An improved Near-Field Computer Vision (NFCV) system for intelligent fire robot was proposed that was based on our previous works in this paper, whose aims are to realize falling position prediction of jet trajectory in fire extinguishing. Firstly, previous studies respecting the NFCV system were briefly reviewed and several issues during application testing were analyzed and summarized. The improved work mainly focuses on the segmentation and discrimination of jet trajectory adapted to complex lighting environment and interference scenes. It mainly includes parameters adjustment on the variance threshold and background update rate of the mixed Gaussian background method, jet trajectory discrimination based on length and area proportion parameters, parameterization, and feature extraction of jet trajectory based on superimposed radial centroid method. When compared with previous works, the proposed method reduces the average error of prediction results from 1.36 m to 0.1 m, and the error variance from 1.58 m to 0.13 m. The experimental results suggest that every part plays an important role in improving the functionality and reliability of the NFCV system, especially the background subtraction and radial centroid methods. In general, the improved NFCV system for jet trajectory falling position prediction has great potential for intelligent fire extinguishing by fire-fighting robots.

A novel method of near-field computer vision (NFCV) was developed to monitor the jet trajectory during the jetting process, which was used to precisely predict the falling point position of the jet trajectory. By means of a high-resolution webcam, the NFCV sensor device collected near-field images of the jet trajectory. Preprocessing of collected images was carried out, which included squint image correction, noise elimination, and jet trajectory extraction. The features of the jet trajectory in the processed image were extracted, including: start-point slope (SPS), end-point slope (EPS), and overall trajectory slope (OTS) based on the proposed mean position method. A multiple regression jet trajectory range prediction model was established based on these trajectory characteristics and the reliability of the model was verified. The results show that the accuracy of the prediction model is not less than 94% and the processing time is less than 0.88 s, which satisfy the requirements of real-time online jet trajectory monitoring.

During the multi-channel confluent water supply process, the pressure control of the main pipe is often held back by such problems as non-linearity, hysteresis and parameter uncertainty, its own unique load dynamic changes, channel switching disturbance and other system characteristics caused by the actual working conditions. Moreover, pressure fluctuations in the main pipe will lead to a reduction in the service life of fire-fighting equipment, an increase in the failure rate, and even an interruption of the fire-fighting water supply. Therefore, a master and auxiliary control strategy is proposed to stabilize the pressure change in the process of multi-channel concentrated water supply switching, by using variable universe fuzzy proportional integral derivative (PID) control as the main controller on the main pipe and traditional PID control as the subsidiary controller on the channel. The control strategy is verified by the co-simulation platforms of LabVIEW and AMESim. Simulation results show that the variable universe fuzzy PID control and the master and auxiliary compound control based on the variable universe fuzzy PID control have advantages in step response, tracking response and anti-interference, respectively. The parameters obtained in the co-simulation are used in the experimental system. The experimental results show that the maximum deviation rate of main pipe pressure can be reduced by about 10% compared with other control methods under different loads. In conclusion, the proposed control strategy has strong anti-interference ability, fast dynamic response speed, high stability and good peak shaving effect.

Accurate image tracking of fire extinguishing jets is crucial to achieving automatic firefighting. However, inevitable noise interference occurs during image processing, adversely affecting precise tracking. In order to address this issue, a method for tracking the jet drop point (JDP) of fire extinguishing jet is proposed based on an improved Efficient Neural Network (ENet) and robust adaptive Cubature Kalman Filter. A novel JDP image state transition model is established to construct the state space equations and depict the motion state of the JDP in images. A two-stage method for recognizing JDP is proposed, which includes an improved ENet and a directional progressive curve search method to enhance the accuracy of observation. A Cubature Kalman filter based on the huber function is proposed to improve the adaptability and robustness of the image tracking method, which takes into account the advantages of L1 and L2 norms. The updated formulas for the state and covariance matrices are derived. Furthermore, the tracking method is improved by the Sage-Husa method, which considers the unknown distribution of noise. Experiments on actual firefighting platforms demonstrate that the proposed method exhibits robustness and adaptability compared to traditional CKF.

Transportation efficiency is a problem of particular interest in multi-channel confluent water supply engineering. Transportation efficiency depends not only on the system control strategy but also on the pressure loss (pressure difference between the inlet and outlet) and pressure drop (amplitude of outlet pressure fluctuations) of its structure. In this article, sensitivity analyses of the pressure loss and pressure drop to changes in multi-channel confluent water supply geometry are presented. An experimental set-up was established to validate computational fluid dynamic (CFD) predictions and obtain the boundary conditions for two-channel synchronous switching. The influences of the geometric structure varies by the clustered pipe diameter (40 mm < Dc < 80 mm), main pipe diameter (30 mm < Do < 80 mm), channel pitch (60 mm < L < 400 mm) and number of channels (2 ≤ n ≤ 4); those variables were investigated with the help of CFD simulations. The results showed that configuration “C” can be considered a costless method of decreasing pressure loss (β_C(2.05) < β_A(2.42) < β_B(2.64)) and that the different configurations are insensitive to pressure drop. The variations of the influence of channel pitch and clustered pipe diameter on pressure loss have extremes at L/d = 5 and Dc/d = 2.5, respectively, but the effect on pressure drop is not obvious. The main pipe diameter and the inlet velocity have more significant influences on efficiency. The results can be used to choose the proper geometry of multi-channel confluent water supply to enable energy savings.