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PMMA plate with different AE sources

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NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/15056368
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This dataset consists of AE signals generated by different sources on a PMMA plate. It is intended for studying and experimenting with data-based approaches for AE source classification. The PMMA plate is excited using three distinct AE sources: Pencil-lead breaks (Hsu-Nielsen source with 0.5 mm leads) Pulsing by the AMSY-6 acoustic emission measurement system with 30 Vpp Salt trickling from a salt shaker, positioned approximately 20 cm away YouTube Video Structure Material: Polymethyl methacrylate (PMMA) Dimensions: 300 x 300 x 9.7 mm Measurement chain Vallen AMSY-6 AE measurement system with ASIP-2A signal processor cards 4x Vallen VS150-RSC sensors with 34 dB preamplifier gain Measurement settings: Filter: 95-300 kHz Threshold: 40 dBAE Duration discrimination time: 1000 µs TR (transient/raw data): Samplerate: 2500 kHz Pretrigger samples: 100 Post-duration samples: 1000 Sensor positions The sensors are arranged in a square configuration on the PMMA plate: Channel X [mm] Y [mm] 1 50 50 2 250 50 3 50 250 4 250 250 Files Each measurement consists of two SQLite3 database files: *.pridb: The primary database, that stores just the AE features (amplitude, energy, counts, duration, rise time, ...) and the index of the transient/raw data TRAI. Use the table view_ae_data. *.tradb: The transient database, that stores the raw data for each hit record referenced by the TRAI index. Use the table view_tr_data. The raw data is stored in the Data column in binary format (int16 values). The factor from column TR_mV can be used to transform the integer values to millivolts. You may want to use the Python library vallenae to easily read the measurement files. Examples classifier-openae.ipynb: SVM classifier trained with OpenAE features classifier-standard.ipynb: SVM classifier trained with standard AE features
创建时间:
2025-03-20
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