Oil film thickness is a significant index to evaluate oil spill pollution at sea surface. Laser induced fluorescence (LIF) is one of the most effective oil spill detection technologies at present. Nowadays, based on LIF detection technology, the effective evaluation of the thickness of thin oil film on the sea surface has been implemented. However, the studies on the evaluation for thick oil film on the sea surface are relatively few. Further the existing inversion algorithm for thick oil film is not applicable to the evaluation of oil film thickness under various detection angles except vertical sea surface. In view of this, a new evaluation algorithm for thick oil film based on fluorescence signal is put forward in this paper. The transport mechanism of photons in oil film medium is regarded as the basis. Simultaneously, the influence factors such as detection mode and detection angle are comprehensively taken into account in the LIF detection process. In this way, the function relationship between the fluorescence signal intensity of the oil film and its thickness is established. Afterwards, the algorithm is experimentally verified by selecting the mixture of crude oil and white oil as the experimental oil. The results show that the algorithm is suitable for evaluating the thickness for thick oil film in a certain thickness range ( that is, the fluorescence intensity of oil film is not saturated ). The effective evaluation of thick oil film on the sea at any detection angle under non-coaxial transmit-receive form and coaxial transmit-receive form can be realized by this algorithm.

Human health and ecological environment are badly affected due to oil pollution. A novel strategy for identifying oil pollutants has been proposed based on generic modular design. A total of three modules are included in the oil identification strategy and each module is consisted of a series of steps. The different steps of each module were experimented and evaluated by excitation-emission matrix fluorescence spectroscopy data set of oil. The experimental results show that the average accuracy with 13.6% was improved by using the histogram equalization than using thresholding in module 1. The average accuracy with 5% was improved by using the low-order Zernike moments than using high-order Zernike moments in module 2. The average accuracy with 28.9% was improved by using angle similarity measure in the nearest-neighbor classifier compared to the other six in module 3. The optimal accuracy with 95% was obtained by combining the margin features of excitation-emission matrix fluorescence spectroscopy extracted by low-order Zernike moments with the nearest-neighbor classifier applied to angle similarity measure. The combination also has a good specificity and sensitivity. The results provide references for identifying oil pollutants.

Oil-water two-phase flow is widespread in petroleum industry processes. The study of oil-water two-phase flow in horizontal pipes and the liquid holdup measurement of oil-water two-phase flow are of great importance for the optimization of the oil production process. This paper presents a novel sensor, i.e., a mini-conductance probe (MCP) for measuring pure-water phase conductivity of oil-water segregated flow in horizontal pipes. The MCP solves the difficult problem of obtaining the pure-water correction for water holdup measurements by using a ring-shaped conductivity water-cut meter (RSCWCM). Firstly, using the finite element method (FEM), the spatial sensitivity field of the MCP is investigated and the optimized MCP geometry structure is determined in terms of the characteristic parameters. Then, the responses of the MCP for the oil-water segregated flow are calculated, and it is found that the MCP has better stability and sensitivity to the variation of water-layer thickness in the condition of high water holdup and low flow velocity. Finally, the static experiments for the oil-water segregated flow were carried out and a novel calibration method for pure-water phase conductivity measurements was presented. The validity of the pure-water phase conductivity measurement with segregated flow in horizontal pipes was verified by experimental results.

This paper presents ceiling light landmarks based localization and motion control for a mobile robot. The novel mechanism design for the mobile robot is introduced, and the method of localization using ceiling light is proposed. Navigation map, network matrix and the method to find shortest path are described. From the path planning, the control scheme of autonomous navigation for the mobile robot can be generated automatically. Navigational experiments indicate the effectiveness of the method presented in the paper.

In order to further improve the accuracy and speed of the present commonly used NURBS surface method, an improved method for NURBS surface based on particle swarm optimization BP neural network is proposed. Firstly, node vectors of the data points are calculated by using the parametrization method of accumulating chord length. Then, prediction model of node vectors is constructed by using the particle swarm optimization BP neural network, and the experiment is presented to justify the feasibility and veracity of constructed prediction model. Finally, using the predicted node vectors, a fast and high-precision NURBS surface is realized. The results showed that the root mean squared error of fitting result of surface was deduced 84.05% and the run time was deduced 92.42% compared with the traditional NURBS method. Therefore, the proposed method is a fast and high-precise NURBS surface fitting method.

In the process of production logging interpretation, a water cut is one of the key factors to obtain the oil phase content in the oil well. In order to measure the water cut of the horizontal oil–water two-phase flow with low yield, the response characteristics of the combined capacitance sensor (CCS) are investigated under different flow patterns. Firstly, the measuring principles of coaxial, cylindrical, and CCS are introduced in detail. Then, according to the different flow pattern conditions of the horizontal oil–water two-phase flow, the response characteristics of the CCS are simulated and analyzed using the finite element method. Additionally, compared with the other two sensors, the advantages of the CCS are verified. Finally, the temperature and pressure calibration experiments are carried out on the CCS. The horizontal oil–water two-phase flow patterns in a low yield liquid level are divided in detail with a high-speed camera. Dynamic experiments are carried out in a horizontal pipe with an inner diameter of 125 mm on the horizontal oil–water two-phase flow experimental equipment. The simulation and experimental results show that the CCS has good response characteristics under different working conditions.