解决布动平网印花机压糊问题刍议

针对真丝绸布动平网印花机印花易产生压糊病疵的问题,提出了解决办法,如掌握和运用描绘黑白稿和制作花版的技巧,控制原糊和色浆的粘度,选择助剂和有关刮印工艺参数,注意操作方法等。

Refracturing candidate selection for MFHWs in tight oil and gas reservoirs using hybrid method with data analysis techniques and fuzzy clustering

The selection of refracturing candidate is one of the most important jobs faced by oilfield engineers. However, due to the complicated multi-parameter relationships and their comprehensive influence, the selection of refracturing candidate is often very difficult. In this paper, a novel approach combining data analysis techniques and fuzzy clustering was proposed to select refracturing candidate. First, the analysis techniques were used to quantitatively calculate the weight coefficient and determine the key factors. Then, the idealized refracturing well was established by considering the main factors. Fuzzy clustering was applied to evaluate refracturing potential. Finally, reservoirs numerical simulation was used to further evaluate reservoirs energy and material basis of the optimum refracturing candidates. The hybrid method has been successfully applied to a tight oil reservoir in China. The average steady production was 15.8 t/d after refracturing treatment, increasing significantly compared with previous status. The research results can guide the development of tight oil and gas reservoirs effectively.

Realizing of Optimization of Binder Backfill Material Under Certain Strength with Fuzzy Sets

The main factors deciding the compressive strength of binder backfill body are tailing density and binder dosage in binder backfill materials. Based on the antecedent of certain pulp density, the method of increasing the tailing density and reducing the binder dosage, or the manner of cutting down the tailing density and gaining the binder dosage are taken to guarantee the strength of backfill body. The problem that should be solved is how to determine the tailing density and the binder dosage rationally. This paper tries to realize the correct selection of the tailing density and the binder dosage in computer with the method of fuzzy mathematics.

Application of adaptive fuzzy control technology to pressure control of a pressurizer

A pressurizer is one of important equipment in a pressurized water reactor plant. It is used to maintain the pressure of primary coolant within allowed range because the sharp change of coolant pressure affects the security of reactor, therefor, the study of pressurizer’s pressure control methods is very important. In this paper, an adaptive fuzzy controller is presented for pressure control of a presurizer in a nuclear power plant. The controller can on-line tune fuzzy control rules and parameters by self-learning in the actual control process, which possesses the way of thinking like human to make a decision. The simulation results for a pressurized water reactor plant show that the adaptive fuzzy controller has optimum and intelligent characteristics, which prove the controller is effective.

FUZZY MATHEMATICAL EVALUATION FOR MASONRY STRUCTURE BUILDINGS' DAMAGE GRADE CAUSED BY COAL MINING

Coal mining under buildings certainly causes surface movement and deformation, therefore, it brings about deformation even fracture for buildings. It is an important task to evaluate correcly the buildings’ damage grabe caused by coal mining. Fuzzy comprehensive evaluation,considering some factors of buildings’ fracture, has been applied to analyze the masonry structure buildings’ damage grade affer coal mining in this paper. It provides a scientific basis for buildings’reidercement before mining and maintenance or compensation after mining.

A new approach to predicting mining induced surface subsidence

There are many parameters influencing mining induced surface subsidence. These parameters usually interact with one another and some of them have the characteristic of fuzziness. Current approaches to predicting the subsidence cannot take into account of such interactions and fuzziness. In order to overcome this disadvantage, many mining induced surface subsidence cases were accumulated, and an artificial neuro fuzzy inference system(ANFIS) was used to set up 4 ANFIS models to predict the rise angle, dip angle, center angle and the maximum subsidence, respectively. The fitting and generalization prediction capabilities of the models were tested. The test results show that the models have very good fitting and generalization prediction capabilities and the approach can be applied to predict the mining induced surface subsidence.

Pneumatic active suspension system for a one-wheel car model using fuzzy reasoning and a disturbance observer

This paper presents the construction of a pneumatic active suspension system for a one-wheel car model using fuzzy reasoning and a disturbance observer. The one-wheel car model can be approximately described as a nonlinear two degrees of freedom system subject to excitation from a road profile. The active control is composed of fuzzy and disturbance controls, and the active control force is constructed by actuating a pneumatic actuator. A phase lead-lag compensator is inserted to counter the performance degradation due to the delay of the pneumatic actuator. The experimental result indicates that the proposed active suspension improves much the vibration suppression of the car model.

High precise control method for a new type of Piezoelectric electro-hydraulic servo valve

A new type of piezoelectric electro-hydraulic servo valve system was proposed. And then multilayer piezoelectric actuator based on new piezoelectric ceramic material was used as the electricity-machine converter of the proposed piezoelectric electro-hydraulic servo valve. The proposed piezoelectric electro-hydraulic servo valve has ascendant performance compared with conventional ones. But the system is of high nonlinearity and uncertainty, it cannot achieve favorable control performance by conventional control method. To develop an efficient way to control piezoelectric electro-hydraulic servo valve system, a high-precise fuzzy control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with Preisach hysteresis nonlinear model and a feedback loop with high-precise fuzzy control. Experimental results show that the hysteresis loop and the maximum output hysteresis by the PID control method are 4.22% and 2.11 μm, respectively; the hysteresis loop and the maximum output hysteresis by the proposed control method respectively are 0.74% and 0.37 μm, respectively; the maximum tracking error by the PID control method for sine wave reference signal is about 5.02%, the maximum tracking error by the proposed control method for sine wave reference signal is about 0.85%.

Fuzzy Comprehensive Assessment Method to Determine Tectonic Stress Patterns

The tectonic stress patterns were determined by a fuzzy comprehensive assessment method. Data of in-situ survey and fault information were utilized in the method. First, by making pressure and tension in the directions of along-river, cross-river, shear clockwise, and shear counterclockwise , 26 types of tectonic stress patterns were presented. And the stress vector of each pattern was obtained with FE software by taking unit displacement as boundary load. Then, by taking the 26 types of tectonic stress patterns as index set and 3 main stresses as factor set and choosing various operators, comparison of directions of computational stress vector and survey stress vector was made and the most possible tectonic stress pattern was obtained. Taking the 26 types of tectonic stress patterns as index set and strike angle as factor set, comparison of relationships between formation of fault and tectonic stress was made,and the tectonic stress patterns were assessed with known fault information. By summarizing the above assessment results, the most impossible tectonic stress pattern was obtained . Finally an engineering case was quoted to validate that the method is more feasible and reliable than traditional empirical method.

Research of the algorithm of the closed-loop control system to control the piezoelectric actuator

The piezoelectric actuator has been widely used in precision instruments and precision control. However, hysteresis, nonlinearity and creep exist in the actuator, which limit actuator applications and affect accuracy. This thesis introduces fuzzy control as the algorithm of a closed-loop control system to control the piezoelectric actuator. Fuzzy control can make this closed-looped system not only have high linearity, repeatability, accuracy and few overshoot, but isalso easily used.

Neuro-fuzzy systems in determining light weight concrete strength

The adaptive neuro-fuzzy inference systems(ANFIS)are widely used in the concrete technology.In this research,the compressive strength of light weight concrete was determined.To this end,the scoria percentage and curing day variables were used as the input parameters,and compressive strength and tensile strength were used as the output parameters.In addition,100 patterns were used,70%of which were used for training and 30%were used for testing.To assess the precision of the neuro-fuzzy system,it was compared using two linear regression models.The comparisons were carried out in the training and testing phases.Research results revealed that the neuro-fuzzy systems model offers more potential,flexibility,and precision than the statistical models.

Adaptive fuzzy integral sliding mode pressure control for cutter feeding system of trench cutter

A nonlinear pressure controller was presented to track desired feeding pressure for the cutter feeding system(CFS) of trench cutter(TC) in the presence of unknown external disturbances.The feeding pressure control of CFS is subjected to unknown load characteristics of rock or soil; in addition,the geological condition is time-varying.Due to the complex load characteristics of rock or soil,the feeding velocity of TC is related to geological conditions.What is worse,its dynamic model is subjected to uncertainties and its function is unknown.To deal with the particular characteristics of CFS,a novel adaptive fuzzy integral sliding mode control(AFISMC) was designed for feeding pressure control of CFS,which combines the robust characteristics of an integral sliding mode controller and the adaptive adjusting characteristics of an adaptive fuzzy controller.The AFISMC feeding pressure controller is synthesized using the backstepping technique.The stability of the overall closed-loop system consisting of the adaptive fuzzy inference system,integral sliding mode controller and the cutter feeding system is proved using Lyapunov theory.Experiments are conducted on a TC test bench with the AFISMC under different operating conditions.The experimental results demonstrate that the proposed AFISMC feeding pressure controller for CFS gives a superior and robust pressure tracking performance with maximum pressure tracking error within ?0.3 MPa.

Accurate Reactive Power Controller and Power Factor Correction Using Fuzzy Logic

This paper presents the use of fuzzy logic technique to control the reactive power of load and hence improve the source power factor. A shunt compensator is proposed, which consists of a voltage controlled reactor by full-wave thyristor bridge in parallel with a capacitor. The proposed voltage control technique composed of two independent fuzzy controllers, primary and secondary. The PFC （primary fuzzy controller） is designed based on linearization method to introduce to the network the nearest value of reactive power （VAR） required to correct the power factor. The SFC （secondary fuzzy controller） is designed to achieve accurate compensation for the required VAR to achieve the pre-set power factor value. Simulations for 15 different practical study cases are presented to evaluate the performance of the controller, and the results show how the designed controller is fast and accurate. Harmonics analyses are carried out up to the 13th harmonic to determine the requirement of harmonics filter.

Fuzzy Logic Based Approach in an Enterprise Resource Planning System for Hydraulic Cylinders Assembly

Trends in modern industry show a tendency towards demassovization of production as a response to the customers＇ specific needs for unique and personalized products. This provokes significant changes in the processes of manufacturing, assembly, and testing The cost of such a type of production can be reduced by employing highly productive reconfigurable equipment with proper software to enable optimization. This paper presents a decision support extension for directing of hydraulic cylinders to assembly-testing lines using fuzzy logic in the Enterprise Resource Planning system of a small size production in a factory in Bulgaria. Different assembly-testing lines are flexibly assigned to the specific cylinder＇s parameters by the developed fuzzy system on the basis of the overlapping of parameters in the hydraulic cylinders classification. The final decision on the line assigned in case of alternatives is made through accounting for the minimal cylinder delay time. The effectiveness of the approach is assessed by simulation. It leads to an increase of the efficiency of the assembly-testing flow lines, a reduction of the time needed for hydraulic cylinders assembling and testing and balanced loading of the modules.

Fuzzy iterative learning control of electro-hydraulic servo system for SRM direct-drive volume control hydraulic press

A new kind of volume control hydraulic press that combines the advantages of both hydraulic and SRM(switched reluctance motor) driving technology is developed.Considering that the serious dead zone and time-variant nonlinearity exist in the volume control electro-hydraulic servo system,the ILC(iterative learning control) method is applied to tracking the displacement curve of the hydraulic press slider.In order to improve the convergence speed and precision of ILC,a fuzzy ILC algorithm that utilizes the fuzzy strategy to adaptively adjust the iterative learning gains is put forward.The simulation and experimental researches are carried out to investigate the convergence speed and precision of the fuzzy ILC for hydraulic press slider position tracking.The results show that the fuzzy ILC can raise the iterative learning speed enormously,and realize the tracking control of slider displacement curve with rapid response speed and high control precision.In experiment,the maximum tracking error 0.02 V is achieved through 12 iterations only.

Energy-Saving Design for Hydraulic Tube Bender

Generally speaking, hydraulic control systems can be divided into two different driving concepts. The first one is the well-known hydraulic valve-controlled system and the second one is the pump-controlled system. The former possesses the feature of fast dynamic response. However, the poor energy-saving performance is its major fault. On the contrary, the hydraulic pump-controlled system has the significant advantage of energy-saving which meets the current demand in modem machine design. In this paper, the simulation analysis using MatLab/SimuLink and DSHplus software for a newly developed energy-saving hydraulic tube bender is conducted. Instead of the conventional fixed displacement hydraulic pump, the new hydraulic tube bender utilizes an internal gear pump with AC servomotor as its driving power source. In the new energy-saving hydraulic circuit, the use of conventional pressure relief valve and unloading valve are no longer necessary since the demanded flow-rate and pressure output can be precisely obtained by continuously changing the speed of the AC servomotor. In addition, two closed-loop control schemes using fuzzy sliding-mode controller are adopted and compared. To compare the energy-saving control systems, such as load-sensing control system, constant supply pressure control scheme and conventional hydraulic control scheme. Furthermore, the simulation results also show that the newly developed hydraulic tube bender can save up to 43% of energy consumption in a working cycle as compared to the conventional hydraulic tube bender.

3-Phase Fault Finding in Oil Field MV Distribution Network Using Fuzzy Clustering Techniques

This paper studies an existing 13.8 kilovolt distribution network which, serves an oil production field spread over an area of approximately 60 kilometers square, in order to locate any fault that may occur anywhere in the network using fuzzy c-mean classification techniques. In addition, Sections 5 and 6 introduce two different methods for normalizing data and selecting the optimum number of clusters in order to classify data. Results and conclusions are given to show the feasibility for the suggested fault location method. Suggestion for future related research has been provided in Section 8.

Variable Universe Fuzzy Control for Battery Equalization

In order to avoid the overcharge and overdischarge damages, and to improve the lifetime of the lithium-ion batteries, it is essential to keep the cell voltages in a battery pack at the same level,i.e., battery equalization. Based on the bi-directional modified Cuk converter, variable universe fuzzy controllers are proposed to adaptively maintain equalizing currents between cells of a serially connected battery pack in varying conditions. The inputs to the fuzzy controller are the voltage differences and the average voltages of adjacent cell pairs. A large voltage difference requires large equalizing current while adjacent cells both with low/high voltages can only stand small discharge/charge currents. Compared with the conventional fuzzy control method, the proposed method differs in that the universe can shrink or expand as the effects of the input changes. This is important as the input may change in a small range. Simulation results demonstrate that the proposed variable universe fuzzy control method has fast equalization speed and good adaptiveness for varying conditions.