Sensor reconstruction

The sensor with Tg indexi ) is first reconstructed using the calibration model and the constrained optimization algorithm described below in sensor reconstruction. After the first iteration, if the SPE remains above its limit, then rs,indea (l, 2) are reconstructed together. This procedure continues until either the SPE falls below its limit or the number of reconstructed sensors equals the number of principal components retained for the calibration model. Meanwhile, the reconstructed values are saved for use in the subsequent instant the SPE goes beyond its limit. 

Sensor Reconstruction Following the fault detection procedure discussed above, the maintenance of unavailable sensors is needed as soon as they are detected. However, if the sensor that conveys information to one of the controllers were to be faulty, it is essential that its value be reconstructed from the remaining sensors on-line. Sensor reconstruction can be performed using the calibration model based on the PCA/NLPCA. 

Before starting the realisation of silicium coils, we construct a simpler probe with a 27 mm long excitation coil and 16 wired coil sensors, with 1 mm diameter and 1 mm long. We cannot hope any reconstruction with such a probe, but this allows to validate the whole approach. We tried it with test tubes with longitudinal or circonferential notches, external or internal, 100 pm wide, 100%, 60%, 40%, 20% and 10% deep. Our attention has been especially focused on circonferential notches, which are difficult to detect with usual probes. For example, the measurement signals at 240 kHz standard frequency are shown figure 6 7. 

Another important application area is the non-destructive defectoscopy of electronic components. Fig.2a shows an X-ray shadow image of a SMC LED. The 3-dimensional displacement of internal parts can only be visualized non-destructively in the tomographic reconstmction. Reconstructed cross sections through this LED are shown in Fig.2b. In the same way most electronic components in plastic and thin metal cases can be visualized. Even small electronic assemblies like hybrid ICs, magnetic heads, microphones, ABS-sensors can be tested by microtomograpical methods. 

Lane, R.G., Tallon, M., 1992, Wave-front reconstruction using a Shack-Hartmann sensor, JOSA.A 31, 6902... 

Figure 2.4.11 Profiles of paintings where different layers can clearly be resolved. A solid-echo train was used with tE = 40 (is, and the first 4 echoes were used to calculate the amplitude. The profiles were reconstructed by moving the sensor in steps of 50 pm in the paint and canvas regions, and 100 pm in the gypsum and wood layers. Using 128 scans per point and a repetition time of 100 ms the total acquisition time per point was 16 s. Profiles of paint based on tempera ( ) and oil ( ) binders show appreciable difference.

Freifeld, B.M., Finsterle, S., Onstott, T.C., Toole, P., Pratt, L.M. 2008. Ground surface temperature reconstructions using in situ estimates for thermal conductivity acquired with a fiber-optic distributed thermal perturbation sensor. Geophysical Research Letters, 35, L14309,... 

A sequential procedure was further developed by Tong and Crowe (1996) by applying sequential analysis of the principal component test using the sequential probability ratio test (SPRT). Dunia et al. (1996) also used PCA for sensor fault identification via reconstruction. In that paper it was assumed that one sensor had failed and the remaining sensors are used for reconstruction. Furthermore, the transient behavior of a number of sensor faults in various types of residuals is analyzed, and a sensor validity index is suggested, determining the status of each sensor. 

An example of the use of soft sensors is given by the automation of a penicillin production dependent on strict adherence to certain hmits in the fermentation process since such biological systems are sensitive to changes in operational conditions. An important issue in the use of soft sensors is what to do if one or more of the input variables are not available due, for example, to sensor failure or maintenance needs. Under such circumstances, one must rely on multivariate models to reconstruct or infer the missing sensor variable. ... 

Muscles contract and expand in response to electrical, thermal, and chemical stimuli. Certain polymers, such as synthetic polypeptides, are known to change shape on application of electric current, temperature, and chemical environment. For instance, selected bioelastic smart materials expand in salt solutions and may be used in desalination efforts and as salt concentration sensors. Polypeptides and other polymeric materials are being studied in tissue reconstruction, as adhesive barriers to prevent adhesion growth between surgically operated tissues, and in controlled drug release, where the material is designed to behave in a predetermined matter according to a specific chemical environment. 

Roth-Nebelsick A (2005) Reconstructing atmospheric carbon dioxide with stomata possibilities and limitations of a botanical pCO(2)-sensor. Trees 19 251-265... 

Dunia R, Qin S. A unified geometric approach to process and sensor fault identification and reconstruction the unidimensional fault case. Computers and Chemical Engineering 1998, 22, 927-943. 

An ECT system is composed of three basic components (1) a capacitance sensor, (2) a data acquisition system, and (3) a computer system for reconstruction and viewing. Figure 1 is a sketch of the ECT system with all three components (Warsito and Fan, 2003). The capacitance sensor is made of nr capacitance electrodes distributed around the wall of the process vessel. The ne capacitance electrodes provide up to ne(ne—1)/2 combinations of independent capacitance measurements between the electrode pairs. The capacitance measurements are related to the local dielectric constant (permittivity) filling the process vessel between electrode pairs (Figure 2) (Warsito and Fan, 2001b). The relation between the electric potential and the permittivity distributions follows Poisson equation shown in Equation (1). 

Figure 1 Sketch of the ECT system including sensor, data acquisition system, and computer for reconstruction (Warsito and Fan, 2003).

Figure S. Interaction networks of ER stress proximal sensors. A literature-based reconstruction of IREl, PERK and ATF6 proximal interaction networks was carried out using Cytoscape v2.0 (www.cytoscape.org/). Nodes represent different fiinctional species based on a color code (including transcription factors, kinases, adaptors, phosphatases, chaperones, proteases, translation factors, RNA and miscellanous), and are classified into three families (activators, targets, inhibitors) of respectively PERK, IREl andATF-6. Edges are characteristic of an interaction, either yet uncharacterized (thin) or characterized (thick). Finally, blue edges are significant of an association upon ER stress and red edges stand for an ER stress induced dissociation.

Gandhi CS, Loots E, Isacoff EY 2000 Reconstructing voltage sensor-pore interaction from a fluorescence scan of a voltage-gated K channel. Neuron 27 585-595... 

---