Multi-defect detection based on ultrasonic Lamb wave sign phase coherence factor imaging method

The ultrasonic Lamb wave total focusing method (TFM) only uses the amplitude of the defective scattered signal for virtual focused imaging, while ignoring the phase information of the scattered signal and the dispersion characteristics of the Lamb wave, resulting in low imaging resolution and easily produced artefacts in imaging. To solve this problem, an ultrasonic Lamb wave imaging method based on phase coherence is proposed in this paper and the sign coherence factor (SCF) in the full matrix scattering signal is extracted. Moreover, the method uses the SCF to weight the amplitude of the full matrix scattering signal, suppresses the side lobes of the defect echo signal and the Lamb wave dispersion effect, improves the ultrasonic Lamb wave imaging resolution and weakens the artefacts. Finally, single- and multiplehole defects in aluminium plates are detected for experimental validation using an ultrasonic phased array. The array performance indicator and signal-to-noise ratio are used as indicators for quantitative assessment of imaging performance. The results show that compared with the TFM imaging, the SCF imaging can effectively suppress the noise and scattered signal side lobes, improve the array performance indicator (API) by 69.1% and improve the signal-to-noise ratio (SNR) by 73.9%. In addition, the SCF imaging can effectively weaken the interference of scattered signals between multiple through-hole defects, resulting in fewer artefacts in imaging.

Industry 4.0-Oriented Chipless RFID Backscatter Signal Variable Polarization Amplitude Deep Learning Coding

Due to the weak network security protection capabilities of control system network protocols under Industry 4.0, the research on industrial control network intrusion detection is still in its infancy. This article discussed and researched the intrusion prevention technology of industrial control networks based on deep learning. According to the electromagnetic scattering theory, the backscatter signal model of the chipless tag was established as a chipless tag structure. Polarized deep learning coding was used for the label; that was, deep learning coding was performed on the copolarization component and the cross-polarization component at the same time, and a 16-bit deep learning coding bit number was obtained. The wave crest deep learning coding was used for the split ellipse ring patch label, and the 6-bit deep learning coding bit number was obtained. Then, the poles of the scattered signal of the tag were extracted to identify the tag. The variable polarization effect was achieved by adopting the dipole resonant unit with the two ends bent. Aiming at the problem of low detection rate caused by the shallow selection of feature classification of intrusion prevention systems, an industrial control network intrusion prevention model based on self-deep learning encoders and extreme learning machines was proposed to extract features from industrial control network data through deep learning. For accurate classification, the theoretical judgment was also verified through simulation experiments, and it was proved that the detection rate of the model has also improved. It forms a set of industrial control network intrusion prevention system with complete functions and superior performance with data acquisition module, system log module, defense response module, central control module, etc. The matrix beam algorithm was used to extract the poles and residues for the late response, and the extracted poles and residues were used to reconstruct the signal. The reconstructed signal was compared with the scattered signal to verify the correctness of the pole extraction. Finally, the tags were processed and tested in the actual environment, and the measured results were consistent with the theoretical analysis and simulation results.

Particle Classification through the Analysis of the Forward Scattered Signal in Optical Tweezers

The ability to select, isolate, and manipulate micron-sized particles or small clusters has made optical tweezers one of the emergent tools for modern biotechnology. In conventional setups, the classification of the trapped specimen is usually achieved through the acquired image, the scattered signal, or additional information such as Raman spectroscopy. In this work, we propose a solution that uses the temporal data signal from the scattering process of the trapping laser, acquired with a quadrant photodetector. Our methodology rests on a pre-processing strategy that combines Fourier transform and principal component analysis to reduce the dimension of the data and perform relevant feature extraction. Testing a wide range of standard machine learning algorithms, it is shown that this methodology allows achieving accuracy performances around 90%, validating the concept of using the temporal dynamics of the scattering signal for the classification task. Achieved with 500 millisecond signals and leveraging on methods of low computational footprint, the results presented pave the way for the deployment of alternative and faster classification methodologies in optical trapping technologies.

Investigation of X-band backscattering from wave breaking in a laboratory experiment

<p>The work is concerned with the study of the breaking surface wave effect on the intensity and spectral characteristics of a scattered radar signal in laboratory conditions.</p><p><span>The experiments were carried out on the reconstructed TSWiWaT wind wave flume of the IAP RAS. The channel is 12 m long, the channel cross-section varies from 0.7 x 0.7 m at the entrance to 0.7 x 0.9 m in the working section at a distance of 9 m. The airflow speed on the axis is 3-35 m/s, which corresponds to the values of the wind speed U</span><sub>10</sub><span> of 11-50 m/s.</span></p><p>The wave characteristics in the flume were measured by an array of three wave gauges positioned in the corners of an equal-side triangle with 2.5 cm side, the data sampling rate was 200 Hz. Such a system gives the opportunity to retrieve 3D frequency-wave number spectra of surface waves.</p><p>The airflow parameters were measured using the profiling method. The velocity profiles were measured in the working section using an S-shaped Pitot tube. Microwave measurements were carried out using an X-band coherent Doppler scatterometer with a wavelength of 3.2 cm with sequential reception of linear polarizations.  The absolute value of the radar cross-section (RCS) on the wavy water surface was determined by comparing the scattered signal with the signal reflected from the calibrator with a known value of the RCS - a metal ball with a diameter of 6 cm. The dimensions of the observation cross-section were 40 cm x 40 cm, the incidence angles were 30°, 40°, 50° for the upwind direction, the distance to the target was 3.15 m.</p><p>Two series of experiments were carried out. In the first case, wind waves on the surface of pure deep water, developing under the action of a fan generated wind, were studied. In the second case, a train of three waves was generated at the beginning of the channel, with the fan turned on, in order to simulate shallow water an inclined plate was placed under water in front of the measurement area. As a result, the breaking waves occurred at a fixed point and at weaker winds compared to the first case.</p><p>As a result, an increase in the scattered signal intensity during artificial wave breaking in the case of weak winds was noted. For strong winds, the effect turned out to be insignificant, despite the increased amplitude of the waves under study. The Doppler spectra analysis is also presented.</p><p>This work was supported by the RFBR projects No. 19-05-00249, 19-05-00366.  </p>

Measurement of Visibility and Present Weather Detection Using Scattering Technique of Light

A forward-scatter meter measures a small portion of light scattered out of a light beam into a relatively narrow band of scattering angles. The forward-scatter meter measurement is then used to estimate the extinction coefficient; the scattered signal is assumed to be proportional to the extinction coefficient.

Ionosphere modification and topology of ionospheric magnetically-oriented irregularities

One of the perspective directions of active impact on the ionosphere is the for-mation of electron concentration irregularities. Such irregularities can be used to increase the efficiency of radar systems and signal transfer in an interlayer ionospheric waveguide. Experiments on Alaska-Antarctica path showed that signal level at a receiving site is de-termined by heating wave parameters. In this case we did not study the character of its level change with time, i.e. possible fading, that is very important for radio-engineering systems. It is known that fading is determined by dimensions and space distribution of irregularity. Observations over EISCAT experiments make it possible, to some degree, to show the character of a scattered signal and the topology of ionospheric magnetically-oriented irregularities in the area of active impact on the ionosphere.

Irkutsk Incoherent Scatter Radar: history, present and future

The article focuses on the history of ionospheric research using the incoherent scatter method at the Institute of Solar-Terrestrial Physics and development of the only incoherent scatter radar in Russia, which is located near Irkutsk. It describes the radar features and the current situation of research at the Irkutsk Incoherent Scatter Radar (IISR). Operating modes and types of measurements of the radar are specified. There is a brief description of the original measurement techniques that were developed considering the IISR features such as the frequency principle of scanning and receiving of one linear polarization of a scattered signal. The main feature of the IISR is the possibility of obtaining absolute values of the ionospheric plasma electron density. The automatic method for constructing the electron density vertical profile is based on registration of vertical profiles of a rotation phase of the polarization plane of a scattered signal. The method does not require calibration with additional facilities.

Преобразование частоты излучения мощных гиротронов в условиях обратного рамановского рассеяния на дополнительном электронном пучке

The regime of Raman backscattering of a pumping wave that is cocurrent with an electron beam into the counterpropagating wave can be used for the radiation frequency conversion in high-power gyrotrons. The absolute instability developing in this system ensures generation of a scattered signal in the absence of external resonators, which allows the frequency of scattered radiation to be smoothly controlled within 20–40% by varying the electron energy in the case of high-power (megawatt) gyrotrons used as sources of pumping radiation.