region at time k when an electric angular velocity fault occurs in a rotor position according to an embodiment of the present invention, wherein an intermediate region between a maximum motor electric angular velocity increment at time k-1 and a minimum motor electric angular velocity increment at time k-1 is a reasonable operation region of the motor electric angular velocity signal increment at time k, and the motor electric angular velocity signal increment at time k does not exceed a limit region all the time.
Fig. 9 to 10 are simulation waveforms when the electric angular velocity noise of the permanent magnet synchronous motor exceeds the standard, the motor controller runs the motor rotor position fault identification method based on model prediction, and the noise signal is gradually increased after 0.6 s.
Fig. 9 is a diagram of motor electrical angular velocity signal, motor electrical angular velocity noise signal, motor rotor position fault flag bit map when motor electrical angular velocity noise exceeds standard in the embodiment of the invention, the noise signal increases gradually after 0.6s, about 0.62s, after the noise exceeds the limit value, the motor electrical angular velocity signal has obvious noise interference, the invention immediately identifies motor rotor position fault, and marks the motor rotor position fault flag position 1.
In fig. 10, when the motor angular velocity noise exceeds the standard, the waveform and the amplified waveform of the increment region of the motor angular velocity signal at the time k are shown, the middle region of the maximum motor angular velocity increment at the time k-1 and the minimum motor angular velocity increment at the time k-1 is the reasonable operation region of the increment of the motor angular velocity signal at the time k, and the increment of the motor angular velocity signal at the time k is higher than the predicted increment of the motor angular velocity at the time k-1 and exceeds the limit region.
Fig. 11 to 12 are simulation waveforms when the phase angle noise of the rotor position of the permanent magnet synchronous motor exceeds the standard, the motor controller runs the motor rotor position fault identification method based on model prediction, and the noise signal is gradually increased after 0.6 s.
Fig. 11 is a diagram of rotor position phase angle noise signal, motor rotor position phase angle signal, motor rotor position fault flag bit map when rotor position phase angle noise exceeds standard, noise signal increases gradually after 0.6s, about 0.64s, after noise exceeds limit value, motor rotor position phase signal has obvious noise interference, the invention immediately identifies motor rotor position fault, and marks motor rotor position fault flag position 1.
Fig. 12 is a waveform of a motor rotor position phase angle increment region and an amplified waveform at a k time when the rotor position phase angle noise exceeds the standard, wherein an intermediate region of a maximum motor rotor position phase angle increment at a k-1 time and a minimum motor rotor position phase angle increment at a k-1 time is a reasonable operation region of the motor rotor position phase angle increment at the k time, and after a 0.64s fault occurs, the motor electric angular velocity signal increment at the k time is lower than the motor electric angular velocity prediction increment at the k-1 time and exceeds a limit region.
Fig. 13 to 14 are simulation waveforms at the time of sudden increase of load torque of the permanent magnet synchronous motor, and the motor controller runs the motor rotor position fault identification method based on model prediction, and at the time of 6s, the load torque is suddenly increased by 16N.
FIG. 13 is a graph showing the torque, motor rotor position phase angle signal, motor rotor position fault flag bit map when the load torque suddenly increases by 16N, the motor electrical angular velocity signal has a drop amplitude of about 35rad/s, the motor rotor position phase angle signal has no obvious change, the motor rotor position fault flag bit is always not 0, and the load torque change does not interfere with fault identification at 6 s.
Fig. 14 shows a waveform of a motor electric angular velocity signal increment region at the k moment and a waveform of a motor rotor position phase angle increment region at the k moment when the load torque suddenly increases by 16N, wherein the motor rotor position phase angle increment at the k moment and the motor electric angular velocity signal increment at the k moment are always in a reasonable operation region, the limit is not exceeded, and the fault identification effect is not influenced by the load torque fluctuation.
As can be seen from fig. 3 to 14, the present application is directed to a synchronous motor with a position sensor, and by taking noise and load margin into consideration through data characteristics of position signals and rotor external characteristics of the synchronous motor, and according to a model prediction method, predicting an operation area of a rotor position signal, and judging whether the rotor position signal is in a reasonable operation area in real time, thereby realizing a rotor position fault identification function. The algorithm engineering is simple to realize, is convenient to be applied to the switching from a motor with position algorithm to a motor without position algorithm, and realizes fault-tolerant control, so that the safe and reliable operation of a motor control system is ensured.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for determining a motor rotor position failure flag, comprising:
s1, respectively acquiring motor electric angular velocity signals at the moment k-1 and the moment k, and respectively acquiring motor rotor position phase angle signals at the moment k-1 and the moment k, wherein the moment k-1 and the moment k are respectively two sampling points in time sequence;
s2, acquiring three-phase current of the motor at the moment k, and converting the three-phase current into a dq axis component of the motor current;
s3, determining an electromagnetic torque prediction increment of the motor at the moment k;
s4, determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k based on the ratio coefficient of the maximum noise of the motor angular velocity and the electric angular velocity, and further determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k-1;
s5, determining the minimum value and the maximum value of the increment of the motor rotor position phase angle at the moment k based on the ratio coefficient of the maximum noise of the motor phase angle and the phase angle, and further determining the minimum value and the maximum value of the increment of the motor rotor position phase angle at the moment k-1;
s6, taking the minimum value and the maximum value of the motor angular velocity prediction increment at the moment k-1 in the step S4 as a first limit range, and determining a first fault if the motor angular velocity signal increment at the moment k exceeds the first limit range; and similarly, taking the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k-1 in the step S5 as a second limit range, if the motor electric angular velocity signal increment at the moment k exceeds the second limit range, determining a second fault, and jointly determining a motor rotor position fault zone bit by the first fault and the second fault.
2. The motor rotor position failure flag determining method according to claim 1, characterized in that step S3 includes:
s31, determining an electromagnetic torque predicted value at the moment k;
step S32, delaying the electromagnetic torque predicted value at the moment k by one motor inverter controller ADC sampling time, thereby obtaining a fixed electromagnetic torque predicted value at the moment k-1;
and step S33, determining the electromagnetic torque prediction increment of the motor at the time k according to the electromagnetic torque prediction value at the time k and the fixed electromagnetic torque prediction value at the time k-1.
3. The motor rotor position failure flag determining method according to claim 1, characterized in that step S31 includes:
step S311, obtaining the pole pair number parameter p of the motor n Motor flux linkage parameter ψ f D-axis inductance parameter L d And q-axis inductance parameter L q ；
Step S312, determining the electromagnetic torque predicted value T at the k time e (k)：
Wherein I is d (k),I q (k) The motor current dq axis component determined for step S2.
4. The motor rotor position failure flag determining method according to claim 1, characterized in that step S4 further includes:
step S41, determining the increment of the motor electric angular velocity signal at the moment k according to the motor electric angular velocity signal at the moment k-1;
step S42, determining the maximum motor angular velocity prediction increment at the moment k and the minimum motor angular velocity prediction increment at the moment k based on the ratio coefficient of the maximum noise of the motor angular velocity and the electric angular velocity and the motor angular velocity signal increment at the moment k;
step S43, delaying the maximum motor electric angular velocity prediction increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the maximum motor electric angular velocity prediction increment at the k-1 moment, and similarly delaying the minimum motor electric angular velocity prediction increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the minimum motor electric angular velocity prediction increment at the k-1 moment.
5. The motor rotor position failure flag determining method according to claim 4, characterized in that step S42 further includes:
step S421, obtaining the pole pair number parameter p of the motor n The motor moment of inertia parameter J, the motor damping coefficient parameter D and the motor maximum load torque T Lmax Ratio coefficient eta of maximum noise of motor electric angular velocity and electric angular velocity ω Minimum fluctuation limit value delta of motor electric angular velocity ωmin ADC sampling time T of motor inverter controller s ；
Step S422, determining the maximum motor electric angular velocity prediction increment delta omega at the moment k emmax (k) And the minimum electromechanical angular velocity prediction increment delta omega at time k emmin (k) Comprising the following steps:
wherein Δω em (k) The electromechanical angular velocity signal delta, omega at time k determined for step S41 em (k) The electromechanical angular velocity signal at time k determined for step S1.
6. The motor rotor position failure flag determining method according to claim 1, characterized in that step S5 further includes:
step S51, determining the motor rotor position phase angle increment at the moment k according to the motor rotor position phase angle signal at the moment k-1;
step S52, determining the maximum motor rotor position phase angle increment at the moment k and the minimum motor rotor position phase angle increment at the moment k based on the ratio coefficient of the maximum noise of the motor phase angle and the phase angle, the motor rotor position phase angle increment at the moment k and the minimum value and the maximum value of the motor electric angular velocity prediction increment at the moment k-1;
step S53, delaying the maximum motor rotor position phase angle increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the maximum motor rotor position phase angle increment at the k-1 moment, and similarly delaying the minimum motor rotor position phase angle increment at the k moment by one motor inverter controller ADC sampling time, thereby obtaining the minimum motor rotor position phase angle increment at the k-1 moment.
7. The motor rotor position failure flag determining method according to claim 6, characterized in that step S51 further includes:
step S511, obtaining the ratio coefficient eta of the maximum noise of the motor phase angle and the phase angle θ Minimum fluctuation limit value delta of motor phase angle θmin ；
Step S512, calculating the motor rotor position phase angle increment delta theta at the moment k em (k) The calculation formula is as follows:
where pi is the circumference ratio.
8. The motor rotor position failure flag determining method according to claim 6, characterized in that step S52 further includes:
step S521, obtaining the ratio coefficient eta of the maximum noise of the motor phase angle and the phase angle θ Minimum fluctuation limit value delta of motor phase angle θmin ；
Step S522, determining the maximum motor rotor position phase angle increment delta theta at k time emmax (k) And the minimum motor rotor position phase angle delta theta at time k emmin (k) Comprising the following steps:
wherein Δω emm ( a k x -1) predicting the increment, Δω, for the maximum electromechanical angular velocity at time k-1 emmin (k-1) is the minimum electromechanical angular velocity prediction increment, ω, at time k-1 em (k) The k time determined for step S1Is provided.
9. The method of determining a motor rotor position failure flag according to claim 6, wherein in step S6, when the first failure occurs, a first failure flag bit is set to 1, when the second failure occurs, a second failure flag bit is set to 1, and the motor rotor position failure flag bit is determined by the first failure flag bit and the second failure flag bit through an and operation.
10. A motor rotor position fault flag determination system, comprising:
the electric angular velocity and phase angle acquisition module is used for respectively acquiring electric angular velocity signals of the motor at the moment k-1 and the moment k and position phase angle signals of the motor rotor at the moment k-1 and the moment k, wherein the moment k-1 and the moment k are respectively two sampling points in time sequence;
the dq axis component acquisition module is used for acquiring three-phase current of the motor at the moment k and converting the three-phase current into a dq axis component of the motor current;
the electromagnetic torque prediction increment calculation module is used for determining the electromagnetic torque prediction increment of the motor at the moment k;
the first range calculation module is used for determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k based on the ratio coefficient of the maximum noise of the motor angular velocity to the motor angular velocity, and further determining the minimum value and the maximum value of the predicted increment of the motor angular velocity at the moment k-1;
the second range calculation module is used for determining the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k based on the ratio coefficient of the maximum noise of the motor phase angle and the phase angle, and further determining the minimum value and the maximum value of the motor rotor position phase angle increment at the moment k-1;
the fault zone bit determining module is used for taking the minimum value and the maximum value of the motor electric angular velocity prediction increment at the moment k-1 in the first range calculating module as a first limiting range, and determining a first fault if the motor electric angular velocity signal increment at the moment k exceeds the first limiting range; and similarly, taking the minimum value and the maximum value of the motor rotor position phase angle increment at the k-1 moment in the second range calculation module as a second limit range, if the motor electric angular velocity signal increment at the k moment exceeds the second limit range, determining a second fault, and jointly determining a motor rotor position fault zone bit by the first fault and the second fault.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101986552A (en) * | 2010-10-28 | 2011-03-16 | 天津大学 | Rotor current control method of double-fed wind driven generator under power grid faults |
| CN106602942A (en) * | 2017-02-27 | 2017-04-26 | 北京新能源汽车股份有限公司 | Fault processing method and apparatus of motor position detection loop, motor and automobile |
| CN107017810A (en) * | 2017-04-24 | 2017-08-04 | 东南大学盐城新能源汽车研究院 | Permagnetic synchronous motor is without weights model prediction moment controlling system and method |
| CN107134965A (en) * | 2017-04-27 | 2017-09-05 | 滨州学院 | Embedded permanent magnet synchronous rotor position angle method of estimation |
| CN107565865A (en) * | 2017-09-13 | 2018-01-09 | 华中科技大学 | A kind of fault-tolerant double vector prediction control method and device of six-phase permanent-magnet motor |
| CN110460281A (en) * | 2019-03-28 | 2019-11-15 | 南通大学 | The double vector models of three level permanent magnet synchronous motor of one kind predict flux linkage control method |
| CN111431453A (en) * | 2020-05-06 | 2020-07-17 | 南通大学 | Fault-tolerant control method for open-winding permanent magnet synchronous motor based on single-phase fault of inverter |
| CN112886880A (en) * | 2021-03-12 | 2021-06-01 | 南通大学 | Three-level permanent magnet synchronous motor position sensorless model prediction current control method |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8664901B2 (en) * | 2012-02-15 | 2014-03-04 | GM Global Technology Operations LLC | Method and system for estimating electrical angular speed of a permanent magnet machine |
| CN103795306B (en) * | 2014-03-05 | 2015-11-04 | 南车株洲电力机车研究所有限公司 | Based on rotor-position acquisition methods and the device of permanent-magnet synchronous drive system |
-
2021
- 2021-07-12 CN CN202110786390.XA patent/CN114325379B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101986552A (en) * | 2010-10-28 | 2011-03-16 | 天津大学 | Rotor current control method of double-fed wind driven generator under power grid faults |
| CN106602942A (en) * | 2017-02-27 | 2017-04-26 | 北京新能源汽车股份有限公司 | Fault processing method and apparatus of motor position detection loop, motor and automobile |
| CN107017810A (en) * | 2017-04-24 | 2017-08-04 | 东南大学盐城新能源汽车研究院 | Permagnetic synchronous motor is without weights model prediction moment controlling system and method |
| CN107134965A (en) * | 2017-04-27 | 2017-09-05 | 滨州学院 | Embedded permanent magnet synchronous rotor position angle method of estimation |
| CN107565865A (en) * | 2017-09-13 | 2018-01-09 | 华中科技大学 | A kind of fault-tolerant double vector prediction control method and device of six-phase permanent-magnet motor |
| CN110460281A (en) * | 2019-03-28 | 2019-11-15 | 南通大学 | The double vector models of three level permanent magnet synchronous motor of one kind predict flux linkage control method |
| CN111431453A (en) * | 2020-05-06 | 2020-07-17 | 南通大学 | Fault-tolerant control method for open-winding permanent magnet synchronous motor based on single-phase fault of inverter |
| CN112886880A (en) * | 2021-03-12 | 2021-06-01 | 南通大学 | Three-level permanent magnet synchronous motor position sensorless model prediction current control method |
Non-Patent Citations (1)
| Title |
|---|
| 基于高频注入法的船舶电推PMSM低速域转子位置估计;白洪芬;高迪驹;;中国航海(04);全文 * |
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