Millimeter Wave Scattering from Neutral and Charged Water Droplets

We investigated 94GHz millimeter wave (MMW) scattering from neutral and charged water mist produced in the laboratory with an ultrasonic atomizer. Diffusion charging of the mist was accomplished with a negative ion generator (NIG). We observed increased forward and backscattering of MMW from charged mist, as compared to MMW scattering from an uncharged mist. In order to interpret the experimental results, we developed a model based on classical electrodynamics theory of scattering from a dielectric sphere with diffusion-deposited mobile surface charge. In this approach, scattering and extinction cross-sections are calculated for a charged Rayleigh particle with effective dielectric constant consisting of the volume dielectric function of the neutral sphere and surface dielectric function due to the oscillation of the surface charge in the presence of applied electric field. For small droplets with (radius smaller than 100nm), this model predicts increased MMW scattering from charged mist, which is qualitatively consistent with the experimental observations. The objective of this work is to develop indirect remote sensing of radioactive gases via their charging action on atmospheric humid air.Comment: 18 pages, 8 figure

Remote Detection of Chemicals by Millimeter-Wave Spectroscopy

This paper discusses the development and field testing of a remote chemical detection system that is based on millimeter-wave (mm-wave) spectroscopy. The mm-wave system is a monostatic swept-frequency radar that consists of a mm-wave sweeper, a hot-electron-bolometer detector, and a trihedral reflector. The chemical plume to be detected is situated between the transmitter/detector and the reflector. Millimeter-wave absorption spectra of chemicals in the plume are determined by measuring the swept-frequency radar return signals with and without the plume in the beam path. The problem of pressure broadening, which hampered open-path spectroscopy in the past, has been mitigated in this work by designing a fast sweeping source over a broad frequency range. The heart of the system is a Russian backward-wave oscillator (BWO) tube that can be tuned over 225--315 GHz. A mm-wave sweeper that includes the BWO tube was built to sweep the entire frequency range within 10 ms. The radar system was field-tested at the DOE Nevada Test Site at a standoff distance of 60 m. Methyl chloride was released from a wind tunnel that produced a 2-m diameter plume at its exit point. The mm-wave system detected methyl chloride plumes down to a concentration of 12 ppm. The measurement results agree well with model-fitted data. Remote or standoff sensing of airborne chemicals is gaining importance for arms control and treaty verification, intelligence collection, and environmental monitoring

Near-field millimeter - wave imaging of nonmetallic materials

A near-field millimeter-wave (mm-wave) imaging system has been designed and built in the 94-GHz range for on-line inspection of nonmetallic (dielectric) materials. The imaging system consists of a transceiver block coupled to an antenna that scans the material to be imaged; a reflector plate is placed behind the material. A quadrature IF mixer in the transceiver block enables measurement of in-phase and quadrature-phase components of reflected signals with respect to the transmitted signal. All transceiver components, with the exception of the Gunn-diode oscillator and antenna, were fabricated in uniform blocks and integrated and packaged into a compact unit (12.7 x 10.2 x 2.5 cm). The objective of this work is to test the applicability of a near-field compact mm-wave sensor for on-line inspection of sheetlike materials such as paper, fabrics, and plastics. This paper presents initial near-field mm-wave images of paper and fabric samples containing known artifacts

Quantitative MRI Measurement of Binder Distributions in Green-State Ceramics

Development of reliable and improved structural ceramics for advanced heat engines and other applications requires process diagnostics and materials evaluation from powder preparation to green-body forming to final sintering. Injection molding is a promising processing method being developed for mass production of complex-shaped heat engine components such as turbochargers (rotors and stator vanes) and engine valves. Major processing steps in injection-molded ceramic manufacturing include preparation of ceramic powders and organic binders, mixing, molding, binder removal, sintering, and finishing [1]. While materials evaluation and diagnostics are needed throughout the process, it is particularly important to evaluate the distributions of binders/plasticizers in as-molded green bodies [2]. Poor distribution of these organics in a green body can lead to a final part that is defective or that has poor mechanical properties after it is sintered

Visual Measurement of Suture Strain for Robotic Surgery

Minimally invasive surgical procedures offer advantages of smaller incisions, decreased hospital length of stay, and rapid postoperative recovery to the patient. Surgical robots improve access and visualization intraoperatively and have expanded the indications for minimally invasive procedures. A limitation of the DaVinci surgical robot is a lack of sensory feedback to the operative surgeon. Experienced robotic surgeons use visual interpretation of tissue and suture deformation as a surrogate for tactile feedback. A difficulty encountered during robotic surgery is maintaining adequate suture tension while tying knots or following a running anastomotic suture. Displaying suture strain in real time has potential to decrease the learning curve and improve the performance and safety of robotic surgical procedures. Conventional strain measurement methods involve installation of complex sensors on the robotic instruments. This paper presents a noninvasive video processing-based method to determine strain in surgical sutures. The method accurately calculates strain in suture by processing video from the existing surgical camera, making implementation uncomplicated. The video analysis method was developed and validated using video of suture strain standards on a servohydraulic testing system. The video-based suture strain algorithm is shown capable of measuring suture strains of 0.2% with subpixel resolution and proven reliability under various conditions

Open-path millimeter-wave spectroscopy in the 225--315 GHz range

This paper discusses the development of an open-path millimeter-wave (mm-wave) spectroscopy system in the 225--315 GHz atmospheric window. The new system is primarily a monostatic swept-frequency radar consisting of a mm-wave sweeper, hot-electron-bolometer or Schottky detector, and trihedral reflector. The heart of the system is a Russian backward-wave oscillator (BWO) tube that is tunable over 225--350 GHz. A mm-wave sweeper has been built with the BWO tube to sweep the entire frequency range within 1 s. The chemical plume to be detected is situated between the transmitter/receiver and the reflector. Millimeter-wave absorption spectra of chemicals in the plume are determined by measuring swept-frequency radar signals with and without the plume in the beam path. Because of power supply noise and thermal instabilities within the BWO structure over time, the BWO frequencies fluctuate between sweeps and thus cause errors in baseline subtraction. To reduce this frequency-jitter problem, a quasi-optical Fabry-Perot cavity is used in conjunction with the radar for on-line calibration of sweep traces, allowing excellent baseline subtraction and signal averaging. Initial results of the new system are given for open-path detection of chemicals

Determining bonding quality in polymer composites with a millimeter wave sensor

Microwave nondestructive testing (NDT) techniques offer alternative solutions to other conventional NDT methods. Microwave/millimeter wave (determined roughly to cover 0.3 to 300 GHz) techniques are particularly useful for examination of dielectric composite materials that their low dielectric losses provide good depth of penetration of electromagnetic radiation in this band. Limitations associated with conventional NDT techniques such as high frequency ultrasonic testing (UT), namely, large variations in elastic properties of low density composite materials cause interpretation of complex UT signals difficult. Further, criticality of coupling of transducer to the sample surface limits the use of such techniques for on-line applications. High frequency microwave (millimeter waves, 30--300 GHz) systems compared to their low frequency counterparts offer higher resolution and sensitivity to variations in dielectric properties of low-loss composites. Further, higher frequencies render utilization of more compact systems which are often important for practical applications. A millimeter wave sensor is described in this work which can be utilized for non-contact NDT of a wide range of thin-sheet dielectric composite materials either as a laboratory-based instrument or for on-line quality control applications. Experimental results are presented on noncontact measurement of bonding quality in polyethylene/carbon composite samples. The w-band monostatic sensor operates based on measurement of the reflection properties of the material under test, which are then used to determine the volumetric uniformity of the joint area. Preliminary experimental results indicate the potential for the use of this sensor in fabrication process control of low-loss dielectric composite materials

An application of wavelet transforms and neural networks for decomposition of millimeter-wave spectroscopic signals

This paper reports on wavelet-based decomposition methods and neural networks for remote monitoring of airborne chemicals using millimeter wave spectroscopy. Because of instrumentation noise and the presence of untargeted chemicals, direct decomposition of the spectra requires a large number of training data and yields low accuracy. A neural network trained with features obtained from a discrete wavelet transform is demonstrated to have better decomposition with faster training time. Results based on simulated and experimental spectra are presented to show the efficacy of the wavelet-based methods