Nc machine tools how to realize the intelligent?

Intelligent machine first appeared in

(Wright P&middot K· Wright) and byrne (D&middot A· Bourne) published in 1998, the first monograph in the field of intelligent Manufacturing research journal of intelligent Manufacturing (Manufacturing Intelligence).Because plays an important role in advanced manufacturing, intelligent technology cause the attention of various countries.The United States launched the intelligent processing platform (SMPI);European implementation & other;Next Generation Production System”Research;Germany introduced & other;4.0 throughout & Industry;Plan;China’s medium and long-term development of science and technology for & other;Intelligent digital manufacturing technology & throughout;Put forward the urgent needs, and formulate the corresponding & other;Much starker choices-and graver consequences-in & throughout;The development plan;In 2006, the Chicago international manufacturing technology show (IMTS2006), Japan Mazak’s first name & other;Intelligent Machine”Intelligent machine and Japan Okuma’s named & other;Thinc”Intelligent CNC system, opens the intelligent CNC machine age.This article embarks from the sensor, the intelligent technology of nc machine tools is hierarchically divided into intelligent sensor, intelligent functions, intelligent components, intelligent system, a part of the intelligent technology is summarized, points out that insufficient, reveals the development direction, and in the future was prospected.

intelligent sensor composed of a machine tool, cutting tool, workpiece in machining process, nc machine tool manufacturing system with material removal, accompanied by a variety of complex physical phenomena, implies abundant information.In such a dynamic, nonlinear, time-varying and uncertain environment, numerical control machine tool’s own perception technology is the basic condition to realize intelligent.Nc machine tools in order to realize intelligent, need a variety of sensors to collect the external environment and internal state information, the approximate the function of the human senses perceive environment changes, as shown in table 1.For people, the eye is the most important features of sense organs, and can obtain more than 90% of the environment information, but visual sensor in the application of nc machine tool is less.With the improvement of automation and intelligent level, visual function will play a more and more important role in nc machine tools.Table 1

nc machine tools available sensors with MEMS (micro-electro-mechanical system) technology, embedded technology, intelligent materials and structures such as the development of technology, the sensor toward miniaturization.MEMS micro sensor, micro sensor film sensors and fiber optic sensor mature application, has paved the way for the sensor embedded nc machine tools.Due to unpredictable exist in the process of manufacturing or unexpected strange phenomenon and the complex problems, as well as the information detected by problems such as timeliness, accuracy, completeness, therefore, requires the sensor has the intelligence such as analysis, reasoning, * *, this requires a sensor should have high performance & other intelligent processor;Throughout the brain &;.Qualcomm is developed to simulate the human brain work of the artificial intelligence system microprocessor.By semiconductor integrated technology in the future, the high performance microprocessor artificial intelligence system and sensor, signal processing circuit, I\/O interface, integrated on the same chip, forming large scale integrated circuit type intelligent sensor, not only has the detection, recognition, memory, analysis, and other functions, but also self-study * * even thinking ability.Believe that along with the computer technology, signal processing technology, MEMS technology, high and new material technology, wireless communication technology advances, such as smart sensors will bring new changes in nc machine tools intellisense.

intelligent function of nc machine tool to high-speed, high efficiency, high development, the elaboration for numerical control machine tool wear characteristics of thermal compensation, vibration monitoring, monitoring, condition monitoring and fault diagnosis of intelligent functions.Several or several smart sensors, using artificial intelligence method, through the identification, analysis, judgment and reasoning, achieve the function of CNC machine intelligence, lays the foundation for the realization of the intelligent components.The error of nc machine tools including geometry error, heat (deformation) and force (deformation) error, assembly error, etc.Studies have shown that the geometric error and thermal error of the machine tool more than 50% of the total error, is the key factor that affect the machining accuracy of machine tool, as shown in figure 1.Among them, the geometric error is caused in the process of manufacture, assembly and the error of machine tool structure itself, little change over time, belong to the static error, error of the prediction model is relatively simple, can get effective control, through the system of compensation function changes over time and thermal error is very big, belongs to the dynamic error, error of prediction model is complex, is a difficulty and a focus of international research.

nc machine tools in the machining process heat source including bearings, ball screw, motor, gear box, guide rail, cutting tools, etc.These parts of warming will cause the main shaft extension, coordinate change, tool change such as elongation, machine tool error caused by increased.As the temperature sensitive more, wide distribution, temperature test point location optimization design is very important, the main method of genetic algorithm, neural network, fuzzy clustering and rough set and information theory, the grey system, etc.In determining the temperature measuring point, on the basis of common neural network, genetic algorithm, fuzzy logic, the grey system, support vector machine (SVM) for error prediction and compensation.

in the aerospace field, such as titanium alloy, nickel alloy, high strength steel difficult-to-machine materials are widely used, and under the condition of high speed cutting, cutting quantity increasing, is easy to occur vibration between tool and workpiece, seriously affect the machining accuracy and surface quality of workpiece.Because of the cutting force is a primitive characteristic signal of cutting process, the most can reflect the dynamic characteristic of the machining process, so can use monitoring and prediction of cutting force in vibration monitoring.Using dynamometer, force sensor, the feed motor current, etc., using particle swarm optimization (pso) algorithm, the fuzzy theory and genetic algorithm, and the theory of grey modeling and projections for cutting force.Considering the cause of the machine tool vibration main spindle, screw, bearing parts, can also the vibration of the acquisition of these components, such as cutting force, the acoustic emission signal, using neural network, fuzzy logic and support vector machine (SVM) for vibration monitoring of intelligent methods such as direct.

tool installed in the spindle front, contact with machining, cutting surface, directly impact on the quality of machining is the most direct and key.Tool wear and breakage of the abnormal phenomenon such as affect the machining precision and work safety.In view of the direct measurement method to offline detection of defects, often collecting current, cutting force, vibration, power, temperature, one or more of the indirect signals, such as by using RBF neural network, fuzzy neural network, wavelet neural network, support vector machine (SVM) and other intelligent algorithm for intelligent monitoring of tool wear state.With the improvement of automation, numerical control machine tool integration more and more features, complex degree enhances unceasingly.In order to run efficiently, the internal status of nc machine tool monitoring and performance evaluation, to warning and fault diagnosis is necessary.Due to the failure mode reproducibility is not strong, specimen collection is difficult, so the BP neural network for sample more intelligent method is not suitable for the occasion.Condition monitoring and fault diagnosis by using SOM neural network, fuzzy logic and support vector machine (SVM), expert system and intelligent methods, such as multiple Agent.Researchers continue to explore and study of the function of the smart new method or a combination of a variety of methods, but most of the focus in the laboratory environment, lack of high real-time, on-line function method, still need to in-depth development of intelligent method of simple, fast and strong adaptability.

intelligent parts of nc machine tool mechanical part mainly includes the support structure, main transmission and feed drive parts, tool parts, such as involving lathe bed, column, spindle, tool, lead screw and guide rail and the axis of rotation and other components.These parts can be integrated intelligent sensor of one or several function of intelligent CNC machine intelligence.

spindle is the main transmission components, as a core component, is directly related to the workpiece machining accuracy.Due to the spindle speed is higher, especially the motorized spindle, heat, wear and tear, vibration impact on the processing quality is very big, therefore, more and more intelligent sensors are integrated into the main shaft, the implementation of work state monitoring, early warning and compensation, and other functions.Developed by Japan yamazaki mazar-e-sharif g & other;Smart spindle & throughout;, equipped with a variety of sensors, such as temperature, vibration, displacement and distance, temperature, vibration, clamp life not only monitoring and protection function, and can according to the vibration, temperature, intelligent coordination processing parameters.Swiss Step – Tec, IBAG, such as manufacturing of motorized spindle, equipped with a variety of sensors, such as temperature, acceleration, axial displacement, as shown in figure 3, to compensate the thermal and vibration monitoring, etc.