A signal voting method of FADEC system based on deviation feedback

Abstract

The application relates to the technical field of FADEC system signal processing, and particularly discloses a FADEC system signal voting method based on deviation feedback, which comprises the following steps: obtaining an engine expected working state interval of a current period, an engine actual working state of the current period and a signal voting result of a previous period; calculating an engine control deviation of the current period according to the engine expected working state interval of the current period and the engine actual working state of the current period; calculating an adjustment amount of the signal voting result of the previous period according to the engine control deviation of the current period, and adjusting the signal voting result of the previous period according to the adjustment amount to obtain an adjusted signal voting result of the previous period; calculating an adjusted signal voting weight of the previous period according to the adjusted signal voting result of the previous period, and taking the adjusted signal voting weight of the previous period as a signal voting weight of the current period to realize the update of the signal voting weight; calculating a signal voting result of the current period according to the collected signals of each sensor of the current period and the signal voting weight of the current period; and controlling the engine working state of the current period according to the signal voting result of the current period. The application can dynamically adjust the signal voting weight according to the engine control deviation, form a voting result beneficial to the engine operation, ensure that the overall engine control meets the expectation, and further guarantee the safety of the engine and the airplane.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of FADEC system signal processing technology, and more particularly, to a FADEC system signal voting method based on deviation feedback. BACKGROUND

[0002] FADEC (Full Authority Digital Electronic Control) system as a key subsystem of aero-engine, contains sensors, servo mechanisms, digital electronic controllers and other main components. In the process of engine operation, FADEC system is responsible for receiving aircraft instructions, comprehensively considering engine inlet conditions and operation limits, calculating the expected state of the engine. At the same time, FADEC system identifies the current state of the engine based on the collected signals of the sensors, and based on the deviation between the expected state and the current state of the engine, the control unit performs control law calculation to adjust the working position of the servo mechanism, so as to change the working state of the engine to meet the flight needs. In this process, the signal acquisition and processing module plays an important role. FADEC system collects signals such as engine speed, temperature, pressure and servo mechanism position through sensors to judge the running environment and working state of the engine, so as to execute reasonable control strategy. If the signal acquisition deviates, it will directly lead to the misjudgment of FADEC system, and the execution of wrong control instructions, which will cause the abnormal control of the engine, and even endanger the safety of the engine and the aircraft.

[0003] With the continuous improvement of engine indicators, the function of FADEC system is becoming more and more complex, and the reliability requirement of the collected signals is also getting higher and higher. In order to ensure the safe operation of the engine, FADEC system generally designs redundant sensors to collect the same signal. The collected signals of each sensor are converted and processed to form pre-voting signals, which are integrated through voting algorithm to obtain the final voting result for control.

[0004] Due to the differences in sensor characteristics and installation positions, different sensors have certain differences in collecting the same object, so a suitable algorithm needs to be designed for signal voting, otherwise the voting result for control will deviate from the actual situation, which will cause the engine to work in an unexpected state. SUMMARY

[0005] In view of the above-mentioned drawbacks in the prior art, the present application provides a FADEC system signal voting method based on deviation feedback to solve the problem of voting of redundant acquisition signals of FADEC system, which can adjust the signal voting weight in real time according to the engine control deviation, realize the effective integration of redundant sensor signals, and ensure that the overall control of the engine meets the expectation.

[0006] As a first aspect of the present application, a FADEC system signal voting method based on deviation feedback is provided, comprising the following steps:

[0007] Step S1: obtaining an engine expected working state interval of a current cycle, an engine actual working state of the current cycle, and a signal voting result of a previous cycle; wherein the signal voting result of the previous cycle is calculated according to collected signals of each sensor of the previous cycle and signal voting weights of the previous cycle;

[0008] Step S2: calculating an engine control deviation of the current cycle according to the engine expected working state interval of the current cycle and the engine actual working state of the current cycle;

[0009] Step S3: calculating an adjustment amount of the signal voting result of the previous cycle according to the engine control deviation of the current cycle, and adjusting the signal voting result of the previous cycle according to the adjustment amount to obtain an adjusted signal voting result of the previous cycle;

[0010] Step S4: calculating an adjusted signal voting weight of the previous cycle according to the adjusted signal voting result of the previous cycle, and taking the adjusted signal voting weight of the previous cycle as a signal voting weight of the current cycle to realize updating of the signal voting weight;

[0011] Step S5: calculating a signal voting result of the current cycle according to collected signals of each sensor of the current cycle and the signal voting weight of the current cycle;

[0012] Step S6: controlling an engine working state of the current cycle according to the signal voting result of the current cycle.

[0013] Further, the obtaining of the engine expected working state interval of the current cycle further includes the following steps:

[0014] determining the engine expected working state interval e0 of the current cycle according to an airplane instruction of the current cycle, an engine working environment, and an engine working constraint;

[0015] wherein any one engine expected working state e i is a state space composed of an engine speed expected value, an engine pressure ratio expected value, and an engine exhaust temperature expected value.

[0016] Further, the calculation of the engine control deviation of the current cycle according to the engine expected working state interval of the current cycle and the engine actual working state of the current cycle further includes the following steps:

[0017] The calculation formula of the engine control deviation Δe of the current cycle is as follows:

[0018]

[0019] Wherein, e is the current cycle engine actual working state, when the engine actual working state e is in the engine expected working state interval e0, Δe = 0.

[0020] Further, the adjustment amount of the signal voting result of the last cycle is calculated according to the engine control deviation of the current cycle, and the signal voting result of the last cycle is adjusted according to the adjustment amount, to obtain the adjusted signal voting result of the last cycle, and the method further comprises the following steps:

[0021] The calculation formula of the adjustment amount Δv of the signal voting result of the last cycle is as follows:

[0022] Δv = k·Δe

[0023] Wherein, k represents the adjustment step;

[0024] The calculation formula of the adjusted signal voting result v + of the last cycle is as follows:

[0025] v + = v 0 + Δv

[0026] Wherein, v 0 is the signal voting result of the last cycle.

[0027] Further, the adjusted signal voting weight of the last cycle is calculated according to the adjusted signal voting result of the last cycle, and the adjusted signal voting weight of the last cycle is taken as the signal voting weight of the current cycle, to realize the update of the signal voting weight, and the method further comprises the following steps:

[0028] The calculation formula of the adjusted signal voting weight u + of the last cycle is as follows:

[0029]

[0030] Wherein, A = [s 0 1 D] T , b = [v + 1d] T , s 0 is the collected signal of each sensor of the last cycle, 1 ∈ R n×1 , D ∈ R n ×m is a predefined projection matrix, d ∈ R 1×m is a corresponding projection length constraint vector, D and d jointly represent the distribution coefficients of the signal voting weight in different signal dimensions, and m is the dimension of the distribution coefficients.

[0031] the signal voting weight of the last period is adjusted as the signal voting weight u of the current period to realize the update of the signal voting weight. + the signal voting weight of the last period is adjusted as the signal voting weight u of the current period to realize the update of the signal voting weight.

[0032] Further, the signal voting result of the current period is calculated according to the collected signals of each sensor of the current period and the signal voting weight of the current period, and further comprises the following steps:

[0033] The calculation formula of the signal voting result v of the current period is as follows:

[0034] v = s T ·u

[0035] Wherein, s T is the collected signal of each sensor of the current period, and u is the signal voting weight of the current period.

[0036] Further, the collected signal s of each sensor of the current period is s n ] T , and the signal voting weight u of the current period is u n ] T ; wherein s1, s2, …, s n is the collected value of each sensor collecting the same physical signal of the current period; and u1, u2, …, u n is the voting weight of the collected value of each sensor of the current period.

[0037] The signal voting method of the FADEC system based on deviation feedback provided by the application has the following advantages:

[0038] (1) The method has strong adaptability, only needs to determine the qualitative influence of the collected signal on the engine control, does not depend on the accurate mathematical model, and has wide applicability;

[0039] (2) When each redundancy collected signal is consistent, the voting result of the method is not sensitive to the voting weight, the voting result is consistent with the collected result of each redundancy, and is beneficial to the system stability;

[0040] (3) When each redundancy collected signal is quite different, the voting result obtained by adjusting the voting weight can control the engine in the expected state, which is beneficial to the safety of the engine. BRIEF DESCRIPTION OF DRAWINGS

[0041] The drawings are used to provide further understanding of the application, and constitute a part of the specification, and are used to explain the application together with the following specific embodiments, but do not constitute a limitation to the application.

[0042] Figure 1The flow chart of the FADEC system signal voting method based on deviation feedback provided by the present application is shown in the figure.

[0043] Figure 2 The embodiment of the FADEC system signal voting method based on deviation feedback provided by the present application is shown in the figure.

[0044] Figure 3 The schematic diagram of the FADEC system applying the present method is shown in the figure.

[0045] Figure 4 The specific schematic diagram of the FADEC system applying the present method is shown in the figure.

[0046] Figure 5 The schematic diagram of the engine speed, fuel flow and voting weight changing with time provided by the present application is shown in the figure. EMBODIMENT

[0047] In order to further clarify the technical means and effects of the present application for achieving the predetermined purposes, the specific embodiments, structures, features and effects of the FADEC system signal voting method based on deviation feedback provided by the present application are described in detail below in combination with the accompanying drawings and preferred embodiments. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0048] In the present embodiment, a FADEC system signal voting method based on deviation feedback is provided, which comprises the following steps as shown in the figure. Figure 1

[0049] Step S1: obtaining the engine expected working state interval of the current period, the engine actual working state of the current period and the signal voting result of the previous period; wherein the signal voting result of the previous period is calculated according to the collected signals of each sensor of the previous period and the signal voting weight of the previous period;

[0050] Preferably, as shown in the figure, the obtaining of the engine expected working state interval of the current period further comprises the following steps: Figure 2

[0051] The FADEC system controls the engine by comprehensively considering the aircraft command, engine working environment and engine working constraints. According to the aircraft command, engine working environment and engine working constraints of the current period, the engine expected working state interval e0 of the current period is determined; wherein e0 can be obtained by engine design parameters or test data;

[0052] ​​Among them, any engine expected operating state e in the engine expected operating state interval e0 i It is a state space consisting of the expected engine speed, the expected engine pressure ratio, and the expected engine exhaust temperature.

[0053] For example, such as Figure 4 As shown, the engine speed control planning module of the FADEC system obtains the expected engine speed n for the current period based on the aircraft command. dem The FADEC system collects the actual engine speed value n for the current cycle, and obtains the fuel flow rate values ​​s1 and s2 through sensors 1 and 2, respectively. The expected engine operating state range e0 is represented by the expected engine speed range n0, and is defined as: e0 = {n0 || n0 - n dem |≤0.01}, where n0 represents the expected engine speed range. Without loss of generality, in this example, the expected engine speed value n is taken. dem =0.

[0054] Step S2: Calculate the engine control deviation for the current cycle based on the expected engine operating state range and the actual engine operating state for the current cycle.

[0055] Preferably, the step of calculating the engine control deviation for the current period based on the expected engine operating state range and the actual engine operating state for the current period further includes the following steps:

[0056] The formula for calculating the engine control deviation Δe in the current cycle is as follows:

[0057]

[0058] Where e represents the actual operating state of the engine in the current cycle, and Δe = 0 when the actual operating state e is within the expected operating state range e0.

[0059] For example, such as Figure 4 As shown, the actual engine speed n = the actual engine operating state e. Under normal circumstances, through the adjustment of the FADEC system, the actual engine speed n should be within the expected engine operating state range e0, i.e., Δe = 0. If sensor 1 or sensor 2 malfunctions, it will cause a deviation in the engine fuel flow control of the current cycle, which will eventually lead to a deviation in the engine speed control of the current cycle. At this time, the engine speed control deviation Δe of the current cycle is calculated.

[0060] Step S3: calculating an adjustment amount of the signal voting result of the previous cycle according to the engine control deviation of the current cycle, and adjusting the signal voting result of the previous cycle according to the adjustment amount to obtain an adjusted signal voting result of the previous cycle;

[0061] Preferably, the step of calculating the adjustment amount of the signal voting result of the previous cycle according to the engine control deviation of the current cycle, and adjusting the signal voting result of the previous cycle according to the adjustment amount to obtain an adjusted signal voting result of the previous cycle further comprises the following steps:

[0062] determining the adjustment amount Δv of the signal voting result of the previous cycle according to the influence of the signal voting result of the previous cycle on the engine actual working state e of the current cycle; the calculation formula of the adjustment amount Δv of the signal voting result of the previous cycle is as follows:

[0063] Δv=k·Δe

[0064] wherein k represents an adjustment step; for example, k=1;

[0065] the calculation formula of the adjusted signal voting result v + of the previous cycle is as follows:

[0066] v + =v 0 +Δv

[0067] wherein v 0 is the signal voting result of the previous cycle.

[0068] Step S4: calculating an adjusted signal voting weight of the previous cycle according to the adjusted signal voting result of the previous cycle, and taking the adjusted signal voting weight of the previous cycle as a signal voting weight of the current cycle to realize the update of the signal voting weight;

[0069] Preferably, the step of calculating an adjusted signal voting weight of the previous cycle according to the adjusted signal voting result of the previous cycle, and taking the adjusted signal voting weight of the previous cycle as a signal voting weight of the current cycle to realize the update of the signal voting weight further comprises the following steps:

[0070] the calculation formula of the adjusted signal voting weight u + of the previous cycle is as follows:

[0071]

[0072] wherein A=[s 0 1 D] T , b=[v + 1d]T , s 0 is the collection signal of each sensor in the last period, 1 ∈ R n×1 , D ∈ R n ×m is a predefined projection matrix, d ∈ R 1×m is a corresponding projection length constraint vector, D and d jointly represent the allocation coefficient of the signal voting weight in different signal dimensions, and m is the dimension of the allocation coefficient.

[0073] For example, as shown in Figure 4 , s 0 is the collection signal of sensor 1 and sensor 2 in the last period, 1 ∈ R 1×1 , D = O is a null matrix, and d = O is a null matrix, that is, no additional constraint is made on the voting weight of sensor 1 and sensor 2.

[0074] The adjusted signal voting weight u + of the last period is taken as the signal voting weight u of the current period, so as to realize the update of the signal voting weight.

[0075] Step S5: calculating the signal voting result of the current period according to the collection signal of each sensor in the current period and the signal voting weight of the current period;

[0076] Preferably, the calculation of the signal voting result of the current period according to the collection signal of each sensor in the current period and the signal voting weight of the current period further comprises the following steps:

[0077] The calculation formula of the signal voting result v of the current period is as follows:

[0078] v = s T ·u

[0079] Wherein, s is the collection signal of each sensor in the current period, and u is the signal voting weight of the current period.

[0080] Specifically, the collection signal s of each sensor in the current period is s = [s1 s2...s n ] T , and the signal voting weight u of the current period is u = [u1 u2...u n ] T ; wherein, s1, s2,..., s n are the collection values of each sensor collecting the same physical signal (such as engine speed, temperature, pressure or displacement signal) in the current period; u1, u2,..., u n are the voting weights of the collection values of each sensor.

[0081] For example, as shown in Figure 4As shown, s is the current cycle sensor 1, sensor 2 signal acquisition.

[0082] Step S6: according to the current cycle signal voting results of the current cycle engine operating state control.

[0083] In this embodiment, as Figure 5 As shown, after t = 0.1s, the sensor 2 fuel flow acquisition value s2 error occurs, the fuel flow acquisition value s2 is always greater than the fuel flow true value 0.2, through the voting algorithm of the application, the voting weight u of s1, s2 is dynamically adjusted, the current cycle fuel flow voting result v is close to the fuel flow true value, and finally the engine speed actual value meets the expectation.

[0084] It should be noted that during the operation of the engine, multiple sensors are used to collect the same physical signal, and the voting method provided by the application is used to integrate the acquisition values of multiple sensors into a signal voting result for participating in engine control.

[0085] As Figure 3 As shown, in each operating cycle of the FADEC system, the above steps S1 to S6 are executed. When the engine actual operating state e is located in the interval e0, it indicates that the engine control is normal, and the voting result v of the signal s reflects the engine actual operating state better; at this time, since Δe = 0, v + = v 0 , the voting weight u is unchanged. When the engine control deviates, Δe ≠ 0, the feedback adjustment plays a role, v + ≠ v 0 , the voting weight u is adjusted, the signal voting result v is changed, and then the control output of the FADEC system and the engine state are changed, so that Δe is reduced, and finally Δe = 0, at this time, the engine actual operating state e is located in the interval e0, and the voting weight u is stopped adjusting.

[0086] As Figure 4 As shown, the speed control plan module of the FADEC system obtains the engine speed expected value n dem of the current cycle according to the aircraft instruction, the FADEC system acquires the engine speed actual value n of the current cycle, and the speed control module adjusts the fuel flow expected value Wf dem according to the engine speed expected value n dem and the engine speed actual value n. The FADEC system obtains the fuel flow acquisition value s1, s2 through the sensor 1, sensor 2 respectively, and integrates the fuel flow acquisition value s1, s2 into the signal voting result v of the current cycle through the signal voting method of the application, and the fuel control module adjusts the fuel flow expected value Wf demThe deviation of the signal voting result v of the current cycle adjusts the control current i, so that the fuel flow Wf actually output by the fuel metering device meets the expectation, and finally the engine speed control meets the expectation.

[0087] The above is only the preferred embodiment of the present application, and does not limit the present application in any form. Although the present application has been disclosed as above with the preferred embodiment, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, without departing from the technical solution of the present application. Any simple modification, equivalent change and modification of the above embodiments according to the technical essence of the present application, which does not depart from the technical solution of the present application, still belongs to the scope of the technical solution of the present application.

Claims

1. A signal voting method for a FADEC system based on deviation feedback, characterized in that, Includes the following steps: Step S1: Obtain the expected operating state range of the engine in the current cycle, the actual operating state of the engine in the current cycle, and the signal voting result of the previous cycle; wherein, the signal voting result of the previous cycle is calculated based on the collected signals of each sensor in the previous cycle and the signal voting weight of the previous cycle. Step S2: Calculate the engine control deviation for the current cycle based on the expected engine operating state range and the actual engine operating state for the current cycle. Step S3: Calculate the adjustment amount of the signal voting result of the previous cycle based on the engine control deviation of the current cycle, and adjust the signal voting result of the previous cycle according to the adjustment amount to obtain the adjusted signal voting result of the previous cycle. Step S4: Calculate the adjusted signal voting weight of the previous period based on the adjusted signal voting result of the previous period, and use the adjusted signal voting weight of the previous period as the signal voting weight of the current period to update the signal voting weight. Step S5: Calculate the signal voting result for the current period based on the acquired signals from each sensor in the current period and the signal voting weight for the current period; Step S6: Control the engine operating status of the current cycle based on the signal voting results of the current cycle.

2. The FADEC system signal voting method based on deviation feedback according to claim 1, characterized in that, The process of obtaining the expected operating state range of the engine in the current cycle also includes the following steps: Based on the aircraft commands, engine operating environment, and engine operating constraints of the current cycle, the expected engine operating state range e0 for the current cycle is determined. Among them, any engine expected operating state e in the engine expected operating state interval e0 i It is a state space consisting of the expected engine speed, the expected engine pressure ratio, and the expected engine exhaust temperature.

3. The FADEC system signal voting method based on deviation feedback according to claim 2, characterized in that, The step of calculating the engine control deviation for the current period based on the expected engine operating state range and the actual engine operating state for the current period further includes the following steps: The formula for calculating the engine control deviation Δe in the current cycle is as follows: Where e represents the actual operating state of the engine in the current cycle, and Δe = 0 when the actual operating state e is within the expected operating state range e0.

4. The FADEC system signal voting method based on deviation feedback according to claim 3, characterized in that, The step of calculating the adjustment amount of the signal voting result of the previous cycle based on the engine control deviation of the current cycle, and adjusting the signal voting result of the previous cycle according to the adjustment amount to obtain the adjusted signal voting result of the previous cycle, further includes the following steps: The formula for calculating the adjustment amount Δv of the signal voting result of the previous cycle is as follows: Δv=k·Δe Where k represents the adjustment step size; The adjusted signal voting result v of the previous cycle + The calculation formula is as follows: v + =v 0 +Δv Among them, v 0 This is the result of the signal voting from the previous cycle.

5. The FADEC system signal voting method based on deviation feedback according to claim 4, characterized in that, The step of calculating the adjusted signal voting weight for the previous period based on the adjusted signal voting results of the previous period, and using the adjusted signal voting weight for the previous period as the signal voting weight for the current period to update the signal voting weight, further includes the following steps: The adjusted signal voting weight u from the previous cycle + The calculation formula is as follows: Where, A = [s 0 1 D] T b = [v + 1 d] T s 0 The signals acquired by each sensor in the previous cycle, 1∈R n×1 , D∈R n ×m Let d ∈ R be a predefined projection matrix. 1×m Let D be the corresponding projection length constraint vector, and let d be the distribution coefficient of the signal voting weights in different signal dimensions. m is the dimension of the distribution coefficients. The adjusted signal voting weight u from the previous cycle + The signal voting weight u is used as the current cycle's signal voting weight to update the signal voting weight.

6. The FADEC system signal voting method based on deviation feedback according to claim 5, characterized in that, The step of calculating the signal voting result for the current period based on the acquired signals of each sensor in the current period and the signal voting weights for the current period also includes the following steps: The formula for calculating the signal voting result v of the current period is as follows: v=s T ·u Among them, s T denoted as , where is the acquisition signal of each sensor in the current period, and u is the signal voting weight in the current period.

7. The FADEC system signal voting method based on deviation feedback according to claim 6, characterized in that, The acquisition signals s = [s1 s2 ... s] of each sensor in the current period n ] T The signal voting weight for the current period is u = [u1u2...u...]. n ] T ; where s1, s2, ..., s n The values ​​of the same physical signal collected by each sensor in the current period; u1, u2, ..., u n The voting weights are the values ​​collected by each sensor in the current period.

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