What is “Movelet”
The “Movelet” captures the sound and vibrations generated from the object under test and conducts quantitative analysis to make judgments similar to those made based on the human senses.
Also cracks can be inspected using the sound generated when the object under test is tapped.
The “Movelet” can enhance specific frequency ranges by its unique analysis method, enabling inspections at noisy production sites with substantial noise.
Conventional waveform analysis technique has such a problem that the result of analysis differs from that made based on human senses.
The “Movelet”, by its unique analysis method, makes judgments similar to those made based on the human senses.
The conventional waveform analysis is broadly divided into time-series analysis and frequency analysis.
In the time-series analysis, chronological changes can be analyzed along the time axis.However, it is difficult to determine the causes of chronological changes.
|In the frequency analysis, the waveform to be analyzed is resolved into frequency components, and their respective amplitudes are analyzed.|
The FFT (Fast Fourier Transform) is typically used for the frequency analysis.
The FFT is effective to analyze respective frequencies since the data to be analyzed can be resolved into each frequency component.
The concept of time does not exist in the FFT. Consequently the result of analysis substantially differs from the one made based on the human senses; such as the timing of amplitude generation is not reflected in the analysis result and the distinction between intermittent generations of large-amplitude and continuous generations of small-amplitude cannot be made.
Waveform analysis by Movelet is an intermediate method between the time-series analysis and the frequency analysis.
Analysis is made on the time-series waveforms obtained by enhancing specific frequency components (fluctuation conversion) for the input waveform.
The fluctuation conversion processes and enhances specific frequency range components included in the raw waveform.
This processing makes it possible to observe the chronological changes of specific fluctuation components invisible in the raw waveform.
|Humans can recognize certain sounds even in a very noisy place if they really want to hear the sounds. You must have had such an experience in a noisy party room or train station.
This is called “cocktail party effect”,
which is achieved by the locations of sound sources and the frequency differences between different tones of the sound sources. In the same way, the Movelet extracts certain sounds from a mixture of various background sounds to make judgment.
|Perceive a sound Perceive the presence of a sound with the ear|
|Extract the sound under evaluation Extract a particular sound from multiple sound sources|
|Analyze the sound characteristics Analyze the loudness, pitch, vibrancy, timing and the like of a particular sound|
|Make a pass/fail judgment Make a judgment based on the amount of the analyzed intensity|
|Sensor signal acquirement Acquires the waveform data of sounds or vibrations of the product under test with a microphone or acceleration sensor|
|Fluctuation conversion Specifies a frequency band and performs enhancement processing|
|Calculate features Uses root mean square processing to make it easy to recognize the differences in the changes of waveforms, and quantifies them using the prescribed judgment criteria|
|Pass/Fail judgment Sends a pass/fail signal and transmits the quantified data simultaneously|
Enhancement processing of specific frequency ranges is effective for extracting noise components in noisy conditions.
It allows inspection at production sites with substantial noise and vibrations. The figure below shows the ratio of amplitudes when the fluctuation conversion is applied to around 12.5hKz for a sample data of 50 kHz.(Amplitude of waveform after conversion / Amplitude of raw waveform) Enhance the specific frequency ranges by its unique analysis method.
The amount of characteristics is a numeric value for quantitatively judging the waveform characteristics.The Movelet has 8 types of judgment criteria.Judgment using a single or multiple criteria realizes highly accurate testing.
|Automobile||Transmission (MT, AT, CVT)、Power seat、Manual seat、Air-conditioning blower、Electric sunshade、Electric door mirror、Electric window、Wiper motor、Engine (Automobile / Motorcycle)、Horn、Fan motor、Various connector fitting sounds、Suspension、Brake pad、Automobile gear|
|Office automation equipment||Copier、FAX machine、Printer|
|Facility monitoring||Various Production Line、Conveyor、Elevator、Pylon、Tunnel|
|Others||Golf club、Camera(shutter sound,focus motor)、Ceramics、Sintered Object、Ferrite Core、Buildings materials、Brake pad、Bicycle components|
Proposal for transmission assembly noise test system → Download page
Proposal for noise test on various types of motors → Download page
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