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Low-Cost Earmuff Shown to Significantly Reduce Cast-Saw Noise
No full textHearing protection devices reduce cast-saw noise. It would be helpful to identify the devices that are both effective and economical. Prior studies have shown that expensive noise-reduction headphones significantly reduced the anxiety associated with cast removal with a powered oscillating saw. The cost of such headphones, however, is a drawback for some practices and hospitals. It would be helpful to determine whether lower cost ear protection can provide effective cast-saw noise reduction. In addition, it is unclear whether the noise reduction ratings (NRRs), the average sound-level reduction provided by a hearing protection device in a laboratory test, provided by manufacturers accurately characterize the effectiveness for reducing cast-saw noise. Note that noise-cancelling devices do not carry an NRR because they are not designed as hearing protectors. Five ear protection devices with different NNRs were tested. The devices varied greatly in cost and included earplugs, low-cost earmuffs, and noise-cancelling headphones. To standardize the evaluation, each device was fitted to an acoustic mannequin with high-fidelity ear microphones while a fiberglass spica cast was cut. An additional test was run without hearing protection as a control. The low-cost devices significantly reduced the saw noise, with the exception of earplugs, which had highly variable performance. The noise reduction was similar between low-cost earmuffs and the high-cost earphones when the noise-cancelling feature was not active. Active noise cancelling provided further reductions in the noise level. Patients can experience high anxiety during cast removal. The current study shows that low-cost earmuffs significantly reduce cast-saw noise. Patient care settings may be more likely to offer hearing protection that is one twenty-fifth the cost of noise-cancelling headphones. An NRR appears to be a reliable guide for selecting hearing protection that reduces cast-saw noise
Orthopedic Surgical Helmet Systems Significantly Impair Speech Intelligibility
No full textSurgical suits provide protection to orthopedic surgeons, but the suits and fan noise may interfere with communication between operative team members. The goal of this study was to quantify the fan sound and effect of the suit, fan, and N95 mask. Sound levels were measured using a specialized manikin and evaluated using preferred speech interference levels (PSILs), noise criterion (NC) ratings, and comparison with speech sound levels from the literature. Additionally, sound blocking due to the surgical suit was measured and combined effects of the fan and suit were described using a signal to noise ratio (SNR). The noise with the fan at medium and high speed was louder than average speech and the PSILs at these speeds were significantly higher than with the fan off. The fan NC rating of 50 to 60 exceeded the recommended range of 25 to 30 for operating rooms. The N95 mask, space suit, and distance between speaker and receiver all reduced the sound signal at the receiver\u27s ear, with the worst case being full personal protective equipment on both and speaker distanced from receiver. The estimated SNR for the suit and fan system was negative for many frequency bands used in speech, indicating more noise than signal. Multiple measures indicated that the fan noises were at levels associated with speech interference. This noise combined with sound blocking provided by the suit produced SNRs commonly associated with noisy to very noisy environments. This study suggests the combined effects of the suit, fan, and distance may negatively impact operating room communication. [Orthopedics. 2021;44(4):208–214.
Strain Monitoring of Wind Turbines Using a Semi-Autonomous Drone
No full textIn this work, an approach is proposed that can perform a nondestructive evaluation of wind turbine structures using a non-contact, three-dimensional full-field optical digital image correlation (DIC) technique. This approach can quantify the level of strain and loading conditions that rotating structures such as wind turbines experience during operation. The optical technique does not interfere with the structural functionality of the wind turbine. Moreover, the use of Unmanned Aerial Vehicles (UAVs) for remote inspection enables robust measurements for periodic inspection. The strain obtained using the proposed approach is validated using strain gauges mounted on the blades. A control algorithm is designed for the UAV to stabilized and obtain the desired field of interest and working distance based on the turbine size. Blending the benefits of the remote accessibility of UAVs and full-field dynamic evaluation of structures using strain data obtained with DIC is a novel method of monitoring wind turbines
A Sensor Fused Rear Cross Traffic Detection System Using Transfer Learning
No full textRecent emerging automotive sensors and innovative technologies in Advanced Driver Assistance Systems (ADAS) increase the safety of driving a vehicle on the road. ADAS enhance road safety by providing early warning signals for drivers and controlling a vehicle accordingly to mitigate a collision. A Rear Cross Traffic (RCT) detection system is an important application of ADAS. Rear-end crashes are a frequently occurring type of collision, and approximately 29.7% of all crashes are rear-ended collisions. The RCT detection system detects obstacles at the rear while the car is backing up. In this paper, a robust sensor fused RCT detection system is proposed. By combining the information from two radars and a wide-angle camera, the locations of the target objects are identified using the proposed sensor fused algorithm. Then, the transferred Convolution Neural Network (CNN) model is used to classify the object type. The experiments show that the proposed sensor fused RCT detection system reduced the processing time 15.34 times faster than the camera-only system. The proposed system has achieved 96.42% accuracy. The experimental results demonstrate that the proposed sensor fused system has robust object detection accuracy and fast processing time, which is vital for deploying the ADAS system
An Optimization Model to Increase the Cross-Dockings Operational Utilization
No full textIntroducing a new version of a cross-docking assignment problem when forklifts carry bulk materials, we address an operational solution to reduce the impact of forklifts congestion in centre of terminals. We develop a mixed-integer bilinear programming model, a Tabu-search algorithm, where the main objective of the model is still to minimize the total transshipment costs, and additionally trying to minimize the weighted forklifts travelled distance (WTD) and the weighted unloading/loading labour costs at inbound and outbound doors (WLC). We hypothesize that longer WTD could shift the location of weighted forklift congestion concentration from the centre of the terminal toward the sides. We assuming four cost pattern’s distributions, all are supposed to lead high flows to doors with low labour costs, which ultimately impact the total WTD, WLC, and TTC. The proposed Tabu-search outperform CPLEX by finding a set of a diverse and high-quality solution within a reasonable computing time
