Improvement of Ultrasonic Pulse Generator for Automatic Pipeline Inspection

Abstract

This paper presents the improvement of an ultrasonic pulse generator for a pipeline inspection gauge (PIG), which uses 64 transducers for inspecting distances up to 100 km with an axial resolution fixed at 3 mm and variable speeds between 0 and 2 m/s. An ultrasonic pulse generator is composed of a high-voltage (HV) MOSFETs, driver logic and an HV power supply. We used a DC-HV DC converter device as the HV power supply because it reduces the size of the ultrasound system considerably. However, pipeline geometry and inspection effects such as hammer and shock cause a variable pulse repetition frequency (PRF), producing voltage drops, poor quality of the HV pulse generated, failures in the dimensioning of defects and damage to devices by over-voltage. Our improvement is to implement a control scheme to maintain the high quality of the HV regardless of the variable PRF. To achieve this, we characterized three transfer functions of the DC-HV DC converter, varying the connected load to 10%, 45% and 80%. For the characterization, we used the least squares technique, considering an autoregressive exogenous (ARX) model. Later, we compared three control schemes: (1) proportional-integral-derivative (PID) tuned by simultaneous optimization of several responses (SOSR), (2) PID tuned by a neural network (NN) and (3) PI tuned by the analytical design method (ADM). The metrics used to compare the control schemes were the recovery time, the maximum over-voltage and the excess energy when the shock and hammer effects happen to occur. Finally, to verify the improvement of the HV pulser, we compared the ultrasonic pulses generated for various frequencies and amplitudes using the pulse generator with and without the control scheme.

Design and Validation of an Articulated Sensor Carrier to Improve the Automatic Pipeline Inspection

“…This type of solution is already used for the transducer excitation voltage, where a voltage is fixed to reduce the error in the defect size estimation. For our system, we use a fixed value of 100 V for the excitation voltage [40], and, at the signal processing level, we propose to improve the online reduction technique, changing the function of the FIR filters. The improvement consists of improving the tuning of the bandpass and lowpass filters so that they not only filter but also amplify, with a gain G1 for the bandpass filter and a gain G2 for the lowpass filter.…”

“…We use a specialized technique for online signal reduction [38], where the signals are stored in an ad hoc data storage system [39]. For the transducer excitation, we improved the ultrasonic pulse generator to maintain a fixed excitation voltage despite the chattering and the hammer effect [40]. However, all these improvements in the system are useless if it is not possible to ensure that the ultrasound signals capture.…”

Corrosion Sensors for Structural Health Monitoring of Oil and Natural Gas Infrastructure: A Review

“…The waves are bounced back by the external surface, inner surface, and geometric irregularities, which are received by the transducer. The tool measures the time interval between the arrivals of reflected echoes from inner and outer surfaces to calculate the wall thickness [36,37,38]. As shown in Figure 5 [39], the wall thickness information combined with the stand-off signal can differentiate the internal and external mass loss/flaw along the pipe.…”

High-Sensitivity Real-Time Tracking System for High-Speed Pipeline Inspection Gauge

“…In China, it was reported that there was a pipeline failure every 4 km [9], and in the USA, the economic and human losses due to the significant pipeline incidents in the past 20-year period are $7 billion and 330 fatalities along with 1292 injuries, respectively [10]. Pipeline inspection gauges (PIGs) are periodically used for pipeline in-line inspections (ILIs) to minimize these risks and maintain pipeline integrity [11,12,13,14,15,16]. However, during the pipeline ILI operation, the PIG is likely to be blocked by the deformed pipelines, while an odometer installed in the PIG can only record the PIG position offline, because the shielding effect of the steel pipe wall makes it difficult to transmit the position information from inside the pipeline to the ground through wireless communication technologies, such as Wi-Fi, Bluetooth, or 3G and 4G networks [17,18].…”