Application of wavelet analysis in tool wear evaluation using image processing method

Tool wear plays a significant role for proper planning and control of machining parameters to maintain the product quality. However, existing tool wear monitoring methods using sensor signals still have limitations. Since the cutting tool operates directly on the work-piece during machining process, the machined surface provides valuable information about the cutting tool condition. Therefore, the objective of present study is to evaluate the tool wear based on the workpiece profile signature by using wavelet analysis. The effect of wavelet families, scale of wavelet and statistical features of the continuous wavelet coefficient on the tool wear is studied. The surface profile of workpiece was captured using a DSLR camera. Invariant moment method was applied to extract the surface profile up to sub-pixel accuracy. The extracted surface profile was analyzed by using continuous wavelet transform (CWT) written in MATLAB. The re-sults showed that average, RMS and peak to valley of CWT coefficients at all scale increased with tool wear. Peak to valley at higher scale is more sensitive to tool wear. Haar was found to be more effective and significant to correlate with tool wear with highest R2 which is 0.9301

Index to NASA Tech Briefs, January - June 1966

Index to NASA technological innovations for January-June 196

PCR-Independent Detection of Bacterial Species-Specific 16S rRNA at 10 fM by a Pore-Blockage Sensor.

A PCR-free, optics-free device is used for the detection of Escherichia coli (E. coli) 16S rRNA at 10 fM, which corresponds to ~100-1000 colony forming units/mL (CFU/mL) depending on cellular rRNA levels. The development of a rapid, sensitive, and cost-effective nucleic acid detection platform is sought for the detection of pathogenic microbes in food, water and body fluids. Since 16S rRNA sequences are species specific and are present at high copy number in viable cells, these nucleic acids offer an attractive target for microbial pathogen detection schemes. Here, target 16S rRNA of E. coli at 10 fM concentration was detected against a total RNA background using a conceptually simple approach based on electromechanical signal transduction, whereby a step change reduction in ionic current through a pore indicates blockage by an electrophoretically mobilized bead-peptide nucleic acid probe conjugate hybridized to target nucleic acid. We investigated the concentration detection limit for bacterial species-specific 16S rRNA at 1 pM to 1 fM and found a limit of detection of 10 fM for our device, which is consistent with our previous finding with single-stranded DNA of similar length. In addition, no false positive responses were obtained with control RNA and no false negatives with target 16S rRNA present down to the limit of detection (LOD) of 10 fM. Thus, this detection scheme shows promise for integration into portable, low-cost systems for rapid detection of pathogenic microbes in food, water and body fluids

DEVELOPMENT OF A SIMPLIFIED, MASS PRODUCIBLE HYBRIDIZED AMBIENT, LOW FREQUENCY, LOW INTENSITY VIBRATION ENERGY SCAVENGER (HALF-LIVES)

Scavenging energy from environmental sources is an active area of research to enable remote sensing and microsystems applications. Furthermore, as energy demands soar, there is a significant need to explore new sources and curb waste. Vibration energy scavenging is one environmental source for remote applications and a candidate for recouping energy wasted by mechanical sources that can be harnessed to monitor and optimize operation of critical infrastructure (e.g. Smart Grid). Current vibration scavengers are limited by volume and ancillary requirements for operation such as control circuitry overhead and battery sources. This dissertation, for the first time, reports a mass producible hybrid energy scavenger system that employs both piezoelectric and electrostatic transduction on a common MEMS device. The piezoelectric component provides an inherent feedback signal and pre-charge source that enables electrostatic scavenging operation while the electrostatic device provides the proof mass that enables low frequency operation. The piezoelectric beam forms the spring of the resonant mass-spring transducer for converting vibration excitation into an AC electrical output. A serially poled, composite shim, piezoelectric bimorph produces the highest output rectified voltage of over 3.3V and power output of 145uW using ¼ g vibration acceleration at 120Hz. Considering solely the volume of the piezoelectric beam and tungsten proof mass, the volume is 0.054cm3, resulting in a power density of 2.68mW/cm3. Incorporation of a simple parallel plate structure that provides the proof mass for low frequency resonant operation in addition to cogeneration via electrostatic energy scavenging provides a 19.82 to 35.29 percent increase in voltage beyond the piezoelectric generated DC rails. This corresponds to approximately 2.1nW additional power from the electrostatic scavenger component and demonstrates the first instance of hybrid energy scavenging using both piezoelectric and synchronous electrostatic transduction. Furthermore, it provides a complete system architecture and development platform for additional enhancements that will enable in excess of 100uW additional power from the electrostatic scavenger

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Microsystems technology: objectives

This contribution focuses on the objectives of microsystems technology (MST). The reason for this is two fold. First of all, it should explain what MST actually is. This question is often posed and a simple answer is lacking, as a consequence of the diversity of subjects that are perceived as MST. The second reason is that a map of the somewhat chaotic field of MST is needed to identify sub-territories, for which standardization in terms of system modules an interconnections is feasible. To define the objectives a pragmatic approach has been followed. From the literature a selection of topics has been chosen and collected that are perceived as belonging to the field of MST by a large community of workers in the field (more than 250 references). In this way an overview has been created with `applications¿ and `generic issues¿ as the main characteristics

Soft Sensors in digital healthcare monitoring

Stretchable sensors are a class of materials with applications across research fields from healthcare to structural engineering. Despite the extensive research aiming to improve the performance of individual materials or components, stretchable sensor devices are difficult to implement because conventional electronic components, mainly used for processing, which are rigid, have to make contact with soft components reliable enough to withstand real-world usage. This thesis introduces a method for creating electrical contacts that can be robustly attached onto soft, stretchable conductive polymer composites on one side and soldered to metal wires on the other side. Mechanically robust electrical contacts were developed to interface (soft) silicone-based strain sensors with conventional (hard) solid-state electronics using a nanoporous silicon-copper contact. Contacts are mounted on custom-made and commercial soft strain sensitive silicone sensors. The contacts are shown to be reliable under large deformations, then compared with a commonly used alternative under real-world strain conditions. The layered structure of the device creates a complex electronic component deriving from the silicon-copper Schottky junction. This thesis tests the versatility of the technology through a series of real-world applications. The silicon-copper contacts were used to produce a series of proof-of-concept devices, including a wearable respiration monitor, leg band for exercise monitoring, and squeezable ball to monitor rehabilitation of patients with hand injuries or neurological disorders. The sensor is shown to operate and detect multiple modes of motion regardless of placement on the body. Next, a proof-of-concept device was employed to measure hand grip strength. The optimized sensor can detect grip strength with high sensitivity. The hardness of the device was shown to increase sensitivity when healthy humans performed manual exercises and completed digital tasks. Providing patients with these devices can help monitor their rehabilitation following hand injuries or neurological disorders. This can be done through self-led at-home therapy which has been shown to improve treatment, engagement, long-term lifestyle adherence, while avoiding repeated visits to clinics which plays an important role in frequency of therapy, effectiveness, and accessibility.Open Acces

Measurement of granular flow in a vertical column using pulse induction (PI)

Gravity flow of granular materials in vertical columns can generate pressure and density fluctuations which are difficult to quantify. Examination of prior research led us to propose a new measurement technique based on the principle of pulse induction (PI) for metal detection. An experimental device using 8 mm diameter spherical particles flowing through a polyvinylchloride (PVC) pipe of 75 mm diameter and 1000 mm height was developed to demonstrate the feasibility of PI. Ten PI coils were used to quantify tracer movement through the column with time. Average and instantaneous velocities were determined for five diameters of outlet orifices: 68.0, 62.5, 54.5, 44.0 and 36.5 mm. Flow rate was calculated and modelled. When compared to prior research, PI proved to be a reliable method for flow measurement in opaque ducts