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A method of sensing vibrations or displacements remotely is provided. Magnets are attached to vibrating objects or the vibrating objects themselves are magnetic. A number of magnetic sensors are placed a specified distance from the magnets. Vibrational displacement of the vibrating objects is determined according to a model that maps changes in magnetic field to vibrations or spatial displacements.
To reduce energy consumption, emissions, and noise, NASA is exploring the use of high aspect ratio wings on subsonic aircraft. Because high aspect ratio wings are susceptible to flutter events, NASA is also investigating methods of flutter detection and suppression. In support of that work a new remote, non-contact method for measuring flutter-induced vibrations has been developed. The new sensing scheme utilizes a microwave reflectometer to monitor the reflected response from an aeroelastic structure to ultimately characterize structural vibrations. To demonstrate the ability of microwaves to detect flutter vibrations, a carbon fiber-reinforced polymer (CFRP) composite panel was vibrated at various frequencies from 1Hz to 130Hz. The reflectometer response was found to closely resemble the sinusoidal response as measured with an accelerometer up to 100 Hz. The data presented demonstrate that microwaves can be used to measure flutter-induced aircraft vibrations.
Modal domain optical fiber sensors have recently been employed in the implementation of system identification algorithms and the closed-loop control of vibrations in flexible structures. The mathematical model of the modal domain optical fiber sensor used in these applications, however, only accounted for the effects of strain in the direction of the fiber's longitudinal axis. In this paper, we extend this model to include the effects of arbitrary stress. Using this sensor model, we characterize the sensor's sensitivity and dynamic range.
Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.
Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.
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The specifications for the Stand Alone Pressure Measurement Device (SAPMD) are as follows: the SAPMD shall measure ambient pressure at the surface of the Orbiter TPS in the range of 0 to 15 pounds per square inch absolute (PSIA). Measurement will begin at solid rocket booster (SRB) ignition as sensed by appropriate vibration sensing elements in the SAPMD. Pressure and corresponding real-time data are to be recorded every one tenth second for 140 seconds and at the end of the recording period, the operation will be discontinued with the data preserved for interrogation subsequent to Orbiter re-entry and landing. The type and size of the battery shall be such as to allow the vibration sensing elements and a real-time clock to be initialized a minimum of 30 day prior to launch and still provide power as necessary to perform the 140 second data recording period after SRB ignition. Battery installation shall be in such a manner as to allow battery replacement without removing the SAPMD from its position or removing more than one TPS tile. The SAPMD must be mounted in specific locations under tile of the TPS. To accommodate such mounting, the absolute maximum physical dimensions much not exceed 6.0 inches in length, 1.5 inches in width, and 0.4 inches in height, and the device shall be of such configuration that it can be bonded to the Orbiter skin at the joint line of two TPS tiles with the pressure sensing port at the surface of the tile. The SAPMD must remain operational in the temperature range of -40 to +85 C and survive storage temperature of -55 to +125 C. The pressure port must withstand 934 C without causing damage to the TPS during entry and must remain functional at 262 C during ascent. The accuracy of the pressure measurement must be plus or minus one-half PSIA over a temperature range of 0 to +36 C. All the specifications were met and verified by prototype testing and documented in the enclosed test data. Four flight-qualified models were fabricated and of these, two were delivered and successfully flown in the cargo bay of STS-26.
Abstract Surface acoustic waves (SAWs) have shown great potential for developing sensors for structural health monitoring (SHM) and lab‐on‐a‐chip (LOC) applications. Existing SAW sensors mainly rely on measuring the frequency shifts of high‐frequency (e.g., >0.1 GHz) resonance peaks. This study presents frequency‐locked wireless multifunctional SAW sensors that enable multiple wireless sensing functions, including strain sensing, temperature measurement, water presence detection, and vibration sensing. These sensors leverage SAW resonators on piezoelectric chips, inductive coupling‐based wireless power transmission, and, particularly, a frequency‐locked wireless sensing mechanism that works at low frequencies (e.g., <0.1 GHz). This mechanism locks the input frequency on the slope of a sensor's reflection spectrum and monitors the reflection signal's amplitude change induced by the changes of sensing parameters. The proof‐of‐concept experiments show that these wireless sensors can operate in a low‐power active mode for on‐demand wireless strain measurement, temperature sensing, and water presence detection. Moreover, these sensors can operate in a power‐free passive mode for vibration sensing, with results that agree well with laser vibrometer measurements. It is anticipated that the designs and mechanisms of the frequency‐locked wireless SAW sensors will inspire researchers to develop future wireless multifunctional sensors for SHM and LOC applications.
Method of active suppression of nonlinear and nonstationary vibrations developed to reduce sonic fatigue and interior noise in high-speed aircraft. Structure of aircraft exhibits periodic, chaotic, and random vibrations when forced by high-intensity sound from jet engines, shock waves, turbulence, and separated flows. Method of suppressing vibrations involves feedback control: Strain gauges or other sensors mounted in paths of propagation of vibrations on structure sense vibrations; outputs of sensors processed into control signal applied to actuator mounted on structure, inducing compensatory forces.
System of analog and digital signal-processing equipment, computers, and programs detects faults in ball bearings in turbomachines. System operates in real time, extracting information from vibrations sensed by accelerometers, strain gauges, and/or acoustical sensors. Vibrations caused when pits in balls contact races, and pits in races contact balls.
In active rotor control, vibrations of flexibly supported rotors suppressed by use of electronic feedback control system. System senses vibration level of rotor system and, in turn, provides damping such that vibration level maintained within acceptable limits. Enables rotor to operate through and above its critical speeds, increases bearing life, reduces size and weight of rotating shafts, and generally enables rotors to operate more smoothly.
Modal domain optical fiber sensors, or distributed effect sensors, for active vibration suppression in flexible structures are considered. Preliminary modeling results indicate that these sensors can be used to sense vibrations in a flexible beam and the signal can be used to damp vibrations in the beam. Weighted distributed-effect sensors can be used to implement high order compensators with low order functional observers.
A method and apparatus wherein phase changes in a material can dampen vibrational energy, dampen noise and facilitate heat transfer. One embodiment includes a method for damping vibrational energy in a body. The method comprises attaching a material to the body, wherein the material comprises a substrate, a shape memory alloy layer, and a plurality of temperature change elements. The method further comprises sensing vibrations in the body. In addition, the method comprises indicating to at least a portion of the temperature change elements to provide a temperature change in the shape memory alloy layer, wherein the temperature change is sufficient to provide a phase change in at least a portion of the shape memory alloy layer, and further wherein the phase change consumes a sufficient amount of kinetic energy to dampen at least a portion of the vibrational energy in the body. In other embodiments, the shape memory alloy layer is a thin film. Additional embodiments include a sensor connected to the material.
From aircraft fuselages and space stations to vacuum cleaners and automobiles, active control of noise and/or vibration has come of age. Determining the number of active control devices (e.g. actuators) to be placed and where they are to be placed is the prototypical location problem. However, unlike typical location problems, where the customer is readily identified and is actively engaged in the assessment of the performance of the chosen locations, the customers that active control devices serve are not so easily identified and their impact on system performance issues may be unclear. For example, consider the problem of where to locate actuators to attenuate cabin noise in a propeller driven aircraft. Clearly, the ultimate customers are the passengers who will travel in these aircraft. But to decide whether one set of actuator locations is better than another it is unlikely we will ask passengers to fly in the aircraft and fill out a questionnaire about noise levels. Instead a set of sensors (pseudo-customers) are placed and the system performance of the actuators, as measured by these sensors, is recorded. Hence, we have yet another location problem. How many sensors should there be and where should they be located? In many instances collocation of sensors and actuators is the answer but in other instances it is not. A variety of approaches have been taken to address these sensor/actuator location problems. With regard to damping vibrations in truss structures (space station prototypes) it was formulated a new noxious location problem and generated high-quality solutions with a combination of LP-relaxations and heuristic search procedures. Other related efforts are summarized the actuator location problem for a single frequency interior noise control problem was examined for an idealized aircraft cabin. A tabu search procedure was shown to generate better locations for the actuators than a modal decomposition approach. The model was extended to include multi-frequency information. The sensor location problem is addressed. In the latter article a reactive tabu search scheme was shown to dominate a static tabu search approach. Our focus here is to determine locations to control and/or sense vibrations on a truss structure. However, instead of using one of the earlier optimization models referenced in the above paragraph we adopt an experimental design approach.
Chiral metamaterials in the mid-infrared wavelength range have tremendous potential for studying thermal emission manipulation and molecular vibration sensing. In this work, we present one type of chiral plasmonic metasurface absorber with high circular dichroism (CD) in absorption of more than 0.56 across the mid-infrared wavelength range of 5-5.5 mu m. The demonstrated chiral metasurface absorbers exhibit a maximum chiral absorption of 0.87 and a maximum CD in absorption of around 0.60. By adjusting the geometric parameters of the unit cell structure of the metasurface, the chiral absorption peak can be shifted to different wavelengths. Due to the strong chiroptical response, the thermal analysis of the designed chiral metasurface absorber further shows the large temperature difference between the left-handed and right-handed circularly polarized light. The demonstrated results can be utilized in various applications such as molecular detection, mid-infrared filter, thermal emission, and chiral imaging.
Collision of birds and bats with wind turbines is a conservation concern for both land-based and offshore wind projects. The fatality rates of birds and bats at land-based turbines are well documented. The measurement strategies on land focus on finding carcasses following collision, estimating the number of carcasses missed through searcher efficiency, carcass persistence trials and carcass fall distributions, and modeling statistically robust fatality rates. Few technologies have been developed to monitor offshore bird and bat collisions, and many that have been developed focused on detecting collisions with large birds. The few studies that have attempted to document collisions at offshore turbines do not account for smaller bodied animals or for collisions that might be missed, which prevents the calculation of statistically robust fatality rates. The overall goal of this report, A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Project), was to develop an effective multi-sensor system for quantifying bird and bat collision rates, specifically for offshore wind facilities. The Project goal and resulting automated collision detection system was achieved through two major technological advancements: 1) refining The Netherlands Organisation for Applied Scientific Research’s (TNO’s) existing WT-Bird® vibration sensing system, that had successfully detected large bird collisions during daytime, to allow for improved detection of smaller birds and bats during both daytime and nighttime hours and 2) improving image processing systems and developing and integrating machine learning algorithms to automatically detect and classify small and large bird and bat collisions with offshore turbines. This final technical report (FTR) summarizes Methods , Results , Conclusions , and Lessons Learned during each of the five Tasks identified for this research and development effort. This FTR includes summaries of the following: Task 1. Initial Engineering Tests to Improve WT-Bird® Task 2. Installation of WT‐Bird® on a Utility-scale Turbine at the National Wind Technology Center – National Renewable Energy Laboratory Task 3. Field Tests and Refinement of the Object Detection System Task 4. Validation of WT-Bird® on a Land-based Turbine Task 5. Preparation for the Implementation of WT-Bird® on an Offshore Turbine. This research and development effort documented successful improvement of the WT Bird® collision detection system to detect small birds and bats, and WT-Bird® is the first collision detection system to validate results compared to land-based post-construction monitoring. The collision trials provide estimates of missed targets that can be used to estimate fatality rates, a significant improvement relative to other offshore collision monitoring systems. Advances were made in developing an edge-processing solution to reduce data storage requirements, which is important if the system is deployed for long periods of time at offshore turbines. The improved WT-Bird® system also provides an important option for wind operators on land or offshore who need to document specific details about when collisions occur, particularly efforts to further research on bat impact minimization, or when standard fatality searches are impractical (e.g. offshore) or inadequate (e.g. challenging locations on land).
Thermal actuators used to stabilize large structures. New damping concept calls for application of suitably timed and shaped thermal-gradient waveforms to generate expansions and contractions counteracting vibrations. Responding to processed signal from accelerometer, thermoelectric heat pumps apply thermal gradients producing expansions and contractions in upper and lower caps of cantilever beam. These expansions and contractions partly counteract vibrations sensed by accelerometer, thus contributing to damping.
The application of the acousto-ultrasonic (AU) technique to composite laminates involves imparting a mechanical excitation to the surface of a composite plate to create a mechanical disturbance within the material. At the same time, a transducer is used at another location on the same or another surface of the material to sense vibrations (ultrasonic waves) caused by the disturbance. Experimental results are presented and related to concepts of through-thickness-transverse resonance and plate wave theory.