Showing posts with label GPR. Show all posts
Showing posts with label GPR. Show all posts

Wednesday, April 16, 2014

Python-3 Ground Penetrating Radar

Wireless Monostatic Ground Penetrating Radar with one receiving-transmitting antenna Python-3.

4 frequency modules (25, 38, 50, 100 MHz) of the Python-3  - Wireless Monostatic Ground Penetrating Radar with one receiving-transmitting antenna4 frequency modules (25, 38, 50, 100 MHz) of the Python-3  - Wireless Monostatic Ground Penetrating Radar with one receiving-transmitting antenna

Features

  • FREQUENCES: 100 / 50 / 38 / 25 MHz
  • ANTENNA LENGTH: from 1 m to 4 m, depends on selected frequency
  • WEIGHT: from 10 kg to 20 kg, depends on selected frequency
  • TIME RANGE: from 1 to 1500 ns, step 1 ns
  • SCAN RATE: 28 scans per second
  • SAMPLES PER SCAN: 1024 samples per scan
  • RESOLUTION: 16 bit
  • FILTERS: Preset and Customized digital filters.
  • GAIN: 9 points digital gain function
  • DATA TRANSFER: through built-in Wi-Fi to PC.
  • POWER: Built-in battery 12 V, 9 A*h with battery life more than 7 h
Python-3 georadar is a portable digital subsurface sounding radar carried by a single operator, especially used for deep surveys (up to 50 meters* in favorable ground). The unit is designed for solving a long-range of geotechnical, geological, engineering and other tasks wherever nondestructive operational environmental monitoring is needed. In the sounding process, the operator is getting real-time information as a radiolocation profile (sometimes also referred to as radargram) on a display. At the same time, data are recorded on a hard disc for further use (processing, printout, interpretation, etc.). Examples of radiolocation profiles you can see below.

Thursday, January 23, 2014

Ancient Stone Bridge Surveying by Ground-Penetrating Radar and Numerical Modeling Methods

Solla, M., Riveiro, B., Lorenzo, H., and Armesto, J. (2014). ”Ancient Stone Bridge Surveying by Ground-Penetrating Radar and Numerical Modeling Methods.” J. Bridge Eng., 19(1), 110–119.

Bridges are considered necessary engineering structures because they connect separated lands to improve economic and social development. In Spain, many of the bridges in service within the network of transport are masonry arch bridges built in ancient times. In addition to their age, the stability of these remaining bridges is questionable because of the changing loading conditions; therefore, they require periodic assessment of the condition state. Moreover, some of these bridges are considered a part of the cultural heritage of a region, so nondestructive evaluation is required to preserve their historical character. In this work, a medieval stone bridge in the Galician territory of Spain was evaluated using ground-penetrating radar, supported by a detailed geometric survey performed through a terrestrial laser scanner. The results revealed unknown geometrical data and hidden characteristics, including the thickness of ring stones in the interior of the vault, as well as the presence of ancient arches and restorations. To assist in the interpretation, finite-difference time-domain modeling was used, where realistic models were built from the accurate geometry provided. The synthetic data obtained were compared with the field data, which allowed for the identification of unknown structural details.

Source

Monday, September 29, 2008

The Detection of Buried Pipes From Time-of-Flight Radar Data

Ultrawideband radar is commonly used in the frequency range of 50–500 MHz to detect buried pipes at a depth of about 1–2 m depending on the soil characteristics. The typical feature used to locate the pipes is the hyperbolic pattern of the time of flight generated by a linear scan of the antenna above the surface. When the pipes are close together, the hyperbolas overlap, and a straightforward least squares fit is not possible. The Hough transform provides one possible solution. This paper extends the Hough transform by introducing a weighting factor depending on the differentials of the unknown parameters with respect to the experimental errors, namely, the probe position error and the time-of-flight error. This enables optimally placed sets of data pairs to be given greater weight than “ill-conditioned” sets, as for example when all data pairs lie near one end of the arc. The result is a decrease in the background amplitude with respect to the maximum of the peaks in the Hough accumulator space. It is shown that this improvement persists even when many arcs are present. A mathematical analysis with analytical results is given for the case of four unknowns: pipe radius $R$ , pipe center position ($Y$, $Z$), and soil propagation velocity $V$. The results are presented through simulations introducing controlled uncertainties in the probe position, the time of flight, and its bin size. The simulations demonstrate the correlations that occur between the radius, depth, and velocity for given experimental uncertainties. - Reference