Tendon Stress Estimation from Strain Data of a Bridge Girder Using Machine Learning-Based Surrogate Model.

Prestressed girders reduce cracking and allow for long spans, but their construction requires complex equipment and strict quality control. Their accurate design depends on a precise knowledge of tensioning force and stresses, as well as monitoring the tendon force to prevent excessive creep. Estimating tendon stress is challenging due to limited access to prestressing tendons. This study utilizes a strain-based machine learning method to estimate real-time applied tendon stress. A dataset was generated using finite element method (FEM) analysis, varying the tendon stress in a 45 m girder. Network models were trained and tested on various tendon force scenarios, with prediction errors of less than 10%. The model with the lowest RMSE was chosen for stress prediction, accurately estimating the tendon stress, and providing real-time tensioning force adjustment. The research offers insights into optimizing girder locations and strain numbers. The results demonstrate the feasibility of using machine learning with strain data for instant tendon force estimation.

Detection and Length Measurement of Cracks Captured in Low Definitions Using Convolutional Neural Networks.

Continuous efforts were made in detecting cracks in images. Varied CNN models were developed and tested for detecting or segmenting crack regions. However, most datasets used in previous works contained clearly distinctive crack images. No previous methods were validated on blurry cracks captured in low definitions. Therefore, this paper presented a framework of detecting the regions of blurred, indistinct concrete cracks. The framework divides an image into small square patches which are classified into crack or non-crack. Well-known CNN models were employed for the classification and compared with each other with experimental tests. This paper also elaborated on critical factors-the patch size and the way of labeling patches-which had considerable influences on the training performance. Furthermore, a series of post-processes for measuring crack lengths were introduced. The proposed framework was tested on the images of bridge decks containing blurred thin cracks and showed reliable performance comparable to practitioners.

Development of a Reference-Free Indirect Bridge Displacement Sensing System.

Bridge displacement measurements are important data for assessing the condition of a bridge. Measuring bridge displacement under moving vehicle loads is helpful for rating the load-carrying capacity and evaluating the structural health of a bridge. Displacements are conventionally measured using a linear variable differential transformer (LVDT), which needs stable reference points and thus prohibits the use of this method for measuring displacements for bridges crossing sea channels, large rivers, and highways. This paper proposes a reference-free indirect bridge displacement sensing system using a multichannel sensor board strain and accelerometer with a commercial wireless sensor platform (Xnode). The indirect displacement estimation method is then optimized for measuring the structural displacement. The performance of the developed system was experimentally evaluated on concrete- and steelbox girder bridges. In comparison with the reference LVDT data, the maximum displacement error for the proposed method was 2.17%. The proposed method was successfully applied to the displacement monitoring of a tall bridge (height = 20 m), which was very difficult to monitor using existing systems.

An Innovative Smart Concrete Anchorage with Self-Stress Sensing Capacity of Prestressing Stress of PS Tendon.

An innovative smart concrete anchorage (SCA) has been developed for monitoring the stress of prestressing (PS) tendons by utilizing smart ultra-high-performance concrete (UHPC). The smart UHPC contained 2 vol% steel fibers and fine steel slag aggregates instead of silica sands. The effects of different electrode materials, arrangements, and connectors on the self-stress sensing capacity of the SCA are discussed. A prototype SCA demonstrated its feasibility and sufficient self-stress sensing capacity to be used in monitoring the prestressing loss of the PS tendon. As the tensile stress of the PS tendon increased from 0 to 1488 MPa, the fractional change in resistivity (FCR) of the prototype SCA, with horizontally paired copper wire electrodes and a plug-in type connector, decreased linearly from 0% to -1.53%, whereas the FCR increased linearly from -1.53% to -0.04% as the tensile stress of the PS tendon decreased from 1488 to 331 MPa.

Development of Low-Cost Wireless Sensing System for Smart Ultra-High Performance Concrete.

This study proposes the development of a wireless sensor system integrated with smart ultra-high performance concrete (UHPC) for sensing and transmitting changes in stress and damage occurrence in real-time. The smart UHPC, which has the self-sensing ability, comprises steel fibers, fine steel slag aggregates (FSSAs), and multiwall carbon nanotubes (MWCNTs) as functional fillers. The proposed wireless sensing system used a low-cost microcontroller unit (MCU) and two-probe resistance sensing circuit to capture change in electrical resistance of self-sensing UHPC due to external stress. For wireless transmission, the developed wireless sensing system used Bluetooth low energy (BLE) beacon for low-power and multi-channel data transmission. For experimental validation of the proposed smart UHPC, two types of specimens for tensile and compression tests were fabricated. In the laboratory test, using a universal testing machine, the change in electrical resistivity was measured and compared with a reference DC resistance meter. The proposed wireless sensing system showed decreased electrical resistance under compressive and tensile load. The fractional change in resistivity (FCR) was monitored at 39.2% under the maximum compressive stress and 12.35% per crack under the maximum compressive stress tension. The electrical resistance changes in both compression and tension showed similar behavior, measured by a DC meter and validated the developed integration of wireless sensing system and smart UHPC.

SSVM: An Ultra-Low-Power Strain Sensing and Visualization Module for Long-Term Structural Health Monitoring.

Structural health monitoring (SHM) is crucial for quantitative behavioral analysis of structural members such as fatigue, buckling, and crack propagation identification. However, formerly developed approaches cannot be implemented effectively for long-term infrastructure monitoring, owing to power inefficiency and data management challenges. This study presents the development of a high-fidelity and ultra-low-power strain sensing and visualization module (SSVM), along with an effective data management technique. Deployment of 24-bit resolution analog to a digital converter and precise half-bridge circuit for strain sensing are two significant factors for efficient strain measurement and power management circuit incorporating a low-power microcontroller unit (MCU), and electronic-paper display (EPD) enabled long-term operation. A prototype for SSVM was developed that performs strain sensing and encodes the strain response in a QR code for visualization on the EPD. For efficient power management, SSVM only activated when the trigger-signal was generated and stayed in power-saving mode consuming 18 mA and 337.9 µA, respectively. The trigger-signal was designed to be generated either periodically by a timer or intentionally by a push-button. A smartphone application and cloud database were developed for efficient data acquisition and management. A lab-scale experiment was carried out to validate the proposed system with a reference strain sensing system. A cantilever beam was deflected by increasing load at its free end, and the resultant strain response of SSVM was compared with the reference. The proposed system was successfully validated to use for long-term static strain measurement.

Bridge Displacement Estimation Using a Co-Located Acceleration and Strain.

Structural displacement is an important metric for assessing structural conditions because it has a direct relationship with the structural stiffness. Many bridge displacement measurement techniques have been developed, but most methods require fixed reference points in the vicinity of the target structure that limits the field implementations. A promising alternative is to use reference-free measurement techniques that indirectly estimate the displacement by using measurements such as acceleration and strain. This paper proposes novel reference-free bridge displacement estimation by the fusion of single acceleration with pseudo-static displacement derived from co-located strain measurements. First, we propose a conversion of the strain at the center of a beam into displacement based on the geometric relationship between strain and deflection curves with reference-free calibration. Second, an adaptive Kalman filter is proposed to fuse the displacement generated by strain with acceleration by recursively estimating the noise covariance of displacement from strain measurements which is vulnerable to measurement condition. Both numerical and experimental validations are presented to demonstrate the efficiency and robustness of the proposed approach.

BLESeis: Low-Cost IoT Sensor for Smart Earthquake Detection and Notification.

The Internet of Things (IoT) has been implemented to provide solutions for certain event detection because of ease of installation, computing and communication capability, and cost-effectiveness. Seismic event detection, however, is still a challenge due to a lack of high-fidelity sensing and classification efficiency. This study proposes BLESeis, an IoT sensor for smart earthquake detection. BLESeis comprises three main parts: (1) high-fidelity vibration sensing using a MEMS accelerometer and digital filtering; (2) an embedded earthquake detection algorithm; (3) BLE (Bluetooth low energy) beacon for earthquake notification. For high-fidelity vibration sensing, a triggering algorithm and embedded finite impulse response (FIR) low-pass filter are developed. The acquired vibration is then classified by the earthquake detection algorithm developed to identify the earthquake signal from other vibration sources using time and frequency domain analysis. Upon detection of an earthquake, the BLE beacon broadcasts using the proposed data packet for efficient notification and visualization. The performance of the proposed system is evaluated through numerical simulations and a set of experiments using shaking table tests. The experiments show the feasibility of the low-cost earthquake detection and notification system.

Non-Target Structural Displacement Measurement Using Reference Frame-Based Deepflow.

Displacement is crucial for structural health monitoring, although it is very challenging to measure under field conditions. Most existing displacement measurement methods are costly, labor-intensive, and insufficiently accurate for measuring small dynamic displacements. Computer vision (CV)-based methods incorporate optical devices with advanced image processing algorithms to accurately, cost-effectively, and remotely measure structural displacement with easy installation. However, non-target-based CV methods are still limited by insufficient feature points, incorrect feature point detection, occlusion, and drift induced by tracking error accumulation. This paper presents a reference frame-based Deepflow algorithm integrated with masking and signal filtering for non-target-based displacement measurements. The proposed method allows the user to select points of interest for images with a low gradient for displacement tracking and directly calculate displacement without drift accumulated by measurement error. The proposed method is experimentally validated on a cantilevered beam under ambient and occluded test conditions. The accuracy of the proposed method is compared with that of a reference laser displacement sensor for validation. The significant advantage of the proposed method is its flexibility in extracting structural displacement in any region on structures that do not have distinct natural features.

Cross-Correlation-Based Structural System Identification Using Unmanned Aerial Vehicles.

Computer vision techniques have been employed to characterize dynamic properties of structures, as well as to capture structural motion for system identification purposes. All of these methods leverage image-processing techniques using a stationary camera. This requirement makes finding an effective location for camera installation difficult, because civil infrastructure (i.e., bridges, buildings, etc.) are often difficult to access, being constructed over rivers, roads, or other obstacles. This paper seeks to use video from Unmanned Aerial Vehicles (UAVs) to address this problem. As opposed to the traditional way of using stationary cameras, the use of UAVs brings the issue of the camera itself moving; thus, the displacements of the structure obtained by processing UAV video are relative to the UAV camera. Some efforts have been reported to compensate for the camera motion, but they require certain assumptions that may be difficult to satisfy. This paper proposes a new method for structural system identification using the UAV video directly. Several challenges are addressed, including: (1) estimation of an appropriate scale factor; and (2) compensation for the rolling shutter effect. Experimental validation is carried out to validate the proposed approach. The experimental results demonstrate the efficacy and significant potential of the proposed approach.

Decentralized system identification using stochastic subspace identification for wireless sensor networks.

Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model.

Development of a wireless displacement measurement system using acceleration responses.

Displacement measurements are useful information for various engineering applications such as structural health monitoring (SHM), earthquake engineering and system identification. Most existing displacement measurement methods are costly, labor-intensive, and have difficulties particularly when applying to full-scale civil structures because the methods require stationary reference points. Indirect estimation methods converting acceleration to displacement can be a good alternative as acceleration transducers are generally cost-effective, easy to install, and have low noise. However, the application of acceleration-based methods to full-scale civil structures such as long span bridges is challenging due to the need to install cables to connect the sensors to a base station. This article proposes a low-cost wireless displacement measurement system using acceleration. Developed with smart sensors that are low-cost, wireless, and capable of on-board computation, the wireless displacement measurement system has significant potential to impact many applications that need displacement information at multiple locations of a structure. The system implements an FIR-filter type displacement estimation algorithm that can remove low frequency drifts typically caused by numerical integration of discrete acceleration signals. To verify the accuracy and feasibility of the proposed system, laboratory tests are carried out using a shaking table and on a three storey shear building model, experimentally confirming the effectiveness of the proposed system.

Sonographically guided tendon sheath injections are more accurate than blind injections: implications for trigger finger treatment.

OBJECTIVES: Trigger finger is frequently treated with tendon sheath injections. This cadaveric study evaluated the accuracy and safety of blind and sonographically guided tendon sheath injections. To our knowledge, a study that precisely mapped the locations of material injected into the tendon sheath has not been reported previously. METHODS: A total of 40 fingers (excluding thumbs) of 5 fresh cadavers were used. Methylene blue dye was injected into the flexor tendon sheath using either a blind or sonographically guided injection technique (20 fingers for each technique). The location of the dye was then determined via dissection. RESULTS: Dye was observed only in the tendon sheath (ie, optimal outcome) in 70% of sonographically guided injections and 15% of blind injections (P = .001). Dye was observed in the tendon proper (ie, unsafe outcome) in 30% of blind injections and 0% of sonographically guided injections (P = .02). CONCLUSIONS: We found that sonographically guided tendon sheath injections were more accurate and may be potentially safer than blind injections. These findings suggest that sonographically guided injections should be considered over blind injections when treating trigger finger.

Anterior and posterior knee laxity in a young adult Korean population.

PURPOSE: The purposes of this study were (1) to determine normal anterior and posterior knee laxity in a healthy young adult (20-30 years old) Korean population, (2) to compare knee laxity between the male and female populations, (3) to investigate whether generalized joint laxity affects anterior and posterior knee laxity, (4) to determine side-side differences between right and left knees, and thus, to determine normal values of side-side differences. METHODS: Normal values of anterior and posterior knee laxity were measured in 100 healthy volunteers (50 men and 50 women) aged between 20 and 30 years. Stress radiography using a Telos device was performed in 20 and 70° of knee flexion for 134N anterior and posterior loads. Anterior and posterior tibial displacements relative to the femur condyle were measured using a computerized system. RESULTS: In the 100 subjects (200 knees), anterior knee laxity was greater at 20° of flexion with a mean of 4.9 ± 2.3 mm (P < 0.05) and posterior knee laxity was greater at 70° of flexion with a mean of 4.6 ± 2.7 mm (P < 0.05). The mean side-side difference was 1.4 ± 0.9 mm (range, -3 to +3). Women had greater anterior laxity (P < 0.05) than men at both 20 and 70° of flexion, but posterior laxity was not different (ns). Generalized joint laxity was greater in women compared to men (P < 0.05). Subjects with generalized joint laxity had greater laxity than normal populations in both 20 and 70° of flexion (P < 0.05). Side-side differences between right and left knees were not significantly different in women and men or between subjects with normal and generalized joint laxity (ns). CONCLUSIONS: This study suggests that the Korean population exhibits a wide range of normal anterior and posterior knee laxity, but small side-side differences. Subjects with generalized laxity showed greater knee laxity than those without, but side-side differences were less than 3 mm in all subjects. Thus, clinical guideline that a side-side difference more than 3 mm of anterior knee laxity is abnormal can be applicable for the subjects with generalized laxity.

Septic arthritis of the knee joint secondary to adjacent chronic osteomyelitis of the femur in an adult.

The present report describes a case of septic knee arthritis secondary to reactivated chronic osteomyelitis. The osteolytic lesion observed on the initial radiographs resulted in further imaging studies including CT and MRI, which confirmed the diagnosis. Based on the patient's history, physical findings and imaging studies, we performed open debridement rather than arthroscopic surgery in order to treat the infected intraarticular knee joint and ream the femur intramedullary canal. Additionally, an antibiotic-impregnated cement rod was inserted into the medullary cavity to fill the dead space and eradicate the infection. A high index of suspicion combined with adequate comprehension of initial plain radiographs is essential for accurate diagnosis of septic knee arthritis with adjacent chronic osteomyelitis.

Use of 2.0 mini plate system as reduction plate.

Fracture stabilization and reduction using temporary plates during intramedullary tibial nailing was introduced as a novel concept in fracture surgery by Benirschke et al. (Orthop Trans 18:1055-1056, 1995). The concept of temporary reduction using one-third tubular plates proved useful in aiding metaphyseal and periarticular fracture fixation also. However, planning the strategic location of final plate was the main limitation with this technique using one-third tubular plates. We used 2.0 mini plates as provisional reduction plates that solved the issue of planning and placement of plates. The main advantage of our technique is that the final definitive plate can be applied directly over the mini plates. Here, we will describe our technique using relevant fracture case in metaphyseal-periarticular location.

A new bite block for panoramic radiographs of anterior edentulous patients: A technical report.

PURPOSE: Panoramic radiographs taken using conventional chin-support devices have often presented problems with positioning accuracy and reproducibility. The aim of this report was to propose a new bite block for panoramic radiographs of anterior edentulous patients that better addresses these two issues. MATERIALS AND METHODS: A new panoramic radiography bite block similar to the bite block for dentulous patients was developed to enable proper positioning stability for edentulous patients. The new bite block was designed and implemented in light of previous studies. The height of the new bite block was 18 mm and to compensate for the horizontal edentulous space, its horizontal width was 7 mm. The panoramic radiographs using the new bite block were compared with those using the conventional chin-support device. RESULTS: Panoramic radiographs taken with the new bite block showed better stability and bilateral symmetry than those taken with the conventional chin-support device. Patients also showed less movement and more stable positioning during panoramic radiography with the new bite block. CONCLUSION: Conventional errors in panoramic radiographs of edentulous patients could be caused by unreliability of the chin-support device. The newly proposed bite block for panoramic radiographs of edentulous patients showed better reliability. Further study is required to evaluate the image quality and reproducibility of images with the new bite block.

Determination of the Optimal Cutoff Values for Pain Sensitivity Questionnaire Scores and the Oswestry Disability Index for Favorable Surgical Outcomes in Subjects With Lumbar Spinal Stenosis.

STUDY DESIGN: Retrospective analysis of prospectively collected data (NCT02134821). OBJECTIVE: The aim of this study was to elucidate the cutoff values for significant predictors for favorable outcomes after lumbar spine surgery in patients with lumbar spinal stenosis (LSS). SUMMARY OF BACKGROUND DATA: Various factors are associated with the surgical outcomes for patients with LSS. However, we did not know the odds ratio and/or cutoff values of a predictive factor for a favorable surgical outcome for LSS. METHODS: A total of 157 patients who underwent spine surgery due to LSS between June 2012 and April 2013 were included in this study. The patients were dichotomized into 2 groups on the basis of an Oswestry Disability Index (ODI) score of 22 or less (favorable outcome group) or more than 22 (unfavorable outcome group) at 12 months after surgery. Regarding favorable outcomes, the odds ratio for each preoperative variable including demographic data, preoperative symptom severity, and pain sensitivity questionnaire (PSQ) score was calculated using univariate and multivariate logistic regression analyses. For the significant variables for surgical outcome, receiver operating characteristic (ROC) curve was plotted with calculation of the area under the ROC curve. RESULTS: Multivariate analysis revealed that the ODI and total PSQ scores were significantly associated with a greater likelihood of an unfavorable surgical outcome [odds ratio (95% confidence interval) of ODI, 1.289 (1.028-1.616); odds ratio (95% confidence interval) of total PSQ, 1.060 (1.009-1.113)]. ROC analysis revealed area under the ROC curves for the total PSQ and ODI scores of 0.638 (P = 0.005) and 0.692 (P < 0.001), respectively. CONCLUSION: Preoperative disability and pain sensitivity can be predictors of the functional level achieved after spine surgery in patients with LSS, and the ideal cutoff values for the total PSQ and ODI scores were 6.6 and 45.0, respectively.

Analysis of hip dysplasia and spinopelvic alignment in cerebral palsy.

BACKGROUND CONTEXT: Knowledge of sagittal spinopelvic parameters and hip dysplasia is important in cerebral palsy (CP) patients because these parameters differ from those found in the general population and can be related to symptoms. PURPOSE: The purpose of this study was to analyze sagittal spinopelvic alignment and determine its relation to hip dysplasia in CP patients. STUDY DESIGN: Radiological analysis was conducted on patients with CP. PATIENT SAMPLE: Fifty-four patients with CP and 24 normal controls were included in this study. OUTCOME MEASURES: Participants underwent radiographs of the whole spine. METHODS: The patient and control groups comprised 54 CP patients and 24 volunteers, respectively. All underwent lateral radiography of the whole spine and hip joint anteroposterior radiography. The radiographic parameters examined were sacral slope, pelvic tilt, pelvic incidence, S1 overhang, thoracic kyphosis, thoracolumbar kyphosis, lumbar lordosis, sagittal balance, center edge angle, acetabular angle, and migration index. Statistical analysis was performed to identify significant differences and correlations between the two groups. RESULTS: Sacral slope, thoracolumbar kyphosis, lumbar lordosis, sagittal balance, acetabular angle, and migration index were significantly higher in CP patients, whereas pelvic tilt, S1 overhang, and center edge angle were significantly lower (p<.05). Correlation analysis revealed that pelvic incidence, sacral slope, pelvic tilt, and S1 overhang were related to each other and that thoracolumbar kyphosis was related to the thoracic kyphosis and lumbar lordosis (p<.05). For spinal and pelvic parameters, lumbar lordosis was related to sacral slope, pelvic incidence, pelvic tilt, and S1 overhang; for hip dysplasia parameters, center edge angle and acetabular angle were found to be interrelated (p<.05). Regarding symptoms, pelvic tilt, S1 overhang, and thoracolumbar kyphosis were found to be correlated with symptom severity in patients. However, no hip dysplasia parameters were found to be related to hip or spinal symptoms. CONCLUSIONS: This study found significant differences between CP patients and normal controls in terms of spinopelvic alignment and hip dysplasia. Furthermore, relationships were found between the sagittal spinopelvic parameters and hip dysplasia, and correlations were found between sagittal spinopelvic parameters and pain.