The accurate measurement of displacement and load in the oil well dynamometer diagram is the need to achieve energy saving, efficiency and stable production. Wherein, the displacement signal is calculated from the acceleration signal in the dynamometer. Theoretically, the acceleration signal can be integrated by two time-domain integrations to obtain the displacement signal. However, the noise and direct-current(DC)components in the time-domain signal would produce a drift-type principle error after two integrals. In order to solve this problem, this paper has proposed a frequency domain integral-based displacement solution method. Meanwhile, this paper has expounded the principle of frequency domain integration and analyzed the possible sources of error of the obtained results. An evaluation model was proposed experimentally verified. Test results indicated this method can be used to improve the accuracy of displacement measurement. This research has important implications for improving the economic benefits of the oil field.
In view of the low efficiency and slow speed caused by the manual inspection of the wheel speed sensor ring gear in the automotive parts industry, this paper proposes a method for detecting the surface defects of the ring gear of the wheel speed sensor based on the neural network. The method is based on the single hidden layer BP neural network model, and the LM algorithm is used to train the network to achieve stability, the defect types are identified by combining the image feature parameters of various gear ring surface defects. The surface defects detection results of the wheel speed sensor ring gear show that the defects classification accuracy of this method is more than 94%, and the detection time of each ring gear is less than 4s. The detection result is better than the manual visual method.
The traditional temperature measurement system used the ratio of stokes light and anti-stokes light to demodulate the temperature, and there was an error when the ratio used directly. The propagation speed of stokes light and anti-stokes light in the same fiber was different because of dispersion effect. The two kinds of reflected light were obtained by photoelectric converter at different time when the scattering occurred at the same place. Therefore, there was a time warping between the two signals after data acquisition. This phenomenon would lead to measurement error in the process of demodulating temperature. A new method of error correction for the distributed temperature measurement system was used to eliminate the signal dislocation by correcting the stokes signal. In the absence of correction, the antistokes signal peak and the stokes signal peak occurred in different place, which leaded to errors in the process of demodulating temperature. This correcting method was used. The demodulation error was reduced from 2.3 °C to 1.2 °C. The shortest time was 4.96s when detected temperature rise rate was not less than 5 °C/min in the case of 10km fiber carried by this system. It was showed that this technique could improve the performance of the traditional distributed fiber Raman temperature measurement system, and it would have a good aspect.
In order to monitor the early fire situation caused by coal spontaneous combustion or cable aging, cable heated, cable overcurrent and other reasons, a dual channel and fast response temperature detection system is designed based on the Raman scattering principle in which anti-stokes signal in back Raman scattering is sensitive to temperature. The performance of the temperature detection system is obtained through experiments. The experimental data shows that the maximum error of temperature measurement is 0.7°C, the stability is 1°C in 30 minutes when both channels carry 2.5km sensing fiber, single channel response time is less than 17s and position-calculated error is less than 2m. This system would have a good application prospect in distributed fire detection and early warning under mine.
In distributed optical fiber sensing system of BOTDR, the frequency of the backward Brillouin scattering signal is modulated by temperature and strain, so the frequency of the signal can be attained with optical fiber to realize the temperature and strain measurement in remote. While, the scattering signal is very weak, the noise is large, and have a frequency width of several decades megahertz. In tradition, the complete high-frequency Brillouin scattering signal is obtained by adopting the method of frequency scanning which capture the frequency in section through changing the rate of sweep frequency module. And then, using multiple averaging measurement to reduce noise. But it is difficult to acquire the signal rapidly and eliminate the interference of noise. Therefore, an edge filter approach is proposed in this paper to get the whole scattering signal, which convert the frequency information into energy message. In order to better represent the effectiveness of this method, an experiment were taken. And the result shows that: SNR had been greatly enhanced, sampling time was reduced to the cost of getting one frequency point when using frequency scanning. It demonstrate that the proposed method can collect the signal quickly and be beneficial to demodulate temperature and pressure in time.
Temperature and strain measurement accuracy of Brillouin distributed optical fiber sensor are easily influenced by the performance of laser light source. A wavelength/power DFB semiconductor laser light source with high-stability used for Brillouin Fiber Sensing is designed. The laser light source works with constant-current drive circuit and temperature control circuit, which precisely controls drive current and operating temperature of the DFB semiconductor laser and makes the wavelength and optical power under control. The results show that: (1) the optical wavelength increases about 0.1nm and the power reduces about 0.05dBm when the temperature increased by 1°C . (2) The maximum drift of wavelength is 0.012nm and the maximum drift of optical power is 0.05dBm (0.0014mW) at 25 °C within one hour. The laser light source can completely meet the demand for Brillouin distributed optical fiber sensing.
Bearing capacity is a most significant parameter to evaluate the quality of aerostatic restrictor system. A gas-impedance model was established using the theory of gas dynamics to determine the bearing capacity of three aerostatic restrictor systems which were multi-micro channel, dual U-shaped and dual circle-shaped aerostatic restrictor system respectively. Experiments were run using gas-impedance method and finite difference method to prove the validity of gas-impedance method. Experimental results indicated the gas-impedance model method was effective in establishing the bearing capacity of aerostatic restrictor system.
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