CN113378351B - On-line intelligent field removing method for satellite attitude sensor measurement data - Google Patents
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Abstract
The online intelligent wild-eliminating method for the satellite attitude sensor measurement data is used for representing the possibility of data jump of each satellite sensor by introducing an attitude sensor data jump probability variable, realizing automatic reasoning and calculation of the satellite sensor data jump abnormal probability, and utilizing a fuzzy logic system to automatically infer the sensor attitude jump probability, avoiding the workload caused by repeated trial and error of parameters such as an alarm threshold value in a conventional method, overcoming the defect of easy misjudgment due to fixed threshold value, and avoiding the difficulty and risk of manually modifying the threshold value by utilizing a remote control instruction during on-orbit operation.
Description
Technical Field
The invention relates to an online intelligent field-picking method for satellite attitude sensor measurement data, and belongs to the field of fault diagnosis of space aircrafts.
Background
When a satellite works in orbit, a plurality of attitude sensors, such as an earth sensor, a sun sensor, a star sensor and the like, are usually arranged, the jump of the output data of the sensors can influence the interpretation and analysis of the data, and in the process of calculating the attitude and orbit of the satellite, the jump of the output data of the sensors can obviously influence the attitude and orbit high-precision control of the satellite, even cause misjudgment and the like. Therefore, accurate elimination of the jump data of the sensor is an urgent problem to be solved in the aspects of real-time or post-processing of spacecraft data, parameter fusion analysis and the like.
In practical engineering application, the current common method is that a satellite presets a corresponding sensor field-picking threshold according to the data output characteristics of a sensor; and if the data measured by the sensor exceeds the threshold value and lasts (or accumulates) for a plurality of sampling periods, determining to jump the sensor data, and performing field picking. This method has the disadvantage that: 1) The setting of the sensor data jump judgment threshold depends on the actual engineering background, and erroneous judgment and missed judgment are easily caused if the threshold is not suitable, so that the application range and effect of the method are greatly restricted. 2) The threshold cannot be automatically adjusted in real time, can be modified only by using a remote control instruction, is complex in operation and has poor adaptability to the system.
Aiming at the defects, the invention provides an online intelligent field-picking method applicable to all the attitude sensor measurement data of satellites by combining the fuzzy logic system with the field-picking method of the sensors based on the background model requirement and utilizing the unique function of the fuzzy logic system, and can realize the real-time intelligent field-picking of the jump data of the sensors.
Disclosure of Invention
The invention solves the technical problems that: aiming at the defects existing in the prior art, an intelligent diagnosis method based on abnormal probability and a fuzzy logic system is provided, the defect that the threshold is fixed and easy to misjudge can be overcome, and meanwhile, the difficulty and risk of manually modifying the threshold by utilizing a remote control instruction during on-orbit running can be avoided.
The invention solves the technical problems by the following technical proposal:
an online intelligent field picking method for satellite attitude sensor measurement data comprises the following steps:
(1) According to the current attitude angle, the angular speed, the reaction wheel rotating speed and the jet control moment of the communication satellite, a satellite dynamics model is established, and an attitude pre-estimation value of a satellite sensor is calculated;
(2) Calculating the front-back beat angle deviation of the satellite sensor according to the measured actual attitude value of the satellite sensor and the estimated value of the satellite sensor obtained in the step (1);
(3) Setting an angle deviation abnormality early warning threshold value, comparing the absolute value of the angle deviation of the satellite sensor obtained in the step (2) with the angle deviation abnormality early warning threshold value, if the absolute value is smaller than the angle deviation abnormality early warning threshold value, no wild value exists, reducing the accumulated number of the angle deviation abnormality early warning by one, otherwise, exceeding the gesture, increasing the accumulated number of the angle deviation abnormality early warning by one, comparing all the data obtained in the step (2), and obtaining the gesture overrun number N of the satellite sensor ESx ；
(4) Establishing a fuzzy logic system, and taking the satellite sensor obtained in the step (2) for angle deviation before and after shooting and the satellite sensor obtained in the step (3) for exceeding the gesture frequency N ESx As the input quantity of the system, acquiring the attitude jump probability P of the sensor;
(5) Comparing the given value range of the sensor attitude jump probability P obtained in the step (4), if the given value range exceeds the given value upper limit, jumping the satellite sensor, and sending out a sensor attitude jump warning through the satellite; if the position of the satellite sensor is lower than the given value lower limit, the satellite sensor does not jump, and the integral initial value of the attitude predicted value of the satellite sensor is updated.
The method for calculating the satellite sensor predicted value comprises the following steps:
wherein I is t Is of satellite type3×3-order inertia matrix, I t ＝(I tx ,I ty ,I tz ) Is a satellite design parameter, h (T) is the angular momentum of the reaction wheel, which is a 3×1 column vector, T d (T) is the disturbance moment to which the satellite is subjected, and is a 3×1 column vector, T c (t) is jet control moment, ω E (t) is the estimated three-axis angular velocity of the satellite, which is 3×1 column vector, ω E (t) triaxial components are ω Ex (t)，ω Ey (t)，ω Ez (t)。
The inertia matrix I t The correction can be carried out through on-orbit calibration, h (T) can be obtained through calculation of the rotation speed of the reaction wheel and the inertia of the reaction wheel, and T d (T) is a slowly decreasing amount, T c (t) is obtained by calculating the thrust force, the jet time and the jet pulse width of the thruster installation matrix and the thruster, and omega E (t) triaxial component omega Ex (t)，ω Ey (t)，ω Ez (t) obtained by calculation of satellite sensor predictive value calculation method, ω E (t) integral calculation to obtain a sensor attitude predicted value S E ，S E The triaxial component is S Ex ，S Ey ，S Ez 。
The front and back beat angle deviation E of the satellite sensor S The calculation method of (2) is as follows:
E S ＝S-S E 。
wherein S is the three-axis attitude angle measured by the sensor, 3X 1 column vector, and the three-axis component is S x ，S y ，S z 。
The fuzzy logic system uses a fuzzy rule base to analyze and project experience, front and back beat angle deviation of the satellite sensor and the out-of-limit times N of the satellite sensor posture according to theory ES Acquiring the attitude jump probability P of the sensor, wherein P is a 3 multiplied by 1 column vector, and the triaxial component is P x ，P y ，P z Respectively representing respective jump probabilities of the XYZ three-axis gestures.
The sensor gesture jump probability P x ，P y ，P z The range of the given value is 0.3 to 0.8.
Compared with the prior art, the invention has the advantages that:
(1) According to the online intelligent field rejection method for the satellite attitude sensor measurement data, provided by the invention, by introducing the sensor data jump probability variable, the probability of each sensor data jump of a satellite is represented, the automatic reasoning calculation of the satellite sensor data jump abnormal probability is realized, the method is more reasonable than a conventional 0/1 type representation method, and the misdiagnosis and missed diagnosis probability is reduced;
(2) The invention utilizes the fuzzy logic system to automatically infer the gesture jump probability of the sensor, and based on the core design process of rule combination of natural language description, the workload caused by repeated trial and error of parameters such as alarm threshold value in the conventional method is avoided, and meanwhile, the invention adopts the table look-up mode to realize the two fuzzy logic systems, has visual physical significance and is convenient and rapid in engineering realization.
Drawings
FIG. 1 is a flow chart of an online intelligent field-picking method for satellite attitude sensor measurement data provided by the invention;
Detailed Description
The method for intelligently picking up the field on line of the measurement data of the satellite attitude sensor overcomes the defects of the existing method for diagnosing the angular velocity abnormality by using a fixed threshold value, provides the method for picking up the field on line of the measurement data of the satellite attitude sensor, can overcome the defect that the threshold value is fixed and easy to misjudge, and avoids the difficulty and risk of manually modifying the threshold value by using a remote control instruction during on-orbit operation, and comprises the following specific steps:
(1) According to the current attitude angle, angular velocity, reaction wheel rotating speed and jet control moment of the communication satellite, a satellite dynamics model is established, and an attitude predicted value S of a satellite sensor is calculated E ；
The method for calculating the estimated value of the satellite sensor comprises the following steps:
wherein I is t Is a 3X 3 order inertia matrix of the satellite, I t ＝(I tx ,I ty ,I tz ) For satellite design parameters, h (t) is the angular momentum of the reaction wheelIs a 3X 1 column vector, T d (T) is the disturbance moment to which the satellite is subjected, 3×1 column vector, T c (t) is jet control moment, 3×1 column vector, ω E (t) is the estimated three-axis angular velocity of the satellite, which is 3×1 column vector, ω E (t) triaxial components are ω Ex (t)，ω Ey (t)，ω Ez (t)；
Inertia matrix I t The correction can be carried out through on-orbit calibration, h (T) can be obtained through calculation of the rotation speed of the reaction wheel and the inertia of the reaction wheel, and T d (T) is a slowly decreasing amount, T c (t) is obtained by calculating the thrust force, the jet time and the jet pulse width of the thruster installation matrix and the thruster, and omega E (t) triaxial component omega Ex (t)，ω Ey (t)，ω Ez (t) obtained by calculation of satellite sensor predictive value calculation method, ω E (t) integral calculation to obtain a satellite sensor attitude predicted value S E ，S E The triaxial component is S Ex ，S Ey ，S Ez 。
(2) Calculating the front-back beat angle deviation of the satellite sensor according to the measured actual attitude value of the satellite sensor and the estimated value of the satellite sensor obtained in the step (1);
wherein, the angle deviation E of front and back beats of the satellite sensor S The calculation method of (2) is as follows:
E S ＝S-S E ；
wherein S is the three-axis attitude angle measured by the sensor, 3X 1 column vector, and the three-axis component is S x ，S y ，S z 。
(3) Setting an angle deviation abnormality early warning threshold value, comparing the absolute value of the angle deviation of the satellite sensor obtained in the step (2) with the angle deviation abnormality early warning threshold value, if the absolute value is smaller than the angle deviation abnormality early warning threshold value, no wild value exists, reducing the number of times of the angle deviation abnormality early warning by one, otherwise, exceeding the limit of the gesture exists, increasing the number of times of the angle deviation abnormality early warning by one, comparing all the data obtained in the step (2), and obtaining the number of times of the gesture overrun N of the satellite sensor ES ，N ES ，N ES For a 3 x 1 column vector, the triaxial component is N ESx ，N ESy ，N ESz Respectively representing the overrun times of the XYZ three-axis gestures;
(4) Establishing a fuzzy logic system, and taking the satellite sensor obtained in the step (2) for angle deviation before and after shooting and the satellite sensor obtained in the step (3) for exceeding the gesture frequency N ES As the input quantity of the system, the attitude jump probability P of the sensor is obtained, wherein P is a 3 multiplied by 1 column vector, and the triaxial component is P x ，P y ，P z Respectively representing respective jump probabilities of XYZ three-axis gestures;
wherein the fuzzy logic system uses a fuzzy rule base to analyze and project experience, front and back beat angle deviation of the satellite sensor and overrun times N of satellite sensor state according to theory ES Acquiring a sensor triaxial attitude jump probability P;
specifically, the fuzzy logic system consists of a fuzzy device, a fuzzy rule base, a fuzzy inference engine and a defuzzifier, wherein the fuzzy rule base is the core of the fuzzy logic system, the defuzzifier is used for restoring a fuzzy set into a true value variable, and the fuzzy inference engine is used for realizing nonlinear mapping from an input domain to an output domain;
(5) Comparing the given value range of the sensor attitude jump probability P obtained in the step (4), if the given value range exceeds the given value upper limit, jumping the satellite sensor, and sending out a sensor attitude jump warning through the satellite; if the three-axis attitude angle S is lower than the given value lower limit, the satellite sensor does not jump, and the three-axis attitude angle S measured by the sensor is used for estimating the attitude predictive value S of the satellite sensor E The integral initial value is updated.
Wherein, the sensor gesture jump probability P x ，P y ，P z The range of the given value is 0.3 to 0.8.
Further description of specific embodiments follows:
in this embodiment, as shown in fig. 1, the method for online intelligent field extraction of satellite sensor measurement data includes 5 steps, and taking the attitude output of an X-axis sun sensor of a certain communication satellite as an example, other sensor attitude jump judging methods are similar, and specific steps are as follows:
(1) Estimating the dynamic posture:
according to the satellite's timeFront attitude angle, angular speed, reaction wheel rotating speed and jet control moment, establishing a satellite dynamics model, and calculating to obtain an x-axis sun sensor predicted value S Ex The method specifically comprises the following steps:
wherein I is t Is a 3X 3 order inertia matrix of the satellite, I t ＝(I tx ,I ty ,I tz ) The satellite design parameters can be corrected through on-orbit calibration; h (t) is the angular momentum of the reaction wheel, 3 x 1 column vectors, and the on-board can be calculated by the rotation speed of the reaction wheel and the rotation inertia of the reaction wheel; t (T) d (T) is the disturbance moment to which the satellite is subjected, 3×1 column vector, due to T d (t) is a slowly decreasing amount, which is negligible in the present invention; t (T) c And (t) is an air injection control moment, and 3 multiplied by 1 column vectors can be calculated by a thruster mounting matrix, the thrust magnitude of a thruster, the air injection time and the air injection pulse width. Omega E (t) is the estimated angular velocity of the satellite triaxial, 3×1 column vector, ω E (t) triaxial components are ω Ex (t)，ω Ey (t)，ω Ez (t) can be calculated by the above extrapolation formula. By para-omega Ex (t) integrating to obtain the estimated value S of the x-axis sun sensor Ex ；
(2) Calculating front-back beat angle deviation E of X-axis sun sensor Sx ：
E Sx ＝S x -S Ex
(3) Calculating the gesture overrun times N of the X-axis sun sensor ESx ：
The angle deviation abnormal early warning threshold is dAlleLimit, is a preset design parameter, is selected to be 0.5 DEG, and the accumulated number of the angle deviation abnormal early warning is cntE SWx The variable initial value is 0;
the method comprises the following steps:
IF1(|E Sx |<da, limit), indicating no wild value,
IF2 cntE SWx >0, let:
cntE SW x＝cntE SWx -1；
END2
ELSE1 means that the attitude difference exceeds the limit, and field picking treatment is carried out:
cntE SWx ＝cntE SWx +1；
END1
(4) Fuzzy logic system design
The domains of input and output variables are determined and corresponding fuzzy sets are defined, wherein the domains of the input and output variables are respectively:
E Sx ＝[0,0.5]，cntE SWx ＝[0,10]，P x ＝[0,1]；
the fuzzy sets are respectively as follows:
E Sx ＝{S2,S1,M,B1,B2}
cntE SWx ＝{S,M,B}
P x ＝{S2,S1,M,B1,B2}
establishing a fuzzy rule base, wherein the fuzzy rule base is described in the form of a fuzzy rule table, as shown in table 1:
the membership function of each variable is determined, and no special requirement is imposed on the membership function of each variable, so that the same membership function is adopted. The membership function is a Gaussian membership function. The expression is as follows:
wherein x is input quantity, c is the mean value of normal distribution of the domain, and sigma is the variance of normal distribution of the domain;
establishing a fuzzy system adopting a single-value fuzzifier, a Mamdani inference engine and a central average defuzzifier,
in the fuzzy inference engine, the inference type adopts a Mamdani fuzzy implication minimum operation method, and an intersection method (a small method) is adopted in the (and) operation, or a merging method (a large method) is adopted in the (also/or) operation, so that a maximum-minimum method is used for synthesis;
(5) Final judgment of solar sensor gesture jump
If P x If the set value exceeds the set value of 0.8, the sensor is regarded as the jump of the sun sensor, and the satellite gives out the gesture jump alarm of the sun sensor; if the jump probability P of the sun sensor x If the value does not exceed the given value of 0.3, the sun sensor is considered to be free from jump, and the initial value of the dynamically extrapolated sensor is updated.
Although the present invention has been described in terms of the preferred embodiments, it is not intended to be limited to the embodiments, and any person skilled in the art can make any possible variations and modifications to the technical solution of the present invention by using the methods and technical matters disclosed above without departing from the spirit and scope of the present invention, so any simple modifications, equivalent variations and modifications to the embodiments described above according to the technical matters of the present invention are within the scope of the technical matters of the present invention.
What is not described in detail in the present specification belongs to the known technology of those skilled in the art.
Claims (5)
1. An online intelligent field removing method for satellite attitude sensor measurement data is characterized by comprising the following steps:
(1) According to the current attitude angle, the angular speed, the reaction wheel rotating speed and the jet control moment of the communication satellite, a satellite dynamics model is established, and an attitude pre-estimation value of a satellite sensor is calculated;
(2) Calculating the front-back beat angle deviation of the satellite sensor according to the measured actual attitude value of the satellite sensor and the estimated attitude value of the satellite sensor obtained in the step (1);
(3) Setting an angle deviation abnormality early warning threshold value, comparing the absolute value of the angle deviation of the satellite sensor obtained in the step (2) with the angle deviation abnormality early warning threshold value, if the absolute value is smaller than the angle deviation abnormality early warning threshold value, no wild value exists, the number of times of the angle deviation abnormality early warning is reduced by one, otherwise, the gesture is overrun, the number of times of the angle deviation abnormality early warning is increased by one, and the satellite sensor is provided with a plurality of sensorsComparing all the data obtained in the step (2), and obtaining the satellite sensor attitude overrun times N ESx ；
(4) Establishing a fuzzy logic system, and taking the satellite sensor obtained in the step (2) for angle deviation before and after shooting and the satellite sensor obtained in the step (3) for exceeding the gesture frequency N ESx As the input quantity of the system, acquiring the attitude jump probability P of the sensor;
(5) Comparing the given value range of the sensor attitude jump probability P obtained in the step (4), if the given value range exceeds the given value upper limit, jumping the satellite sensor, and sending out a sensor attitude jump warning through the satellite; if the position of the satellite sensor is lower than the given value lower limit, the satellite sensor does not jump, and the integral initial value of the attitude predicted value of the satellite sensor is updated;
the attitude pre-estimation value S of the satellite sensor E The calculation method of (2) is as follows:
wherein I is t Is a 3X 3 order inertia matrix of the satellite, I t ＝(I tx ,I ty ,I tz ) Is a satellite design parameter, h (T) is the angular momentum of the reaction wheel, which is a 3×1 column vector, T d (T) is the disturbance moment to which the satellite is subjected, and is a 3×1 column vector, T c (t) is jet control moment, ω E (t) is the estimated three-axis angular velocity of the satellite, which is 3×1 column vector, ω E (t) triaxial components are ω Ex (t)，ω Ey (t)，ω Ez (t)。
2. The online intelligent field picking method for measuring data of satellite attitude sensor according to claim 1, wherein the method comprises the following steps:
the inertia matrix I t The correction can be carried out through on-orbit calibration, h (T) can be obtained through calculation of the rotation speed of the reaction wheel and the inertia of the reaction wheel, and T d (T) is a slowly decreasing amount, T c (t) is obtained by calculating the thrust force, the jet time and the jet pulse width of the thruster installation matrix and the thruster, and omega E (t) triaxial component omega Ex (t)，ω Ey (t)，ω Ez (t) obtained by calculation of satellite sensor predictive value calculation method, ω E (t) integral calculation to obtain a satellite sensor attitude predicted value S E ，S E The triaxial component is S Ex ，S Ey ，S Ez 。
3. The online intelligent field picking method for measuring data of satellite attitude sensor according to claim 2, wherein the method comprises the following steps:
the front and back beat angle deviation E of the satellite sensor S The calculation method of (2) is as follows:
E S ＝S-S E ；
wherein S is the three-axis attitude angle measured by the sensor, 3X 1 column vector, and the three-axis component is S x ，S y ，S z 。
4. The online intelligent field picking method for measuring data of satellite attitude sensor according to claim 1, wherein the method comprises the following steps:
the fuzzy logic system uses a fuzzy rule base to analyze and project experience, front and back beat angle deviation of the satellite sensor and the out-of-limit times N of the satellite sensor posture according to theory ES Acquiring the attitude jump probability P of the sensor, wherein P is a 3 multiplied by 1 column vector, and the triaxial component is P x ，P y ，P z Respectively representing respective jump probabilities of the XYZ three-axis gestures.
5. The online intelligent field picking method for measuring data of satellite attitude sensor according to claim 1, wherein the method comprises the following steps:
the sensor gesture jump probability P x ，P y ，P z The range of the given value is 0.3 to 0.8.
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