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 a laser diode, a 12 × 6 photodiode array sensor, and machine learning techniques, a new void fraction measurement method for gas-liquid two-phase flow in small channels is proposed. To overcome the influence of flow pattern on the void fraction measurement, the flow pattern of the two-phase flow is firstly identified by Fisher Discriminant Analysis (FDA). Then, according to the identification result, a relevant void fraction measurement model which is developed by Support Vector Machine (SVM) is selected to implement the void fraction measurement. A void fraction measurement system for the two-phase flow is developed and experiments are carried out in four different small channels. Four typical flow patterns (including bubble flow, slug flow, stratified flow and annular flow) are investigated. The experimental results show that the development of the measurement system is successful. The proposed void fraction measurement method is effective and the void fraction measurement accuracy is satisfactory. Compared with the conventional laser measurement systems using standard laser sources, the developed measurement system has the advantages of low cost and simple structure. Compared with the conventional void fraction measurement methods, the proposed method overcomes the influence of flow pattern on the void fraction measurement. This work also provides a good example of using low-cost laser diode as a competent replacement of the expensive standard laser source and hence implementing the parameter measurement of gas-liquid two-phase flow. The research results can be a useful reference for other researchers’ works.

Based on the transit-time ultrasonic gas flowrate measurement principle, a new model-based time-of-flight (TOF) measurement method is proposed. The proposed TOF measurement method includes two parts, the signal preprocessing and the model-fitting. Zero-phase filtering and independent component analysis with reference (ICA-R) are used to realize the signal preprocessing. The least-squares algorithm is used to implement the model-fitting and hence to obtain the TOF. A new singleacoustic-path ultrasonic gas flowmeter prototype with the inner diameter of 100 mm is developed and experiments are carried out to test the performance of the prototype. Experimental results show that the proposed signal preprocessing can effectively correct the distorted/noise-polluted measurement signal. In addition, the proposed model-based TOF measurement method is effective and can implement TOF measurement with higher repeatability and low standard deviation. For the gas flowrate ranges from 5 to 50 m ³ /h, the repeatability error of gas flowrate measurement is less than 1.99% and the maximum relative error of flowrate measurement is less than 3.27%. For the gas flowrate ranges from 50 to 500 m ³ /h, the repeatability error of gas flowrate measurement is less than 0.51% and the maximum relative error of flowrate measurement is less than 1.43%.

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.

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.