Engine thrust measurement method based on acceleration measurement signal
By acquiring multi-point acceleration signals in the engine thrust measurement system, a three-degree-of-freedom model was established to identify damping and stiffness characteristics, thus solving the problem of large thrust measurement error under dynamic conditions in traditional models and achieving higher precision thrust measurement.
Patent Information
- Application Number
- CN202511274141.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-08
- Publication Date
- 2025-12-23
AI Technical Summary
Existing technologies have large thrust measurement errors during engine dynamic processes. Traditional single-degree-of-freedom models are difficult to accurately capture real thrust changes, especially under unsteady flow and high-frequency vibration conditions.
By installing multiple acceleration sensors in the engine thrust measurement system, multi-point acceleration signals are collected, a spring oscillator model of a three-degree-of-freedom system is established, and the damping and stiffness characteristic matrices are identified using a time series inversion algorithm, thus constructing a multi-degree-of-freedom measurement model that more closely resembles the actual physical process.
It significantly reduces measurement errors during dynamic processes, improves the accuracy and reliability of thrust measurement, and provides a high-precision theoretical basis for engine design optimization and fault diagnosis.
Smart Images
Figure CN121185488A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of aero-engine technology, and in particular to an engine thrust measurement method based on acceleration measurement signals. Background Technology
[0002] As the core component of a power system, the engine's performance and reliability directly affect the system's performance and safety. Thrust measurement is a crucial step in evaluating engine performance. Accurately acquiring thrust characteristic data under different operating conditions is of great significance for engine design optimization, performance verification, and fault diagnosis. Under the aerodynamic, thermodynamic, and dynamic load conditions of real flight environments, the system can reproduce and test the engine's operating state under complex conditions. Complex engine testing measurement systems typically consist of key components such as dynamic and fixed frames, a cabin, and an exhaust diffuser, enabling full-state testing of the engine while controlling parameters such as temperature, pressure, and airflow velocity.
[0003] In existing technologies, thrust measurement generally employs a single-degree-of-freedom assumption model based on the relationship between the moving and fixed frame structures. This model mounts the engine on the moving frame and measures thrust output through the mechanical relationship between the engine and the fixed support. This simplified model can meet engineering requirements in steady-state thrust measurement and static thrust calibration, possessing a certain level of accuracy and practicality. However, in practical applications, especially when the engine undergoes complex dynamic processes, traditional measurement methods reveal numerous shortcomings. Because these processes are accompanied by intense unsteady flows, high-frequency vibrations, and structural dynamic responses, traditional single-degree-of-freedom models struggle to accurately capture real thrust changes, leading to significant measurement errors.
[0004] Therefore, a more accurate thrust measurement method is urgently needed to effectively identify system characteristic parameters. This is particularly important for the thrust response of an engine under dynamic operating conditions. This requires establishing a measurement model that more closely approximates the actual physical process. Establishing a more accurate measurement model necessitates precisely identifying the stiffness and damping characteristics of the test bench system under multi-degree-of-freedom conditions, thereby improving the accuracy and reliability of thrust measurement. Summary of the Invention
[0005] In view of this, this application provides an engine thrust measurement method based on acceleration measurement signals. The aim is to identify the dynamic characteristic parameters of the platform system by collecting and analyzing multi-point acceleration signals during engine operation, and apply them to the thrust measurement model, thereby improving the accuracy and adaptability of thrust measurement in engine testing.
[0006] This application provides a method for measuring engine thrust based on acceleration measurement signals, the method comprising: Based on the structural form of the engine thrust measurement system and the factors affecting thrust, an oscillator model of the spring of the three-degree-of-freedom system of the engine thrust measurement bench is established; Accelerometers were fixed on the cabin, moving frame, and exhaust diffuser components, respectively. Accelerometers were also installed on the excitation device to collect cabin acceleration, moving frame acceleration, exhaust diffuser acceleration, and excitation acceleration, respectively. Timing processing was performed on the cabin acceleration, moving frame acceleration, exhaust diffuser acceleration, and acquired excitation acceleration, respectively. Based on the time-series processed data and the spring oscillator model, the damping characteristic matrix and stiffness characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement test bench are solved by the time series inversion algorithm. Engine thrust measurement is performed based on damping characteristic matrix and stiffness characteristic matrix.
[0007] According to a specific implementation of an embodiment of this application, the expression for the oscillator model of the spring is: , Among them, R m The excitation force is given by a moving frame with mass m. ms The mass of the cabin is m tc The mass of the exhaust diffuser is m ed The damping of the moving frame is C. ms The cabin damping is C tc The exhaust diffuser damping is C. ed The stiffness of the moving frame is K. ms The cabin stiffness is K. tc The exhaust diffuser stiffness is K. ed The acceleration of the moving frame is a ms The cabin acceleration is a tc The acceleration of the exhaust diffuser is a. ed The moving frame speed is v ms The cabin speed is v tc The exhaust diffuser speed is v ed The displacement of the moving frame is x ms The displacement of the cabin is x tc The displacement of the exhaust diffuser is x ed .
[0008] According to a specific implementation of an embodiment of this application, the timing processing of the cabin acceleration, moving frame acceleration, exhaust diffuser acceleration, and acquired excitation acceleration includes: The excitation acceleration is discretized into multiple time points according to the smallest time unit 1,...,k-1,k that is less than or equal to the equal sampling time interval, where k is the kth sampling time point; The cabin acceleration is discretized into multiple time-time cabin accelerations according to the smallest time unit 1,...,k-1,k, which is less than or equal to the average sampling time interval; Discretize the moving frame acceleration into multiple moments according to the smallest time unit 1,...,k-1,k that is less than or equal to the equal sampling time interval; The exhaust diffuser acceleration is discretized into multiple time-time exhaust diffuser accelerations based on the smallest time unit 1,...,k-1,k, which is less than or equal to the equal sampling time interval.
[0009] According to a specific implementation of an embodiment of this application, the plurality of time-series excitation accelerations collected include the excitation acceleration a collected at the current time. m (k) Excitation acceleration a collected at the previous moment m (k-1), the excitation acceleration a is collected in the first two time moments. m (k-2), the multiple time-lapse cabin accelerations include the current time-lapse cabin acceleration a. tc (k) The acceleration of the cabin at the previous moment, a tc (k-1) and the cabin acceleration a at the first two time points tc (k-2), the multiple moments of the moving frame acceleration include the current moment's moving frame acceleration a ms (k) Acceleration of the moving frame at the previous moment a ms (k-1) and the acceleration a of the moving frame at the first two moments ms (k-2), the multiple time-lapse diffuser accelerations include the current time-lapse diffuser acceleration a. ed (k) Acceleration of the exhaust diffuser at the previous moment a ed (k-1) and the exhaust diffuser acceleration a at the first two time points ed (k-2).
[0010] According to a specific implementation of an embodiment of this application, based on the time-series processed data and the oscillator model of the spring, the damping characteristic matrix and stiffness characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement rig are solved using a time series inversion algorithm, including: The input vector of the time series inversion algorithm is constructed based on the excitation acceleration collected at multiple times, and the output vector of the time series inversion algorithm is constructed based on the cabin acceleration, moving frame acceleration, and exhaust diffuser acceleration at multiple times. Based on the input vector and output vector, and the time series identification formula based on the time series inversion algorithm, multiple coefficient matrices are solved by the least squares method. Based on multiple coefficient matrices and the oscillator model of the spring, matrix transformation is performed to obtain the damping mass ratio matrix and the stiffness mass ratio matrix. Based on the mass of the moving frame, the mass of the cabin, the mass of the exhaust diffuser, and the damping mass ratio matrix, the damping characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement bench is obtained. Based on the mass of the moving frame, the mass of the cabin, the mass of the exhaust diffuser, and the stiffness-mass ratio matrix, the stiffness characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement bench is obtained.
[0011] According to a specific implementation of this application, the expression for the input vector of the time series inversion algorithm is: , in, The input vector at the current time. The input vector from the previous time step. These are the input vectors for the first two time steps.
[0012] According to a specific implementation of an embodiment of this application, the expression for the output vector of the time series inversion algorithm is: , in, Output the vector for the current time step. The output vector from the previous time step. This is the output vector for the first two time steps.
[0013] According to a specific implementation of an embodiment of this application, the expression of the time series identification formula is: , Where A1 is the first coefficient matrix, A2 is the second coefficient matrix, B is the third coefficient matrix, D1 is the fourth coefficient matrix, and D2 is the fifth coefficient matrix.
[0014] According to a specific implementation of an embodiment of this application, the calculation process of the matrix transformation includes: , , , , Where I is a third-order identity matrix, E c G is the first intermediate matrix. c X is the second intermediate matrix. c Z is the third intermediate matrix. c S1 is the fourth intermediate matrix, S2 is the fifth intermediate matrix, S3 is the sixth intermediate matrix, K0 is the stiffness-to-mass ratio matrix, and C0 is the damping-to-mass ratio matrix.
[0015] According to a specific implementation of this application, the formula for calculating the damping characteristic matrix is: , The formula for calculating the stiffness characteristic matrix is: , Where C is the damping characteristic matrix and K is the stiffness characteristic matrix.
[0016] Beneficial effects: The engine thrust measurement method based on acceleration measurement signals in this application overcomes the limitations of traditional single-degree-of-freedom assumption models. By real-time acquisition and analysis of multi-point acceleration signals, it can identify the dynamic characteristic parameters (such as stiffness and damping) of the test bench system, thereby constructing a multi-degree-of-freedom measurement model that more closely resembles the real physical process. Compared to traditional methods that suffer from thrust measurement errors due to structural dynamic response and high-frequency vibration under dynamic conditions, this method can effectively identify and compensate for the coupling effect of the test bench system itself, significantly reducing errors caused by structural hysteresis or nonlinear characteristics during dynamic processes, and improving the accuracy and reliability of dynamic thrust measurement. This invention fills the technical gap in parameter identification in the field of dynamic thrust measurement and lays a high-precision, highly adaptable theoretical and practical foundation for engine design optimization, fault diagnosis, and performance verification, possessing significant engineering value and promising industry application prospects. Attached Figure Description
[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is a schematic diagram of an engine thrust measurement method based on acceleration measurement signals according to an embodiment of the present invention. Figure 2 The following is a simulation calculation diagram of sinusoidal simulation excitation according to an embodiment of the present invention: (a) is a schematic diagram of input force, (b) is a schematic diagram of moving frame acceleration, (c) is a schematic diagram of exhaust diffuser acceleration, and (d) is a schematic diagram of cabin acceleration. Detailed Implementation
[0019] The embodiments of this application will now be described in detail with reference to the accompanying drawings.
[0020] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0021] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.
[0022] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.
[0023] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.
[0024] This application provides an embodiment of an engine thrust measurement method based on acceleration measurement signals, which is described below with reference to... Figure 1 and Figure 2 Provide a detailed description.
[0025] Reference Figure 1 This application provides a method for measuring engine thrust based on acceleration measurement signals, the method comprising: Step 1: Based on the structural form of the engine thrust measurement system and the factors affecting thrust, establish the spring oscillator model of the three-degree-of-freedom system of the engine thrust measurement bench; Step 2: Fix the acceleration sensors to the cabin, moving frame, and exhaust diffuser components respectively, and install acceleration sensors on the excitation device to collect cabin acceleration, moving frame acceleration, exhaust diffuser acceleration, and excitation acceleration respectively. Step 3: Perform time-series processing on the cabin acceleration, moving frame acceleration, exhaust diffuser acceleration, and acquired excitation acceleration respectively; Step 4: Based on the time-series processed data and the spring oscillator model, solve the damping characteristic matrix and stiffness characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement rig using the time series inversion algorithm; Step 5: Measure engine thrust based on the damping characteristic matrix and stiffness characteristic matrix.
[0026] In practical implementation, the engine thrust measurement system mainly includes: an intake chamber, a test chamber, a flow pipe, a thrust measurement rig, an engine, a mounting bracket, and an exhaust diffuser. During engine testing, gas at a certain pressure and temperature in the intake chamber is introduced into the engine through the flow pipe. Simultaneously, gas at a certain pressure and temperature is introduced into the test chamber to simulate an atmospheric environment. The engine generates thrust, which is transmitted to the thrust measurement rig. Meanwhile, the engine exhaust gas is cooled by the exhaust diffuser. The principle of the engine thrust measurement method based on acceleration measurement signals in this embodiment is as follows: Figure 1 As shown, the method includes a discrete algorithm based on the acquired signal sequence, a regression algorithm module, and a time series parameter (coefficient matrix) back-derived damping and stiffness algorithm module.
[0027] Furthermore, the expression for the oscillator model of the spring is: (1), Among them, R m The excitation force is given by a moving frame with mass m. ms The mass of the cabin is m tc The mass of the exhaust diffuser is m ed The damping of the moving frame is C. ms The cabin damping is C tc The exhaust diffuser damping is C. ed The stiffness of the moving frame is K. ms The cabin stiffness is K. tc The exhaust diffuser stiffness is K. ed The acceleration of the moving frame is a ms The cabin acceleration is a tc The acceleration of the exhaust diffuser is a. ed The moving frame speed is v ms The cabin speed is v tc The exhaust diffuser speed is v ed The displacement of the moving frame is x ms The displacement of the cabin is xtc The displacement of the exhaust diffuser is x ed .
[0028] Furthermore, the timing processing of the cabin acceleration, moving frame acceleration, exhaust diffuser acceleration, and acquired excitation acceleration includes: The excitation acceleration is discretized into multiple time points according to the smallest time unit 1,...,k-1,k that is less than or equal to the equal sampling time interval, where k is the kth sampling time point; The cabin acceleration is discretized into multiple time-time cabin accelerations according to the smallest time unit 1,...,k-1,k, which is less than or equal to the average sampling time interval; Discretize the moving frame acceleration into multiple moments according to the smallest time unit 1,...,k-1,k that is less than or equal to the equal sampling time interval; The exhaust diffuser acceleration is discretized into multiple time-time exhaust diffuser accelerations based on the smallest time unit 1,...,k-1,k, which is less than or equal to the equal sampling time interval.
[0029] In practice, an excitation device is used to apply a certain force to the moving frame, the data acquisition software is adjusted for data acquisition, the acquisition time is fixed at a certain time, and the acquired excitation acceleration 'a' is recorded. m , acceleration a of the moving frame ms cabin acceleration a tc , Exhaust diffuser acceleration a ed .
[0030] Specifically, the multiple moments of excitation acceleration acquisition include the current moment's excitation acceleration a. m (k) Excitation acceleration a collected at the previous moment m (k-1), the excitation acceleration a is collected in the first two time moments. m (k-2), the multiple time-lapse cabin accelerations include the current time-lapse cabin acceleration a. tc (k) The acceleration of the cabin at the previous moment, a tc (k-1) and the cabin acceleration a at the first two time points tc (k-2), the multiple moments of the moving frame acceleration include the current moment's moving frame acceleration a ms (k) Acceleration of the moving frame at the previous moment a ms (k-1) and the acceleration a of the moving frame at the first two moments ms (k-2), the multiple time-lapse diffuser accelerations include the current time-lapse diffuser acceleration a. ed (k) Acceleration of the exhaust diffuser at the previous moment a ed(k-1) and the exhaust diffuser acceleration a at the first two time points ed (k-2).
[0031] In one embodiment, based on the time-series processed data and the oscillator model of the spring, the damping characteristic matrix and stiffness characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement rig are solved using a time-series inversion algorithm, including: The input vector of the time series inversion algorithm is constructed based on the excitation acceleration collected at multiple times, and the output vector of the time series inversion algorithm is constructed based on the cabin acceleration, moving frame acceleration, and exhaust diffuser acceleration at multiple times. Based on the input vector and output vector, and the time series identification formula based on the time series inversion algorithm, multiple coefficient matrices are solved by the least squares method. Based on multiple coefficient matrices and the oscillator model of the spring, matrix transformation is performed to obtain the damping mass ratio matrix and the stiffness mass ratio matrix. Based on the mass of the moving frame, the mass of the cabin, the mass of the exhaust diffuser, and the damping mass ratio matrix, the damping characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement bench is obtained. Based on the mass of the moving frame, the mass of the cabin, the mass of the exhaust diffuser, and the stiffness-mass ratio matrix, the stiffness characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement bench is obtained.
[0032] Furthermore, the expression for the input vector of the time series inversion algorithm is: (2), in, The input vector at the current time. The input vector from the previous time step. These are the input vectors for the first two time steps.
[0033] Furthermore, the expression for the output vector of the time series inversion algorithm is: (3), in, Output the vector for the current time step. The output vector from the previous time step. This is the output vector for the first two time steps.
[0034] Furthermore, the expression for the time series identification formula is as follows: (4), Where A1 is the first coefficient matrix, A2 is the second coefficient matrix, B is the third coefficient matrix, D1 is the fourth coefficient matrix, and D2 is the fifth coefficient matrix.
[0035] Furthermore, the calculation process of the matrix transformation includes: (5), (6), (7), (8), Where I is a third-order identity matrix, E c G is the first intermediate matrix. c X is the second intermediate matrix. c Z is the third intermediate matrix. c S1 is the fourth intermediate matrix, S2 is the fifth intermediate matrix, S3 is the sixth intermediate matrix, K0 is the stiffness-to-mass ratio matrix, and C0 is the damping-to-mass ratio matrix.
[0036] Furthermore, the formula for calculating the damping characteristic matrix is: (9), The formula for calculating the stiffness characteristic matrix is: (10) Where C is the damping characteristic matrix and K is the stiffness characteristic matrix.
[0037] In practice, the mass m of the moving frame of the system is obtained through geometric surveying or weighing. ms , cabin mass m tc Mass of exhaust diffuser m ed .
[0038] In one embodiment, the moving frame mass m is set on the simulation platform. ms , cabin mass m tc Discharge and expansion quality m ed , moving frame damping Cms , cabin damping C tc , Expansion Damping C ed , dynamic frame stiffness K ms , cabin stiffness K tc , expansion stiffness K ed Simulation was performed, and the excitation acceleration R (satisfying equation (11)) was used to obtain the exhaust diffuser acceleration a. ed (Expansion acceleration), moving frame acceleration a ms cabin acceleration a tc ,like Figure 2 As shown in Figures (a), (b), (c), and (d), the maximum damping error is 1.48% and the maximum stiffness error is 1.45% obtained by the engine thrust measurement method based on acceleration measurement signals in the above embodiments.
[0039] R=38000sin(2π*20*t)(11).
[0040] The embodiments provided by this invention propose an engine thrust measurement method based on acceleration measurement signals, which has significant technical advantages and practical application value in engine testing. First, this method overcomes the limitations of traditional single-degree-of-freedom assumption models. Through real-time acquisition and analysis of multi-point acceleration signals, it can identify the dynamic characteristic parameters (such as stiffness and damping) of the test bench system, thereby constructing a multi-degree-of-freedom measurement model that more closely resembles the real physical process. Compared to traditional methods that suffer from thrust measurement errors due to structural dynamic response and high-frequency vibration under dynamic conditions, this method can effectively identify and compensate for the coupling effect of the test bench system itself, significantly reducing errors caused by structural hysteresis or nonlinear characteristics during dynamic processes, and improving the accuracy and reliability of dynamic thrust measurement. This invention fills the technical gap in parameter identification in the field of dynamic thrust measurement and lays a high-precision, highly adaptable theoretical and practical foundation for engine design optimization, fault diagnosis, and performance verification, possessing significant engineering value and promising industry application prospects.
[0041] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A method for measuring engine thrust based on acceleration measurement signals, characterized in that, The method includes: Based on the structural form of the engine thrust measurement system and the factors affecting thrust, an oscillator model of the spring of the three-degree-of-freedom system of the engine thrust measurement bench is established; Accelerometers were fixed on the cabin, moving frame, and exhaust diffuser components, respectively. Accelerometers were also installed on the excitation device to collect cabin acceleration, moving frame acceleration, exhaust diffuser acceleration, and excitation acceleration, respectively. Timing processing was performed on the cabin acceleration, moving frame acceleration, exhaust diffuser acceleration, and acquired excitation acceleration, respectively. Based on the time-series processed data and the spring oscillator model, the damping characteristic matrix and stiffness characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement test bench are solved by the time series inversion algorithm. Engine thrust measurement is performed based on damping characteristic matrix and stiffness characteristic matrix.
2. The engine thrust measurement method based on acceleration measurement signals according to claim 1, characterized in that, The expression for the oscillator model of the spring is: ， Among them, R m The excitation force is given by a moving frame with mass m. ms The mass of the cabin is m tc The mass of the exhaust diffuser is m ed The damping of the moving frame is C. ms The cabin damping is C tc The exhaust diffuser damping is C. ed The stiffness of the moving frame is K. ms The cabin stiffness is K. tc The exhaust diffuser stiffness is K. ed The acceleration of the moving frame is a ms The cabin acceleration is a tc The acceleration of the exhaust diffuser is a. ed The moving frame speed is v ms The cabin speed is v tc The exhaust diffuser speed is v ed The displacement of the moving frame is x ms The displacement of the cabin is x tc The displacement of the exhaust diffuser is x ed .
3. The engine thrust measurement method based on acceleration measurement signals according to claim 2, characterized in that, The timing processing of the cabin acceleration, moving frame acceleration, exhaust diffuser acceleration, and acquired excitation acceleration includes: The excitation acceleration is discretized into multiple time points according to the smallest time unit 1,...,k-1,k that is less than or equal to the equal sampling time interval, where k is the kth sampling time point; The cabin acceleration is discretized into multiple time-time cabin accelerations according to the smallest time unit 1,...,k-1,k, which is less than or equal to the average sampling time interval; Discretize the moving frame acceleration into multiple moments according to the smallest time unit 1,...,k-1,k that is less than or equal to the equal sampling time interval; The exhaust diffuser acceleration is discretized into multiple time-time exhaust diffuser accelerations based on the smallest time unit 1,...,k-1,k, which is less than or equal to the equal sampling time interval.
4. The engine thrust measurement method based on acceleration measurement signals according to claim 3, characterized in that, The multiple excitation accelerations collected at different times include the excitation acceleration a collected at the current time. m (k) Excitation acceleration a collected at the previous moment m (k-1), the excitation acceleration a is collected in the first two time moments. m (k-2), the multiple time-lapse cabin accelerations include the current time-lapse cabin acceleration a. tc (k) The acceleration of the cabin at the previous moment, a tc (k-1) and the cabin acceleration a at the first two time points tc (k-2), the multiple moments of the moving frame acceleration include the current moment's moving frame acceleration a ms (k) Acceleration of the moving frame at the previous moment a ms (k-1) and the acceleration a of the moving frame at the first two moments ms (k-2), the multiple time-lapse diffuser accelerations include the current time-lapse diffuser acceleration a. ed (k) Acceleration of the exhaust diffuser at the previous moment a ed (k-1) and the exhaust diffuser acceleration a at the first two time points ed (k-2).
5. The engine thrust measurement method based on acceleration measurement signals according to claim 4, characterized in that, Based on the time-series processed data and the oscillator model of the spring, the damping characteristic matrix and stiffness characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement rig are solved using a time-series inversion algorithm, including: The input vector of the time series inversion algorithm is constructed based on the excitation acceleration collected at multiple times, and the output vector of the time series inversion algorithm is constructed based on the cabin acceleration, moving frame acceleration, and exhaust diffuser acceleration at multiple times. Based on the input vector and output vector, and the time series identification formula based on the time series inversion algorithm, multiple coefficient matrices are solved by the least squares method. Based on multiple coefficient matrices and the oscillator model of the spring, matrix transformation is performed to obtain the damping mass ratio matrix and the stiffness mass ratio matrix. Based on the mass of the moving frame, the mass of the cabin, the mass of the exhaust diffuser, and the damping mass ratio matrix, the damping characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement bench is obtained. Based on the mass of the moving frame, the mass of the cabin, the mass of the exhaust diffuser, and the stiffness-mass ratio matrix, the stiffness characteristic matrix of the three-degree-of-freedom system of the engine thrust measurement bench is obtained.
6. The engine thrust measurement method based on acceleration measurement signals according to claim 5, characterized in that, The expression for the input vector of the time series inversion algorithm is: ， in, The input vector at the current time. The input vector from the previous time step. These are the input vectors for the first two time steps.
7. The engine thrust measurement method based on acceleration measurement signals according to claim 6, characterized in that, The expression for the output vector of the time series inversion algorithm is: ， in, Output the vector for the current time step. The output vector from the previous time step. This is the output vector for the first two time steps.
8. The engine thrust measurement method based on acceleration measurement signals according to claim 7, characterized in that, The expression for the time series identification formula is: ， Where A1 is the first coefficient matrix, A2 is the second coefficient matrix, B is the third coefficient matrix, D1 is the fourth coefficient matrix, and D2 is the fifth coefficient matrix.
9. The engine thrust measurement method based on acceleration measurement signals according to claim 8, characterized in that, The calculation process of the matrix transformation includes: ， ， ， ， Where I is a third-order identity matrix, E c G is the first intermediate matrix. c X is the second intermediate matrix. c Z is the third intermediate matrix. c S1 is the fourth intermediate matrix, S2 is the fifth intermediate matrix, S3 is the sixth intermediate matrix, K0 is the stiffness-to-mass ratio matrix, and C0 is the damping-to-mass ratio matrix.
10. The engine thrust measurement method based on acceleration measurement signals according to claim 9, characterized in that, The formula for calculating the damping characteristic matrix is: ， The formula for calculating the stiffness characteristic matrix is: ， Where C is the damping characteristic matrix and K is the stiffness characteristic matrix.