In this study, a novel strategy for accelerating the production of pumpable ice slurry (PIS) by using ozone micro–nano bubbles (O₃-MNBs) was proposed. The effect of PIS containing sodium alginate (SA) and O₃-MNBs on the preservation of small yellow croaker (Larimichthys polyactis) was investigated. The results indicate that using SA solution containing O₃-MNBs instead of only SA solution resulted in quicker production of PIS by promoting ice nucleation and eliminating supercooling. The distribution and positive effect of O₃-MNBs as a nucleation agent on freezing characteristics were discussed. Microbial concentrations, pH, total volatile basic nitrogen, and thiobarbituric acid reactive substance content were also examined. Storage in novel PIS (containing O₃-MNBs) had higher performance than storage in flake ice or conventional PIS due to the strong bacteriostatic ability of O₃. Therefore, O₃-MNBs injection can be used as a novel method for PIS production and the preservation of fresh marine products.

The hydraulic and acoustic performance of centrifugal pump is closely related to hydraulic structure parameters, and they are contradictory. In order to solve this contradiction, this paper introduces the pit bionic structure, and proposes an optimization method based on multi-objective test design and response surface to improve the hydraulic and acoustic performance. Taking the bionic vane pit diameter, axial spacing and radial spacing as design variables. Taking the maximum hydraulic efficiency and total sound pressure level reduction of centrifugal pump as the corresponding objectives. The multiple regression response surface model was constructed to determine the optimal parameter combination of hydraulic performance and noise collaborative optimization. The optimization results were verified by numerical simulation and experimental test. The results show that the response surface multi-objective optimization method has high prediction accuracy, has obvious synergistic effect on the hydraulic and acoustic performance. The highest point of the efficiency curve after optimization is shifted to the direction of large flow, which widens the high efficiency working area of centrifugal pump. Under the rated condition, the hydraulic efficiency is increased by 3.03%, the efficiency increase rate is 4.21%, the total sound pressure level is reduced by 4.96 dB, and the noise reduction rate is 3.01%.

The marine vertical centrifugal pump is an important piece of auxiliary equipment for ships. Due to the complex operating conditions of marine equipment and the frequent swaying of the hull, typical pump failures such as rotor misalignment, rotor unbalance and mechanical loosening occur frequently, which seriously affect the service life of the marine vertical centrifugal pump. Based on multi-domain characteristic parameters, a fault identification method combining weighted kernel principal component analysis (WKPCA) and particle swarm optimization support vector machine (PSO-SVM) is proposed in this paper. It can effectively solve the problem of multi-fault classification of the centrifugal pump and provide reference for efficient maintenance of equipment. Firstly, a vertical centrifugal pump test bench is set up to simulate typical faults. The collected original fault data are denoised by Kalman filtering. Then, a multi-domain feature set composed of 20 feature parameters was constructed. However, due to high dimension, data redundancy and calculation time were increased. After dimensionality reduction, a fault feature set with 9 feature indexes was established by combining with the WKPCA method. Finally, the PSO-SVM model is used to realize multi-fault identification, and the recognition results of the traditional support vector machine and the genetic algorithm support vector machine (GA-SVM) are compared to verify the diagnosis results and classification performance of PSO-SVM. The results show that the accuracy of WKPCA and PSO-SVM fault recognition methods based on multi-domain characteristic parameters is 1, and it has good convergence.

The mixed transport pump is the core equipment of hydraulic lifting deep-sea mining system. The conveying medium is a solid-liquid two-phase flow. The impeller is prone to mass eccentricity due to the wear of ore particles. Therefore, it is great significance to study the unbalanced response characteristics of the impeller of the mixed transport pump. The unbalanced test of the impeller of the pump was carried out in a closed-cycle test bench. The unbalanced response characteristics were proved by data analysis method. The results indicated the hydraulic performance of the pump with the rotor system balance quality grade in G2.5 (scheme 2) was better than that of the balance quality grade in G6.3 (scheme 1). The pump efficiency was increased by 3.12%. When the medium was a solid-liquid two-phase flow, the amplitude of the vibration acceleration level ( L_a) of the pump outlet flange in scheme 2 was generally lower in the low frequency range than that in scheme 1. The periodic variation law of the pump outlet pressure coefficient ( C_p) was obvious. With the increase in the volume fraction of ore particle, the amplitude of the main frequency of the L_a in scheme 1 gradually was increased, which were 91.16, 97.11, and 102.57 dB, respectively. The main frequency amplitude of scheme 2 was basically unchanged. The main frequency amplitude change rates of the two schemes were −1.72%, −7.58%, and −12.78%, respectively. With the increase in the running time, the periodic change trend of the time-domain signal of the pump outlet flange vibration acceleration in scheme 1 was more obvious than that in scheme 2. The axial passing frequency amplitude was gradually increased. The pump efficiency was gradually decreased. Finally, the sliding bearing B₂ was severely worn and the service life was greatly reduced.

As the core power equipment of the deep-sea mining system, the deep-sea mineral lifting pump continuously operates under harsh service conditions coupled with high hydrostatic pressure, complex marine environments, and solid particle media. Its operating state shows obvious strong nonlinearity, time-varying fluctuation, and local abrupt change features. Therefore, time series health state prediction of the deep-sea mineral lifting pump is of vital engineering significance for realizing predictive maintenance and ensuring the safety of offshore trials and mining operations. Taking the 500 m-level offshore sea trial conducted in the Xisha area of the South China Sea as the engineering background, four critical health characteristic parameters, including shaft power, pump efficiency, motor winding temperature, and outlet radial vibration, are selected to construct a hybrid CNN-LSTM time series prediction model. Comprehensive model evaluation metrics and ablation comparison experiments are adopted to analyze the multi-step-ahead prediction performance of the proposed model. The results show that the CNN-LSTM model achieves optimal comprehensive evaluation indices in one-step prediction and possesses excellent tracking capability for inflection points and amplitude fluctuations of time series data. Although the prediction accuracy decreases gradually with the increase in prediction steps, the model can still effectively characterize the evolutionary trend of pump operating states, and its overall prediction performance is significantly superior to that of single models. This study provides model support and technical reference for the health evaluation, early fault alarm, and maintenance optimization of deep-sea mineral lifting pumps in offshore trials.