Torsional Vibration in shafts and other mechanical systems
The torsional vibration of a crank or motor shaft is an important factor in the suitability and reliability of a system design. Finite element modelling can predict the natural vibration and forced vibration based on the expected harmonics and speeds. However, modelling can only go so far, and oftentimes a measurement setup is required, such as ENSURE, for physical validation of the key assumptions. The key design strategy for reducing the risk of torsional-induced component failures (which is to ensure that torsional natural frequencies of the shaft systems are sufficiently detuned from the induced stimulus occurring at specific harmonics of the shaft speed) can be verified by measuring the torsional natural frequencies to ensure they are properly detuned.
One method of identifying the torsional natural frequencies is based on the instantaneous rotational speed of the shaft and its subsystems at various points. This method is preferred because of its advantages over vibration analysis. A data acquisition system based on a timer/counter method for pulse signal detection is key. It must be ensured that it can handle the varying rotational speeds and that the digital or analog signatures can be obtained effectively. Owing to the simultaneous data acquisition of these signals, the information is captured at the same instantaneous rotational speed at the various points of interest on the shaft subsystems. Thus, the difference in signal between the various instantaneous rotational speed measurements can be post-processed to derive the resulting torsional excitations.
The signals that are fed to the data acquisition system are typically magnetic pick-ups that detect changes in the magnetic field or magnetic flux, typically resulting from metallic teeth passing the sensor. Passive sensors like the magneto-resistive or magneto-inductive pick-ups are often used in such applications because of their robustness and low sensitivity to ambient contaminants. The measured voltage from the sensor is generated by the changing flux, given by Faraday’s law. As the change of the magnetic flux comes from the rotation of the shaft, the sensor does not need to be powered. The amplitude and shape of the delivered signal however vary with the speed of the shaft and may affect the accuracy of the teeth detection, mostly at low rotational speeds.
Other magnetic sensors are based on the Hall-effect. Often those sensors are equipped with miniaturized electronic circuits to condition the output to deliver a TTL type of output signal and need to be powered.
Once the desired experimental validation data is acquired and logged to the file, it is then ready for analysis with specialized software such as FloINT. There are several types of frequency spectra that are commonly used. Each of the three main methods will be covered.
The Joint-Time Frequency spectrum provides noise or vibration information on a data set divided up into time intervals. For rotating machinery, order analysis is very effective for examining vibration magnitudes correlated to the unit under the test's rotational speed. Joint-Time Frequency analysis divides a data set into time intervals and performs a Fast-Fourier Transform (FFT) on the data in each time interval separately. This enables you to inspect how the frequency content of a signal develops over time.
In the Order Analysis Frequency Spectrum method, the magnitude of the frequency content is examined slightly differently. Frequency is displayed on one axis, Rotational Speed on a second axis, and frequency magnitudes on a third axis. This enables analysis of vibration magnitudes tracked with rotational speed. For example, as a motor is run from startup (0 RPM) to low speed (1000 RPM), the vibration the motor experiences changes at different RPM levels. Order analysis allows identification of the critical rotational speeds that drive the noise or vibration of the UUT, perhaps to examine natural frequencies or other design problems.
The Order Analysis Order Spectrum method is very similar to the Order Analysis Frequency Spectrum method. The main difference is that a quantity called "Order" replaces frequency on one axis. Order simply represents the frequency of the vibration divided by the instantaneous rotational frequency of the unit under test. This analysis easily identifies relative overtone amplitudes of the rotational speed as the rotation speed develops.
Many issues have been solved or even prevented by the consistent application of torsional vibration measurement, analysis, and design improvement. ATA engineers are available for consultations on methods, software tools, and hardware systems to eliminate unwanted torsional vibration.
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