A density detection system uses a magnetic force feedback actuator positioner to maintain a precise selected pressure between transducer wheels and the surface of a sheet of material as the sheet of material moves through a position between transducer wheel and lift wheel. Consequently, the antiquated mechanical/pneumatic springs/airbags of prior art ultrasonic density detection systems are replaced with a highly responsive magnetic force feedback actuator positioner capable of providing a precise and relatively constant force that can react to the introduction of a sheet of material, and/or variations in the surface of a sheet of material, extremely rapidly without the bounce/recovery oscillations associated with prior art ultrasonic density detection systems. Consequently, precise density measurements of an entire sheet of material can be obtained with unprecedented accuracy.

An optical fiber distributed acoustic sensor (DAS) system for detecting a red palm weevil and/or its larvae inside a tree. The system includes an optical fiber that is configured to be placed next to a tree; and a DAS box optically connected to the optical fiber and configured to receive a reflected light from the optical fiber. The DAS box includes electronics that extracts from the reflected light a frequency in a range of [400 Hz, 4 kHz], and sends a message indicating a presence of the red palm weevil and/or its larvae inside the tree.

Non-limiting examples of the present disclosure describe a non-destructive evaluation (NDE) application/service that is configured for NDE of a wooden specimen. The NDE application/service provides a user-friendly graphical user interface that enables inspectors to manage each phase of NDE of a wooden specimen through one or more computing devices. An exemplary NDE application/service is configured to analyze captured acoustic signal data (e.g., ultrasonic signal data) and transform that captured signal data into feature information that is used to more accurately assess the structural integrity of a wooden specimen. For instance, execution of a programmed NDE application/service employs a trained artificial intelligence (AI) classifier that evaluates waveform propagation (e.g., TOF and energy attenuation) through a wooden specimen to classify a condition and a quality the wooden specimen. An NDE report may be generated that provides an inspector with an assessment of the wooden specimen and/or a network of wooden specimen.

A method for determining tree infestation includes placing an optical fiber around a trunk of a tree; recording with a distributed acoustic sensor (DAS) box a Rayleigh signal reflected from the tree, along the optical fiber; processing the Rayleigh signal to obtain a processed signal; calculating a signal-to-noise ratio (SNR) of the processed signal for the tree; and comparing the SNR to a threshold value and counting an alarm if the SNR is larger than the threshold value. The SNR is defined as a ratio between (1) a maximum value of a processed signal and (2) a minimum value of the processed signal.

An integrated system for detecting a red palm weevil (RPW), farm fire, and soil moisture includes an optical fiber configured to be extending to a tree, and a distributed acoustic sensor (DAS) box connected to the optical fiber. The DAS box is configured to process first to third different optical signals reflected from the optical fiber, to determine a presence of the RPW from the first optical signal, a temperature at a location along the optical fiber from the second optical signals, and a moisture at a location around the tree from the third optical signal.

A measuring system includes a plurality of support posts, a winding device configured to wind a cable supported by the support posts, a winding device configured to wind the cable, a hoisting device coupled to the cable and configured to move in an air when the cable is wound by the winding device, and a measuring device hung from the hoisting device and configured to measure a strength of a tree.

Structural health monitoring (SHM)/nondestructive evaluation (NDE) exists as a tool in conjunction with manufactured pieces. Presently disclosed subject matter integrates automated video with a structural health monitoring system. In conjunction with bridge monitoring, integration of such two systems automates determination of the effect or correlation of vehicular loading on SHM data from a subject bridge. Such correlations help to understand the sources of structural health monitoring data, particularly acoustic emission data, in bridges and other structures, such as dams and nuclear plants. Automation of the evaluation of bridges and other structures increases accuracy and minimizes risk to workers and the public. Assessing the structural condition of bridges and other structures as presently disclosed also facilitates automated asset management of transportation systems, such as by state departments of transportation and other bridge/structural owners.

Methods and systems, including computer-implemented methods, computer program products, and computer systems for wooden pole integrity assessment. One computer-implemented method includes emitting, by one or more acoustic sources mounted onto a wooden pole, one or more sound waves through the wooden pole. Further, the method includes measuring, by one or more acoustic receivers mounted on the wooden pole, a respective amplitude and time of arrival of at least a portion of each of the one or more sound waves. Additionally, the method includes calculating, using the respective amplitude, the respective time of arrival, and a predetermined function, the real-time integrity level of the wooden pole. The method also includes in response to determining that the real-time integrity level of the wooden pole is less than a threshold level, outputting an alert indicating that the integrity level of the wooden pole is less than the threshold level.

A filler material is applied to a plurality of wood elements. The plurality of wood elements is bonded into a composite wood product, where the bonding includes delivering ultrasound energy to the plurality of wood elements. The ultrasound energy has a frequency within a frequency range of 10 kHz-20 MHz.

Embodiments provide systems, apparatuses, and method for determining the Modulus of Elasticity (MOE) of a wood workpiece based on the travel time and/or velocity of an impact-induced acoustic stress wave. A housing may be configured to reduce extraneous acoustic waves and/or contaminants near an acoustic transducer to thereby reduce errors in the detection/identification of the acoustic stress wave. A computer system may be programmed to determine the MOE of the workpiece based on the travel time and/or velocity of multiple acoustic stress waves induced by corresponding impacts at respective locations along the end of the workpiece as the workpiece travels in a first direction. Corresponding methods and an induction system for rapidly and repeatedly striking the end of the workpiece are also described herein.