In this study, X-ray diffraction, thermogravimetric analysis and differential scanning calorimetry (DSC) method were used to analyze the main characteristics of sweet potato starch, and to analyze the thermal degradation process of sweet potato starch. Specifically, X-ray diffraction to study its structure, thermogravimetric analysis to study the thermal degradation kinetics, and differential scanning calorimetry to study the thermogram of sweet potato starch. The thermal decomposition kinetics of sweet potato starch was examined within different heating rates in nitrogen atmosphere. Different models of kinetic analysis were used to calculate the activation energies using thermogravimetric data of the thermal degradation process. Activation energies obtained from Kissinger, Flynn-Wall- Ozawa, and Šatava-Šesták models were 173.85, 174.87 and 174.34 kJ/mol, respectively. The values of activation energy indicated that the thermal degradation of the sweet potato starch was a single reaction mechanism or the combination of multi-reaction mechanisms. The differential scanning calorimetry analysis show that two decomposition stages were presented: the first at a low temperature involves the decomposition of long chain; and the second at a high temperature represents the scission of glucose ring. This information was helpful to design the processing process of many natural polymers. Thermogravimetric Fourier transform-infrared (TG–FTIR) analysis showed that the main pyrolysis products included water, methane, carbon dioxide, ammonia, and others.
In the extra-thick coal seams and multi-layered hard roofs, the longwall hydraulic support yielding, coal face spalling, strong deformations of goaf-side entry, and severe ground pressure dynamic events typically occur at the longwall top coal caving longwall faces. Based on the Key strata theory an overburden caving model is proposed here to predict the multilayered hard strata behaviour. The proposed model together with the measured stress changes in coal seam and underground observations in Tongxin coal mine provides a new idea to analyse stress changes in coal and help to minimise rock bursts in the multi-layered hard rock ground. Using the proposed primary Key and the sub-Key strata units the model predicts the formation and instability of the overlying strata that leads to abrupt dynamic changes to the surrounding rock stress. The data obtained from the vertical stress monitoring in the 38 m wide coal pillar located adjacent to the longwall face indicates that the Key strata layers have a significant influence on ground behaviour. Sudden dynamically driven unloading of strata was caused by the first caving of the sub-Key strata while reloading of the vertical stress occurred when the goaf overhang of the sub-Key strata failed. Based on this findings several measures were recommended to minimise the undesirable dynamic occurrences including pre-split of the hard Key strata by blasting and using the energy consumption yielding reinforcement to support the damage prone gate road areas. Use of the numerical modelling simulations was suggested to improve the key theory accuracy.
The underground complicated testing environment and the fan operation instability cause large random errors and outliers of the wind speed signals. The outliers and large random errors result in distortion of mine wind speed monitoring, which possesses safety hazards in mine ventilation system. Application of Kalman filter in velocity monitoring can improve the accuracy of velocity measurement and eliminate the outliers. Adaptive Kalman Filter was built by automatically adjusting process noise covariance and measurement noise covariance depending on the differences between measured and expected speed signals. We analyzed the fluctuation of airflow flow using data of wind speed flow and distribution characteristics of the tunnel obtained by the Laser Doppler Velocimetry system (LDV) studies. A state-space model was built based on the tunnel airflow fluctuations and wind speed signal distribution. The adaptive Kalman Filter was calculated according to the actual measurement data and the Expectation Maximization (EM) algorithm. The adaptive Kalman filter was used to shield fluid pulsation while preserving system-induced fluctuations. Using the Kalman filter to treat offline wind speed signal acquired by LDV, the reliability of Kalman filter wind speed state model and the characteristics of adaptive Kalman Filter were investigated. Results showed that the adaptive Kalman filter effectively eliminated the outliers and reduced the root-mean-squares error (RMSE), and the adaptive Kalman filter had better performance than the traditional Kalman filter in eliminating outliers and reducing RMSE. Field experiments in online wind speed monitoring were conducted using the optimized adaptive Kalman Filter. Results showed that adaptive Kalman filter treatment could monitor the wind speed with smaller RMSE compared with LVD monitor. The study data demonstrated that the adaptive Kalman filter is reliable and suitable for online signal processing of mine wind speed monitor.
Power big data contains a lot of information related to equipment fault. The analysis and processing of power big data can realize fault diagnosis. This study mainly analyzed the application of association rules in power big data processing. Firstly, the association rules and the Apriori algorithm were introduced. Then, aiming at the shortage of the Apriori algorithm, an IM-Apriori algorithm was designed, and a simulation experiment was carried out. The results showed that the IM-Apriori algorithm had a significant advantage over the Apriori algorithm in the running time. When the number of transactions was 100 000, the running of the IM-Apriori algorithm was 38.42% faster than that of the Apriori algorithm. The IM-Apriori algorithm was little affected by the value of supportmin. Compared with the Extreme Learning Machine (ELM), the IM-Apriori algorithm had better accuracy. The experimental results show the effectiveness of the IM-Apriori algorithm in fault diagnosis, and it can be further promoted and applied in power grid equipment.
Bacterial adsorption on mineral surface is one of the key steps in bioleaching process. The bacteria adsorb on the mineral surface via the extracellular polymeric substances (EPS) layer. In this paper, the behavior of glucuronic acid, one of the key substances in EPS layer, adsorbed on the pyrite surface is studied using DFT and electrochemical methods. Adsorption capacity of glucuronic acid is stronger than that of water. Glucuronic acid adsorbs on pyrite surfaces and it follows a mixed type of interactions (physisorption and chemisorption). Adsorption of glucuronic acid on pyrite surface followed Langmuir’s adsorption isotherm with adsorption standard free energy of –27.67kJ mol–1. The structural and electronic parameters were calculated and discussed.
Ladle plays an important role in the metallurgical industry whose maintenance directly affects the production efficiency of enterprises. In view of the problems such as low maintenance efficiency and untimely maintenance in the current ladle passive maintenance scheme, the life prediction mechanism for ladle composite structures is established which bases on the stress analysis of steel shell and ladle lining in the production process, combining conventional fatigue analysis and extended fracture theory. The mechanism is accurate and effective according to the simulation results. Through which, the useful life of steel shell can be accurately predicted by detecting the crack length of it. Due to the large number of factors affecting the life of the lining of the ladle, it is difficult to accurately predict the life of the ladle lining, so a forecasting mean based on the thermal shock method is proposed to predict the service life of the ladle lining in this paper. The life prediction mechanism can provide data support and theoretical guidance for the active maintenance of the ladle, which is the prerequisite for scientifically formulating ladle initiative maintenance program.
Q235 steel is widely used in engineering and construction. Therefore, it is important to identify the damage mechanism and the acoustic emission (AE) response of the material to ensure the safety of structures. In this study, an AE monitor system and an in situ tensile test with an optical microscope were used to investigate the AE response and insight into the damage process of Q235 steel. The surface of the specimen was polished and etched before the test in order to improve the quality of micrographs. Two kinds of AE responses, namely a burst and a continuous signal, were recorded by the AE monitor system during the test. Based on the in situ test, it was observed that the damage of Q235 steel was induced by the crystal slip and the inclusion fracture. Since the crystal slip was an ongoing process, continuous AE signals were produced, while burst AE signals were possibly produced by the inclusion fracture which occurred suddenly with released higher energy. In addition, a great number of AE signals with high amplitude were observed during the yielding stage and then the number and amplitude decreased.
To improve the power quality of a multi-pulse rectifier, a zigzag 18-pulse uncontrolled rectifier with an auxiliary circuit at the DC side is proposed. When the grid-side currents are sinusoidal waves, the required DC side injection currents to be compensated can be obtained by analyzing the AC-DC side relationship of diode bridge rectifiers. Then the 6 compensation currents generated by an active auxiliary circuit are injected into the DC side to eliminate the grid-side harmonics of the rectifier. The simulation results verifying the correctness of the theoretical analysis show that the proposed rectifier can mitigate the harmonic content, as the total harmonic distortion of the grid-side current is about 1.45%. In addition, the single-phase inverter used in the active auxiliary circuit has the characters of simple circuit structure and easy controllability.
MDAP-2 is a new AMP with high inhibitory activity on Salmonella gallinarum, which may be developed as an antimicrobial agent in the agricultural industry and food preservation. To investigate the underlying the action mechanism of MDAP-2 on Salmonella gallinarum, impacts of MDAP-2 on the growth curve and bacterial morphology of Salmonella gallinarum were studied. iTRAQ-based proteomics analysis was also performed on proteins extracted from treated and untreated Salmonella gallinarum cells. The differentially expressed proteins were then analyzed using the KEGG and GO databases. Finally, the function of some differentially expressed proteins was verified. The results showed that 150 proteins (41 up-regulated and 109 down-regulated) were found differentially expressed (fold > 1.8, p<0.05). The results indi- cate that MDAP-2 kills Salmonella gallinarum mainly through two mechanisms: (i) direct inhibi- tion of cell wall/ membrane/ envelope biogenesis, energy production/ conversion, carbohydrate transport/ metabolism, and DNA transcription/ translation through regulation of special protein levels; (ii) indirect effects on the same pathway through the accumulation of Reactive oxygen species (O2 ▪-, H2O2 and OH▪-).