Bolted joints are among the most common building blocks used across different types of structures, and are often the key components that sew all other structural parts together. Monitoring and assessment of looseness in bolted structures is one of the most attractive topics in mechanical, aerospace, and civil engineering. This paper presents a new percussion-based non-destructive approach to determine the health condition of bolted joints with the help of machine learning. The proposed method is very similar to the percussive diagnostic techniques used in clinical examinations to diagnose the health of patients. Due to the different interfacial properties among the bolts, nuts and the host structure, bolted joints can generate unique sounds when it is excited by impacts, such as from tapping. Power spectrum density, as a signal feature, was used to recognize and classify recorded tapping data. A machine learning model using the decision tree method was employed to identify the bolt looseness level. Experiments demonstrated that the newly proposed method for bolt looseness detection is very easy to implement by ‘listening to tapping’ and the monitoring accuracy is very high. With the rapid in robotics, the proposed approach has great potential to be implemented with intimately weaving robotics and machine learning to produce a cyber-physical system that can automatically inspect and determine the health of a structure.

The coordinated regulation of gene expression is essential for pathogens to infect and cause disease. A recently appreciated mechanism of regulation is that afforded by small regulatory RNA (sRNA) molecules. Here, we set out to assess the prevalence of sRNAs in the human bacterial pathogen group A Streptococcus (GAS). Genome-wide identification of candidate GAS sRNAs was performed through a tiling Affymetrix microarray approach and identified 40 candidate sRNAs within the M1T1 GAS strain MGAS2221. Together with a previous bioinformatic approach this brings the number of novel candidate sRNAs in GAS to 75, a number that approximates the number of GAS transcription factors. Transcripts were confirmed by Northern blot analysis for 16 of 32 candidate sRNAs tested, and the abundance of several of these sRNAs were shown to be temporally regulated. Six sRNAs were selected for further study and the promoter, transcriptional start site, and Rho-independent terminator identified for each. Significant variation was observed between the six sRNAs with respect to their stability during growth, and with respect to their inter- and/or intra-serotype-specific levels of abundance. To start to assess the contribution of sRNAs to gene regulation in M1T1 GAS we deleted the previously described sRNA PEL from four clinical isolates. Data from genome-wide expression microarray, quantitative RT-PCR, and Western blot analyses are consistent with PEL having no regulatory function in M1T1 GAS. The finding that candidate sRNA molecules are prevalent throughout the GAS genome provides significant impetus to the study of this fundamental gene-regulatory mechanism in an important human pathogen.

No abstract

Corrosion of concrete reinforcement members has been recognized as a predominant structural deterioration mechanism for steel reinforced concrete structures. Many corrosion detection techniques have been developed for reinforced concrete structures, but a dependable one is more than desired. Acoustic emission technique and fiber optic sensing have emerged as new tools in the field of structural health monitoring. In this paper, we present the results of an experimental investigation on corrosion monitoring of a steel reinforced mortar block through combined acoustic emission and fiber Bragg grating strain measurement. Constant current was applied to the mortar block in order to induce accelerated corrosion. The monitoring process has two aspects: corrosion initiation and crack propagation. Propagation of cracks can be captured through corresponding acoustic emission whereas the mortar expansion due to the generation of corrosion products will be monitored by fiber Bragg grating strain sensors. The results demonstrate that the acoustic emission sources comes from three different types, namely, evolution of hydrogen bubbles, generation of corrosion products and crack propagation. Their corresponding properties are also discussed. The results also show a good correlation between acoustic emission activity and expansive strain measured on the specimen surface.

Rock bolts have been widely used as rock reinforcing members in underground coal mine roadways and tunnels. Failures of rock bolts occur as a result of overloading, corrosion, seismic burst and bad grouting, leading to catastrophic economic and personnel losses. Monitoring the health condition of the rock bolts plays an important role in ensuring the safe operation of underground mines. This work presents a brief introduction on the types of rock bolts followed by a comprehensive review of rock bolt monitoring using smart sensors. Smart sensors that are used to assess rock bolt integrity are reviewed to provide a firm perception of the application of smart sensors for enhanced performance and reliability of rock bolts. The most widely used smart sensors for rock bolt monitoring are the piezoelectric sensors and the fiber optic sensors. The methodologies and principles of these smart sensors are reviewed from the point of view of rock bolt integrity monitoring. The applications of smart sensors in monitoring the critical status of rock bolts, such as the axial force, corrosion occurrence, grout quality and resin delamination, are highlighted. In addition, several prototypes or commercially available smart rock bolt devices are also introduced.

For reinforced concrete structures, the use of fiber-reinforced polymer rebars to replace the steel reinforcement is a topic that is receiving increasing attention, especially where corrosion is a serious issue. However, fiber-reinforced polymer rebar–reinforced concrete always carries the risk of structural failure initiated from the debonding damage that might occur at the reinforcement–concrete interface. This study employed an electro-mechanical impedance–based structural health monitoring technique by applying lead–zirconate–titanate ceramic patches to detect the debonding damage of a carbon fiber–reinforced polymer rebar reinforced concrete. In the experimental study, a carbon fiber–reinforced polymer rebar reinforced concrete specimen was fabricated and it was subjected to a pullout test to initiate the debonding damage at the reinforcement–concrete interface. The impedance and admittance signatures were measured from an impedance analyzer according to the different debonding conditions between the reinforcement and the concrete. Statistical damage metrics, root-mean-square deviation and mean absolute percentage deviation, were used to quantify the changes in impedance signatures measured at the lead–zirconate–titanate patches due to debonding conditions. The results illustrated the capability of the electro-mechanical impedance–based structural health monitoring technique for detecting the debonding damage of fiber-reinforced polymer rebar–reinforced concrete structures.

Bolted joints are ubiquitous structural elements, and form critical connections in mechanical and civil structures. As such, loosened bolted joints may lead to catastrophic failures of these structures, thus inspiring a growing interest in monitoring of bolted joints. A novel energy based wave method is proposed in this study to monitor the axial load of bolted joint connections. In this method, the time reversal technique was used to focus the energy of a piezoelectric (PZT)generated ultrasound wave from one side of the interface to be measured as a signal peak by another PZT transducer on the other side of the interface. A tightness index (TI) was defined and used to correlate the peak amplitude to the bolt axial load. The TI bypasses the need for more complex signal processing required in other energy-based methods. A coupled, electromechanical analysis with elasto-plastic finite element method was used to simulate and analyze the PZT based ultrasonic wave propagation through the interface of two steel plates connected by a single nut and bolt connection. Numerical results, backed by experimental results from testing on a bolted connection between two steel plates, revealed that the peak amplitude of the focused signal increases as the bolt preload (torque level) increases due to the enlarging true contact area of the steel plates. The amplitude of the focused peak saturates and the TI reaches unity as the bolt axial load reaches a threshold value. These conditions are associated with the maximum possible true contact area between the surfaces of the bolted connection.

No abstract