Root cause isolation of propagated oscillations in process plants

Persistent whole-plant disturbances can have an especially large impact on product quality and running costs. There is thus a motivation for the automated detection of a plant-wide disturbance and for the isolation of its sources. Oscillations increase variability and can prevent a plant from operating close to optimal constraints. They can also camouflage other behaviour that may need attention such as upsets due to external disturbances. A large petrochemical plant may have a 1000 or more control loops and indicators, so a key requirement of an industrial control engineer is for an automated means to detect and isolate the root cause of these oscillations so that maintenance effort can be directed efficiently. The propagation model that is proposed is represented by a log-ratio plot, which is shown to be ‘bell’ shaped in most industrial situations. Theoretical and practical issues are addressed to derive guidelines for determining the cut-off frequencies of the ‘bell’ from data sets requiring little knowledge of the plant schematic and controller settings. The alternative method for isolation is based on the bispectrum and makes explicit use of this model representation. A comparison is then made with other techniques. These techniques include nonlinear time series analysis tools like Correlation dimension and maximal Lyapunov Exponent and a new interpretation of the Spectral ICA method, which is proposed to accommodate our revised understanding of harmonic propagation. Both simulated and real plant data are used to test the proposed approaches. Results demonstrate and compare their ability to detect and isolate the root cause of whole plant oscillations. Being based on higher order statistics (HOS), the bispectrum also provides a means to detect nonlinearity when oscillatory measurement records exist in process systems. Its comparison with previous HOS based nonlinearity detection method is made and the bispectrum-based is preferred

One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor

Pathological tremors are symptomatic to several neurological disorders that are difficult to differentiate and the way by which central oscillatory networks entrain tremorogenic contractions is unknown. We considered the alternative hypotheses that tremor arises from one oscillator (at the tremor frequency) or, as suggested by recent findings from the superimposition of two separate inputs (at the tremor frequency and twice that frequency). Approach. Assuming one central oscillatory network we estimated analytically the relative amplitude of the harmonics of the tremor frequency in the motor neuron output for different temporal behaviors of the oscillator. Next, we analyzed the bias in the relative harmonics amplitude introduced by superimposing oscillations at twice the tremor frequency. These findings were validated using experimental measurements of wrist angular velocity and surface electromyography (EMG) from 22 patients (11 essential tremor, 11 Parkinson’s disease). The ensemble motor unit action potential trains identified from the EMG represented the neural drive to the muscles. Main results. The analytical results showed that the relative power of the tremor harmonics in the analytical models of the neural drive was determined by the variability and duration of the tremor bursts and the presence of the second oscillator biased this power towards higher values. The experimental findings accurately matched the analytical model assuming one oscillator, indicating a negligible functional role of secondary oscillatory inputs. Furthermore, a significant difference in the relative power of harmonics in the neural drive was found across the patient groups, suggesting a diagnostic value of this measure (classification accuracy: 86%). This diagnostic power decreased substantially when estimated from limb acceleration or the EMG. Signficance. The results indicate that the neural drive in pathological tremor is compatible with one central network providing neural oscillations at the tremor frequency. Moreover, the regularity of this neural oscillation varies across tremor pathologies, making the relative amplitude of tremor harmonics a potential biomarker for diagnostic use

Applications of optical processing for improving ERTS data, volume 1

Application of optically diagnosed noise information toward development of filtering subroutines for improvement of digital sensing data tape quality - Vol.

Neural Network-Based Noise Suppressor and Predictor for Quantifying Valve Stiction in Oscillatory Control Loops

Valve stiction-induced oscillations in chemical processing systems adversely affects control loop performance and can degrade the quality of products. Estimating the degree of stiction in a valve is a crucial step in compensating for the effect. This work proposes a neural network approach to quantify the degree of stiction in a valve once the phenomenon has been detected. Several degrees of stiction are simulated in a closed loop control system by specifying the magnitude of static (fs) and dynamic (fd) friction in a physical valve model. Each simulation generates controller output OP(t) and process variable PV(t) time series data. A feed-forward neural network (the predictor) is trained to model the relationship between a given OP and PV pattern, and the stiction parameters. To test the models predictive capability, a separate set of stiction patterns are generated with and without added process noise. An inverse neural network-based nonlinear principal component analysis (INLPCA) noise-suppressor effectively extracts the underlying stiction behaviour from the noise-corrupted OP and PV stiction patterns. In the noiseless test patterns, the predictor is shown to estimate fs and fd with a 0.65% average error. In the case of the noisy test patterns, the average error achieved was 1.85%. Since the predictor is developed offline, the use of computationally intensive real-time search/optimization routines to quantify stiction is avoided. The neural networks proved to be easily implementable, highly flexible models for extracting stiction behavior from control loops and accurately quantifying stiction, as long as an adequate first-principles description of the process dynamics can be developed

Nicht-invasive elektrophysiologische Biomarker des Alterns und der Parkinson-Krankheit

Parkinson’s disease (PD) is a frequent neurodegenerative disorder. It mainly affects motor functions and it has a long preclinical phase. Dopaminergic medication is an effective treatment but also comes with adverse effects. Therefore, investigating early biomarkers of PD and effects of dopaminergic medication is crucial for advancing the understanding and treatment of this disease. In my dissertation, two studies are presented that contribute to this field. In the first study, we studied PD-related neuronal biomarkers, including excessive PAC (phase-amplitude coupling) between the beta phase and amplitude from broadband gamma and abnormal beta burst dynamics in a group of young (N=71, age 20–35 years) and apparently healthy elderly (N=66, age 59–77 years) subjects with electroencephalography (EEG) recordings. In the second study, based on a group of patients with PD (N=15), we investigated the effects of dopaminergic medication on non-oscillatory component of the neural activity (estimated by the spectral slope), the inter-areal functional connectivity and functional network’s configuration properties. The results from the first study confirmed that the elderly subjects show elevated PAC compared to the younger ones; and this effect is most pronounced in motor-related areas. In addition, the elderly are characterized by prolonged and more often bursting beta activity compared to the young subjects. In the second study, we observed that the spectral slope is steeper after dopaminergic medication intake. Moreover, the medication administration induces an up-regulation of the inter-regional connectivity in the beta band, mainly in fronto-centro-parietal regions. However, there is no evidence showing a significant alteration in the global properties of the functional network. Interestingly, we found that only in the Off medication state there is a close association between the spectral slope and the integrative ability of the brain network. These effects are consistently present in the centro-parietal region. These findings provide evidence that the electrophysiological biomarkers associated with PD are also present in a group of presumably healthy elderly compared to a young one. This, in turn, indicates that these biomarkers might be promising for the detection of a pre-clinical stage of PD given a close relationship between aging and PD. Future prospective studies should test their unique predictive value in the development of PD. Furthermore, dopaminergic medication induces changes not only locally in the spectral slope but also in the interaction between the areas with a specific spatial interaction pattern. Crucially, the spectral slope (which may index the local excitation/inhibition ratio) appears to be essential in forming the global network’s ability to integrate information from remote areas in PD. This could be relevant for the interventional studies directed at non-invasive modulation of neuronal activity in these areas.Die Parkinson-Krankheit (PK) ist eine neurodegenerative Störung. Sie betrifft die motorischen Funktionen und hat eine lange präklinische Phase. Dopaminerge Medikamente (DM) sind eine wirksame Behandlung, haben aber auch Nebenwirkungen. Daher ist die Untersuchung früher Biomarker für PK und der Auswirkungen DM von Bedeutung, um das Verständnis und die Behandlung dieser Krankheit voranzutreiben. In meiner Dissertation werden zwei Studien vorgestellt, die einen Beitrag zu diesem Thema leisten. ​ In Studie 1 nutzten wir Elektroenzephalografie (EEG) und untersuchten neuronale PD-bezogene Biomarker, einschließlich erhöhter PAC (Phasen-Amplituden-Kopplung) zwischen der Beta-Phase und der Breitband-Gamma-Amplitude und abnormaler Beta-Burst-Dynamik in jungen (N=71, Alter 20-35 Jahre) und gesunden älteren (N=66, Alter 59–77 Jahre) Probanden. In Studie 2 mit PK-Patienten (N=15) untersuchten wir die Auswirkungen von DM auf die nicht-oszillatorische Komponente der neuronalen Aktivität, die interareale funktionelle Konnektivität und dessen Konfigurationseigenschaften. ​ Die Ergebnisse von Studie 1 bestätigten, dass ältere Probanden eine erhöhte PAC aufweisen; dieser Effekt ist in den motorischen Bereichen am stärksten ausgeprägt. Darüber hinaus weisen ältere Probanden eine verlängerte und häufiger auftretende Bursting-Beta-Aktivität auf. In Studie 2 beobachteten wir, dass die spektrale Steigung nach der DM-Einnahme steiler ist. Außerdem führt DM zu einer Hochregulierung der Konnektivität im Betaband, vor allem in fronto-zentral-parietalen Regionen. Es gibt jedoch keine Hinweise auf eine signifikante Veränderung der globalen Eigenschaften des funktionellen Netzwerks. Interessanterweise haben wir festgestellt, dass nur im Zustand „ohne“ DM ein enger Zusammenhang zwischen der spektralen Steigung und der Integrationsfähigkeit des Netzwerks besteht. Diese Effekte sind durchweg in der zentro-parietalen Region vorzufinden. ​ Diese Ergebnisse belegen, dass die EEG-Biomarker, die mit PK in Verbindung gebracht werden, auch in gesunden, älteren Menschen vorhanden sind. Dies wiederum deutet darauf hin, dass diese Biomarker vielversprechend für die Erkennung eines präklinischen Stadiums der PK sein könnten. Künftige prospektive Studien sollten ihren prädiktiven Wert in der Entwicklung der PK untersuchen. Darüber hinaus induzieren DM Veränderungen nicht nur lokal in der spektralen Steigung, sondern auch in der Interaktion zwischen den Bereichen mit einem bestimmten räumlichen Interaktionsmuster. Entscheidend ist, dass die spektrale Steigung (die möglicherweise das lokale Verhältnis zwischen Erregung und Hemmung anzeigt) für die Fähigkeit des globalen Netzwerks, Informationen aus entfernten Bereichen zu integrieren, bei der PK von Bedeutung ist. Dies könnte für interventionelle Studien relevant sein, die auf eine nicht-invasive Modulation der neuronalen Aktivität in diesen Bereichen abzielen