A method and system for testing the inertia of a dynamic torque sensor calibration device

Abstract

This invention provides a method and system for inertia testing of a dynamic torque sensor calibration device, relating to the field of inertia testing technology. The method includes acquiring multiple angular acceleration waveforms; extracting frequency features from the multiple angular acceleration waveforms through signal processing to obtain multiple frequency measurements corresponding to periods of frequency smoothness; using the quantity containing the frequency measurements as the independent variable and the inertia of the standard inertia disk corresponding to the multiple angular acceleration waveforms as the dependent variable, performing linear fitting to obtain a linear fitting function; and obtaining the inertia value of the load shaft system based on the linear fitting function. This method can calculate the inertia of the load shaft system based on waveform data from dynamic sensor calibration tests, eliminating the need for separate measurements. Therefore, the load shaft system inertia value is used to compensate for the dynamic torque amplitude measurement, effectively improving the accuracy of dynamic torque sensor measurements and saving calibration time.

Description

Technical Field

[0001] This invention relates to the field of inertia testing technology, and more specifically, to an inertia testing method and system for a dynamic torque sensor calibration device. Background Technology

[0002] Dynamic torque parameter measurement is widely used in materials testing, engine performance testing, and other measurement activities. The measurement accuracy of dynamic torque sensors directly determines the performance evaluation of the test subject. Currently, there are no metrological verification procedures for dynamic torque parameters published in China, and various types of dynamic torque sensor calibration devices are still in the development or performance verification stage.

[0003] Currently, patent ZL201911285482.9 discloses a braking-type sinusoidal dynamic torque sensor calibration device. The basic principle of this device is as follows: the torque sensor to be calibrated is rigidly connected to a standard inertia device to form a first-order inertia-torsion bar system, which is then connected to a magnetic powder brake and a servo driver. While the inertia-torsion bar system possesses kinetic energy, a braking torque is applied. The angular acceleration of the standard inertia device is measured using a circular grating angle measuring instrument, and the dynamic torque parameters are traced back to the inertia and angular acceleration parameters. Generally, the load shaft inertia is the sum of the inertia of the air bearing rotor (belonging to the air bearing), the upper coupler, the circular grating, the upper clamping fixture, and the upper end of the torque sensor shaft (belonging to the torque sensor to be calibrated); the transmission shaft inertia is the sum of the inertia of the lower end of the torque sensor shaft, the lower clamping fixture, the lower coupler, the magnetic powder brake main shaft, and the driven part of the electromagnetic clutch.

[0004] According to the formula for calculating dynamic torque (i.e., ... In the formula, T For dynamic torque; I Inertia; ε As can be seen from the angular acceleration, during the operation of the braking-type sinusoidal dynamic torque calibration device, it is necessary to measure the inertia values ​​of the standard inertia disk and the load shaft system, as well as their angular acceleration values. The angular acceleration value can be directly measured and calculated using a circular grating angular acceleration measuring instrument. The inertia of the standard inertia disk has been calibrated, while the value of the load shaft system inertia is unknown. The accuracy of the load shaft system inertia measurement will have a significant impact on the dynamic torque measurement results; therefore, this value must be remeasured after calibrating different torque sensors or changing the clamping fixture. In addition, the transmission shaft system inertia is an important reference value for the braking torque loading value and also needs to be accurately measured. Summary of the Invention

[0005] The purpose of this invention is to provide an inertia testing method for a dynamic torque sensor calibration device, which can solve the problem that the inertia of a braking sinusoidal dynamic torque sensor calibration device cannot be directly measured.

[0006] The embodiments of the present invention are implemented as follows:

[0007] On one hand, the present invention provides an inertia testing method for a dynamic torque sensor calibration device, used to measure the inertia of the dynamic torque sensor calibration device, mainly including:

[0008] Multiple angular acceleration waveforms are acquired, which are measured by a dynamic torque sensor calibration device, and the multiple angular acceleration waveforms correspond to multiple different standard inertia disks;

[0009] By using signal processing, frequency features are extracted from multiple angular acceleration waveforms to obtain multiple frequency measurements when the frequency is flat.

[0010] Using quantities containing frequency measurements as independent variables and the inertia of standard inertia disks corresponding to multiple angular acceleration waveforms as dependent variables, a linear fitting is performed to obtain a linear fitting function.

[0011] The inertia value of the load shaft system is obtained based on the linear fitting function.

[0012] On the other hand, the present invention provides an inertia testing system for a dynamic torque sensor calibration device, mainly comprising:

[0013] The acquisition module is used to acquire multiple angular acceleration waveforms, which are measured by a dynamic torque sensor calibration device, and the multiple angular acceleration waveforms correspond to multiple different standard inertia disks.

[0014] The processing module is used to extract frequency features from multiple angular acceleration waveforms through signal processing to obtain multiple frequency measurement values ​​when the frequency is flat.

[0015] The fitting module is used to perform linear fitting with a quantity containing frequency measurements as the independent variable and the inertia of the standard inertia disk corresponding to multiple angular acceleration waveforms as the dependent variable, to obtain a linear fitting function.

[0016] The module is used to obtain the inertia value of the load axis system based on the linear fitting function.

[0017] The embodiments of the present invention have at least the following advantages or beneficial effects:

[0018] The inertia testing method of this dynamic torque sensor calibration device can calculate the inertia of the load shaft system based on the waveform data of the dynamic sensor calibration test during the dynamic torque sensor calibration process, without the need for separate measurement. Thus, the shaft inertia value is used to compensate for the dynamic torque amplitude measurement. On the one hand, it can effectively improve the accuracy of dynamic torque sensor measurement, and on the other hand, it can effectively save the calibration time of dynamic torque sensor. It can be seen that the above method can provide a foundation for the structural parameter identification of dynamic torque sensor calibration device and accurate measurement of dynamic torque amplitude. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the dynamic torque sensor calibration device provided by the present invention;

[0021] Figure 2 A schematic flowchart illustrating the inertia testing method of the dynamic torque sensor calibration device provided by the present invention;

[0022] Figure 3 A schematic diagram of the angular acceleration waveform provided by the present invention;

[0023] Figure 4 A schematic diagram illustrating the relationship between ordinal numbers and frequencies provided by this invention;

[0024] Figure 5 A schematic diagram illustrating the microscopic relationship between ordinal number and frequency provided by this invention;

[0025] Figure 6 This is a schematic diagram of the inertia testing system of the dynamic torque sensor calibration device provided by the present invention.

[0026] Icons: 1. Standard inertia disk; 2. Air bearing; 3. Upper coupler; 4. Circular grating; 5. Upper clamping fixture; 6. Torque sensor to be calibrated; 7. Lower clamping fixture; 8. Lower coupler; 9. Magnetic powder brake; 10. Electromagnetic clutch; 11. Connecting shaft; 12. Drive mechanism; 13. Support plate; 14. Column. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Generally, the components of the embodiments of the present invention described and shown in the accompanying drawings can be arranged and designed in various different configurations.

[0028] Please refer to Figures 1 to 4 An embodiment of the present invention provides an inertia testing method for a dynamic torque sensor calibration device, mainly comprising:

[0029] Step 102: Obtain multiple angular acceleration waveforms, which are measured by a dynamic torque sensor calibration device, and the multiple angular acceleration waveforms correspond to multiple different standard inertia disks;

[0030] Step 104: Using signal processing, extract frequency features based on the multiple angular acceleration waveforms to obtain multiple frequency measurements when the frequency is flat.

[0031] Step 106: Using the quantity containing the frequency measurement value as the independent variable and the inertia of the standard inertia disk corresponding to multiple angular acceleration waveforms as the dependent variable, perform linear fitting to obtain the linear fitting function.

[0032] Step 108: Obtain the inertia value of the load shaft system based on the linear fitting function.

[0033] In this embodiment, a schematic diagram of the mechanical structure of the existing braking-type sinusoidal dynamic torque calibration device is attached. Figure 1 As shown. The rotating components include a standard inertia disk 1, an air bearing 2, an upper coupler 3, a circular grating 4, an upper clamping fixture 5, a torque sensor to be calibrated 6, a lower clamping fixture 7, a lower coupler 8, a magnetic powder brake 9, an electromagnetic clutch 10, a connecting shaft 11, a drive mechanism 12, a column 14, and a support plate 13. The inertia of the standard inertia disk is the inertia value of the standard inertia disk 1; the inertia of the load shaft system is the sum of the inertia of the air bearing rotor (belonging to air bearing 2), the upper coupler 3, the circular grating 4, the upper clamping fixture 5, and the upper end of the torque sensor shaft to be calibrated (belonging to torque sensor 6); the inertia of the transmission shaft system is the sum of the inertia of the lower end of the torque sensor shaft to be calibrated, the lower clamping fixture 7, the lower coupler 8, the main shaft of the magnetic powder brake, and the driven part of the electromagnetic clutch.

[0034] In this embodiment, the standard inertia disk 1, air bearing 2, upper coupler 3, circular grating 4, upper clamping fixture 5, torque sensor to be calibrated 6, lower clamping fixture 7, lower coupler 8, magnetic powder brake 9 and electromagnetic clutch 10 are coaxially arranged from top to bottom. The torque sensor to be calibrated 6 is installed between the upper coupler 3 and the lower coupler 8 through the upper clamping fixture 5 and the lower clamping fixture 7.

[0035] Specifically, the above method can calculate the inertia of the load shaft system based on the waveform data of the dynamic torque sensor calibration test during the dynamic torque sensor calibration process, without the need for separate measurement. Thus, the shaft inertia value is used to compensate for the dynamic torque amplitude measurement. On the one hand, it can effectively improve the accuracy of dynamic torque sensor measurement, and on the other hand, it can effectively save the calibration time of dynamic torque sensor. It can be seen that the above method can provide a foundation for the identification of structural parameters of dynamic torque sensor calibration device and accurate measurement of dynamic torque amplitude.

[0036] In this embodiment, one implementation of step 102 is as follows:

[0037] Step 112: Determine multiple standard inertia disks with different inertia;

[0038] Step 114: Using the dynamic torque sensor calibration device, brake excitation is performed under the condition of multiple standard inertia disks with different inertia to obtain the output signals corresponding to the multiple standard inertia disks with different inertia.

[0039] Step 116: Synthesize angular vibration waveforms using each of the output signals;

[0040] Step 118: Perform second-order differential calculations on each of the angular vibration waveforms to obtain multiple angular acceleration waveforms.

[0041] In this embodiment, the aforementioned different standard inertia disks refer to inertia disks of different specifications. Step 112 determines at least two standard inertia disks of different specifications, and classifies them according to their inertia values ​​from largest to smallest. ,in, This refers to the number of standard inertia disks.

[0042] In other embodiments, the arrangement of the above ordinal numbers can be determined based on actual testing and experiments.

[0043] In this embodiment, the above-mentioned multiple angular acceleration waveforms correspond to standard inertia disks of different specifications, and the order of the multiple angular acceleration waveforms corresponds to the above-mentioned ordinal numbers.

[0044] In this embodiment, the installation and testing steps of the standard inertia disk are as follows:

[0045] Install an inertia value on air bearing 2 The standard inertia disk 1 is then used to install the torque sensor 6 to be calibrated between the upper coupler 3 and the lower coupler 8 of the braking sinusoidal dynamic torque sensor calibration device through the upper clamping fixture 5. The regulated power supply provides power to the circular grating reading head, and then the torque sensor 6 to be calibrated is subjected to braking excitation. The output signal of the circular grating reading head is collected by the data acquisition and analysis instrument, and the output signal is synthesized into an angular vibration waveform.

[0046] Sequentially assign inertia values The standard inertia disk 1 was tested in the above manner to obtain the angular vibration waveform corresponding to each inertia value. The angular acceleration waveform corresponding to each inertia value was obtained by second-order differential calculation.

[0047] In this embodiment, the braking excitation method of the dynamic torque sensor is a sinusoidal method. Further, one implementation of step 104 is as follows:

[0048] Step 122: Extract the sinusoidal decay segment from the angular acceleration waveform to obtain the first segmented data;

[0049] Step 124: Filter the first extracted data segment;

[0050] Step 126: Select the continuous sinusoidal waveform of the first filtered data segment to obtain the second data segment. The second data segment can reflect the frequency change trend of the angular acceleration waveform.

[0051] Step 128: Calculate the upper and lower envelopes of the second extracted data segment;

[0052] Step 130: Based on the upper and lower envelopes of the second extracted data segment, shape the second extracted data segment to obtain the first shaped data segment;

[0053] Step 132: Extract frequency features based on the first shaped data segment to obtain the frequency measurement value when the frequency is flat.

[0054] In this embodiment, the sinusoidal attenuation band of the angular acceleration waveform is extracted. Please refer to the following for details. Figure 3 In segment BC, it can be seen that the above-mentioned truncation method can make the first truncated data segment reflect the sinusoidal attenuation trend of the frequency, and further extract the effective frequency features, so as to avoid the unstable waveform signal at the beginning of the test from affecting the subsequent fitting results and calculation results.

[0055] In this embodiment, the initial frequency of the first segmented data is initially estimated using the periodic method, which is:

[0056]

[0057] in, and These are the ordinal numbers corresponding to the adjacent peak points or adjacent valley points of the first extracted data segment. The sampling frequency.

[0058] In this embodiment, the filter cutoff frequency when filtering the first truncated data segment is: The above filtering can make the waveform of the first segment of data regular and reduce noise.

[0059] In this embodiment, Figure 3 Point a shown in the figure is used as the starting position for interception (this point is the minimum value of angular acceleration) to intercept and obtain the second intercepted data segment mentioned above. It can be seen that the above method of intercepting from the starting position of the sine wave can make the waveform of the second intercepted data segment a complete and continuous sine wave, which is convenient for subsequent calculation and fitting.

[0060] In this embodiment, the number of sinusoidal waveforms in the second data segment should be a continuous plurality, so that the second data segment can fully reflect the frequency change trend of the angular acceleration waveform.

[0061] In this embodiment, the upper and lower envelopes of the waveform data of the second truncated data segment are calculated, and the average value of the upper and lower envelopes is calculated. The first shaped data segment is obtained by subtracting the average value from the waveform data of the second truncated data segment. ,in , The length of the first integer data segment.

[0062] It is evident that the first shaped data segment obtained through the above signal processing method can further extract effective frequency features and avoid the extraction of frequency features containing many interference factors.

[0063] In this embodiment, one implementation of step 132 is as follows:

[0064] Step 142: Based on the first shaped data segment, obtain the phase data segment through Hilbert transformation;

[0065] Step 144: Calculate the instantaneous frequency corresponding to each data point based on the phase data segment, where each data point corresponds to a data point in the phase data segment;

[0066] Step 146: Fit the instantaneous frequencies corresponding to the multiple data points in the form of a logarithmic function to obtain the logarithmic fitting function;

[0067] Step 148: Determine the slope of the logarithmic fitting function when the frequency is flat;

[0068] Step 150: Determine the function value corresponding to the slope of the logarithmic fitting function when the frequency is flat, and the measured frequency value when the frequency is flat can be obtained.

[0069] Specifically, the above method uses the slope of the logarithmic fitting function as the criterion to determine the measured frequency values.

[0070] In this embodiment, the phase data segment is used as... ,in , Given the data length of the phase data segment, the instantaneous frequency... for:

[0071]

[0072] in, .

[0073] The exponential function is fitted using continuous instantaneous frequency data segments, with the exponential form being: We obtain the logarithmic fitting function, where a is the coefficient of the above exponential function, b is the base of the above exponential function, and c is the constant term of the above exponential function.

[0074] In this embodiment, please refer to the above instantaneous frequency curve for details. Figure 4 For the 22 segments above, please refer to the specific exponential fitting curve. Figure 4 Paragraph 23.

[0075] In this embodiment, one implementation of step 148 is as follows:

[0076] Step 162: Determine the ordinal segment of the curve based on the sampling frequency and initial frequency of the angular acceleration waveform;

[0077] Step 164: Perform logarithmic fitting based on the ordinal segment of the curve and the instantaneous frequency corresponding to each data point of the ordinal segment of the curve to obtain the logarithmic fitting function;

[0078] In this embodiment, the sampling frequency is the frequency at which the data acquisition card collects data points, and the initial frequency is determined based on the sampling frequency and the angular acceleration waveform.

[0079] In this embodiment, the above curve ordinal numbers are:

[0080]

[0081] Logarithmic fitting is performed on the instantaneous frequencies corresponding to the ordinal segments of the above curves to obtain the above logarithmic fitting function. The point with a slope of 0.0001 is taken as the time point of frequency flattening, and the function value corresponding to the above logarithmic fitting function is calculated, which is the obtained frequency value. .

[0082] In this embodiment, the above The 20 in the figure represents the number of periods of the angular acceleration waveform.

[0083] In this embodiment, the inertia values ​​of each standard inertia disk are calculated using the method described above. The corresponding frequency measurement value .

[0084] In other embodiments, the slope when the frequency is flat can be determined based on the curve characteristics of the logarithmic fitting function, or the slope can be determined based on the measurement accuracy.

[0085] As can be seen, the above method can effectively and accurately extract the frequency characteristics of the angular acceleration waveform through curve fitting.

[0086] In this embodiment, one implementation of step 142 is as follows:

[0087] Step 172: Mirror the first shaped data segment to obtain a mirrored data segment;

[0088] Step 174: Form a transformed data segment using the first shaped data segment and the mirrored data segment;

[0089] Step 176: Perform Hilbert transform on the transformed data segment to obtain the phase data segment.

[0090] In this embodiment, the first shaped data segment is mirrored to obtain a mirrored data segment, and the mirrored data segment and the first shaped data segment are combined to form a transformed data segment.

[0091] In this embodiment, the above-mentioned transformed data segment is subjected to Hilbert transform to obtain the phase data segment.

[0092] The above mirroring process can effectively avoid edge effects in the first shaped data segment, thereby effectively improving the waveform data quality of the phase data segment and improving the accuracy of frequency feature extraction.

[0093] In this embodiment, the quantity containing the frequency measurement value is used as the independent variable:

[0094]

[0095] in, The values ​​are the frequency measurements corresponding to the multiple angular acceleration waveforms. The number of angular acceleration waveforms is the number of standard inertia disks.

[0096] In this embodiment, the quantity containing the frequency measurement value is used as the independent variable, and... As the dependent variable, a linear fit is performed to obtain a linear function, the constant term of which is the inertia value of the load shaft system. The coefficient of the first term of the above linear function is the stiffness value of the dynamic sensor. .

[0097] In this embodiment, one implementation of step 108 is as follows:

[0098] Step 182: Obtain the inertia value of the load shaft system based on the constant term of the linear fitting function;

[0099] Step 184: Obtain the stiffness value of the dynamic sensor based on the coefficients of the first-order term of the linear fitting function.

[0100] Specifically, the above method uses the angular acceleration waveform obtained from the test as a basis to sequentially perform waveform data segment extraction, waveform signal processing, curve fitting, and linear fitting to obtain the inertia value of the load axis system.

[0101] In this embodiment, the following steps are included after step 108:

[0102] Step 192: Based on the multiple angular acceleration waveforms, extract the frequency features to obtain the frequency results corresponding to each angular acceleration waveform;

[0103] Step 194: Calculate the inertia of the transmission shaft system based on the inertia value of the load shaft system, the stiffness value of the dynamic sensor, and the inertia value of the standard inertia disk corresponding to multiple angular acceleration waveforms.

[0104] Specifically, extract the data segments corresponding to the rising and sustained angular acceleration values ​​in the above angular acceleration waveform. Please refer to [reference needed]. Figure 3 In the AB segment, the upper and lower envelopes of this AB data segment (which can be divided into a third segment) are calculated, and the average value of the upper and lower envelopes of this data segment is calculated. The second shaped data segment is obtained by subtracting the average value from the waveform data of the AB data segment. ,in , The length of the second integer data segment mentioned above.

[0105] In this embodiment, a windowed FFT calculation is performed on the second shaped data segment to obtain the frequency result. ,right The frequency results were obtained by calculating the corresponding angular acceleration waveforms in sequence. .

[0106] Calculate the inertia of the transmission shaft system based on the above frequency results. That is:

[0107]

[0108] in, .

[0109] Please refer to Figure 6 Another embodiment of the present invention provides an inertia testing system for a dynamic torque sensor calibration device, mainly comprising:

[0110] The acquisition module 202 is used to acquire multiple angular acceleration waveforms, which are measured by a dynamic torque sensor calibration device, and the multiple angular acceleration waveforms correspond to multiple different standard inertia disks.

[0111] Processing module 204 is used to extract frequency features from multiple angular acceleration waveforms through signal processing to obtain multiple frequency measurement values ​​when the frequency is flat.

[0112] The fitting module 206 is used to perform linear fitting with a quantity containing frequency measurements as the independent variable and the inertia of the standard inertia disk corresponding to multiple angular acceleration waveforms as the dependent variable, to obtain a linear fitting function.

[0113] The module 208 is used to obtain the inertia value of the load axis system based on the linear fitting function.

[0114] Specifically, the above method can calculate the inertia of the load shaft system based on the waveform data of the dynamic torque sensor calibration test during the dynamic torque sensor calibration process, without the need for separate measurement. Thus, the shaft inertia value is used to compensate for the dynamic torque amplitude measurement. On the one hand, it can effectively improve the accuracy of dynamic torque sensor measurement, and on the other hand, it can effectively save the calibration time of dynamic torque sensor. It can be seen that the above method can provide a foundation for the identification of structural parameters of dynamic torque sensor calibration device and accurate measurement of dynamic torque amplitude.

[0115] In this embodiment, the acquisition module 202 is used to determine multiple standard inertia disks with different inertia; the dynamic torque sensor calibration device performs braking excitation under the condition of multiple standard inertia disks with different inertia to obtain output signals corresponding to multiple standard inertia disks with different inertia; angular vibration waveforms are synthesized from each of the output signals; and the second derivative calculation is performed on each of the angular vibration waveforms to obtain multiple angular acceleration waveforms.

[0116] In this embodiment, the braking excitation method of the dynamic torque sensor is a sine wave. The processing module 204 is used to extract the sinusoidal decay segment from the angular acceleration waveform to obtain a first extracted data segment; filter the first extracted data segment; select the continuous sinusoidal waveform of the filtered first extracted data segment to obtain a second extracted data segment, which can reflect the frequency change trend of the angular acceleration waveform; calculate the upper and lower envelopes of the second extracted data segment; shape the second extracted data segment according to the upper and lower envelopes to obtain a first shaped data segment; extract frequency features according to the first shaped data segment to obtain the frequency measurement value when the frequency is flat. Based on the first shaped data segment, a phase data segment is obtained through Hilbert transform. Based on the phase data segment, the instantaneous frequency corresponding to each data point is calculated, with each data point corresponding to a data point in the phase data segment. The instantaneous frequencies corresponding to multiple data points are fitted using a logarithmic function to obtain a logarithmic fitting function. The slope of the logarithmic fitting function when the frequency is flat is determined. The function value corresponding to the slope of the logarithmic fitting function when the frequency is flat is determined, thus obtaining the measured frequency value when the frequency is flat. Based on the sampling frequency and initial frequency of the angular acceleration waveform, a curve ordinal segment is determined. Logarithmic fitting is performed on the curve ordinal segment and the instantaneous frequency corresponding to each data point of the curve ordinal segment to obtain the logarithmic fitting function. The first shaped data segment is mirrored to obtain a mirrored data segment. A transformed data segment is formed using the first shaped data segment and the mirrored data segment. A Hilbert transform is performed on the transformed data segment to obtain the phase data segment. As can be seen, the above mirroring method can effectively avoid the edge effect of the first shaped data segment, thereby effectively improving the waveform data quality of the phase data segment and improving the accuracy of frequency feature extraction.

[0117] In this embodiment, the obtaining module 208 is used to obtain the inertia value of the load shaft system based on the constant term of the linear fitting function; and to obtain the stiffness value of the dynamic sensor based on the coefficient of the first-order term of the linear fitting function. Based on multiple angular acceleration waveforms, frequency features are extracted to obtain the frequency results corresponding to each angular acceleration waveform; and the inertia of the transmission shaft system is calculated based on the inertia value of the load shaft system, the stiffness value of the dynamic sensor, and the inertia of the standard inertia disks corresponding to the multiple angular acceleration waveforms. Specifically, the above method uses the tested angular acceleration waveforms as a basis to sequentially perform waveform data segment extraction, waveform signal processing, curve fitting, and linear fitting to obtain the inertia value of the load shaft system.

[0118] Another embodiment of the present invention provides a computer-readable storage medium storing one or more programs, which, when executed by an electronic device including multiple applications, cause the electronic device to perform... Figure 2 The corresponding embodiment provides an inertia testing method for a dynamic torque sensor calibration device.

[0119] The various embodiments in this invention are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0120] The foregoing has described specific embodiments of the invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0121] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0122] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 The device that provides the function specified in each box.

[0123] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0124] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0125] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0126] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0127] The above description is merely an embodiment of this application and is not intended to limit the invention. Various modifications and variations can be made to this invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this invention should be included within the scope of the claims.

Claims

1. A method for testing the inertia of a dynamic torque sensor calibration device, used to measure the inertia of the dynamic torque sensor calibration device, characterized in that, include: S1. Acquire multiple angular acceleration waveforms, which are measured by a dynamic torque sensor calibration device, and the multiple angular acceleration waveforms correspond to multiple different standard inertia disks; S2. Through signal processing, frequency features are extracted from multiple angular acceleration waveforms to obtain multiple frequency measurements when the frequency is flat. The excitation method of the dynamic torque sensor is a braking sine wave method, including: The sinusoidal decay segment of the angular acceleration waveform is extracted to obtain the first segmented data; Filter the first extracted data segment; Selecting the continuous sinusoidal waveform of the first filtered data segment yields the second data segment, which reflects the frequency variation trend of the angular acceleration waveform. Calculate the upper and lower envelopes of the second extracted data segment; Based on the upper and lower envelopes of the second extracted data segment, the second extracted data segment is shaped to obtain the first shaped data segment; Based on the first shaped data segment, frequency features are extracted to obtain the corresponding frequency measurement values ​​when the frequency is flat, including: Based on the first shaped data segment, the phase data segment is obtained through Hilbert transformation; Based on the phase data segment, the instantaneous frequency corresponding to each data point is calculated, and each data point corresponds to a data point in the phase data segment; The instantaneous frequencies corresponding to multiple data points are fitted using a logarithmic function to obtain a logarithmic fitting function; Determine the slope of the logarithmic fitting function when the frequency is flat; By determining the function value corresponding to the slope of the logarithmic fitting function when the frequency is flat, the measured frequency value when the frequency is flat can be obtained. S3. Using the quantity containing the frequency measurement value as the independent variable and the inertia of the standard inertia disk corresponding to multiple angular acceleration waveforms as the dependent variable, perform linear fitting to obtain the linear fitting function. S4. Obtain the inertia value of the load shaft system based on the linear fitting function.

2. The inertia testing method for the dynamic torque sensor calibration device according to claim 1, characterized in that, The acquisition of multiple angular acceleration waveforms includes: Determine multiple standard inertia disks with different inertia; The dynamic torque sensor calibration device is used to apply braking excitation under the condition of multiple standard inertia disks with different inertia, and output signals corresponding to multiple standard inertia disks with different inertia are obtained. The output signals are used to synthesize angular vibration waveforms respectively; By performing second-order differential calculations on each of the angular vibration waveforms, multiple angular acceleration waveforms are obtained.

3. The inertia testing method for the dynamic torque sensor calibration device according to claim 1, characterized in that, The step of fitting the instantaneous frequencies corresponding to multiple data points in logarithmic form to obtain a logarithmic fitting function includes: Based on the sampling frequency and initial frequency of the angular acceleration waveform, determine the ordinal segment of the curve; Logarithmic fitting is performed based on the ordinal segments of the curve and the instantaneous frequencies corresponding to each data point of the ordinal segments of the curve to obtain the logarithmic fitting function.

4. The inertia testing method for the dynamic torque sensor calibration device according to claim 1, characterized in that, The step of obtaining the phase data segment based on the first shaped data segment using the Hilbert transform method includes: The first shaped data segment is mirrored to obtain a mirrored data segment; A transformed data segment is formed by combining the first shaped data segment and the mirrored data segment; The transformed data segment is subjected to Hilbert transform to obtain the phase data segment.

5. The inertia testing method for the dynamic torque sensor calibration device according to any one of claims 1-4, characterized in that, The quantity containing the frequency measurement value is used as the independent variable: Among them, f 01 ,......,f 0n These are the frequency measurements corresponding to the multiple angular acceleration waveforms, where n is the number of standard inertia disks.

6. The inertia testing method for the dynamic torque sensor calibration device according to claim 1, characterized in that, The step of obtaining the inertia value of the load shaft system based on the linear fitting function includes: The inertia value of the load shaft system is obtained based on the constant term of the linear fitting function. The stiffness value of the dynamic sensor is obtained based on the coefficients of the first-order term of the linear fitting function.

7. The inertia testing method for the dynamic torque sensor calibration device according to claim 6, characterized in that, After obtaining the inertia value of the load shaft system based on the linear fitting function, the method further includes: Based on the multiple angular acceleration waveforms, frequency features are extracted to obtain the frequency results corresponding to each angular acceleration waveform; The inertia of the transmission shaft system is calculated based on the inertia value of the load shaft system, the stiffness value of the dynamic sensor, and the inertia of the standard inertia disks corresponding to multiple angular acceleration waveforms.

8. An inertia testing system for a dynamic torque sensor calibration device, comprising performing the inertia testing method for the dynamic torque sensor calibration device according to any one of claims 1-7, characterized in that, include: The acquisition module is used to acquire multiple angular acceleration waveforms, which are measured by a dynamic torque sensor calibration device, and the multiple angular acceleration waveforms correspond to multiple different standard inertia disks. The processing module is used to extract frequency features from multiple angular acceleration waveforms through signal processing to obtain multiple frequency measurement values ​​when the frequency is flat. The fitting module is used to perform linear fitting with a quantity containing frequency measurements as the independent variable and the inertia of the standard inertia disk corresponding to multiple angular acceleration waveforms as the dependent variable, to obtain a linear fitting function. The module is used to obtain the inertia value of the load axis system based on the linear fitting function.

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