This work proposes a new positioning method based on multiple ultrasonic sensors for the autonomous mobile robot. Unlike the conventional ultrasonic positioning methods, this new method can realize higher accuracy ultrasonic positioning without additional temperature information. Three ultrasonic sensors are used for positioning. A generalized measurement model is established for general sensor configuration. A simplified measurement model, which considers the computational complexity, is also established for linear/simplified sensor configuration. Three time-of-flight signals are obtained from the three ultrasonic sensors. The coordinates of the target are calculated by the ratios of time-of-flights. Positioning experiments were carried out to verify the feasibility and effectiveness of the proposed method. Experimental results show that the new ultrasonic positioning method is effective, both the two established models can implement positioning successfully, and the positioning accuracy is satisfactory. Compared with the conventional ultrasonic positioning method with the default ultrasonic velocity, the positioning accuracy is greatly improved by the proposed method. Compared with the ultrasonic positioning method with additional temperature compensation, the results obtained by the proposed method are comparable.

Based on linear back projection (LBP) algorithm, density-based spatial clustering of applications with noise (DBSCAN) algorithm and image fusion technique, a new image reconstruction method of capacitively coupled electrical impedance tomography (CCEIT) is proposed in this work. LBP is used to obtain the original image of the real part and the original image of the imaginary part. The gray level thresholds of the two original images are determined by DBSCAN clustering algorithm and the initial image of the real part and the initial image of the imaginary part are obtained by gray level threshold filtering, respectively. Finally, the two initial images are fused and the final image is obtained. Image reconstruction experiments are carried out with a 12-electrode CCEIT system prototype. The experimental results verify the effectiveness of the proposed image reconstruction method. Experimental results show that the quality of the final image is satisfactory. Compared with the conventional electrical tomography (ET) image reconstruction methods, the new proposed image reconstruction method needs less prior knowledge or manual intervention and realizes more effective usage of the impedance information. The research results also indicate that the DBSCAN clustering algorithm is an effective way to determine the gray level thresholds of the original images and the mean square error (MSE) is a reasonable criterion for image fusion. Meanwhile, LBP + DBSCAN is an effective algorithm for image reconstruction and image fusion technique is an effective way to utilize the whole impedance information of the conductive gas–liquid two-phase flow.

This article focuses on the improvement of density peaks clustering (DPC, also known as clustering by fast search and find of density peaks) by the introduction of the grid clustering. A grid division is used to divide the data space into grid cells. The global characteristic of grid cell replaces the characteristic of the data points. The local density of DPC is replaced by the density of the grid cell. The cut-off distance of DPC is no longer needed. Then, the cluster centers are determined adaptively based on the quantities. Finally, a two-stage allocation strategy (neighborhood searching and border grid cell assigning) is introduced to obtain the final clustering results. Six datasets are used to experimentally verify the effectiveness and performance of the proposed algorithm. Experimental results show that the improvement of DPC is successful. Compared with DPC, the proposed algorithm is more efficient with less manual intervention.

Oil-air two-phase flow measurement was investigated with a Venturi and void fraction meters in this work. This paper proposes a new flow rate measurement correlation in which the effect of the velocity ratio between gas and liquid was considered. With the pressure drop across the Venturi and the void fraction that was measured by electrical capacitance tomography apparatus, both mixture flow rate and oil flow rate could be obtained by the correlation. Experiments included bubble- slug-, wave and annular flow with the void fraction ranging from 15% to 83%, the oil flow rate ranging from 0.97 kg/s to 1.78 kg/s, the gas flow rate ranging up to 0.018 kg/s and quality ranging nearly up to 2.0%. The root-mean-square errors of mixture mass flow rate and that of oil mass flow rate were less than 5%. Furthermore, coefficients of the correlation were modified based on flow regimes, with the results showing reduced root-mean-square errors.

Combining the transmission “Z” mode and the reflection “V” mode, a new hybrid dual-path ultrasonic sensor is designed to make full use of the advantages of the two modes. With the hybrid sensor and a new model-based time-of-flight (TOF) measurement method, a new model-based hybrid ultrasonic gas flowmeter is developed. The model-based TOF measurement method, which includes a signal filtering part and a model fitting part, is proposed to implement accurate TOF measurement. The signal filtering is implemented by a Butterworth bandpass filter and the model fitting is implemented by a hybrid Gauss–Newton structured BFGS method. A new hybrid ultrasonic flowmeter prototype with the inner diameter of 100 mm was developed and dynamic experiments were carried out. Experimental results show that the development of the hybrid ultrasonic flowmeter is successful. With the flowmeter prototype, the maximum relative error and the repeatability error of gas flowrate measurement are 1.80% and 0.45%, respectively, for a common flowrate ranges from 30 to 500 m ³ /h.

The aim of this work is to study the image reconstruction of capacitively coupled electrical impedance tomography (CCEIT) by using total impedance of a gas–liquid two-phase flow. The results of image reconstruction that utilise the real part, the imaginary part, the amplitude of the impedance, and the image reconstruction results by making use of different parts of the total impedance are investigated and discussed. By combining a linear back projection (LBP) algorithm and a K-means clustering algorithm, a new image reconstruction algorithm for CCEIT is proposed. The LBP is used to obtain the original reconstructed image. The K-means is adopted to automatically obtain the gray level threshold. The final reconstructed image is acquired with an established gray level threshold filter. With the new algorithm (LBP + K-means), the images reconstructed by using different parts of the impedance are obtained. To make full use of total impedance information, an image fusion method based on the weighted combination method is presented. With a developed 12-electrode CCEIT prototype, the image reconstruction experiments are conducted. Experimental results show that all three parts of the impedance can reflect the phase distribution characteristics of the gas–liquid two-phase flow from different aspects. Image fusion results indicate that making full use of the different parts of the total impedance of the gas–liquid two-phase flow can effectively improve the quality of the image reconstruction. The experimental results also verify the feasibility and the effectiveness of the proposed new image reconstruction algorithm. Compared with conventional algorithms, the proposed image reconstruction method can obtain comparable/better image reconstruction results with less prior knowledge. The influence of manual intervention on the image reconstruction results can be effectively avoided.