Use LTspice to analyze vibration data in condition monitoring system

This article describes how to use LTspice® to analyze the frequency spectrum of vibration data in a condition monitoring system, so as to be able to issue early warnings of industrial machinery motor failures. It also introduces how to extract X, Y and Z plane data from Microsoft Excel® spreadsheets and convert them into a format that can be Fourier transformed by LTspice to generate a harmonic content map of vibration data.

Summary

This article describes how to use LTspice® Analyze the frequency spectrum of the vibration data in the condition monitoring system so as to be able to issue early warnings of industrial machinery motor failures. At the same time, how to download from Microsoft Excel® Extract the X, Y, and Z plane data from the spreadsheet and convert them into a format that can be Fourier transformed by LTspice to generate a harmonic content map of the vibration data.

Introduction

The progress of digital technology shows no signs of slowing down, and has penetrated into all aspects of our lives. Providing intelligence for machines is not an Orwellian dystopia; because the automated feedback loop helps reduce direct maintenance time, it can increase the efficiency of factory automation.

Industry 4.0 describes the concept of bringing the advantages of big data to the factory floor. Machines equipped with sensors can monitor their own performance and communicate with each other, thereby sharing the entire workload together, while providing important diagnostic information to the background, and it can be implemented whether in the same building or ON different continents.

A quick survey of ADI products shows that ADI is mainly committed to providing solutions for the Industrial Internet of Things (IIOT), that is, a variety of stable and reliable high-performance signal chain components from sensors to the cloud.

One application area in industrial automation is condition monitoring (CbM), which carefully calibrates the nominal operating characteristics of the machine, and then uses local sensors to closely monitor the status of the machine itself. A state deviating from the nominal signal indicates that the machine needs maintenance. Therefore, machines equipped with a condition monitoring system can be maintained according to actual needs, rather than arbitrarily scheduled maintenance plans.

A better way to determine the running state of a motor is to check its vibration characteristics. ADI’s MEMS technology can be used to continuously monitor the vibration characteristics of the motor and compare it with the characteristics of a known fault-free motor to determine the operating status of the motor. In fact, each motor fault has its own unique harmonic characteristics. By looking at the harmonic components of the vibration mode, faults in bearings, inner and outer rings, and even gearbox teeth can be detected.

Analyze vibration data in LTspice

To generate data for Fourier analysis in LTspice, connect three ADXL1002 accelerometers to the motor, as shown in Figure 1, to measure lateral, vertical, and longitudinal (X, Y, and Z, respectively) vibrations .

Use LTspice to analyze vibration data in condition monitoring system
Figure 1. The vibrations of the X, Y and Z channels were measured in the lateral, vertical and longitudinal directions, respectively.

Download and save the vibration data to a Microsoft Excel spreadsheet. The data is sampled at a rate of 500 kSPS, and three columns of Microsoft Excel data are obtained through one second of vibration data, and each column of data is 500,000 rows long. X, Y, and Z data samples are shown in Figure 2.

Use LTspice to analyze vibration data in condition monitoring system
Figure 2. Extract X, Y, and Z data.

The harmonic content of this data can now be checked to determine the operating condition of the motor. Fourier analysis is the mathematical process of extracting the component spectrum from the waveform. The spectrum of a pure sine wave contains only one frequency, which is called the fundamental frequency. If the sine wave is distorted, frequencies other than the fundamental frequency will appear. By analyzing the frequency spectrum of the vibration mode of the motor, its operating status can be accurately diagnosed.

Because the hardware and software that can perform Fourier analysis are usually expensive, here we introduce a method that can perform Fourier analysis on MEMS data, basically without any cost.

LTspice is a powerful, free-to-use circuit simulator. It can use the vibration data obtained from the MEMS sensor of the condition monitoring system to draw the spectrum of any waveform through Fourier analysis.

Through the data format shown in Figure 3, LTspice can generate Fourier analysis graphs, where each vibration data point is paired with its corresponding time stamp.

Use LTspice to analyze vibration data in condition monitoring system
Figure 3. Format of time and voltage examples.

It is relatively easy to convert data into this format using Microsoft Excel. The process is as follows.

First, divide the data column in Figure 2 into three worksheets in the Excel file and name them X, Y, and Z, as shown in Figure 4.

Use LTspice to analyze vibration data in condition monitoring system
Figure 4. After creating three worksheets, copy the X, Y, and Z data to the corresponding worksheets.

Insert a column on the left side of the data-this column is the timestamp of each data value.

Since 500,000 data samples are taken in one second, each data point is separated by 2 µs.Therefore, in the first cell of the new column, enter

2E-6

Represents the first time stamp at 2µs.

The easiest way to fill in the remaining timestamp column values ​​is to use the Series command. In the Microsoft Excel search box, type “Series” to display the menu options shown in Figure 5.

Select Fill Series or Pattern from the drop-down menu, and then select Series….

Use LTspice to analyze vibration data in condition monitoring system
Figure 5. How to fill multiple cells in Microsoft Excel.

The dialog box shown in Figure 6 appears, select the Columns and Linear radio buttons. Enter 2E-6 in Step value and 1 in Stop value.

Use LTspice to analyze vibration data in condition monitoring system
Figure 6. Filling cells with a linearly expanding data set.

Click OK to fill in the data timestamp in the left column, increasing from 2 µs to 1 second. Fill in the first few values ​​first, and then drag the cursor all the way to the bottom cell at the end of the data range to achieve the same purpose-but for 500,000 rows of data, it needs to be dragged very long.

Now get the data format that LTspice can handle, as shown in Figure 7.

Use LTspice to analyze vibration data in condition monitoring system
Figure 7. Columns showing timestamps and corresponding data samples.

If the data set is large and the sampling interval is short, Microsoft Excel may round the timestamp to an inappropriate number of decimal places. If this happens, highlight the first column, then select and then choose Format> Format Cells, as shown in Figure 8.

Use LTspice to analyze vibration data in condition monitoring system
Figure 8. Re-select the cell format to remove all rounding errors.

Choose the appropriate number of decimal places, as shown in Figure 9.

Use LTspice to analyze vibration data in condition monitoring system
Figure 9. Increasing the time stamp resolution to 5 decimal places.

After filling the timestamp column and expanding the effective number of digits, copy the two columns of each worksheet to a notepad or other text editor file, as shown in Figure 10.

Use LTspice to analyze vibration data in condition monitoring system
Figure 10. Text file containing time and vibration data.

There should be three text files in total, which contain the vibration data of the X, Y, and Z axes in the condition monitoring system.

Now, this data can be read directly into LTspice.

Build the schematic in LTspice as shown in Figure 11. In this design, there are six Voltage sources corresponding to faulty and non-faulty X, Y, and Z axis data. In this way, Fourier analysis can be performed on the vibration data of the new motor, and the analysis results can be compared with the Fourier analysis of the data of the suspected faulty motor. A big advantage of this method is that the frequency map of the new (non-faulty) motor can be superimposed on the frequency map of the suspected faulty motor, so the performance difference is clear at a glance.

Use LTspice to analyze vibration data in condition monitoring system
Figure 11. LTspice schematic diagram showing the voltage output of the vibration data of a faulty motor and a non-faulty motor.

LTspice command

.options plotwinsize=0 numdgt=15

The removal of the default compression settings in LTspice sometimes produces clearer results. If you ignore this line, the simulation will run faster, but the results may be less accurate.

After completing the schematic, right-click each voltage source, select the Advanced button, select the PWL File radio button, and enter the file name of the corresponding text file containing the vibration data, as shown in Figure 12. This will create a piecewise linear voltage source that contains a series of voltages and their corresponding time instances. If these text files are stored in the same directory as the LTspice file, the operation will be simpler.

Use LTspice to analyze vibration data in condition monitoring system
Figure 12. Create a piecewise linear voltage source based on vibration data.

The following commands should then be used to configure to run transient analysis during the original vibration test

.tran 1

Finally, run the simulation. The simulation may take a while to complete, depending on the data points and the duration of the transient analysis.

The simulation results of the faulty motor and the non-faulty motor are shown in Figure 13. The experiment was performed on a 587.3 rpm motor. The motor’s bearings failed, the outer ring was misaligned, and the load was 12 pounds. The figure also shows the vibration pattern of a fault-free motor at the same speed. Obviously, compared with the non-faulty motor, the vibration characteristic amplitude of the faulty motor is significantly higher.

Use LTspice to analyze vibration data in condition monitoring system
Figure 13. Time domain results of vibration data for faulted and non-faulty motors.

Highlight the Waveform window and select View> FFTT from the menu bar. This will calculate the FFT based on the transient data.

From the data in Figure 2, we can see that at such a high offset voltage as 35000V, we can only see small changes through the numbers. When simulating in LTspice, these data will be converted into a 35,000 V DC offset voltage, and an AC waveform will be superimposed on this offset voltage.

In the Fourier analysis graph, this offset voltage appears as a large spike at the DC point of the frequency spectrum. Therefore, when LTspice automatically scales the Y axis, the proportion of related harmonics is extremely small. Right-click on the X axis and specify the frequency range higher than the DC voltage, so that the DC offset voltage can be ignored-5 Hz to 1 kHz should be sufficient.

Right-click on the Y axis and select the Linear radio button to view the harmonics, as shown in Figure 14.

Use LTspice to analyze vibration data in condition monitoring system
Figure 14. Fourier diagram showing the removal of DC spurs in a linear coordinate system.

Click the right mouse button in the graphics area to add additional drawing panes, and the vibration spectrum components can be presented as X, Y, and Z diagrams, as shown in Figure 15.

Use LTspice to analyze vibration data in condition monitoring system
Figure 15. X, Y, and Z vibration diagrams are separated.

You can clearly see the 10 Hz rotation frequency of the motor, as well as obvious harmonics at 60 Hz, 142 Hz, and 172 Hz. Although this article will not analyze which components inside the motor cause these harmonics, there is no doubt that the vibration pattern changes due to motor wear.

in conclusion

ADI’s MEMS accelerometer series can provide critical data to detect motor failures at an early stage, but this is only half of the solution. These data must be carefully studied through Fourier analysis. Unfortunately, equipment or software capable of performing Fourier analysis is often expensive. And LTspice can accurately analyze CbM data for free, so as to realize early detection and diagnosis of machine faults.

author

Use LTspice to analyze vibration data in condition monitoring system

Simon Bramble

Simon Bramble graduated from Brunel University in London in 1991 with a degree in electrical engineering and electronics, specializing in analog electronic devices and power supplies. His professional career is mainly engaged in analog electronic devices, working at Linear Technology (now part of ADI).

Summary

This article describes how to use LTspice® Analyze the frequency spectrum of the vibration data in the condition monitoring system so as to be able to issue early warnings of industrial machinery motor failures. At the same time, how to download from Microsoft Excel® Extract the X, Y, and Z plane data from the spreadsheet and convert them into a format that can be Fourier transformed by LTspice to generate a harmonic content map of the vibration data.

Introduction

The progress of digital technology shows no signs of slowing down, and has penetrated into all aspects of our lives. Providing intelligence for machines is not an Orwellian dystopia; because the automated feedback loop helps reduce direct maintenance time, it can increase the efficiency of factory automation.

Industry 4.0 describes the concept of bringing the advantages of big data to the factory floor. Machines equipped with sensors can monitor their own performance and communicate with each other, thereby sharing the entire workload together, while providing important diagnostic information to the background, and it can be implemented whether in the same building or on different continents.

A quick survey of ADI products shows that ADI is mainly committed to providing solutions for the Industrial Internet of Things (IIOT), that is, a variety of stable and reliable high-performance signal chain components from sensors to the cloud.

One application area in industrial automation is condition monitoring (CbM), which carefully calibrates the nominal operating characteristics of the machine, and then uses local sensors to closely monitor the status of the machine itself. A state deviating from the nominal signal indicates that the machine needs maintenance. Therefore, machines equipped with a condition monitoring system can be maintained according to actual needs, rather than arbitrarily scheduled maintenance plans.

A better way to determine the operating status of a motor is to check its vibration characteristics. ADI’s MEMS technology can be used to continuously monitor the vibration characteristics of the motor and compare it with the characteristics of a known fault-free motor to determine the operating status of the motor. In fact, each motor fault has its own unique harmonic characteristics. By looking at the harmonic components of the vibration mode, faults in bearings, inner and outer rings, and even gearbox teeth can be detected.

Analyze vibration data in LTspice

To generate data for Fourier analysis in LTspice, connect three ADXL1002 accelerometers to the motor, as shown in Figure 1, to measure lateral, vertical, and longitudinal (X, Y, and Z, respectively) vibrations .

Use LTspice to analyze vibration data in condition monitoring system
Figure 1. The vibrations of the X, Y and Z channels were measured in the lateral, vertical and longitudinal directions, respectively.

Download and save the vibration data to a Microsoft Excel spreadsheet. The data is sampled at a rate of 500 kSPS, and three columns of Microsoft Excel data are obtained through one second of vibration data, and each column of data is 500,000 rows long. X, Y, and Z data samples are shown in Figure 2.

Use LTspice to analyze vibration data in condition monitoring system
Figure 2. Extract X, Y, and Z data.

The harmonic content of this data can now be checked to determine the operating condition of the motor. Fourier analysis is the mathematical process of extracting the component spectrum from the waveform. The spectrum of a pure sine wave contains only one frequency, which is called the fundamental frequency. If the sine wave is distorted, frequencies other than the fundamental frequency will appear. By analyzing the frequency spectrum of the vibration mode of the motor, its operating status can be accurately diagnosed.

Because the hardware and software that can perform Fourier analysis are usually expensive, here we introduce a method that can perform Fourier analysis on MEMS data, basically without any cost.

LTspice is a powerful, free-to-use circuit simulator. It can use the vibration data obtained from the MEMS sensor of the condition monitoring system to draw the spectrum of any waveform through Fourier analysis.

Through the data format shown in Figure 3, LTspice can generate Fourier analysis graphs, where each vibration data point is paired with its corresponding time stamp.

Use LTspice to analyze vibration data in condition monitoring system
Figure 3. Format of time and voltage examples.

It is relatively easy to convert data into this format using Microsoft Excel. The process is as follows.

First, divide the data column in Figure 2 into three worksheets in the Excel file and name them X, Y, and Z, as shown in Figure 4.

Use LTspice to analyze vibration data in condition monitoring system
Figure 4. After creating three worksheets, copy the X, Y, and Z data to the corresponding worksheets.

Insert a column on the left side of the data-this column is the timestamp of each data value.

Since 500,000 data samples are taken in one second, each data point is separated by 2 µs.Therefore, in the first cell of the new column, enter

2E-6

Represents the first time stamp at 2µs.

The easiest way to fill in the remaining timestamp column values ​​is to use the Series command. In the Microsoft Excel search box, type “Series” to display the menu options shown in Figure 5.

Select Fill Series or Pattern from the drop-down menu, and then select Series….

Use LTspice to analyze vibration data in condition monitoring system
Figure 5. How to fill multiple cells in Microsoft Excel.

The dialog box shown in Figure 6 appears, select the Columns and Linear radio buttons. Enter 2E-6 in Step value and 1 in Stop value.

Use LTspice to analyze vibration data in condition monitoring system
Figure 6. Filling cells with a linearly expanding data set.

Click OK to fill in the data timestamp in the left column, increasing from 2 µs to 1 second. Fill in the first few values ​​first, and then drag the cursor all the way to the bottom cell at the end of the data range to achieve the same purpose-but for 500,000 rows of data, it needs to be dragged very long.

Now get the data format that LTspice can handle, as shown in Figure 7.

Use LTspice to analyze vibration data in condition monitoring system
Figure 7. Columns showing timestamps and corresponding data samples.

If the data set is large and the sampling interval is short, Microsoft Excel may round the timestamp to an inappropriate number of decimal places. If this happens, highlight the first column, then select and then choose Format> Format Cells, as shown in Figure 8.

Use LTspice to analyze vibration data in condition monitoring system
Figure 8. Re-select the cell format to remove all rounding errors.

Choose the appropriate number of decimal places, as shown in Figure 9.

Use LTspice to analyze vibration data in condition monitoring system
Figure 9. Increasing the time stamp resolution to 5 decimal places.

After filling the timestamp column and expanding the effective number of digits, copy the two columns of each worksheet to a notepad or other text editor file, as shown in Figure 10.

Use LTspice to analyze vibration data in condition monitoring system
Figure 10. Text file containing time and vibration data.

There should be three text files in total, which contain the vibration data of the X, Y, and Z axes in the condition monitoring system.

Now, this data can be read directly into LTspice.

Build the schematic in LTspice as shown in Figure 11. In this design, there are six voltage sources corresponding to faulty and non-faulty X, Y, and Z axis data. In this way, Fourier analysis can be performed on the vibration data of the new motor, and the analysis results can be compared with the Fourier analysis of the data of the suspected faulty motor. A big advantage of this method is that the frequency map of the new (non-faulty) motor can be superimposed on the frequency map of the suspected faulty motor, so the performance difference is clear at a glance.

Use LTspice to analyze vibration data in condition monitoring system
Figure 11. LTspice schematic diagram showing the voltage output of the vibration data of a faulty motor and a non-faulty motor.

LTspice command

.options plotwinsize=0 numdgt=15

The removal of the default compression settings in LTspice sometimes produces clearer results. If you ignore this line, the simulation will run faster, but the results may be less accurate.

After completing the schematic, right-click each voltage source, select the Advanced button, select the PWL File radio button, and enter the file name of the corresponding text file containing the vibration data, as shown in Figure 12. This will create a piecewise linear voltage source that contains a series of voltages and their corresponding time instances. If these text files are stored in the same directory as the LTspice file, the operation will be simpler.

Use LTspice to analyze vibration data in condition monitoring system
Figure 12. Create a piecewise linear voltage source based on vibration data.

The following commands should then be used to configure to run transient analysis during the original vibration test

.tran 1

Finally, run the simulation. The simulation may take a while to complete, depending on the data points and the duration of the transient analysis.

The simulation results of the faulty motor and the non-faulty motor are shown in Figure 13. The experiment was performed on a motor with a speed of 587.3 rpm. The motor’s bearing failed, the outer ring was misaligned, and the load was 12 pounds. The figure also shows the vibration pattern of a fault-free motor at the same speed. Obviously, compared with the non-faulty motor, the vibration characteristic amplitude of the faulty motor is significantly higher.

Use LTspice to analyze vibration data in condition monitoring system
Figure 13. Time domain results of vibration data for faulted and non-faulty motors.

Highlight the Waveform window and select View> FFTT from the menu bar. This will calculate the FFT based on the transient data.

From the data in Figure 2, we can see that at such a high offset voltage as 35000V, we can only see small changes through the numbers. When simulating in LTspice, these data will be converted into a 35,000 V DC offset voltage, and an AC waveform will be superimposed on this offset voltage.

In the Fourier analysis graph, this offset voltage appears as a large spike at the DC point of the spectrum position. Therefore, when LTspice automatically scales the Y axis, the proportion of related harmonics is extremely small. Right-click on the X axis and specify the frequency range higher than the DC voltage, so that the DC offset voltage can be ignored-5 Hz to 1 kHz should be sufficient.

Right-click on the Y axis and select the Linear radio button to view the harmonics, as shown in Figure 14.

Use LTspice to analyze vibration data in condition monitoring system
Figure 14. Fourier diagram showing the removal of DC spurs in a linear coordinate system.

Click the right mouse button in the graphics area to add an additional drawing pane, and the vibration spectrum components can be presented as X, Y, and Z diagrams, as shown in Figure 15.

Use LTspice to analyze vibration data in condition monitoring system
Figure 15. X, Y, and Z vibration diagrams are separated.

You can clearly see the 10 Hz rotation frequency of the motor, as well as obvious harmonics at 60 Hz, 142 Hz, and 172 Hz. Although this article will not analyze which components inside the motor cause these harmonics, there is no doubt that the vibration pattern changes due to motor wear.

in conclusion

ADI’s MEMS accelerometer series can provide critical data to detect motor failures at an early stage, but this is only half of the solution. These data must be carefully studied through Fourier analysis. Unfortunately, equipment or software capable of performing Fourier analysis is often expensive. And LTspice can accurately analyze CbM data for free, so as to realize early detection and diagnosis of machine faults.

author

Use LTspice to analyze vibration data in condition monitoring system

Simon Bramble

Simon Bramble graduated from Brunel University in London in 1991 with a degree in electrical engineering and electronics, specializing in analog electronic devices and power supplies. His professional career is mainly engaged in analog electronic devices, working at Linear Technology (now part of ADI).

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