Dai Qianjin

Bio: Dai Qianjin is an academic researcher from Xuzhou Institute of Technology. The author has contributed to research in topics: Fault (power engineering) & Roadheader. The author has an hindex of 1, co-authored 3 publications receiving 4 citations.

Data-Driven Approaches for Diagnosis of Incipient Faults in Cutting Arms of the Roadheader

Abstract: Incipient fault detection and identification (IFDI) of cutting arms is a crucial guarantee for the smooth operation of a roadheader. However, the shortage of fault samples restricts the application of the fault diagnosis technique, and the data analysis tools should be optimized efficiently. In this study, four machine learning tools (the back-propagation neural network based on genetic algorithm optimization, the naive Bayes based on genetic algorithm optimization, the support vector machines based on particle swarm optimization, and the support vector machines based on dynamic cuckoo) are applied to address the challenge in the IFDI of cutting arms. The commonly measured current and vibration data cutting arms are used in the IFDI. The experimental results show that the support vector machines based on dynamic cuckoo outperform the other methods. Besides, the performance of the four methods under different operating conditions is compared. The fault cause of cutting arms of the roadheader is analyzed and the design improvement scheme for cutting arms is provided. This study provides a reference for improving the fault diagnosis of the roadheader.

Bottom discharge type sludge microwave pyrolysis system for collecting products

Abstract: The utility model discloses a bottom-discharge sludge microwave pyrolysis system for product collection. The bottom-discharge sludge microwave pyrolysis system comprises a microwave oven, a conical flask, a flask, a gas washing bottle, a quartz beaker and a thermocouple arranged in the quartz beaker, the quartz beaker is correspondingly arranged in the microwave oven cavity; a quartz tube is fixedly inserted into the quartz tube channel, a purge gas inlet pipeline is connected to the quartz tube, a quartz cover is arranged at the upper end of the quartz tube, and the lower end of the quartz tube, the conical flask, the condenser, the flask, the resin tube and the gas washing bottle are sequentially connected in series; the method comprises: mixing to prepare a sample; vertically supportingthe quartz beaker filled with the sample in a quartz tube; nitrogen with the flow speed of 3 L/min is supplied, and purging is conducted for 10 min; then nitrogen with the flow rate of 0.2 L/min is supplied, and the inert atmosphere in the pyrolysis process is guaranteed; carrying out pyrolysis on the sample, and obtaining temperature data in real time; and taking out solids in the quartz beakerafter the pyrolysis is finished. According to the system and the method, accurate and effective collection of solid, liquid and gas products can be ensured, and the interference of the thermocouple onthe microwave pyrolysis process can be reduced.

Light-concentrating heating two-stage spiral sludge drying pyrolysis system and method

Abstract: The invention relates to a light-concentrating heating two-stage spiral sludge drying pyrolysis system and method. The system comprises a drier automatic sun-tracking device which heats a sludge drying cylinder in a dryer thermal-insulation cylinder by reflecting the captured sunlight by a drier reflecting mirror array; an automatic sun tracing device of a pyrolysis machine which heats the a sludge pyrolysis cylinder in a pyrolysis machine thermal-insulation cylinder by reflecting the captured sunlight by a pyrolysis machine reflecting mirror array; the discharging material of the sludge drying cylinder enters the sludge pyrolysis cylinder through a crusher and then enters and discharges through a pulverizer; a condenser circularly condenses the dirty vapor generated in the pyrolysis process; a pyrolysis gas storage tank recovers combustible gases from the pyrolysis process. The method is as followed: the pyrolysis atmosphere is ensured by nitrogen, and the thermal energy is provided by capturing the sunlight with the automatic sun tracing device; the circulation of pyrolysis gas is realized and water is recovered by a condenser; the combustible gas is recovered; solid product is recovered. The system and the method can fully utilize solar energy for heating, have a good energy saving effect, and improve the pyrolysis efficiency of sludge.

SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets

Abstract: Predictive maintenance has lately proved to be a useful tool for optimizing costs, performance and systems availability. Furthermore, the greater and more complex the system, the higher the benefit but also the less applied: Architectural, computational and complexity limitations have historically ballasted the adoption of predictive maintenance on the biggest systems. This has been especially true in military systems where the security and criticality of the operations do not accept uncertainty. This paper describes the work conducted in addressing these challenges, aiming to evaluate its applicability in a real scenario: It presents a specific design and development for an actual big and diverse ecosystem of equipment, proposing an semi-unsupervised predictive maintenance system. In addition, it depicts the solution deployment, test and technological adoption of real-world military operative environments and validates the applicability.

Solar heated biomass pyrolysis furnace and application method thereof

Abstract: The invention discloses a solar heated biomass pyrolysis furnace and an application method thereof. The solar heated biomass pyrolysis furnace comprises a pyrolysis furnace and a condensation device.The pyrolysis furnace is in a cylinder shape; the pyrolysis furnace is horizontally installed on a rotating support; the bottom end of the rotating support is installed on a rotating base; the pyrolysis furnace is erected overhead through the rotating support, and the rotating support is used for rotating the adjusting the pyrolysis furnace from the horizontal state to the vertical state; the rotating base is used for rotating and adjusting the rotating support together with the pyrolysis furnace on the rotating support inside the horizontal plane; the condensation device is arranged around the pyrolysis furnace and used for condensing and reflecting solar light irradiated on the condensation device on the pyrolysis furnace for heating the pyrolysis furnace; the biomass pyrolysis durance can adjust the direction and angle of the pyrolysis furnace and a compound collecting lens according to the position of the sun, solar energy is utilized to the maximum extent to supply heat energy tothe pyrolysis furnace, the device is applied to biomass pyrolysis, and the purposes of energy conservation and environmental protection are achieved.

Health Diagnosis of Roadheader Based on Reference Manifold Learning and Improved K-Means

Abstract: The safe and stable operation of roadheader is of great significance to the efficient and rapid production of a coal mine. Health diagnosis based on vibration signals has been studied in bearings and motors. Complex geological conditions and bad working environment lead to the characteristics of nonlinear and time-varying vibration signals of a roadheader. In this paper, a health state analysis method based on reference manifold (RM) learning and improved K-means clustering analysis was proposed; the method was verified by using the real-time collected roadheader cutting reducer fault signal. Firstly, the comparison signal and analysis signal were extracted from the actual collected vibration data of the roadheader, and the referential analysis samples were constructed through time domain and wavelet packet energy analysis. Then, the characteristic structure of the low-dimensional space of the referential analysis samples is obtained by Locally Linear Embedding (LLE), which is a method of manifold learning. Through the improved K-means clustering analysis method, the low-dimensional structure parameters were analyzed and the clustering effect index was obtained, which was used as the health evaluation index (HEI). Finally, the normal distribution model of the health evaluation index is established, and the confidence interval of the health evaluation index is determined, so as to realize the health state analysis of the roadheader and realize the fault warning function. Through the analysis of data of three sensors, the results show that the roadheader failed on the 15th day, which is consistent with the actual working condition. Through practical analysis, the effectiveness of the method was verified and provided a kind of fault analysis idea and method for equipment working under complex working conditions and the theoretical basis for fault type analysis.

Method for depolymerizing lignin by using microwave continuous reaction device

Abstract: The invention discloses a method for depolymerizing lignin by using a microwave continuous reaction device. The microwave continuous reaction device comprises a microwave oven with microwave power of900W, a quartz reaction tube which penetrates through the left side wall of the microwave oven and is arranged in the middle of an oven cavity of the microwave oven, a liquid feeding system and a condensation sampling system; the liquid feeding system comprises a liquid tank filled with NaOH aqueous solution and hydrogen peroxide, a high-pressure feeding pump and a feeding pipe; the condensation sampling system comprises a discharging pipe, a serpentine coil pipe, a cold trap and an outlet valve arranged at the bottom end of the cold trap; the device is simple in structure, rapid in heating, convenient in temperature control, uniform in heating and continuously adjustable in feeding speed, and products generated by reaction and intermediate products can be rapidly taken out of the high-temperature reaction zone, condensed and collected in time, so that side reactions are effectively inhibited.

Fault Diagnosis Method of Roadheader Bearing Based on VMD and Domain Adaptive Transfer Learning

Abstract: The roadheader is a core piece of equipment for underground mining. The roadheader bearing, as its key component, often works under complex working conditions and bears large radial and axial forces. Its health is critical to efficient and safe underground operation. The early failure of a roadheader bearing has weak impact characteristics and is often submerged in complex and strong background noise. Therefore, a fault diagnosis strategy that combines variational mode decomposition and a domain adaptive convolutional neural network is proposed in this paper. To start with, VMD is utilized to decompose the collected vibration signals to obtain the sub-component IMF. Then, the kurtosis index of IMF is calculated, with the maximum index value chosen as the input of the neural network. A deep transfer learning strategy is introduced to solve the problem of the different distributions of vibration data for roadheader bearings under variable working conditions. This method was implemented in the actual bearing fault diagnosis of a roadheader. The experimental results indicate that the method is superior in terms of diagnostic accuracy and has practical engineering application value.