Method comparisons, mathematics and practical know-how from 25+ years of inline acoustics. From FFT through natural frequencies to AI classifiers.
Signal processing Filters are the invisible preprocessing without which no clean acoustic evaluation succeeds. We compare IIR and FIR filters, Butterworth and Chebyshev characteristics and show where each topology shines.
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Method comparison Avoid defects or detect defects? We compare continuous process monitoring with classical end-of-line inspection – data integration, reaction time, traceability, investment. And show when both together are unbeatable.
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Practical know-how Where do you set the OK/NOK limit? Too tight = false rejects. Too wide = real defects slip through. We show how normal distribution, Cp/Cpk and tolerance intervals derive robust limits from reference data.
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Foundations Natural frequency alone is half the story. How fast a resonance decays – its Q-factor – is at least as informative. We show the maths and its meaning for defect detection.
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Signal processing When the spectrum itself shows periodicity – e.g. harmonic series of bearing damage – an FFT on the spectrum helps: the cepstrum. We explain quefrency, rahmonics and show when this exotic method is unbeatable.
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Method comparison Cameras see surfaces, acoustics sees insides. We compare vision systems and acoustic testing along defect spectrum, speed and false-positive rates – and show why combination often wins.
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Signal processing The frequency response function describes the ratio of excitation to response as function of frequency. We derive the FRF mathematically, explain coherence as quality metric and show how SonicTC.AT extracts natural frequencies with it.
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Trends & innovation How many OK/NOK samples do you really need? How do you structure data collection across multiple shifts? Field-tested recommendations from 200+ projects.
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Method comparison Computed tomography delivers breathtaking detail – but is too slow and too expensive for 100 % inline. We compare both methods along seven criteria and show where acoustics wins and where CT remains unbeatable.
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Practical know-how Inline integration or downstream offline station? We show the cost model with cycle time, investment, staffing and traceability – including a 5-year example calculation.
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Signal processing Raw FFT amplitude depends on frame length and window. Power spectral density (PSD) makes measurements comparable and yields energy per Hz. We explain autocorrelation, Parseval, Welch and what it means for vibration monitoring.
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Method comparison Rockwell, Vickers, Brinell are sample-only – acoustic resonance measures 100 %. We show the correlation between hardness and natural frequency and compare both methods along six criteria.
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Signal processing Humans do not hear in dB. We explain the key psychoacoustic metrics, their mathematical models and how SonicTC computes them in real time on inline lines.
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Method comparison Both evaluate mechanical products – but carry different information. Airborne sound mirrors customer perception, structure-borne sound delivers root cause. When does one suffice, when do you need both?
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Signal processing On rotating machines fixed frequencies say little – relevant components move with speed. We show how order tracking, resampling and Campbell diagrams reveal the true root causes.
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Method comparison Eddy current sees surfaces, acoustics sees volume. Eddy current needs conductive materials, acoustics does not. A comparison along five practical criteria – including when to combine them.
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Foundations Every body has characteristic vibration frequencies. We derive them from Newton, show the mode shapes of simple geometries and explain why a crack in a brake disc lowers its 4th natural frequency – making it measurable.
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Signal processing Cutting a signal abruptly creates artificial frequency content – the notorious leakage. We compare the most important window functions mathematically and show which window suits which inspection task.
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Method comparison Both methods use sound waves – but they could hardly differ more. Volume inspection vs. holistic assessment, ms vs. seconds, point inspection vs. 100 % inline. A direct comparison along eight criteria.
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Signal processing Sample too slowly and you will see frequencies that do not exist – classical aliasing. We explain the Shannon-Nyquist theorem rigorously, visualise aliasing and give practical recommendations for NVH and resonance analysis.
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Method comparison Microphone, accelerometer or laser vibrometer? We compare the three main sensor classes by frequency range, noise immunity, mounting and cost – including a decision matrix for typical inspection tasks.
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Signal processing The Fast Fourier Transform is the foundation of every acoustic evaluation. We derive DFT and FFT mathematically, explain the butterfly algorithm and show on an electric motor what becomes visible in the spectrum.
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Foundations Three methods, one principle: sound and vibration as information carriers. We explain where noise testing, resonance analysis and process monitoring are used – and where acoustic methods outperform classical NDT.
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