An improved gene expression programming algorithm for function mining of map-reduce job execution in catenary monitoring systems.

Gene expression programming (GEP) is one of the most prominent algorithms in function mining. In order to obtain a more accurate function model in configuration parameters-execution efficiency (CP-EE) of map-reduce job in the high-speed railway catenary monitoring system, this paper proposes a novel algorithm, called GEP based on multi-strategy (MS-GEP). Compared to traditional GEP, the proposed algorithm can escape premature convergence and jump out of local optimum. First, an adaptive mutation rate is designed according to the evolutionary generations, population diversity, and individual fitness values. A manual intervention strategy is then proposed to determine whether the algorithm enters the dilemma of local optimum based on the generations of population evolutionary stagnation. Finally, the average quality of the population is changed by randomly replacing individuals, and the ancestral population is traced to change the evolutionary direction. The experimental results on the benchmarks of function mining show that the proposed MS-GEP has better solution quality and higher population diversity than other GEP algorithms. Furthermore, the proposed MS-GEP has higher accuracy on the function model of CP-EE of high-speed railway catenary monitoring system than other commonly used algorithms in the field of function mining.

Pantograph Detection Algorithm with Complex Background and External Disturbances.

As an important equipment for high-speed railway (HSR) to obtain electric power from outside, the state of the pantograph will directly affect the operation safety of HSR. In order to solve the problems that the current pantograph detection method is easily affected by the environment, cannot effectively deal with the interference of external scenes, has a low accuracy rate and can hardly meet the actual operation requirements of HSR, this study proposes a pantograph detection algorithm. The algorithm mainly includes three parts: the first is to use you only look once (YOLO) V4 to detect and locate the pantograph region in real-time; the second is the blur and dirt detection algorithm for the external interference directly affecting the high-speed camera (HSC), which leads to the pantograph not being detected; the last is the complex background detection algorithm for the external complex scene "overlapping" with the pantograph when imaging, which leads to the pantograph not being recognized effectively. The dirt and blur detection algorithm combined with blob detection and improved Brenner method can accurately evaluate the dirt or blur of HSC, and the complex background detection algorithm based on grayscale and vertical projection can greatly reduce the external scene interference during HSR operation. The algorithm proposed in this study was analyzed and studied on a large number of video samples of HSR operation, and the precision on three different test samples reached 99.92%, 99.90% and 99.98%, respectively. Experimental results show that the algorithm proposed in this study has strong environmental adaptability and can effectively overcome the effects of complex background and external interference on pantograph detection, and has high practical application value.

Investigation on thermokinetic suppression of ammonium polyphosphate on sucrose dust deflagration: Based on flame propagation, thermal decomposition and residue analysis.

In this investigation, ammonium polyphosphate (APP) is applied to suppress the deflagration of sucrose dust. Through the systematic research on flame propagation images and temperature, decomposition behavior of powder samples and the compositions of deflagration residue, the suppression performance and mechanism of APP on sucrose deflagration are profoundly summarized. Timing diagrams show that APP contributes to reduce deflagration flame brightness, increases ignition delay time and flame fault area. The minimum inerting concentration of APP for sucrose deflagration is determined to be 8 %. From the collected deflagration flame temperature curves, it is confirmed that APP can delay peak temperature arrival time, weaken temperature fluctuation, and decrease peak values of flame temperature and temperature rising rate. Through the analysis on thermal decomposition of samples and deflagration residue, it is reflected that APP has superior composite suppression effect. It can not only absorb reaction heat, but also decrease deflagration exotherm to improve thermal stability of sucrose particles. Thus, the easily oxidized components in sucrose are protected, and deflagration intensity is effectively weakened. This work provides a new solution for prevention and suppression deflagration of dust waste in sugar industry.

Nacre-biomimetic graphene oxide paper intercalated by phytic acid and its ultrafast fire-alarm application.

A novel nacre-like flame-retardant paper based on graphene oxide (GO), and phytic acid (PTA) is fabricated via evaporation-induced self-assembly. This facile method is time saving and low energy consuming. A facile approach is proposed to improve thermal oxidative stability of GO paper by in situ phosphorus doping during flame exposure. Then fire-alarm system is designed based on the high-temperature thermal reduction characteristic of GO. The GO paper functionalized with PTA (GO-PTA) can provide ultrasensitive, reliable and longtime fire early-warning signal. Fire alarm can be triggered at approximately 0.50 s when GO-PTA samples are attacked by fire. Phosphorus atoms are in situ doped into graphene layers during fire exposure, endowing GO-PTA paper with outstanding thermal oxidative stability, and thus alarm duration time of GO is greatly improved. The work develops advanced fire detection and early-warning sensors that provide reliable and continuous signals, which provide more available time for fire evacuation.

Insight into suppression performance and mechanisms of ultrafine powders on wood dust deflagration under equivalent concentration.

Flame propagation characteristics of wood dust deflagration and suppression mechanism of ultrafine powders are investigated systematically. The deflagration reaction intensity of wood dust increases firstly and then decreases with the increase in dust cloud concentration. This is due to factors such as oxygen supply, positive feedback among flame characteristic parameters. Thus, there is an equivalent dust concentration for greatest deflagration intensity. Nano-sized ultrafine zirconium hydroxide (Zr(OH)4) and silicon dioxide (SiO2) powder are introduced to suppress wood dust deflagration at the equivalent concentration. It is found that Zr(OH)4 has a suppression effect of endothermic decomposition to generate zirconia (ZrO2), dilution of oxygen and absorption of free radicals; while SiO2 exerts suppression effect due to its high melting point and heat absorption. The suppression performance of Zr(OH)4 is better than that of SiO2. This is because that Zr(OH)4 and ZrO2 have a catalytic carbonization effect. It can not only improve thermal stability of wood particles by catalyzing production of high-temperature resistant residuals, but also promote the formation of catalytic sites to reduce crystallite size of carbon layer on wood particles surface, weakening heat and mass transfer between particles.

Suppression of wood dust explosion by ultrafine magnesium hydroxide.

The suppression effects of ultrafine Mg (OH)2 powders with different particle sizes and mass fractions on explosion flame of wood dust are experimentally studied in a half-closed vertical experimental duct. Flame structures and characteristic parameters, including flame light emission images, propagation velocity, temperature, during the flame propagation of wood dust explosion are recorded by high-speed photography and fine thermocouple. Thermal decomposition behaviors of wood dust and Mg(OH)2 powders are studied using synchronous thermal analyzer. Chemical structures of residual dust samples after the explosion are characterized by Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy. The experimental results show that explosion flame of wood dust is obviously suppressed by physical and chemical effects of Mg(OH)2 powders, and the suppression effect of nano-Mg(OH)2 is better than that of micron-Mg(OH)2 under same mass fractions. By analyzing multiple characteristics of nano-powders, the advantages of nano-Mg(OH)2 over micron-powders are further investigated.

Facile preparation of layered melamine-phytate flame retardant via supramolecular self-assembly technology.

Melamine-phytate (MEL-PA) nanoflakes are formed by supramolecular self-assembly technology using melamine (MEL) and bio-based phytic acid (PA) as the building blocks. This work explores the possibility of this two-dimensional nanomaterial as flame retardant. The layered MEL-PA with the loading of 1, 2 and 3 wt% are incorporated into polypropylene (PP) matrix. MEL-PA is dispersed well in the PP matrix. Thermal stability and flame retardant performance of PP/MEL-PA composites are investigated. Compared with neat PP, the addition of 2 wt% MEL-PA decreases the peak heat release rate from 756 to 608 kW/m2. Char yield of PP is improved by MEL-PA, and the chemical structure and graphitization degree of residual char are studied to reveal flame retardant mechanism.