The state estimation of flow demands in gas networks from sparse pressure telemetry

This paper presents novel observer-based techniques for the estimation of flow demands in gas networks, from sparse pressure telemetry. A completely observable model is explored, constructed by incorporating difference equations that assume the flow demands are steady. Since the flow demands usually vary slowly with time, this is a reasonable approximation. Two techniques for constructing robust observers are employed: robust eigenstructure assignment and singular value assignment. These techniques help to reduce the effects of the system approximation. Modelling error may be further reduced by making use of known profiles for the flow demands. The theory is extended to deal successfully with the problem of measurement bias. The pressure measurements available are subject to constant biases which degrade the flow demand estimates, and such biases need to be estimated. This is achieved by constructing a further model variation that incorporates the biases into an augmented state vector, but now includes information about the flow demand profiles in a new form.

A three-dimensional magnetometer for motion sensing of a balloon-carried atmospheric measurement package

An instrument is described which carries three orthogonal geomagnetic field sensors on a standard meteorological balloon package, to sense rapid motion and position changes during ascent through the atmosphere. Because of the finite data bandwidth available over the UHF radio link, a burst sampling strategy is adopted. Bursts of 9s of measurements at 3.6Hz are interleaved with periods of slow data telemetry lasting 25s. Calculation of the variability in each channel is used to determine position changes, a method robust to periods of poor radio signals. During three balloon ascents, variability was found repeatedly at similar altitudes, simultaneously in each of three orthogonal sensors carried. This variability is attributed to atmospheric motions. It is found that the vertical sensor is least prone to stray motions, and that the use of two horizontal sensors provides no additional information over a single horizontal sensor

A double-Gerdien instrument for simultaneous bipolar air conductivity measurements on balloon platforms

A bipolar air conductivity instrument is described for use with a standard disposable meteorological radiosonde package. It is intended to provide electrical measurements at cloud boundaries, where the ratio of the bipolar air conductivities is affected by the presence of charged particles. The sensors are two identical Gerdien-type electrodes, which, through a voltage decay method, measure positive and negative air conductivities simultaneously. Voltage decay provides a thermally stable approach and a novel low current leakage electrometer switch is described which initiates the decay sequence. The radiosonde supplies power and telemetry, as well as measuring simultaneous meteorological data. A test flight using a tethered balloon determined positive (σ+) and negative (σ−) conductivities of σ+ = 2.77±0.2 fS m−1 and σ− = 2.82±0.2 fS m−1, respectively, at 400 m aloft, with σ+/σ− = 0.98±0.04.

Comparison of balloon-carried atmospheric motion sensors with Doppler lidar turbulence measurements

Magnetic sensors have been added to a standard weather balloon radiosonde package to detect motion in turbulent air. These measure the terrestrial magnetic field and return data over the standard uhf radio telemetry. Variability in the magnetic sensor data is caused by motion of the instrument package. A series of radiosonde ascents carrying these sensors has been made near a Doppler lidar measuring atmospheric properties. Lidar-retrieved quantities include vertical velocity (w) profile and its standard deviation (w). w determined over 1 h is compared with the radiosonde motion variability at the same heights. Vertical motion in the radiosonde is found to be robustly increased when w>0.75 m s−1 and is linearly proportional to w. ©2009 American Institute of Physics

A block coprocessor for user data rate improvements to GPRS coding scheme 4

The general packet radio service (GPRS) has been developed to allow packet data to be transported efficiently over an existing circuit-switched radio network, such as GSM. The main application of GPRS are in transporting Internet protocol (IP) datagrams from web servers (for telemetry or for mobile Internet browsers). Four GPRS baseband coding schemes are defined to offer a trade-off in requested data rates versus propagation channel conditions. However, data rates in the order of > 100 kbits/s are only achievable if the simplest coding scheme is used (CS-4) which offers little error detection and correction (EDC) (requiring excellent SNR) and the receiver hardware is capable of full duplex which is not currently available in the consumer market. A simple EDC scheme to improve the GPRS block error rate (BLER) performance is presented, particularly for CS-4, however gains in other coding schemes are seen. For every GPRS radio block that is corrected by the EDC scheme, the block does not need to be retransmitted releasing bandwidth in the channel and improving the user's application data rate. As GPRS requires intensive processing in the baseband, a viable field programmable gate array (FPGA) solution is presented in this paper.

Improving CS-4 user data rate in GPRS enabled devices by using a BLER co-processor

The General Packet Radio Service (GPRS) was developed to allow packet data to be transported efficiently over an existing circuit switched radio network. The main applications for GPRS are in transporting IP datagram’s from the user’s mobile Internet browser to and from the Internet, or in telemetry equipment. A simple Error Detection and Correction (EDC) scheme to improve the GPRS Block Error Rate (BLER) performance is presented, particularly for coding scheme 4 (CS-4), however gains in other coding schemes are seen. For every GPRS radio block that is corrected by the EDC scheme, the block does not need to be retransmitted releasing bandwidth in the channel, improving throughput and the user’s application data rate. As GPRS requires intensive processing in the baseband, a viable hardware solution for a GPRS BLER co-processor is discussed that has been currently implemented in a Field Programmable Gate Array (FPGA) and presented in this paper.

Using modelling tools to optimise the calculation and subsequent reduction of cable distortion parameters with application to oil well logging systems

This paper discusses how the use of computer-based modelling tools has aided the design of a telemetry unit for use with oil well logging. With the aid of modern computer-based simulation techniques, the new design is capable of operating at data rates of 2.5 times faster than previous designs.

Relationship between dietary-induced changes in intestinal commensal microflora and duodenojejunal myoelectric activity monitored by radiotelemetry in the rat in vivo

Interdigestive intestinal motility, and especially phase III of the migrating myoelectric/motor complex (MMC), is responsible for intestinal clearance and plays an important role in prevention of bacterial overgrowth and translocation in the gut. Yet previous results from gnotobiotic rats have shown that intestinal microflora can themselves affect the characteristics of the myoelectric activity of the gut during the interdigestive state. Given that the composition of the intestinal microflora can be altered by dietary manipulations, we investigated the effect of supplementation of the diet with synbiotics on intestinal microflora structure and the duodenojejunal myoelectric activity in the rat. To reduce animal distress caused by restraint and handling, which can itself affect GI motility, we applied radiotelemetry for duodenojejunal EMG recordings in conscious, freely moving rats. Thirty 16-month-old Spraque-Dawley rats were used. The diet for 15 rats (E group) was supplemented with chicory inulin, Lactobacillus rhamnosus and Bifidobacterium lactis. The remaining 15 rats were fed control diet without supplements (C group). Three rats from each group were implanted with three bipolar electrodes positioned at 2, 14 and 28 cm distal to the pylorus. After recovery, two 6 h recordings of duodenojejunal EMG were carried out on each operated rat. Subsequently, group C rats received feed supplements and group E rats received only control diet for 1 week, and an additional two 6 h recordings were carried out on each of these rats. Non-operated C and E rats were killed and samples of GI tract were collected for microbiological analyses. Supplementation of the diet with the pro- and prebiotics mixture increased the number of bifidobacteria, whereas it decreased the number of enterobacteria in jejunum, ileum, caecum and colon. In both caecum and colon, the dietary supplementation increased the number of total anaerobes and lactobacilli. Treatment with synbiotics increased occurrence of phase III of the MMC at all three levels of the small intestine. The propagation velocity of phase III in the whole recording segment was also increased from 3.7 +/- 0.2 to 4.4 +/- 0.2 cm min(-1) by dietary treatment. Treatment with synbiotics increased the frequency of response potentials of the propagated phase III of the MMC at both levels of the jejunum, but not in the duodenum. In both parts of the jejunum, the supplementation of the diet significantly decreased the duration of phase II of the MMC, while it did not change the duration of phase I and phase III. Using the telemetry technique it was demonstrated that changes in the gastrointestinal microflora exhibited an intestinal motility response and, more importantly, that such changes can be initiated by the addition of synbiotics to the diet.

Towards expressive rule induction on IP network event streams

In order to gain insights into events and issues that may cause errors and outages in parts of IP networks, intelligent methods that capture and express causal relationships online (in real-time) are needed. Whereas generalised rule induction has been explored for non-streaming data applications, its application and adaptation on streaming data is mostly undeveloped or based on periodic and ad-hoc training with batch algorithms. Some association rule mining approaches for streaming data do exist, however, they can only express binary causal relationships. This paper presents the ongoing work on Online Generalised Rule Induction (OGRI) in order to create expressive and adaptive rule sets real-time that can be applied to a broad range of applications, including network telemetry data streams.