小波域地震资料的处理方法（WSSP）研究

The modeling formula based on seismic wavelet can well simulate zero - phase wavelet and hybrid-phase wavelet, and approximate maximal - phase and minimal - phase wavelet in a certain sense. The modeling wavelet can be used as wavelet function after suitable modification item added to meet some conditions. On the basis of the modified Morlet wavelet, the derivative wavelet function has been derived. As a basic wavelet, it can be sued for high resolution frequency - division processing and instantaneous feature extraction, in acoordance with the signal expanding characters in time and scale domains by each wavelet structured. Finally, an application example proves the effectiveness and reasonability of the method. Based on the analysis of SVD (Singular Value Decomposition) filter, by taking wavelet as basic wavelet and combining SVD filter and wavelet transform, a new de - noising method, which is Based on multi - dimension and multi-space de - noising method, is proposed. The implementation of this method is discussed the detail. Theoretical analysis and modeling show that the method has strong capacity of de - noising and keeping attributes of effective wave. It is a good tool for de - noising when the S/N ratio is poor. To give prominence to high frequency information of reflection event of important layer and to take account of other frequency information under processing seismic data, it is difficult for deconvolution filter to realize this goal. A filter from Fourier Transform has some problems for realizing the goal. In this paper, a new method is put forward, that is a method of processing seismic data in frequency division from wavelet transform and reconstruction. In ordinary seismic processing methods for resolution improvement, deconvolution operator has poor part characteristics, thus influencing the operator frequency. In wavelet transform, wavelet function has very good part characteristics. Frequency - division data processing in wavelet transform also brings quite good high resolution data, but it needs more time than deconvolution method does. On the basis of frequency - division processing method in wavelet domain, a new technique is put forward, which involves 1) designing filter operators equivalent to deconvolution operator in time and frequency domains in wavelet transform, 2) obtaining derivative wavelet function that is suitable to high - resolution seismic data processing, and 3) processing high resolution seismic data by deconvolution method in time domain. In the method of producing some instantaneous characteristic signals by using Hilbert transform, Hilbert transform is very sensitive to high - frequency random noise. As a result, even though there exist weak high - frequency noises in seismic signals, the obtained instantaneous characteristics of seismic signals may be still submerged by the noises. One method for having instantaneous characteristics of seismic signals in wavelet domain is put forward, which obtains directly the instantaneous characteristics of seismic signals by taking the characteristics of both the real part (real signals, namely seismic signals) and the imaginary part (the Hilbert transfom of real signals) of wavelet transform. The method has the functions of frequency division and noise removal. What is more, the weak wave whose frequency is lower than that of high - frequency random noise is retained in the obtained instantaneous characteristics of seismic signals, and the weak wave may be seen in instantaneous characteristic sections (such as instantaneous frequency, instantaneous phase and instantaneous amplitude). Impedance inversion is one of tools in the description of oil reservoir. one of methods in impedance inversion is Generalized Linear Inversion. This method has higher precision of inversion. But, this method is sensitive to noise of seismic data, so that error results are got. The description of oil reservoir in researching important geological layer, in order to give prominence to geological characteristics of the important layer, not only high frequency impedance to research thin sand layer, but other frequency impedance are needed. It is difficult for some impedance inversion method to realize the goal. Wavelet transform is very good in denoising and processing in frequency division. Therefore, in the paper, a method of impedance inversion is put forward based on wavelet transform, that is impedance inversion in frequency division from wavelet transform and reconstruction. in this paper, based on wavelet transform, methods of time - frequency analysis is given. Fanally, methods above are in application on real oil field - Sansan oil field.

岩性油藏储层预测的地震理论与方法研究

At present the main object of the exploration and development (E&D) of oil and gas is not the structural oil-gas pools but the subtle lithological oil-gas reservoir. Since the last 90's, the ratio of this kind of pools in newly-added oil reserves is becoming larger and larger, so is the ratio in the eastern oilfields. The third oil-gas resource evaluation indicates the main exploration object of Jiyang depression is the lithological oil-gas pools in future. However, lack of effective methods that are applied to search for this kind of pool makes E&D difficult and the cost high. In view of the urgent demand of E&D, in this paper we deeply study and analyze the theory and application in which the seismic attributes are used to predict and describe lithological oil-gas reservoirs. The great results are obtained by making full use of abundant physics and reservoir information as well as the remarkable lateral continuity involved in seismic data in combination with well logging, drilling-well and geology. ①Based on a great deal of research and different geological features of Shengli oilfield, the great progresses are made some theories and methods of seismic reservoir prediction and description. Three kinds of extrapolation near well seismic wavelet methods-inverse distance interpolation, phase interpolation and pseudo well reflectivity-are improved; particularly, in sparse well area the method of getting pseudo well reflectivity is given by the application of the wavelet theory. The formulae for seismic attributes and coherent volumes are derived theoretically, and the optimal method of seismic attributes and improved algorithms of picking up coherent data volumes are put forward. The method of making sequence analysis on seismic data is put forward and derived in which the wavelet transform is used to analyze not only qualitatively but also quantitatively seismic characteristics of reservoirs.② According to geologic model and seismic forward simulation, from macro to micro, the method of pre- and post-stack data synthetic analysis and application is put forward using seismic in close combination with geology; particularly, based on making full use of post-stack seismic data, "green food"-pre-stack seismic data is as possible as utilized. ③ In this paper, the formative law and distributing characteristic of lithologic oil-gas pools of the Tertiary in Jiyang depression, the knowledge of geological geophysics and the feasibility of all sorts of seismic methods, and the applied knowledge of seismic data and the geophysical mechanism of oil-gas reservoirs are studied. Therefore a series of perfect seismic technique and software are completed that fit to E&D of different categories of lithologic oil-gas reservoirs. ④ This achievement is different from other new seismic methods that are put forward in the recent years, that is multi-wave multi-component seismic, cross hole seismic, vertical seismic, and time-lapse seismic etc. that need the reacquisition of seismic data to predict and describe the oil-gas reservoir. The method in this paper is based on the conventional 2D/3D seismic data, so the cost falls sharply. ⑤ In recent years this technique that predict and describe lithologic oil-gas reservoirs by seismic information has been applied in E&D of lithologic oil-gas reservoirs on glutenite fans in abrupt slop and turbidite fans in front of abrup slop, slump turbidite fans in front of delta, turbidite fans with channel in low slope and channel sanbody, and a encouraging geologic result has been gained. This achievement indicates that the application of seismic information is one of the most effective ways in solving the present problem of E&D. This technique is significant in the application and popularization, and positive on increasing reserves and raising production as well as stable development in Shengli oilfield. And it will be directive to E&D of some similar reservoirs

基于信息重建技术的地震信号处理方法研究

The dissertation addressed the problems of signals reconstruction and data restoration in seismic data processing, which takes the representation methods of signal as the main clue, and take the seismic information reconstruction (signals separation and trace interpolation) as the core. On the natural bases signal representation, I present the ICA fundamentals, algorithms and its original applications to nature earth quake signals separation and survey seismic signals separation. On determinative bases signal representation, the paper proposed seismic dada reconstruction least square inversion regularization methods, sparseness constraints, pre-conditioned conjugate gradient methods, and their applications to seismic de-convolution, Radon transformation, et. al. The core contents are about de-alias uneven seismic data reconstruction algorithm and its application to seismic interpolation. Although the dissertation discussed two cases of signal representation, they can be integrated into one frame, because they both deal with the signals or information restoration, the former reconstructing original signals from mixed signals, the later reconstructing whole data from sparse or irregular data. The goal of them is same to provide pre-processing methods and post-processing method for seismic pre-stack depth migration. ICA can separate the original signals from mixed signals by them, or abstract the basic structure from analyzed data. I surveyed the fundamental, algorithms and applications of ICA. Compared with KL transformation, I proposed the independent components transformation concept (ICT). On basis of the ne-entropy measurement of independence, I implemented the FastICA and improved it by covariance matrix. By analyzing the characteristics of the seismic signals, I introduced ICA into seismic signal processing firstly in Geophysical community, and implemented the noise separation from seismic signal. Synthetic and real data examples show the usability of ICA to seismic signal processing and initial effects are achieved. The application of ICA to separation quake conversion wave from multiple in sedimentary area is made, which demonstrates good effects, so more reasonable interpretation of underground un-continuity is got. The results show the perspective of application of ICA to Geophysical signal processing. By virtue of the relationship between ICA and Blind Deconvolution , I surveyed the seismic blind deconvolution, and discussed the perspective of applying ICA to seismic blind deconvolution with two possible solutions. The relationship of PC A, ICA and wavelet transform is claimed. It is proved that reconstruction of wavelet prototype functions is Lie group representation. By the way, over-sampled wavelet transform is proposed to enhance the seismic data resolution, which is validated by numerical examples. The key of pre-stack depth migration is the regularization of pre-stack seismic data. As a main procedure, seismic interpolation and missing data reconstruction are necessary. Firstly, I review the seismic imaging methods in order to argue the critical effect of regularization. By review of the seismic interpolation algorithms, I acclaim that de-alias uneven data reconstruction is still a challenge. The fundamental of seismic reconstruction is discussed firstly. Then sparseness constraint on least square inversion and preconditioned conjugate gradient solver are studied and implemented. Choosing constraint item with Cauchy distribution, I programmed PCG algorithm and implement sparse seismic deconvolution, high resolution Radon Transformation by PCG, which is prepared for seismic data reconstruction. About seismic interpolation, dealias even data interpolation and uneven data reconstruction are very good respectively, however they can not be combined each other. In this paper, a novel Fourier transform based method and a algorithm have been proposed, which could reconstruct both uneven and alias seismic data. I formulated band-limited data reconstruction as minimum norm least squares inversion problem where an adaptive DFT-weighted norm regularization term is used. The inverse problem is solved by pre-conditional conjugate gradient method, which makes the solutions stable and convergent quickly. Based on the assumption that seismic data are consisted of finite linear events, from sampling theorem, alias events can be attenuated via LS weight predicted linearly from low frequency. Three application issues are discussed on even gap trace interpolation, uneven gap filling, high frequency trace reconstruction from low frequency data trace constrained by few high frequency traces. Both synthetic and real data numerical examples show the proposed method is valid, efficient and applicable. The research is valuable to seismic data regularization and cross well seismic. To meet 3D shot profile depth migration request for data, schemes must be taken to make the data even and fitting the velocity dataset. The methods of this paper are used to interpolate and extrapolate the shot gathers instead of simply embedding zero traces. So, the aperture of migration is enlarged and the migration effect is improved. The results show the effectiveness and the practicability.

利用分频与反演提高地震资料信噪比与分辨率方法研究

This thesis mainly talks about the wavelet transfrom and the frequency division method. It describes the frequency division processing on prestack or post-stack seismic data and application of inversion noise attenuation, frequency division residual static correction and high resolution data in reservoir inversion. This thesis not only describes the frequency division and inversion in theory, but also proves it by model calculation. All the methods are integrated together. The actual data processing demonstrates the applying results. This thesis analyzes the differences and limitation between t-x prediction filter and f-x prediction filter noise attenuation from wavelet transform theory. It considers that we can do the frequency division attenuation process of noise and signal by wavelet frequency division theory according to the differences of noise and signal in phase, amplitude and frequency. By comparison with the f-x coherence noise, removal method, it approves the effects and practicability of frequency division in coherence and random noise isolation. In order to solve the side effects in non-noise area, we: take the area constraint method and only apply the frequency division processing in the noise area. So it can solve the problem of low frequency loss in non-noise area. The residual moveout differences in seismic data processing have a great effect on stack image and resolutions. Different frequency components have different residual moveout differences. The frequency division residual static correction realizes the frequency division and the calculation of residual correction magnitude. It also solves the problems of different residual correction magnitude in different frequency and protects the high frequency information in data. By actual data processing, we can get good results in phase residual moveout differences elimination of pre-stack data, stack image quality and improvement of data resolution. This thesis analyses the characters of the random noises and its descriptions in time domain and frequency domain. Furthermore it gives the inversion prediction solution methods and realizes the frequency division inversion attenuation of the random noise. By the analysis of results of the actual data processing, we show that the noise removed by inversion has its own advantages. By analyzing parameter's about resolution and technology of high resolution data processing, this thesis describes the relations between frequency domain and resolution, parameters about resolution and methods to increase resolution. It also gives the processing flows of the high resolution data; the effect and influence of reservoir inversion caused by high resolution data. Finally it proves the accuracy and precision of the reservoir inversion results. The research results of this thesis reveal that frequency division noise attenuation, frequency residual correction and inversion noise attenuation are effective methods to increase the SNR and resolution of seismic data.

陆相砂泥岩层序的高精度检测方法研究及应用

Ordos Basin is a typical cratonic petroliferous basin with 40 oil-gas bearing bed sets. It is featured as stable multicycle sedimentation, gentle formation, and less structures. The reservoir beds in Upper Paleozoic and Mesozoicare are mainly low density, low permeability, strong lateral change, and strong vertical heterogeneous. The well-known Loess Plateau in the southern area and Maowusu Desert, Kubuqi Desert and Ordos Grasslands in the northern area cover the basin, so seismic data acquisition in this area is very difficult and the data often takes on inadequate precision, strong interference, low signal-noise ratio, and low resolution. Because of the complicated condition of the surface and the underground, it is very difficult to distinguish the thin beds and study the land facies high-resolution lithologic sequence stratigraphy according to routine seismic profile. Therefore, a method, which have clearly physical significance, based on advanced mathematical physics theory and algorithmic and can improve the precision of the detection on the thin sand-peat interbed configurations of land facies, is in demand to put forward.Generalized S Transform (GST) processing method provides a new method of phase space analysis for seismic data. Compared with wavelet transform, both of them have very good localization characteristics; however, directly related to the Fourier spectra, GST has clearer physical significance, moreover, GST adopts a technology to best approach seismic wavelets and transforms the seismic data into time-scale domain, and breaks through the limit of the fixed wavelet in S transform, so GST has extensive adaptability. Based on tracing the development of the ideas and theories from wavelet transform, S transform to GST, we studied how to improve the precision of the detection on the thin stratum by GST.Noise has strong influence on sequence detecting in GST, especially in the low signal-noise ratio data. We studied the distribution rule of colored noise in GST domain, and proposed a technology to distinguish the signal and noise in GST domain. We discussed two types of noises: white noise and red noise, in which noise satisfy statistical autoregression model. For these two model, the noise-signal detection technology based on GST all get good result. It proved that the GST domain noise-signal detection technology could be used to real seismic data, and could effectively avoid noise influence on seismic sequence detecting.On the seismic profile after GST processing, high amplitude energy intensive zone, schollen, strip and lentoid dead zone and disarray zone maybe represent specifically geologic meanings according to given geologic background. Using seismic sequence detection profile and combining other seismic interpretation technologies, we can elaborate depict the shape of palaeo-geomorphology, effectively estimate sand stretch, distinguish sedimentary facies, determine target area, and directly guide oil-gas exploration.In the lateral reservoir prediction in XF oilfield of Ordos Basin, it played very important role in the estimation of sand stretch that the study of palaeo-geomorphology of Triassic System and the partition of inner sequence of the stratum group. According to the high-resolution seismic profile after GST processing, we pointed out that the C8 Member of Yanchang Formation in DZ area and C8 Member in BM area are the same deposit. It provided the foundation for getting 430 million tons predicting reserves and unite building 3 million tons off-take potential.In tackling key problem study for SLG gas-field, according to the high-resolution seismic sequence profile, we determined that the deposit direction of H8 member is approximately N-S or NNE-SS W. Using the seismic sequence profile, combining with layer-level profile, we can interpret the shape of entrenched stream. The sunken lenticle indicates the high-energy stream channel, which has stronger hydropower. By this way we drew out three high-energy stream channels' outline, and determined the target areas for exploitation. Finding high-energy braided river by high-resolution sequence processing is the key technology in SLG area.In ZZ area, we studied the distribution of the main reservoir bed-S23, which is shallow delta thin sand bed, by GST processing. From the seismic sequence profile, we discovered that the schollen thick sand beds are only local distributed, and most of them are distributary channel sand and distributary bar deposit. Then we determined that the S23 sand deposit direction is NW-SE in west, N-S in central and NE-SW in east. The high detecting seismic sequence interpretation profiles have been tested by 14 wells, 2 wells mismatch and the coincidence rate is 85.7%. Based on the profiles we suggested 3 predicted wells, one well (Yu54) completed and the other two is still drilling. The completed on Is coincident with the forecastThe paper testified that GST is a effective technology to get high- resolution seismic sequence profile, compartmentalize deposit microfacies, confirm strike direction of sandstone and make sure of the distribution range of oil-gas bearing sandstone, and is the gordian technique for the exploration of lithologic gas-oil pool in complicated areas.

Ocena wiarygodności metod identyfikacji strumieni meteoroidowych

Wydział Fizyki:Instytut Obserwatorium Astronomiczne

Graph Wavelets for Spatial Traffic Analysis

A number of problems in network operations and engineering call for new methods of traffic analysis. While most existing traffic analysis methods are fundamentally temporal, there is a clear need for the analysis of traffic across multiple network links — that is, for spatial traffic analysis. In this paper we give examples of problems that can be addressed via spatial traffic analysis. We then propose a formal approach to spatial traffic analysis based on the wavelet transform. Our approach (graph wavelets) generalizes the traditional wavelet transform so that it can be applied to data elements connected via an arbitrary graph topology. We explore the necessary and desirable properties of this approach and consider some of its possible realizations. We then apply graph wavelets to measurements from an operating network. Our results show that graph wavelets are very useful for our motivating problems; for example, they can be used to form highly summarized views of an entire network's traffic load, to gain insight into a network's global traffic response to a link failure, and to localize the extent of a failure event within the network.

Identifying the damage mechanisms in paper using the acoustic emission monitoring technique

This paper investigates the use of the acoustic emission (AE) monitoring technique for use in identifying the damage mechanisms present in paper associated with its production process. The microscopic structure of paper consists of a random mesh of paper fibres connected by hydrogen bonds. This implies the existence of two damage mechanisms, the failure of a fibre-fibre bond and the failure of a fibre. This paper describes a hybrid mathematical model which couples the mechanics of the mass-spring model to the acoustic wave propagation model for use in generating the acoustic signal emitted by complex structures of paper fibres under strain. The derivation of the mass-spring model can be found in [1,2], with details of the acoustic wave equation found in [3,4]. The numerical implementation of the vibro-acoustic model is discussed in detail with particular emphasis on the damping present in the numerical model. The hybrid model uses an implicit solver which intrinsically introduces artificial damping to the solution. The artificial damping is shown to affect the frequency response of the mass-spring model, therefore certain restrictions on the simulation time step must be enforced so that the model produces physically accurate results. The hybrid mathematical model is used to simulate small fibre networks to provide information on the acoustic response of each damage mechanism. The simulated AEs are then analysed using a continuous wavelet transform (CWT), described in [5], which provides a two dimensional time-frequency representation of the signal. The AEs from the two damage mechanisms show different characteristics in the CWT so that it is possible to define a fibre-fibre bond failure by the criteria listed below. The dominant frequency components of the AE must be at approximately 250 kHz or 750 kHz. The strongest frequency component may be at either approximately 250 kHz or 750 kHz. The duration of the frequency component at approximately 250 kHz is longer than that of the frequency component at approximately 750 kHz. Similarly, the criteria for identifying a fibre failure are given below. The dominant frequency component of the AE must be greater than 800 kHz. The duration of the dominant frequency component must be less than 5.00E-06 seconds. The dominant frequency component must be present at the front of the AE. Essentially, the failure of a fibre-fibre bond produces a low frequency wave and the failure of a fibre produces a high frequency pulse. Using this theoretical criteria, it is now possible to train an intelligent classifier such as the Self-Organising Map (SOM) [6] using the experimental data. First certain features must be extracted from the CWTs of the AEs for use in training the SOM. For this work, each CWT is divided into 200 windows of 5E-06s in duration covering a 100 kHz frequency range. The power ratio for each windows is then calculated and used as a feature. Having extracted the features from the AEs, the SOM can now be trained, but care is required so that the both damage mechanisms are adequately represented in the training set. This is an issue with paper as the failure of the fibre-fibre bonds is the prevalent damage mechanism. Once a suitable training set is found, the SOM can be trained and its performance analysed. For the SOM described in this work, there is a good chance that it will correctly classify the experimental AEs.

An analysis of the changes to the mechanical and acoustical properties of paper caused by the damage mechanisms present in the fibre structure

This paper will analyse two of the likely damage mechanisms present in a paper fibre matrix when placed under controlled stress conditions: fibre/fibre bond failure and fibre failure. The failure process associated with each damage mechanism will be presented in detail focusing on the change in mechanical and acoustic properties of the surrounding fibre structure before and after failure. To present this complex process mathematically, geometrically simple fibre arrangements will be chosen based on certain assumptions regarding the structure and strength of paper, to model the damage mechanisms. The fibre structures are then formulated in terms of a hybrid vibro-acoustic model based on a coupled mass/spring system and the pressure wave equation. The model will be presented in detail in the paper. The simulation of the simple fibre structures serves two purposes; it highlights the physical and acoustic differences of each damage mechanism before and after failure, and also shows the differences in the two damage mechanisms when compared with one another. The results of the simulations are given in the form of pressure wave contours, time-frequency graphs and the Continuous Wavelet Transform (CWT) diagrams. The analysis of the results leads to criteria by which the two damage mechanisms can be identified. Using these criteria it was possible to verify the results of the simulations against experimental acoustic data. The models developed in this study are of specific practical interest in the paper-making industry, where acoustic sensors may be used to monitor continuous paper production. The same techniques may be adopted more generally to correlate acoustic signals to damage mechanisms in other fibre-based structures.

Area-efficient high-speed 3D DWT processor architecture

An area-efficient high-throughput architecture based on distributed arithmetic is proposed for 3D discrete wavelet transform (DWT). The 3D DWT processor was designed in VHDL and mapped to a Xilinx Virtex-E FPGA. The processor runs up to 85 MHz, which can process the five-level DWT analysis of a 128 x 128 x 128 fMRI volume image in 20 ms.

The application of a Trous wave filtering and Monte Carlo analysis on secis 2001 solar eclipse observations

Eight thousand images of the solar corona were captured during the June 2001 total solar eclipse. New software for the alignment of the images and an automated technique for detecting intensity oscillations using multi-scale wavelet analysis were developed. Large areas of the images covered by the Moon and the upper corona were scanned for oscillations and the statistical properties of the atmospheric effects were determined. The a Trous wavelet transform was used for noise reduction and Monte Carlo analysis as a significance test of the detections. The effectiveness of those techniques is discussed in detail.

TDM modelling and evaluation of different domain transforms for LSI

Latent semantic indexing (LSI) is a popular technique used in information retrieval (IR) applications. This paper presents a novel evaluation strategy based on the use of image processing tools. The authors evaluate the use of the discrete cosine transform (DCT) and Cohen Daubechies Feauveau 9/7 (CDF 9/7) wavelet transform as a pre-processing step for the singular value decomposition (SVD) step of the LSI system. In addition, the effect of different threshold types on the search results is examined. The results show that accuracy can be increased by applying both transforms as a pre-processing step, with better performance for the hard-threshold function. The choice of the best threshold value is a key factor in the transform process. This paper also describes the most effective structure for the database to facilitate efficient searching in the LSI system.

Progressive Audio Scrambling in Compressed Domain

Audio scrambling can be employed to ensure confidentiality in audio distribution. We first describe scrambling for raw audio using the discrete wavelet transform (DWT) first and then focus on MP3 audio scrambling. We perform scrambling based on a set of keys which allows for a set of audio outputs having different qualities. During descrambling, the number of keys provided and the number of rounds of descrambling performed will decide the audio output quality. We also perform scrambling by using multiple keys on the MP3 audio format. With a subset of keys, we can descramble to obtain a low quality audio. However, we can obtain the original quality audio by using all of the keys. Our experiments show that the proposed algorithms are effective, fast, simple to implement while providing flexible control over the progressive quality of the audio output. The security level provided by the scheme is sufficient for protecting MP3 music content.

Measurement-based Method for Wind Farm Power System Oscillations Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

Flow-mediated dilatation of the brachial artery is a poorly reproducible indicator of microvascular function in Type I diabetes mellitus

Aim: Two Type I diabetes and control group comparator studies were conducted to assess the reproducibility of FMD and to analyse blood flow data normally discarded during FMD measurement.

Design: The studies were sequential and differed only with regard to operator and ultrasound machine. Seventy-two subjects with diabetes and 71 controls were studied in total.

Methods: Subjects had FMD measured conventionally. Blood velocity waveforms were averaged over 10 pulses post forearm ischaemia and their component frequencies analysed using the wavelet transform, a mathematical tool for waveform analysis. The component frequencies were grouped into 11 bands to facilitate analysis.

Results: Subjects were well-matched between studies. In Study 1, FMD was significantly impaired in subjects with Type I diabetes vs. controls (median 4.35%, interquartile range 3.10-4.80 vs. 6.50, 4.79-9.42, P < 0.001). No differences were detected between groups in Study 2, however. However, analysis of blood velocity waveforms yielded significant differences between groups in two frequency bands in each study.

Conclusions: This report highlights concerns over the reproducibility of FMD measures. Further work is required to fully elucidate the role of analysing velocity waveforms after forearm ischaemia.