Introduction

In this article, I will explain about systems that use vibration waveform and phase reference data for the analysis and diagnosis of vibration on large rotating machinery.

4. Vibration Analysis & Diagnostic Systems

One method of vibration analysis and fault diagnosis is to use an accelerometer which may be fixed or portable for periodic measurement of bearing vibration. Mechanical vibration is diagnosed using frequency analysis and trend monitoring of vibration amplitude. This is a well-known method that has long been used for vibration analysis and fault diagnosis on small general-purpose rotating machinery supported by rolling bearings. Here, however, I will focus on explaining a system for the analysis and diagnosis of vibration on large rotating machinery that is supported by journal bearings. The large rotating machinery typically operated at above the critical speed as a flexible rotor. The frequency analysis (spectrum analysis) of shaft vibration waveform is generally used for the large rotating machinery, and the phase analysis by using phase reference signal of one pulse per revolution is also applied as one of important diagnostic techniques.

Figure 5 shows the basic components of this system. A keyway-shaped notch is cut out at one point on the rotor. This notch is used as the rotor’s mechanical phase reference position. It is possible to install an eddy-current sensor at this point to obtain a phase reference signal that has one pulse per rotation. These eddy-current sensors were explained in Part 2.

The shaft vibration sensors are installed in pairs with a 90 degree angle between them. These pairs are installed on each bearing, so there are multiple shaft vibration sensors installed for each machine train. However, for the sake of simplicity, Figure 5 shows only one sensor.

As I explained in Part 3, the phase reference signals and vibration waveform signals are input into a condition monitor and the monitor performs conversion to the rotational speed and vibration amplitude and also outputs an alarm and trip signals. At the same time, the signal that is input into the condition monitor is output as a buffer signal. This buffer signal is output via the buffer amplifier and has the same waveform as in the input signal. Normally, this buffer signal is used for vibration analysis. The buffer signal that is output from the condition monitor is input into the data acquisition unit DAQpod. A/D conversion and then arithmetic processing are performed inside the DAQpod. This processing includes analysis such as phase analysis and frequency analysis.

The data that has been arithmetically processed for analysis is then transmitted to a PC for analysis. This PC contains software for analysis (Analysis View VM-773B). The analysis PC performs the drawing processing that is necessary for vibration analysis of rotating machines. This may include diagrams such as trend plots, spectrum plots, orbit plots, and Bodeplots. The analysis PC also saves the data.

Figure 6 shows an example configuration of infiSYS RV-200 analysis and diagnostic system. As shown in the figure, the VM-7 Series condition monitors are equipped with built-in analysis boards so that it is possible to connect the monitors directly to an analysis PC with Ethernet. This means that It is not necessary to connect the VM-7 Series to an external data acquisition unit such as the DAQpod.

Figure 7 shows an infiSYS RV-200 screen display. If, instead of just performing conventional monitoring of machinery abnormalities with a condition monitor, you introduce this kind of analysis and diagnostic system, you can expect the following effects.

It is possible to detect abnormalities that cannot be found when only the overall vibration amplitude is monitored
Some rotor abnormalities can cause sudden phase changes during rated constant-speed operation. However, these abnormalities may not cause an obvious increase in the vibration amplitude. In fact, there may also be an improvement in balance, which may mean that the vibration value decreases. It is possible to detect this kind of abnormality by setting an area alarm (acceptance region) on a polar plot (vector plot).

Accumulation of diagnosis expertise for each machine in the field
Abnormality data is not simply stored as a vibration value. It can also be stored as analysis data such as vibration waveforms and spectrums. This means that the maintenance personnel can perform quantitative and qualitative analysis by linking the analysis data to the results of diagnosis using their five senses and experience, and by linking the analysis data to the results of investigations performed with the machinery disassembled. These quantitative and qualitative analysis results can then be accumulated as diagnosis expertise in the field.

Support for analysis and diagnosis of the cause of abnormalities
When an abnormality occurs, the diagnostic program in the analysis system can perform abnormality cause estimation. This abnormality cause estimation (weighing of possible causes of the abnormality) is performed based on the vibrational spectrum data. This can therefore be used to support the judgments made by maintenance personnel or analysts.

Presenting data to specialists
When an abnormality occurs in the machinery, it is possible to provide the machinery manufacturer and internal and external specialists with detailed data such as waveforms and spectrum data. Sharing data in this way makes it possible to diagnose more quickly and accurately.

Formulating maintenance plans based on vibration trend management
It is possible to use trend data for trend management as a reference when formulating and revising maintenance plans. Even if an abnormal trend appears before the scheduled time of planned maintenance, countermeasures can be considered before the abnormality turns into a major breakdown. It is therefore possible to minimize the effects of the abnormality.

So far, in four articles, I have given an outline of condition monitoring systems for large rotating machinery. I am afraid that some parts may have been difficult to understand for people who are not familiar with these kinds of systems, but I am sure that you have gained some understanding of monitoring systems overall.