S.L. Cruz

Pressure wave behaviour and leak detection in pipelines

Abstract In the present work on-line computational techniques have been developed and used in the analysis of hydraulic transients caused by leakage, in order to detect and locate pipeline ruptures. Pressure transients were obtained in two PVC pipelines 3 4 ″ diameter by using four pressure transducers connected to a PC computer equipped with A/D and D/A converters. The pipelines were 433 m and 1,248 m long. Leaks were simulated at different positions along the pipelines. Experiments were carried out for different liquid flow rates corresponding to Reynolds number in the range from 2,000 to 13,000. Leak percentage were in the range from 5% to 50% of the nominal liquid flow. A computer program to be run on-line was developed to simulate the leak, to read and filter the pressure transducers data, to display the pressure transient plots and to obtain leak location information. The detection system showed good performance in the detection of small leaks. Leaks as small as 5 % of the nominal liquid flow rate are readily detected. Leak locations were computed from pulse time delay between the various pressure transducers. The computed leak positions approached the actual values with precision. The developed software shows to be a very useful tool to the automatic supervision of pipelines as instantaneous leaks are readily detected and located.

State estimation of batch distillation columns using an extended Kalman filter

Composition monitoring and control play an essential role during a batch distillation cycle, but on-line composition analyzers are expensive, difficult to maintain and give delayed responses. Considering the need and lack of a stochastic estimator for batch distillation columns, a discrete extended Kalman filter (EKF) for binary and multicomponent systems has been developed and tested. The aim of the EKF was to provide reliable and real-time column composition profiles from few temperature measurements and easily available information. Accurate composition estimates and fast convergence were obtained, and the EKF has confirmed its ability to incorporate the effects of noise (from both measurement and modeling). The number of sensors and the observation frequency have shown to be important variables in the design of the EKF, especially for systems with fast dynamics.

Control strategies analysis for a batch distillation column with experimental testing

Abstract The dynamic nature and the non-linear behaviour of batch distillation equipment pose challenging control system design when products of constant purity are to be recovered. Several alternative column configurations and operating policies have been studied. However, issues related to the on-line operation of such process have not been properly addressed. The present work describes the investigation with experimental verification of computer based control strategies to batch distillation: a programmable adaptive controller (PAC), a self-tuning regulator (STR) and a non-linear model predictive control (MPC). The developed control systems made the conventional batch distillation column more efficient and easy to operate. Experiments performed on the pilot column confirm the simulation results.

Leak detection in pipelines through spectral analysis of pressure signals

The development and test of a technique for leak detection in pipelines is presented. The technique is based on the spectral analysis of pressure signals measured in pipeline sections where the formation of stationary waves is favoured, allowing leakage detection during the start/stop of pumps. Experimental tests were performed in a 1250 m long pipeline for various operational conditions of the pipeline (liquid flow rate and leakage configuration). Pressure transients were obtained by four transducers connected to a PC computer. The obtained results show that the spectral analysis of pressure transients, together with the knowledge of reflection points provide a simple and efficient way of identifying leaks during the start/stop of pumps in pipelines.

Digital filtering in the control of a batch distillation column

Abstract Measurement signals that a computer uses to take control actions are usually contaminated by noise. The presence of noise is undesirable because it may be detrimental to the operational control. In order to reduce the noise level in a batch distillation column control loop, two digital filters were experimentally tested: the double exponential filter and the moving average filter. The runs have shown how important the choice of the digital filter is to achieve a good control performance. For control tasks, this choice must be a compromise between data smoothing and the ability to respond rapidly to real changes in the process.

Monitoring Pipelines Through Acoustic Method.

Abstract Pipeline networks are complex systems of ducts used for liquid and gas transportation through long distances. They frequently cross highly populated regions, water supplies or natural reserves. Even small leaks in pipelines can lead to great losses of products and serious damages to the environment before it could be detected. With the purpose to track these leaks, a methodology is proposed for detection of leaks in pipelines based on acoustic method and on analysis of pressure transients generated by leak occurrence. Pressure transients and the sound noise generated by leakage are detected and analyzed in a pipeline operating with continuous flow of gas (air) under various operation conditions. The experimental results showed that it is possible to detect leaks in pipelines based on hydraulic transients and on acoustic methods. The acoustic method was decisive for leak detection; since the changes in pressure observed through the pressure transducer was not significant depending on the gas flow rate. The analysis of the signal amplitude for different frequencies shows that the leakage noise signal changes with both leak magnitude and pipeline pressure

Sensor locations and noise reduction in high-purity batch distillation control loops

The influence of the sensor locations on the composition control of high-purity batch distillation columns has been investigated. Using concepts of the nonlinear control theory, an input-output linearizing controller was implemented to keep the distillate composition constant at a desired value by varying the reflux ratio. An Extended Kalman Filter was developed to estimate the compositions required in the control algorithm using temperature measurements. In the presence of measurement noise, the control performance depended greatly on the sensor locations. Placing the sensors further from the top stages reduced the detrimental effects of noise but increased the inference error. To achieve accurate composition control, both noise reduction and composition estimate accuracy should be considered in the selection of the sensor locations.

A Self-Tuning Regulator and a Feedforward Controller Based on Mass Balance to Control a Pilot-Scale Batch Distillation Column

Abstract In the present work, two control strategies were tested on a pilot-scale batch distillation column operating with the nonideal binary system ethanol/water: a selftuning regulator with variable forgetting factor and a feedforward controller based on the mass balance between the top and bottom of the column. To keep the distillate purity constant, control actions were calculated using composition values, which were inferred from temperature measurements. Both controllers have shown good performance.

MONITORING FLEXIBLE GAS PIPELINE WITH A MICROPHONE AND ARTIFICIAL NEURAL NETWORKS

Pipeline networks are complex systems of ducts transporting gas and chemical products through long distances. With the purpose to track these leaks a technique, based on the analysis of sound noises ca ptured by a microphone and on pressure transients generate d by leak occurrence, was developed. Neural Artificial Networks were applied to determine leak magnitude and leak location. The experimental results showed that it is possible to detect leaks in pipelines. The dynamics of these noises in time were used as input to the neur al model to determine the location and magnitude of th e leaks.

Selecting the Sensor Locations for Inferential Control of High-Purity Batch Distillation Columns

Abstract The influence of the sensor locations on the composition control of high-purity batch distillation columns has been investigated. A GLC control law was implemented and an Extended Kalman Filter was developed to estimate the required compositions from temperature measurements. It was found that, depending on the sensor locations, the control actions can be very corrupted by noise. Placing the sensors away from the top stages reduced the detrimental effects of noise but increased the inference error. To achieve a tight composition control, both noise reduction and composition estimate accuracy should be considered in the selection of the sensor locations.