Experimental study on optimization of low frequency acoustic transmission frequency in loose coal

The selection of signal frequency in acoustic temperature measurement technology is the key to improve the accuracy of temperature measurement. In order to explore the optimal propagation frequency of low-frequency sound waves in loose coal, lignite, coking coal, and anthracite are used as the research objects. The acoustic loss of three coal samples under six particle sizes（0.9 mm to ＜3 mm, 3 mm to ＜5 mm, 5 mm to ＜7 mm, 7 mm to 10 mm, 9 mm to 10 mm and larger than 10 mm） by using the acoustic loss test system is tested. The experimental results show that the sound transmission loss of three coal samples presents a wave-like rising shape with the increase of the sound wave frequency. Compared with coal samples of other particle sizes, the sound transmission loss of coal samples in the range of 0.9 mm to ＜3 mm is the largest. As the particle size of coal samples increases, the sound transmission loss of coal samples continues to increase, and the sound wave frequency corresponding to the lowest point of sound transmission loss also increases. The degree of coal sample deterioration has no obvious regularity in the influence of sound transmission loss. The sample size is the main factor that affects the change of the sound transmission loss of the coal sample, and the sound waves mainly propagate along the gaps between the particle sizes of the loose coal. By comparing and analyzing the maximum and minimum values of sound transmission loss, there is a maximum value between 250 Hz to 600 Hz and 900 Hz to 1 600 Hz about the sound transmission loss of coal samples of different particle sizes, and the maximum sound transmission loss range is between 4.66 dB and 7.64 dB. By testing the sound transmission loss in the low-frequency sound waves of the mixture of three coal samples, it is determined that the optimal sound transmission frequency range in the loose coal is 600 Hz to 900 Hz

Active Defense Research against False Data Injection Attacks of Power CPS Based on Data-Driven Algorithms

The terminal equipment interconnection and the network communication environment are complex in power cyber–physical systems (CPS), and the frequent interaction between the information and energy flows aggravates the risk of false data injection attacks (FDIAs) in the power grid. This paper proposes an active defense framework against FDIAs of power CPS based on data-driven algorithms in order to ensure that FDIAs can be efficiently detected and processed in real-time during power grid operation. First, the data transmission scenario and false data injection forms of power CPS were analyzed, and the FDIA mathematical model was expounded. Then, from a data-driven perspective, the algorithm improvement and process design were carried out for the three key links of data enhancement, attack detection, and data reconstruction. Finally, an active defense framework against FDIAs was proposed. The example analysis verified that the method proposed in this paper could effectively detect FDIAs and perform data reconstruction, providing a new idea for the active defense against FDIAs of power CPS

Study on Tourism Spatial Structure of Urban Agglomeration in Central Region Based on Social Network Method

With the passage of time, China’s economic development, people’s life gradually pursue enjoyment, so the development of tourism has gradually become an important pillar of national economic development. According to the urban geographical location of the central region, combined with the existing tourism economic conclusions, this paper studies the urban tourism economic data of the central region by using the method of social network, so as to understand the economic development of tourism in the central region in 2019. Through the research, it can be concluded that the correlation of urban tourism economy in Central China is not high among cities, and the tourism economy of cities is relatively different. The strength and influence of tourism economy of central cities with better tourism economic development are much higher than those without tourism economic strength. The tourism economy of each adjacent city circle is relatively close and develops relatively evenly, which shows that the development of tourism economy is closely related to the tourism economic development of adjacent cities. In the urban agglomeration in the central region, there is a high connection between the tourism economy of the cities in the six urban circles. In addition, it can be seen from the tourism economic network diagram of the urban agglomeration in the central region that among the six sub urban agglomerations, the cities in the sub urban agglomerations are closely related to the tourism economy of the central cities in the sub urban agglomerations, but from the perspective of the overall tourism economy, the tourism economic relations among cities are layered, This paper puts forward some suggestions conducive to the integrated development of urban tourism economy in Central China

Influence of Cooling Water Parameters on the Thermal Performance of the Secondary Circuit System of a Modular High-Temperature Gas-Cooled Reactor Nuclear Power Plant

This study quantitatively analysed the influence of cooling water parameters on the performance of a modular high-temperature gas-cooled reactor (MHTGR) nuclear power plant (NPP). The secondary circuit system and cold-end system were modelled using EBSILON software, version 16.0. The influence of cooling water inlet temperature and mass flow rate on the thermal performance of the secondary circuit system was analysed over the full power range with the goal of optimising net power. Under 100% rated condition, for each 1 °C increase in cooling water inlet temperature between 10 and 33 °C, the net power and cycle efficiency decreased by 0.67 MW and 0.14%, respectively, whereas the heat consumption rate increased by 28.72 kJ/(kW·h). The optimal cooling water mass flow rates corresponding to cooling water inlet temperatures of 16 °C and 33 °C were obtained. The optimal cooling water mass flow rate decreased nonlinearly with decreasing power levels. At a cooling water inlet temperature of 33 °C, an increase in cooling water mass flow rate from the designed value (7697.61 kg/s) to the optimal value (10,922.14 kg/s) resulted in a 1.03 MW increase in net power. These findings provide guidelines for MHTGR NPP operation optimisation and economic improvement, especially under high-temperature weather conditions

Cladding Mode Fitting-Assisted Automatic Refractive Index Demodulation Optical Fiber Sensor Probe Based on Tilted Fiber Bragg Grating and SPR

In the paper based on surface plasmon resonance (SPR) in a tilted fiber Bragg grating (TFBG), a novel algorithm is proposed, which facilitates demodulation of surrounding refractive index (SRI) via cladding mode interrogation and accelerates calibration and measurement of SRI. Refractive indices with a tiny index step of 2.2 × 10−5 are prepared by the dilution of glucose aqueous solution for the test and the calibration of this fiber sensor probe. To accelerate the calibration process, automatic selection of the most sensitive cladding mode is demonstrated. First, peaks of transmitted spectrum are identified and numbered. Then, sensitivities of several potentially sensitive cladding modes in amplitude adjacent to the left of the SPR area are calculated and compared. After that, we focus on the amplitudes of the cladding modes as a function of a SRI, and the highest sensitivity of −6887 dB/RIU (refractive index unit) is obtained with a scanning time of 15.77 s in the range from 1520 nm to 1620 nm. To accelerate the scanning speed of the optical spectrum analyzer (OSA), the wavelength resolution is reduced from 0.028 nm to 0.07 nm, 0.14 nm, and 0.28 nm, and consequently the scanning time is shortened to 6.31 s, 3.15 s, and 1.58 s, respectively. However, compared to 0.028 nm, the SRI sensitivity for 0.07 nm, 0.14 nm, and 0.28 nm is reduced to −5685 dB/RIU (17.5% less), −5415 dB/RIU (21.4% less), and −4359 dB/RIU (36.7% less), respectively. Thanks to the calculation of parabolic equation and weighted Gauss fitting based on the original data, the sensitivity is improved to −6332 dB/RIU and −6721 dB/RIU, respectively, for 0.07 nm, and the sensitivity is increased to −5850 dB/RIU and −6228 dB/RIU, respectively, for 0.14 nm

Active Defense Research against False Data Injection Attacks of Power CPS Based on Data-Driven Algorithms

The terminal equipment interconnection and the network communication environment are complex in power cyber–physical systems (CPS), and the frequent interaction between the information and energy flows aggravates the risk of false data injection attacks (FDIAs) in the power grid. This paper proposes an active defense framework against FDIAs of power CPS based on data-driven algorithms in order to ensure that FDIAs can be efficiently detected and processed in real-time during power grid operation. First, the data transmission scenario and false data injection forms of power CPS were analyzed, and the FDIA mathematical model was expounded. Then, from a data-driven perspective, the algorithm improvement and process design were carried out for the three key links of data enhancement, attack detection, and data reconstruction. Finally, an active defense framework against FDIAs was proposed. The example analysis verified that the method proposed in this paper could effectively detect FDIAs and perform data reconstruction, providing a new idea for the active defense against FDIAs of power CPS