Dynamic load performance testing method for simulation motion platform based on continuous sliding time window analysis

Abstract

The present invention provides a method for testing the dynamic load performance of a simulation motion platform based on continuous sliding time window analysis, comprising the following steps: driving the motion platform to continuously move on the corresponding degrees of freedom according to a preset motion mode, and applying a load to the motion platform according to a preset change rule through a dynamic load simulation device, and collecting parameters, with force, displacement, acceleration and torque as analysis indicators; dividing the test time series into multiple continuous time windows according to the length of the time window; obtaining the data sequence of each indicator in the time window; for each time window, based on the standard deviation of each indicator and the indicator weight, calculating the comprehensive standard deviation and analyzing the dynamic stability. The present invention evaluates the dynamic stability of the system by analyzing the fluctuation of various performance indicators of the platform during long-term operation, and realizes the dynamic load performance test evaluation of the motion platform.

Description

Technical Field

[0001] The present invention relates to the technical field of six-degree-of-freedom motion platforms, and in particular to a method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis. Background Art

[0002] The stability, reliability and motion smoothness of the six-degree-of-freedom parallel motion platform are the key basic technologies for realizing high-level flight simulators. Traditional platform testing obtains simulation and testing capabilities through the input of acceleration, force and displacement, and conducts vibration, durability, abnormal sound and noise tests. The load capacity test, which has a key impact on the reliable operation and stability of the platform itself, often relies on the performance parameters of the motion mechanism such as the linear electric cylinder used to make judgments based on the results of simulation tests, and only applies the limit load of the test results for testing, which makes it difficult to truly reflect the actual load capacity of the platform and the platform deformation rate and stability under different effective loads.

[0003] For the test of the dynamic performance of the platform, the existing test methods characterize it by evaluating the motion accuracy and force / load response characteristics of the platform. For example, under load conditions, the motion accuracy is evaluated by comparing the actual motion position of the platform with the set motion position. The mean square error (MSE) algorithm is usually used for calculation and judgment, and the MSE value is analyzed to determine whether the motion accuracy meets the requirements. If the MSE value is less than the set threshold, the motion accuracy meets the requirements; otherwise, further analysis of the cause is required, such as whether there is a control system error, sensor error, or mechanical structure problem.

[0004] In the force / load response characteristic analysis, the relationship between force and torque over time, load and motion mode is analyzed, and curve fitting algorithms, such as polynomial fitting or spline fitting, are used to describe this relationship. By analyzing the fitted curve, the changing rules of force and torque under different conditions can be understood, and whether the force and torque response characteristics of the platform meet the design requirements can be evaluated.

[0005] The above two test methods reflect the dynamic performance of the platform movement to a certain extent, but MSE mainly focuses on the difference between the actual movement position and the set movement position, and does not take into account the impact of dynamic characteristics during the movement, such as acceleration, force, and torque change characteristics, on accuracy. The curve fitting method is not capable of dynamic indicator changes and transient responses under dynamic load conditions, and the analysis of force and torque response characteristics is usually performed independently without establishing a connection with other important dynamic performance indicators. In fact, changes in force and torque will directly affect the movement accuracy and stability of the platform. The lack of correlation analysis with position, acceleration, moving distance, etc. may lead to an incomplete understanding of the overall performance of the platform and an inability to comprehensively evaluate the performance of the platform under complex working conditions. Summary of the invention

[0006] The purpose of the present invention is to provide a dynamic load performance testing method for a simulation motion platform based on continuous sliding time window analysis, which evaluates the dynamic stability of the system by analyzing the fluctuations of various performance indicators of the platform during long-term operation, thereby realizing the dynamic load performance test evaluation of the motion platform.

[0007] According to a first aspect of the present invention, a method for testing the dynamic load performance of a simulation motion platform based on continuous sliding time window analysis is proposed, comprising the following steps:

[0008] The control system drives the motion platform to continuously move in the corresponding degrees of freedom according to the preset motion mode, and applies load to the motion platform according to the preset change law through the dynamic load simulation device;

[0009] Collect and obtain the force, displacement of each degree of freedom, acceleration and torque of the joints on the platform at different times, and define force, displacement, acceleration and torque as comprehensive analysis indicators;

[0010] Divide the test time series into multiple continuous time windows according to the total test time and the length of the time window;

[0011] For each time window, extract the data of each indicator in the time window to obtain the data sequence of each indicator in the time window;

[0012] For each time window, the comprehensive standard deviation is calculated based on the standard deviation of each indicator and the indicator weight;

[0013] Based on the comprehensive standard deviation of each time window within the total test time range, the changing trend of the comprehensive standard deviation of continuous time windows is analyzed to evaluate the system stability of the motion platform.

[0014] As an optional embodiment, the test time series is divided into a plurality of continuous time windows according to the total test time and the time window length, including:

[0015] For the total test time T total , according to the time window length T, T total Divided into multiple time windows, the number of windows M is expressed as:

[0016] in, Indicates floor operation.

[0017] As an optional embodiment, for each time window, calculating the comprehensive standard deviation based on the standard deviation of each indicator and the indicator weight includes:

[0018] First, for each indicator Ii and time window W k , calculate the standard deviation SD within the time window i,k :

[0019]

[0020] in, Indicator I i In the time window W k The average value of the data series within ;

[0021]

[0022] Then, for each time window W k , use each indicator in this time window W k The standard deviation of the index and the corresponding index weight ω i , get the composite standard deviation CompositeSD k :

[0023]

[0024] Among them, the indicator weight ω i It is set to the indicator weight value determined based on the coefficient of variation of each indicator.

[0025] As an optional embodiment, the indicator weight ω corresponding to each indicator i is set to be determined as follows:

[0026] For each indicator I i , calculate its coefficient of variation CV i,k :

[0027]

[0028] Normalize the coefficient of variation of each indicator so that their sum is 1, then the indicator weight ω i It is expressed as:

[0029]

[0030] As an optional embodiment, the comprehensive standard deviation of each time window within the total test time range is analyzed based on the change trend of the comprehensive standard deviation of the continuous time windows to evaluate the system stability of the motion platform, including:

[0031] Perform moving average smoothing on the comprehensive standard deviation of the continuous time window, set the moving average window size to m, and m is an odd number greater than or equal to 3. For each time window W k , calculate the comprehensive standard deviation after moving average

[0032] When k<m,

[0033] When k ≥ m,

[0034] The stability is judged according to the preset stability threshold. If any time window W within the total test time k , the comprehensive standard deviation after moving average If both are less than the stability threshold, the platform motion is judged to have long-term stability; otherwise, the platform is judged to have short-term anomalies and the window time is marked as abnormal.

[0035] Compared with the prior art, the dynamic load performance testing method of the simulation motion platform based on continuous sliding time window analysis of the present invention has the following significant advantages:

[0036] 1) Divide the test time series into multiple continuous time windows to capture the dynamic stability performance of the platform in different time periods, including the difference in platform response when the load changes at different stages, the gradual attenuation or increased fluctuation of performance over time, and capture the dynamic characteristics of the dynamic change of torque, force, and displacement over time under continuous load;

[0037] 2) Combined with the moving average smoothing of the comprehensive standard deviation of the continuous time window, while reducing the interference of data fluctuations, it more clearly highlights the changing trend of platform stability. Especially in the face of complex and random changes, the moving average processing filters out short-term and accidental fluctuations, allowing testers to more intuitively observe the long-term trend of the overall stability of the platform, and facilitate accurate judgment of whether the platform has systematic stability problems or performance change trends;

[0038] 3) By marking the abnormal time window, the test personnel can reversely trace the load loading and platform motion control function in the time window during the platform movement, and perform simulation and troubleshooting based on the detected force, torque, displacement and other data. Based on the platform operation data, load conditions and control system status during the abnormal time period, the cause of the abnormality is analyzed and located, and the platform is optimized and maintained.

[0039] It should be understood that all combinations of the aforementioned concepts and the additional concepts described in more detail below can be considered as part of the inventive subject matter of the present disclosure as long as such concepts are not mutually inconsistent. In addition, all combinations of the claimed subject matter are considered as part of the inventive subject matter of the present disclosure.

[0040] The foregoing and other aspects, embodiments and features of the present invention can be more fully understood from the following description in conjunction with the accompanying drawings. Other additional aspects of the present invention, such as the features and / or beneficial effects of the exemplary embodiments, will be apparent from the following description or learned from the practice of the specific embodiments according to the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flow chart of a method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis according to an embodiment of the present invention.

[0042] Figure 2 4 is a flow chart of analyzing the changing trend of the comprehensive standard deviation of a continuous time window according to an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to better understand the technical content of the present invention, specific embodiments are given and described as follows in conjunction with the accompanying drawings.

[0044] Various aspects of the present invention are described in this disclosure with reference to the accompanying drawings, in which many illustrative embodiments are shown. The embodiments of the present disclosure are not necessarily intended to include all aspects of the present invention. It should be understood that the various concepts and embodiments introduced above, as well as those described in more detail below, can be implemented in any of many ways, because the concepts and embodiments disclosed by the present invention are not limited to any implementation. In addition, some aspects disclosed by the present invention can be used alone or in any appropriate combination with other aspects disclosed by the present invention.

[0045] {Example 1}

[0046] Combination Figure 1 As shown, the dynamic load performance testing method of a simulation motion platform based on continuous sliding time window analysis according to an embodiment of the present invention comprises the following steps:

[0047] The control system drives the motion platform to continuously move in the corresponding degrees of freedom according to the preset motion mode, and applies load to the motion platform according to the preset change law through the dynamic load simulation device;

[0048] Collect and obtain the force, displacement of each degree of freedom, acceleration and torque of the joints on the platform at different times, and define force, displacement, acceleration and torque as comprehensive analysis indicators;

[0049] Divide the test time series into multiple continuous time windows according to the total test time and the length of the time window;

[0050] For each time window, extract the data of each indicator in the time window to obtain the data sequence of each indicator in the time window;

[0051] For each time window, the comprehensive standard deviation is calculated based on the standard deviation of each indicator and the indicator weight;

[0052] Based on the comprehensive standard deviation of each time window within the total test time range, the changing trend of the comprehensive standard deviation of continuous time windows is analyzed to evaluate the system stability of the motion platform.

[0053] As an optional embodiment, the aforementioned degrees of freedom include degrees of freedom in the α, β, and γ axes in space, that is, the degrees of freedom of movement of the geometric center of the upper platform of the motion mechanism around the X, Y, and Z axes and the degrees of freedom of rotation in the pitch, roll, and yaw directions;

[0054] The preset motion mode is set to follow the motion function The position of the control platform on the corresponding degree of freedom changes with time, where A represents the amplitude, t represents the time, ω represents the angular frequency, Indicates the initial phase.

[0055] As an optional embodiment, the dynamic load simulation device is an electromagnetic load loader or a hydraulic load loader;

[0056] The dynamic load simulation device is configured to apply a load to the motion platform according to a variation rule of a linear function F=kt+F0, wherein k represents a load increase rate, t represents time, and F0 represents an initial load.

[0057] As an optional embodiment, the test time series is divided into a plurality of continuous time windows according to the total test time and the length of the time window, including:

[0058] For the total test time T total , according to the time window length T, T total Divided into multiple time windows, the number of windows M is expressed as:

[0059] in, Indicates floor operation.

[0060] According to the platform accuracy and stability standards, the total test time T total Set it to be greater than or equal to 10 minutes, and the time window length is set to one of 5s, 10s, and 15s.

[0061] As an optional embodiment, for each time window, extracting data of each indicator in the time window to obtain a data sequence of each indicator in the time window includes:

[0062] In any time window W k , k = 1, 2, 3, ..., M, extract the data of each indicator in the window; for indicator I i , i=1,2,3,4, in the time window W k The data sequence in is x i,k (t), where t satisfies:

[0063] t∈[(k-1)T+1,kT].

[0064] As an optional embodiment, for each time window, based on the standard deviation of each indicator and the indicator weight, a comprehensive standard deviation is calculated, including:

[0065] First, for each indicator I i and time window W k , calculate the standard deviation SD within the time window i,k :

[0066]

[0067] in, Indicator I i In the time window W k The average value of the data series within ;

[0068]

[0069] Then, for each time window W k , use each indicator in this time window W k The standard deviation of the index and the corresponding index weight ω i , get the composite standard deviation CompositeSD k :

[0070]

[0071] Among them, the indicator weight ω i It is set to the indicator weight value determined based on the coefficient of variation of each indicator.

[0072] As an optional embodiment, the indicator weight ω corresponding to each indicator i is set to be determined as follows:

[0073] For each indicator I i , calculate its coefficient of variation CV i,k :

[0074]

[0075] Normalize the coefficient of variation of each indicator so that their sum is 1, then the indicator weight ω i It is expressed as:

[0076]

[0077] It should be understood that in the embodiments of the present invention, within each time window, weights are reasonably allocated according to the coefficient of variation of each indicator data. The indicator with a larger coefficient of variation has a higher weight in the system stability analysis, and can better reflect its impact on the system stability, thereby achieving an accurate and scientific assessment of dynamic stability.

[0078] As an optional embodiment, combining Figure 2 As shown in the figure, based on the comprehensive standard deviation of each time window within the total test time range, the change trend of the comprehensive standard deviation of the continuous time window is analyzed to evaluate the system stability of the motion platform, including:

[0079] Perform moving average smoothing on the comprehensive standard deviation of the continuous time window, set the moving average window size to m, and m is an odd number greater than or equal to 3. For each time window W k , calculate the comprehensive standard deviation after moving average

[0080] When k<m,

[0081] When k ≥ m,

[0082] The stability is judged according to the preset stability threshold. If any time window W within the total test time k , the comprehensive standard deviation after moving average If both are less than the stability threshold, the platform motion is judged to have long-term stability; otherwise, the platform is judged to have short-term anomalies and the window time is marked as abnormal.

[0083] The dynamic load performance testing method of a simulation motion platform based on continuous sliding time window analysis proposed in the present invention applies a load to the motion platform according to a preset change rule through a dynamic load simulation device, which can simulate the complex load conditions that the motion platform may face in actual operation, so that the test results can better reflect the performance of the platform in real working scenarios, and are not limited to the ideal state of no load or fixed load, thereby discovering problems of the platform during dynamic movement in advance and ensuring that the platform can operate stably and reliably after being put into actual use.

[0084] The test process uses force, displacement, acceleration and torque as comprehensive analysis indicators, reflecting the characteristics of the platform in terms of force, motion state and joint force from different angles. Through comprehensive analysis, we can fully and deeply understand the overall performance of the motion platform under dynamic load. Combined with time series analysis, the dynamic characteristics of the platform under different load states are captured and analyzed, providing an effective means for detailed evaluation of the dynamic performance evolution of the platform.

[0085] Although the present invention has been disclosed as above with preferred embodiments, it is not intended to limit the present invention. A person with ordinary knowledge in the technical field to which the present invention belongs may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be determined by the definition of the claims.

Claims

1. A method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis, characterized in that: The following steps are involved: The control system drives the motion platform to continuously move in the corresponding degrees of freedom according to the preset motion mode, and applies load to the motion platform according to the preset change law through the dynamic load simulation device; Collect and obtain the force, displacement of each degree of freedom, acceleration and torque of the joints on the platform at different times, and define force, displacement, acceleration and torque as comprehensive analysis indicators; Divide the test time series into multiple continuous time windows according to the total test time and the length of the time window; For each time window, extract the data of each indicator in the time window to obtain the data sequence of each indicator in the time window; For each time window, the comprehensive standard deviation is calculated based on the standard deviation of each indicator and the indicator weight; Based on the comprehensive standard deviation of each time window within the total test time range, the changing trend of the comprehensive standard deviation of continuous time windows is analyzed to evaluate the system stability of the motion platform.

2. The method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis according to claim 1 is characterized in that: The degrees of freedom include the degrees of freedom in the α, β, and γ axes in space, that is, the degrees of freedom of movement of the geometric center of the upper platform of the motion mechanism around the X, Y, and Z axes, and the degrees of freedom of rotation in the pitch, roll, and yaw directions; The preset motion mode is set to follow the motion function The position of the control platform on the corresponding degree of freedom changes with time, where A represents the amplitude, t represents the time, ω represents the angular frequency, Indicates the initial phase.

3. The method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis according to claim 1 is characterized in that: The dynamic load simulation device is an electromagnetic load loader or a hydraulic load loader; The dynamic load simulation device is configured to apply a load to the motion platform according to a variation rule of a linear function F=kt+F0, wherein k represents a load increase rate, t represents time, and F0 represents an initial load.

4. The method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis according to claim 1 is characterized in that: The test time series is divided into a plurality of continuous time windows according to the total test time and the time window length, including: For the total test time T total , according to the time window length T, T total Divided into multiple time windows, the number of windows M is expressed as: in, Indicates floor operation.

5. The method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis according to claim 4 is characterized in that: For each time window, extracting the data of each indicator in the time window to obtain the data sequence of each indicator in the time window includes: In any time window W k , k = 1, 2, 3, ..., M, extract the data of each indicator in the window; for indicator I i , i=1,2,3,4, in the time window W k The data sequence in is x i,k (t), where t satisfies: t∈[(k-1)T+1,kT].

6. The method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis according to claim 4 is characterized in that: For each time window, the comprehensive standard deviation is calculated based on the standard deviation of each indicator and the indicator weight, including: First, for each indicator I i and time window W k , calculate the standard deviation SD within the time window i,k : in, Indicator I i In the time window W k The average value of the data series within ; Then, for each time window W k , use each indicator in this time window W k The standard deviation of the index and the corresponding index weight ω i , get the composite standard deviation CompositeSD k : Among them, the indicator weight ω i It is set to the indicator weight value determined based on the coefficient of variation of each indicator.

7. The method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis according to claim 6 is characterized in that: The indicator weight ω corresponding to each indicator i is set to be determined as follows: For each indicator I i , calculate its coefficient of variation CV i,k : Normalize the coefficient of variation of each indicator so that their sum is 1, then the indicator weight ω i It is expressed as:

8. The method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis according to claim 6 is characterized in that: The comprehensive standard deviation of each time window within the total test time range is analyzed to analyze the change trend of the comprehensive standard deviation of the continuous time window and evaluate the system stability of the motion platform, including: Perform moving average smoothing on the comprehensive standard deviation of the continuous time window, set the moving average window size to m, and m is an odd number greater than or equal to 3. For each time window W k , calculate the comprehensive standard deviation after moving average When k<m, When k ≥ m, The stability is judged according to the preset stability threshold. If any time window W within the total test time k , the comprehensive standard deviation after moving average If both are less than the stability threshold, the platform motion is judged to have long-term stability; otherwise, the platform is judged to have short-term anomalies and the window time is marked as abnormal.

9. The method for testing dynamic load performance of a simulation motion platform based on continuous sliding time window analysis according to claim 1 is characterized in that: The total test time T total Set it to be greater than or equal to 10 minutes, and the time window length is set to one of 5s, 10s, and 15s.

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