LabVIEW Adaptive Filter Toolkit for Road Simulation

Road simulation is useful to test the reliability of products that operate in an environment with a large amount of vibration. Road simulation generally replicates a vibration waveform recorded in a real-world transportation environment in order to simulate vibration in an experimental transportation environment. This article describes how to use the LabVIEW Adaptive Filter Toolkit to implement a road simulation system.

Road Simulation

Many applications use adaptive filtering technology. One important application is waveform replication. Wavelet replication uses mechanical or electrical devices to replicate an expected waveform precisely.

Road simulation is a one type of waveform replication application. Most road simulators are shakers that simulate vibration in an experimental transportation environment by replicating a vibration waveform recorded in a real-world transportation environment. When you apply a waveform to a shaker, the shaker cannot produce a vibration that is identical to the waveform because of the shaker's dynamic properties. In this case, you can use an adaptive filter to control the shaker and to make the shaker produce a vibration that is identical to the real-world vibration you recorded. Figure 1 shows the diagram of a road simulation system.

Figure 1: Typical Road Simulation System

where   s(n) is the stimulus signal

            x(n) is the input signal to an LMS adaptive filter

            d(n) is the delayed signal

            e(n) is the error signal

            y(n) is the corresponding output signal

            H(z) is the transfer function of the adaptive filter

            Z^-∆ is the delay function.

The reference input signal is the waveform that you expect the shaker to produce, and H(z) is the transfer function of the adaptive filter or the inverse transfer function of the shaker. If you send the reference input signal to H(z) and use the output signal from H(z) to stimulate the shaker, x(n) is identical to the reference input signal except for a delay.

The application in this article uses the LabVIEW Adaptive Filter Toolkit, the FPGA Module, the CompactRIO hardware, and other National Instruments hardware to implement a road simulation system. The system is based on a cRIO-9104 backplane with an NI 9233 module in slot 1 and an NI 9263 module in slot 2. Refer to the National Instruments Web site for information about the cRIO-9104, NI 9233, and NI 9263.

Figure 2 shows a road simulation system using National Instruments software and hardware. The AI0 channel of the NI 9233 module acquires the actual vibration of the shaker from an accelerometer. The AO0 channel of the NI 9263 module generates a driving signal for the shaker. The least mean square (LMS) based adaptive filter control algorithm is implemented using LabVIEW FPGA.

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Figure 2: Road Simulation System Using the LabVIEW Adaptive Filter Toolkit and National Instruments Hardware

The Adaptive Filter Toolkit provides a way to generate the FPGA code for an LMS-based adaptive filter. Complete the following steps to generate the FPGA code in a LabVIEW project.

1. Right-click the FPGA Target in the LabVIEW project and select Start IP Generator as shown in Figure 3. The Generate LabVIEW FPGA Code for LMS Adaptive Filter dialog box displays.

Figure 3: Start IP Generator

2. Configure the fixed-point (FXP) settings for the LMS adaptive filter in the Generate LabVIEW FPGA Code for LMS Adaptive Filter dialog box, as shown in figure 4. Because the coefficients of the adaptive filter are useful to generate s(n), place a checkmark in the Read coefficients? checkbox.

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Figure 4: Generate the FPGA Code for the LMS Adaptive Filter

3. Click the OK button. The FPGA code generates to the LabVIEW project automatically.

After LabVIEW generates the FPGA code, you can create a road simulation system project, such as the Project Explorer in figure 5. The Waveform Replication (FPGA) VI runs in the FPGA target.

Figure 5: Project Tree of Road Simulation System

The Waveform Replication (RT) VI runs on the host PC. This VI starts the controlling VI on the FPGA target and generates the expected waveforms. This VI also communicates with the controlling VI on the FPGA target in order to read the actual vibration of the shaker and the inverse model of the shaker.

Figure 6 shows the Waveform Replication (FPGA) block diagram according to figure 2.

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Figure 6: Block Diagram of the Road Simulation System

Figure 7 shows the front panel of the Waveform Replication (RT) VI. After configuring the settings, such as Filter Length and Step Size, you can observe the inverse model of the shaker from the front panel.

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Figure 7: Actual Shaker Output when the Reference Signal directly Inputs the Shaker

Figure 7 shows that when the reference input applies directly to the shaker, the actual shaker output is different from the expected shaker output. If the Control on? control is FALSE, the reference input applies to the shaker directly as shown in figure 8.

Figure 8: Road Simulation System with Reference Input Directly Applied to Shaker

If the Control on? button is TRUE, the reference input applies to the shaker according to figure 1. The actual shaker output is identical to the expected shaker output, as shown in figure 9.

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Figure 9: Front panel of Waveform Replication (RT).

Summary

Road Simulation is a means to reproduce measured time history vibration in a laboratory on a shaker system. By using the LabVIEW Adaptive Filter Toolkit, LabVIEW FPGA Module, and National Instruments hardware, you can build a road simulation system quickly and efficiently.

Please contact dsp.nish@ni.com to request more information about this article.

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