Scanning seismic intrusion detection method and apparatus

An intrusion monitoring system includes an array of seismic sensors, such as geophones, arranged along a perimeter to be monitored for unauthorized intrusion as by surface movement or tunneling. Two wires lead from each sensor to a central monitoring station. The central monitoring station has three modes of operation. In a first mode of operation, the output of all of the seismic sensors is summed into a receiver for amplification and detection. When the amplitude of the summed signals exceeds a certain predetermined threshold value an alarm is sounded. In a second mode of operation, the individual output signals from the sensors are multiplexed into the receiver for sequentially interrogating each of the sensors

Market analysis of seismic security systems

This report provides information on the commercialization potential of the NASA Activity Monitor. Data on current commercially available products, market size, and growth are combined with information on the NASA technology and the projected impact of this technology on the market

Stacked Convolutional and Recurrent Neural Networks for Bird Audio Detection

This paper studies the detection of bird calls in audio segments using stacked convolutional and recurrent neural networks. Data augmentation by blocks mixing and domain adaptation using a novel method of test mixing are proposed and evaluated in regard to making the method robust to unseen data. The contributions of two kinds of acoustic features (dominant frequency and log mel-band energy) and their combinations are studied in the context of bird audio detection. Our best achieved AUC measure on five cross-validations of the development data is 95.5% and 88.1% on the unseen evaluation data.Comment: Accepted for European Signal Processing Conference 201

Study concerning nonlinear mixing of radio frequency signals in steel structures Final report

Locating technique for nonlinear interference source of radio frequency signals in steel structur

Context Aware Sensor Collaboration for Intelligent Wireless Communications an AI Approach to Moving Sensor Managemet

Collaborative sensor data service is an emerging technology and it is beneficial to various applications including robotics, medicals, industry and military. Sensor collaborations improve technical difficultiesonthe verification and validation of sensor data or reduction of wireless sensor data transmission. However, typical approaches to sensor collaborations are less satisfactory. It is in part because the sensor calibrations are pre-fixed and therefore they are less adaptive to dynamic changes in environment. It is also because sensors are calibrated one time before deployment, and their collaborations do not take into consideration the dynamic movement of sensors. Their calibrations are not satisfactorily adaptive to environmental changes, or their collaborations are less efficient to cope with abrupt presence/absence of sensors. This paper proposes a two-tier deep learning technique to enable sensor devices to be adaptive and moving sensors to be collaborative. The contribution of this paper is an intelligent identification of environment changes and intelligent rearrangement of wireless sensor network

Noncontacting device to indicate deflection of turbopump internal rotating parts

Phase 2 (development) which was concluded for the ultrasonic Doppler device and the light-pipe-reflectance device is reported. An ultrasonic Doppler breadboard system was assembled which accurately measured runout in the J-2 LOX pump impeller during operation. The transducer was mounted on the outside of the pump volute using a C-clamp. Vibration was measured by conducting the ultrasonic wave through the volute housing and through the fluid in the volute to the impeller surface. The impeller vibration was also measured accurately using the light-pipe probe mounted in an elastomeric-gland fitting in the pump case. A special epoxy resin developed for cryogenic applications was forced into the end of the fiber-optic probe to retain the fibers. Subsequently, the probe suffered no damage after simultaneous exposure to 2150 psi and 77 F. Preliminary flash X-radiographs were taken of the turbine wheel and the shaft-bearing-seal assembly, using a 2-megavolt X-ray unit. Reasonable resolution and contrast was obtained. A fast-neutron detector was fabricated and sensitivity was measured. The results demonstrated that the technique is feasible for integrated-time measurements requiring, perhaps, 240 revolutions to obtain sufficient exposure at 35,000 rpm. The experimental verification plans are included