CN113324684A - Compensation method for high-frequency dynamic force measurement performance of strain type force sensor - Google Patents
Compensation method for high-frequency dynamic force measurement performance of strain type force sensor Download PDFInfo
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- CN113324684A CN113324684A CN202110615604.7A CN202110615604A CN113324684A CN 113324684 A CN113324684 A CN 113324684A CN 202110615604 A CN202110615604 A CN 202110615604A CN 113324684 A CN113324684 A CN 113324684A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L1/00—Measuring force or stress, in general
- G01L1/26—Auxiliary measures taken, or devices used, in connection with the measurement of force, e.g. for preventing influence of transverse components of force, for preventing overload
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
Abstract
The invention relates to a compensation method for high-frequency dynamic force measurement performance of a strain type force sensor, which comprises the steps of carrying out data acquisition by utilizing an acceleration sensor and the strain type force sensor, obtaining actual stress data by recursion calculation of the acceleration sensor, and obtaining stress acquisition data by the strain type force sensor; fitting actual stress data and stress acquisition data into a transfer function in a multi-order suboptimal linear fitting mode; packaging the transfer function obtained by fitting, and writing the transfer function into the data acquisition controller; and restarting to acquire data of the strain type force sensor to obtain compensated data. The invention can compensate the data on line in real time; the system can be adapted to different data acquisition systems without adding additional modules; the error of the compensated signal is small.
Description
Technical Field
The invention relates to a compensation method for high-frequency dynamic force measurement performance of a strain type force sensor, and belongs to the technical field of industrial measurement.
Background
The strain type force sensor has the advantages of simple structure, small volume, high measurement precision, stable performance and the like, and is widely applied to scientific experiments and industrial automation.
The existing strain type force sensor is widely applied to industrial measurement, but because the strain type force sensor has amplitude attenuation and linear hysteresis phenomena along with the increase of frequency during measurement, as shown in fig. 10, when the frequency is higher than 200Hz, the amplitude gain is less than 0.8, the phase lag is more than 20 degrees, a larger error exists, and the dynamic characteristic is insufficient, so that the use error is brought, and therefore, the strain type force sensor needs to be compensated.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a compensation method for the high-frequency dynamic force measurement performance of a strain type force sensor, and the specific technical scheme is as follows:
the compensation method for the high-frequency dynamic force measurement performance of the strain type force sensor comprises the following steps:
step one, sensor data acquisition
Acquiring data by using an acceleration sensor and a strain type force sensor, calculating by recursion of the acceleration sensor to obtain actual stress data, and acquiring stress acquisition data by using the strain type force sensor;
step two, fitting of variable order optimization transfer function
Fitting actual stress data and stress acquisition data into a transfer function in a multi-order suboptimal linear fitting mode;
step three, packaging transfer function
Packaging the transfer function obtained by fitting in the second step;
step four, writing in the controller
Writing the transfer function into a data acquisition controller;
step five, starting to collect compensated data
And restarting to acquire data of the strain type force sensor to obtain compensated data.
As an improvement of the technical scheme, in the first step, a standard mass block is arranged above the strain type force sensor, and an acceleration sensor is arranged on the upper surface of the standard mass block.
As an improvement of the above technical solution, in step one, white noise excitation is applied below the strain gauge force sensor.
As an improvement of the above technical solution, in the second step, stress acquisition data acquired by a strain type force sensor is used as an input signal, actual stress data acquired by an acceleration sensor is used as an output signal, and the transfer function G (z) is fitted-1)，
Where z represents the input/output signal.
As an improvement of the above technical solution, in step three, the obtained transfer function is packaged into a data acquisition controller support format.
As an improvement of the above technical solution, in step four, the packaged transfer function is imported into a designated data acquisition controller.
The invention has the beneficial effects that:
1) and online real-time compensation can be carried out on the data. The transfer function is packaged into the controller, real-time compensation can be carried out while collecting, and the method is particularly suitable for on-line real-time compensation feedback of force collection in a real-time mixing test and can be understood as being used in real-time feedback. If the online real-time compensation is not performed, the acquired data is guided into Matlab for data processing, and a transfer function does not need to be packaged into a controller.
2) The device can be adapted to different data acquisition systems without adding additional modules. The general data acquisition system has an online data processing interface, is consistent with the Pulsar in the embodiment, packages and compiles the transfer function to a corresponding controller, and prepares a signal interface.
3) And the error of the compensated signal is small.
Drawings
FIG. 1 is a flow chart of a method of compensating for high frequency dynamic force measurement performance of a strain gauge force sensor according to the present invention;
FIG. 2 is a schematic view of the installation of the strain gauge force sensor, proof mass, and acceleration sensor of the present invention;
FIG. 3 is a diagram of a controller end write interface encapsulated by a Pulsar controller model according to the present invention;
FIG. 4 is a graph of fit ratio versus order;
FIG. 5 is a graph of RMS error as a function of order;
FIG. 6 is a graph of fit error coefficients as a function of order;
FIG. 7 is an online real-time compensation schedule data display interface;
FIG. 8 is an analysis of the compensation effect of the collected data;
FIG. 9 is an enlarged view of a portion of an analysis of the compensation effect of the collected data;
fig. 10 is a graph of amplitude ratio and phase before and after compensation.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
The invention relates to a compensation method for high-frequency dynamic force measurement performance of a strain type force sensor, which utilizes discrete transfer function fitting to compile a transfer function into a data acquisition controller to compensate a force signal in real time. As shown in fig. 1, it includes the following steps:
step one, sensor data acquisition
Acquiring data by using an acceleration sensor and a strain type force sensor, calculating by recursion of the acceleration sensor to obtain actual stress data, and acquiring stress acquisition data by using the strain type force sensor;
step two, fitting of variable order optimization transfer function
Fitting actual stress data and stress acquisition data into a transfer function in a multi-order suboptimal linear fitting mode;
step three, packaging transfer function
Packaging the transfer function obtained by fitting in the second step;
step four, writing in the controller
Writing the transfer function into a data acquisition controller;
step five, starting to collect compensated data
And restarting to acquire data of the strain type force sensor to obtain compensated data.
Example 2
Based on the embodiment 1, in the first step, as shown in fig. 2, a standard mass is installed above the strain gauge force sensor, and an acceleration sensor is installed on the upper surface of the standard mass. Furthermore, white noise excitation is applied below the strain type force sensor, and data collected by the acceleration sensor and the strain type force sensor are recorded.
The white noise excitation is used for broadband excitation of the force sensor to obtain response output for system identification and transfer function fitting. In this example, the white noise loading device is a vibrating table, which can ensure the accurate loading of the white noise.
Example 3
Based on example 1, in step two, the process of transfer function fitting is as follows:
the acceleration sensor has higher frequency response, and the actual stress data of the strain type force sensor is obtained by recursion and solution according to the mass of the acceleration sensor and the mass standard block. The stress acquisition data acquired by the strain type force sensor is u (t), the actual stress data acquired by the acceleration sensor is y (t) through recursion calculation, and the following formula is satisfied:
y(t)＝m(a+g)，
wherein m is the mass of the standard mass block in kg; a represents the value collected by the acceleration sensor in m/s2(ii) a g is gravity acceleration, and is 9.8m/s2。
Taking data (stress acquisition data) actually acquired by a strain type force sensor as an input signal, taking actual stress data as an output signal, fitting a multi-order discrete transfer function by using a tfest function, obtaining a fitting ratio (FitPercent), testing the RMS error (RMSerror) of the fitting ratio, obtaining a fitting error Coefficient (Coefficient), wherein the calculation formula is as follows:
Coefficient＝(1-FitPercent+RMSError)*100％
in this embodiment, the multi-order is defined as 1-20, the FitPercent, RMSError, and Coefficient are obtained as shown in fig. 4, 5, and 6, and the detailed data is shown in table 1 below. In fig. 4, the X axis is the order and the Y axis is the fitting ratio. In FIG. 5, the X-axis is the order and the Y-axis is the RMS error. In fig. 6, the X-axis is the order and the Y-axis is the fitting error coefficient. The Order in FIGS. 4-6 means "Order".
TABLE 1
| Order | | RMSError | Coefficient | |
| 1 | 84.82％ | 8.04％ | 23.22％ | |
| 2 | 98.88％ | 8.24％ | 9.36％ | |
| 3 | 99.13％ | 8.24％ | 9.11％ | |
| 4 | 99.45％ | 8.02％ | 8.57％ | |
| 5 | 99.46％ | 8.01％ | 8.55％ | |
| 6 | 99.51％ | 8.00％ | 8.49％ | |
| 7 | 99.51％ | 8.00％ | 8.49％ | |
| 8 | 99.51％ | 8.00％ | 8.49％ | |
| 9 | 99.51％ | 8.00％ | 8.49％ | |
| 10 | 99.51％ | 8.00％ | 8.49％ | |
| 11 | 99.52％ | 8.00％ | 8.48％ | |
| 12 | 99.51％ | 8.00％ | 8.49％ | |
| 13 | 99.52％ | 8.00％ | 8.48％ | |
| 14 | 99.52％ | 8.00％ | 8.48％ | |
| 15 | 99.26％ | 7.95％ | 8.69％ | |
| 16 | 99.52％ | 8.00％ | 8.48％ | |
| 17 | 99.52％ | 8.00％ | 8.48％ | |
| 18 | 99.10％ | 8.41％ | 9.31％ | |
| 19 | 99.52％ | 8.00％ | 8.48％ | |
| 20 | 99.37％ | 8.22％ | 8.85％ |
Analysis of FIG. 4 reveals that: when the value of the order is 1-4, the fitting ratio is in an ascending trend; when the value of the order is 4-14, the fitting ratio is in a steady trend; the fitting ratio is in a continuously fluctuating trend when the value of the order is between 14 and 20.
Analysis of FIG. 5 reveals that: when the order value is 1-6, the RMS error shows a fluctuation trend of firstly rising and then falling; the RMS error is in a steady trend when the order value is 6-14; the RMS error tends to fluctuate up and down with order values of 14-20.
Analysis of FIG. 6 reveals that: when the value of the order is 1-6, the fitting error coefficient is in a descending trend; when the value of the order is 6-14, the fitting error coefficient is in a stable trend; the fitting error coefficient is in a continuous fluctuation trend when the order value is between 14 and 20.
As can be seen from the combination of FIGS. 4-6: the order value is preferably 6 to 14. Researchers of our company find that, under the condition of the same precision, the lower the value of the order, the better, the higher the order, and the more unstable the order; therefore, the value of the order is most preferably 6.
An optimal transfer function is selected. The selection mode is that the minimum order is selected for ensuring stability under the condition that the Coefficient is optimal (the difference value between the Coefficient and the minimum value is less than 0.05%), and the optimal order in the embodiment is 6 orders; on the basis of order 6, a great deal of calculation is carried out on the preamble parameters of the transfer function and the transfer function with the minimum error is selectedCounting to obtain the optimal transfer function G (z)-1)，
Where z represents the input/output signal.
Further, in step three, the obtained transfer function is packaged into a data acquisition controller support format. The present embodiment is packaged in the out format.
Furthermore, in step four, the packaged transfer function is imported into a designated data acquisition controller, in this embodiment, Sockets of the Pulsar system. FIG. 3 is a diagram of a controller side write interface encapsulated by a Pulsar controller model according to the present invention, as shown in FIG. 3.
And finally, restarting to acquire the compensated data, and performing error comparison calculation. Starting data acquisition at the structure shown in fig. 2, respectively acquiring a force signal (actual stress data) calculated by an acceleration sensor, an original force sensor signal (stress acquired data before uncompensation, namely original stress acquired data) and a compensated force sensor signal, wherein the force signal (actual stress data) calculated by the acceleration sensor is used as a reference signal, the original force sensor signal is uncompensated data, the compensated force sensor signal is strain-type force sensor data after compensation, the strain-type force sensor data is data with amplitude attenuation and linear hysteresis eliminated, the time course compensation result is shown in fig. 7, 8 and 9, and the compensated data has almost no hysteresis; the frequency domain analysis is carried out on the frequency domain compensation, the compensation effect is shown in figure 9, the amplitude is not attenuated with the increase of the frequency after the compensation, and the phase has no lag. The error of the original signal (original force sensor signal) to the reference signal and the error of the compensated signal (compensated force sensor signal) to the reference signal were calculated to be 11.65% and 8.00%, respectively, and reduced by 31.33%. In fig. 7, the X-axis is time, and the Y-axis is actual force reference, pre-compensation force, and post-compensation force. In FIG. 8, the X-axis is time and the Y-axis is actual force reference, pre-compensation force, and post-compensation force. In FIG. 9, the X-axis is time and the Y-axis is actual force reference, pre-compensation force, and post-compensation force. In fig. 10, the X-axis is frequency, the left Y-axis is amplitude gain, and the right Y-axis is phase. As shown in fig. 10, the amplitude gain after compensation is stable at 1, the phase lag is almost 0, and there is almost no error, so that the implementation effect is good.
In the above embodiment, according to the compensation method for high-frequency dynamic force measurement performance of the strain gauge force sensor, the error of the compensated signal is small, and is reduced by 31.33% compared with the original signal before the compensation.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (6)
1. The compensation method for the high-frequency dynamic force measurement performance of the strain type force sensor is characterized by comprising the following steps of:
step one, sensor data acquisition
Acquiring data by using an acceleration sensor and a strain type force sensor, calculating by recursion of the acceleration sensor to obtain actual stress data, and acquiring stress acquisition data by using the strain type force sensor;
step two, fitting of variable order optimization transfer function
Fitting actual stress data and stress acquisition data into a transfer function in a multi-order suboptimal linear fitting mode;
step three, packaging transfer function
Packaging the transfer function obtained by fitting in the second step;
step four, writing in the controller
Writing the transfer function into a data acquisition controller;
step five, starting to collect compensated data
And restarting to acquire data of the strain type force sensor to obtain compensated data.
2. The method for compensating for high frequency dynamic force measurement capability of a strain gauge force sensor of claim 1, wherein in step one, a proof mass is mounted above the strain gauge force sensor, and an acceleration sensor is mounted on the upper surface of the proof mass.
3. A method of compensating for high frequency dynamic force measurement capability of a strain gauge force sensor as claimed in claim 1 wherein in step one a white noise excitation is applied below the strain gauge force sensor.
4. The method for compensating high frequency dynamic force measurement capability of a strain gauge force sensor as claimed in claim 1, wherein in the second step, the strain gauge force sensor is used to acquire the stress data as the input signal, the acceleration sensor is used to calculate the actual stress data as the output signal, and the transfer function is fitted to G (z)-1)，
Where z represents the input/output signal.
5. A method of compensating for high frequency dynamic force measurement capability of a strain gauge force sensor as defined in claim 1 wherein in step three, the resulting transfer function is packaged into a data acquisition controller support format.
6. A method of compensating for high frequency dynamic force measurement capability of a strain gauge force sensor as defined in claim 1 wherein in step four, the encapsulated transfer function is imported into a designated data acquisition controller.
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