Destruction monitoring of oil and gas pipelines

The routine damage of pipelines such as leakage, pipe wall corrosion, damage of anti-corrosion layer, etc. is mainly based on pipe shape, electrical properties, acoustic properties, fluid state, fluid properties, leakage sensitive lines along with pipes, etc. However, recently, China’s oil and gas pipeline network has been seriously suffered. Drilling damage for the purpose of theft. First of all, this

The routine damage of pipelines such as leakage, pipe wall corrosion, damage of anti-corrosion layer, etc. is mainly based on pipe shape, electrical properties, acoustic properties, fluid state, fluid properties, leakage sensitive lines along with pipes, etc. However, recently, China’s oil and gas pipeline network has been seriously suffered. Drilling damage for the purpose of theft.

First of all, this kind of damage is concealed. If the process of stealing oil and gas is slow, no obvious negative pressure waves or sound waves will form in the fluid; even if a negative pressure wave appears and is detected, the patrol arrives at the accident site (possibly long). 10 km) It is also too late. Therefore, it is a relatively basic measure to monitor the stage of perforation damage before the theft. In view of the power supply of the monitoring equipment and its own anti-theft problem, all equipment must be installed. To this end of the pumping station, we, here, the high and low frequency noise has been removed, purely reflecting the destructive vibration. a2C2 suddenly and largely decays rapidly, which is caused by sharp impact. b2d2 is slowly and slowly decaying. The slamming from the pipe wall is the characteristic of two destructive vibration sources. Through continuous monitoring, it can more accurately identify the damage process if it has bd2 characteristics. Frequent waveforms appear, indicating that the pipeline is likely to be attacked; if the waveform of the a2C2 feature appears later, the identification and denoising of the 3.2 source direction can be broken. Some noise and signal are in the same time-frequency domain, but as long as the signal Source (destructive vibration source) noise sources (other sources) are located on different sides of the sensor and can still be identified and denoised. The sensor SiS2S3S4 is arranged in groups. The purpose is to obtain the spatial information of the vibration source. Take S3S4 as an example. The waveform of the same vibration source is aibi, and the other experiment is cidi. See the difference between ai and bici and di in the time domain. Not obvious; after the 3rd order wavelet decomposition, they are distributed in the 3rd order approximation band, as shown in the aata cb in the figure, but it can be found that the wavefront of a2 lags behind b2, and the wavefront of c lags behind d2, which indicates that The two columns of vibration waves first reach the sensor S4 and then reach S3, so the vibration source is located on the right side of S3, which is the vibration noise in the right pumping station. This method uses two sensors to identify the vibration source orientation, thereby distinguishing between signals and noise. Eliminate in-station process switching, switching valves, and pump running noise. It is effective for pairing of 3.3 waveforms. For two consecutive signals measured by S and S3, the waveforms to be matched must be paired to find the corresponding waveforms of the same vibration. In order to obtain the time difference, two columns of vibration waves are transmitted along the pipeline, the amplitude attenuation is different and the possible dispersion effects are also inconsistent, which makes it difficult to pair the waveforms from the amplitude or the single frequency distribution. The pipeline failure process is not completed in an instant, and similar vibrations are repeated many times. Based on this, the waveform matching method used in this experiment is to separately decompose the two columns of signals, and then obtain the delay from the time-frequency domain distribution map. Attenuation ratio, frequency change condition, and then integrated pairing, improve accuracy and reliability. 4 The junction vibration wave propagates in the metal tube wall with a certain speed and small attenuation. The destructive vibration originates from the same excitation tool. It has similar time-distribution characteristics and will be repeated many times. Based on this, this paper discusses the problems of wavelet transform denoising vibration source identification and vibration source localization and experiments. (Go down to page 377) value.

Take A., B), Tx., Ty., C0 as the initial value, and use the least squares method to solve the problem, and then calculate the initial value, and then solve it by least squares method until IsI, Il, ISrxI, lSry|, lSI Both are smaller than the selected minimum value. 3 The actual measurement results are reconstructed based on the hardware of PG-15 flatness interferometer produced by Shanghai Opto-mechanical Co., Ltd., and the digital flatness interferometer is developed as the interferogram collected in it. And remove the boundary as an extrapolation result. The algorithm program flow chart, such as 4-external extrapolation, is an important step in the processing of interferogram by FFT. The result of extrapolation has a great influence on the processing result. This paper starts from the whole graph and uses the least squares method to iterate. The number of the entire face

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