Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Mechanical measurement system
Reexamination Certificate
2002-12-04
2004-09-14
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Mechanical measurement system
C073S579000
Reexamination Certificate
active
06792360
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention generally relates to vibration analysis for monitoring the condition of machinery. More specifically, the invention is directed to systems and methods for detecting the development or presence of defects, or other impactive forces, in the components of a machine by analysis of the frequency spectrum of the vibrations of the machine.
2. Description of the Related Art
It is common for industrial and commercial facilities to operate a large number of machines concurrently, many of which may cooperate in a large interdependent process or system. Despite increasingly efficient maintenance programs, at any time some percentage of the machines develop defects that are likely to lead to machine failure. For example, machines having moving parts (e.g., bearings) experience constant friction that results in wear. It is known that bearing failures are a major cause of motor faults. Bearing damage due to wear may not be apparent, however, absent gross damage or failure of the motor because the bearing's wear site is most likely concealed in the motor's assembled state.
Consequently, the use of machine condition monitoring systems has become essential to preventive maintenance of industrial machinery in order to avoid down time or catastrophic failure of machines. Unscheduled plant shutdowns can result in considerable financial losses. Failure of high performance machinery can lead to fatal injury and processing system backup. Typical benefits from a preventive maintenance program include longer periods between machinery shutdowns, evaluation of the condition of machine components without resorting to costly and/or destructive disassembly for visual inspection, and prolonging the machinery's operational life by taking corrective action when developing faults are identified early.
Rotating and reciprocating components of a machine produce vibrations having a wide range of frequencies. The vibration of a machine or a machine component may be characterized as the sum of amplitudes (or “peaks”) at a “fundamental frequency” (or “natural frequency”) and its harmonic frequencies. As used here the term “harmonic frequency” refers to a frequency that is a multiple of the fundamental frequency. Typically, the harmonic components (i.e., peak and frequency values) of a vibration are plotted as vertical lines on a diagram of amplitude versus frequency. This diagram is commonly referred to as a “frequency spectrum,” “spectral diagram,” or “spectrum plot.”
The frequencies and associated peaks of the vibrations of a specific machine collectively make up the “frequency spectrum” for the machine, also known as the machine's “vibration signature.” A machine's vibration signature varies with, for example, the design, manufacture, application, and wear of its components. The machine's normal operating conditions determine the amplitude of steady (or “normal”) vibration. It is a common practice to obtain a reference frequency spectrum when the machine is known to be in good condition for comparison against future measurements of the machine's frequency spectrum. Such comparison aids in detecting changes in the condition of the machine or its subcomponents. Hence, analysis of a machine's vibration signature provides valuable insights into the condition of the machine.
The machine's frequency spectrum typically shows one or more discrete frequencies around which the vibration energy concentrates. Since the vibration characteristics of individual components of a machine are usually known or can be estimated, distinct frequencies of the frequency spectrum may be associated with specific machine components. That is, it is possible to relate each peak of the machine's frequency spectrum to a specific component of the machine. For example, a peak at a given frequency may be associated with the rotational speed of a particular motor. The machine's frequency spectrum serves to indicate that the motor might be the cause of the machine's vibrations. If the motor is causing excessive vibrations, changing either the motor or its speed of operation might avoid deleterious resonance (i.e., excessive and damaging vibrations).
Typically, as a component of a machine wears down or develops a defect, the vibration level of the component and the machine increases. Hence, many machine faults have a noticeable effect on the size and shape of the peaks of the machine's frequency spectrum. If a component defect produces a known frequency, the peak at that frequency increases as the fault progresses. The frequency thus arising is termed a “fault frequency” or “defect frequency.” Usually the defect also produces vibrations of frequencies that are multiples of the fault frequency (i.e., harmonics), in addition to the fault frequency. For example, the meshing of gears produces several harmonics, and the peaks of the higher harmonics indicate the quality of the gear mesh. Thus, changes in peaks of vibrations may indicate developing defects, and the health of a particular component may be analyzed by considering the peaks at its fundamental and/or harmonic frequencies.
The term “component defect” as used here refers in general to any undesirable machine or component vibration condition (“fault”) that is detected by a vibration sensor and may be represented with a spectral harmonic series. The term “defect” is to be understood as a developing or fully developed fault. For example, a defect may be simply the wear of a gear tooth, or a flat spot on a bearing.
There are several methods of identifying a component defect by analysis of a machine's frequency spectrum. In one method, detection of a component defect is made by identifying amplitude peaks at the vibration frequency, or frequencies, of the component defect. However, in practical applications, the true component defect frequency may not be the same as that given by the component manufacturer or that which is predicted by on-site measurements. Additionally, although a nominal value for the defect frequency is readily calculable, measurement errors and the combination of the vibration signals from different components and other sources result in a signal-to-noise ratio at the defect frequency that may be insufficient for accurate analysis.
Another method of detecting component defects is to use a frequency search band around the nominal component defect frequency, the search band having a bandwidth of a certain percentage of its center frequency. The highest peak within the search band is identified as the component defect signal. This method is often referred to as constant percentage bandwidth (CPB) analysis.
However, CPB has its shortcomings and, consequently, in some cases it is not satisfactory. Since the bandwidth of the search band is a percentage of the center frequency, the higher the center frequency the wider the search band. At the high frequencies the search band grows very wide and includes more peaks within it. Often, for high order harmonic search bands, the strongest peak within the band may not be harmonically related. This results in non-harmonic peaks being identified as component defect harmonics, which leads to inaccurate results.
Thus, there is a continuing need in the industry for systems and methods that define current condition of the machine and predict safe operating life accurately relying on the fewest measurements and incurring the least cost.
SUMMARY OF THE INVENTION
The methods and systems of the invention have several aspects, no single one of which is solely responsible for its desirable attributes. Without limiting the scope of this invention as expressed by the claims which follow, its more prominent features will now be discussed briefly.
The systems and methods of the invention generally concern devices and techniques for detection of component defects, or other impactive phenomena, in machinery. In one embodiment, the invention provides a method of deriving a parameter (“I
HAL
”) whose value is correlated with th
Boerhout Johannes I.
Smulders Adrianus J.
Wei Jim J.
Hoff Marc S.
Knobbe Martens Olson & Bear LLP
SKF Condition Monitoring Inc.
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