1. Smart technology is fully revitalized Today's intelligent science and technology branches are vigorous and prosperous, and have achieved rapid development at home and abroad, such as fuzzy logic, genetic algorithms, neural networks, expert systems, humanoid intelligence, rough set theory, matter-element extension methods, knowledge engineering, models Recognition, qualitative control, wavelet analysis, fractal geometry, chaos control, data fusion technology, etc., can be described as eight immortals crossing the sea, each showing their magical powers. Each has its own strengths and combines them to complement each other. Artificial neural network is the basic technology in today's intelligent technology. Its connection mechanism is in parallel with the symbolic inference mechanism of artificial intelligence, and has become the two camps of intelligent technology. It simulates the anatomical and physiological characteristics of the human brain. It uses many simple neurons in parallel to form a network with a certain topology. It not only receives external information, but also stimulates each other. It is better at distributed storage, associative memory, feedback refinement, and black box mapping. , Weight balance, dynamic approximation, holographic recording, error tolerance and loss prevention, combined with huge interconnection of neurons, forming a strong self-learning, self-adaptive, self-organizing, self-diagnostic, self-repairing ability, and weights between its network nodes Continuous intensity feedback, dynamic analysis, and close cooperation with language and audio-visual man-machine interfaces can automatically obtain the rich knowledge and experience of human experts, and simulate the logical reasoning, visual thinking and inspiration of the human brain, and deal with various inaccuracies appropriately. , Imperfect, uncertain information, reasoning to draw correct conclusions. Fuzzy logic imitates the uncertainty concept judgment and reasoning thinking mode of the human brain. For description systems where the model is unknown or uncertain, and the control objects with strong nonlinearity and large lag, fuzzy sets and fuzzy rules are used for inference to express transitional boundaries. Or qualitative knowledge experience, simulate the human brain mode, implement fuzzy comprehensive judgment, reasoning to solve the problem of regular fuzzy information that conventional methods are difficult to deal with. Fuzzy logic is good at expressing qualitative knowledge and experience with unclear boundaries. With the help of the concept of membership function, it distinguishes fuzzy sets, handles fuzzy relations, simulates human brain to implement regular reasoning, and solves the various problems caused by the logic break of the "exclusion law" Identify the problem. Genetic algorithm is a search method that uses the "electron beam search" feature to suppress the explosion of the calculation amount of the search space. It can fully search with multiple points in the solution space, use genetic algorithms, repeatedly cross, operate in a mutant way, and simulate the inside of things Diversity and high adaptability to environmental changes, characterized by strong operability, can avoid falling into local minima at the same time, and make the problem quickly converge globally. It is a type of autonomous decentralized system that can use multiple information globally. Evolvable hardware (EHW) made using genetic algorithms (GA) and other evolutionary methods can produce novel circuits that exceed the technical synthesis of existing models and the capabilities of designers, especially GA ’s unique global optimization performance, making it self-learning, Adaptive, self-organizing, and self-evolving capabilities are more fully utilized. For automatic synthesis in an unmanned space, expansion of massive parallel processing (MPP), and real-time, flexible configuration and invocation of EPGA-based function-level EHW to solve multidimensional The complex problem of uncertainty in space opens the course. The expert system is to collect and apply the knowledge and experience of human experts, imitate the methods of experts to deal with knowledge and solve problems, and compile into a computer intelligent software system. Under the condition of continuously obtaining feedback information through the combination of man and machine, real-time online rules, examples and A problem solving or control system in which the model implements independent decision-making. This computer intelligence system is inspiring, transparent and flexible. Without being affected by time, space and environment, it can complete work efficiently, accurately, comprehensively, quickly and tirelessly. Its problem solving ability and knowledge The breadth can exceed that of human experts, and it overcomes the deviations and errors caused by human experts due to negligence, forgetting, nervousness, fatigue and other interference factors. Therefore, its promotion and application have huge economic and social benefits. Pattern recognition is an intelligent decision-making method and technology that simulates human brain image thinking, recognizes, judges and processes things based on the characteristics, image or relationship of things. It is widely used in scientific research and production and is a technical method with great value . Rough set theory is to discretely normalize the data set obtained in the measurement. Through algebraic operations based on the indistinguishable relationship of the set elements, a large number of useful features and effective data in the condition and result attributes are used to discover knowledge. The core value is obtained in the preliminary simplified calculation of the rules, and then the rules are further simplified and the minimum decision algorithm is selected for practical application according to the problem requirements, removing redundant attributes in a large amount of information, and reducing the dimension and number of attributes in the information space. It can greatly simplify the network structure and the number of samples and shorten the training time. It is a fundamental analysis method in intelligent technology. This method acquires knowledge based on measurement data sets, so it is of great significance to the intelligent development of virtual instruments. Chaotic motion is a highly unstable motion confined to a finite phase space in a deterministic system. It is an order in disorder. It causes things to show some kind of confusion on the surface during long-term behavior. The characteristics of chaotic phenomena are "order hidden behind non-periodic" and "sensitive dependence on initial conditions", make full use of chaotic characteristics, implement nonlinear decision-making and prediction, nonlinear system identification, and pattern recognition in intelligent information processing , Image data compression, high-performance confidentiality, multi-target search, and infinitely rich and wonderful computer painting and other magical applications. Fractal theory studies the non-smooth and non-differentiable geometric shapes and their self-similarity of internal structures produced by nonlinear systems, which provides a powerful tool and method for studying the laws of motion change of all complex things in nature. Wavelet analysis is the backbone and the most perfect crystallization of this big tree of modern analytical mathematics. From a visual point of view, wavelet refers to the shortest and simplest oscillating wave with the same sign and attenuation that people can observe; mathematically speaking, the wavelet function f (t) has three conditions at its center Window function, which can not only characterize the localized characteristics of the signal in the time and frequency domain, but also completely retain all the information of the signal, and has the zoom property, that is, it has a very narrow time for high-frequency signals that appear only instantaneously The window, and in the low frequency band, has a wide range of different scale transformations. The essence of wavelet analysis is to reflect the wave-particle duality of the world of things and the dialectical relationship between the local and the overall multi-level display. Its most attractive features are time-frequency positioning and multi-scale approximation capabilities. In adaptive control, robust control, non- Linear control, process identification, neural networks and many other fields have achieved fruitful results. Fractal and chaos are two aspects that are essentially identical. Chaotic events show similar patterns of change at different times, while fractals are similarities expressed on a spatial scale. Chaos is concerned with its complicated process of instability, divergence, and convergence, while fractal is an intuitive geometric language that describes chaotic motion. The organic combination of chaos, fractal and wavelet analysis has a very rich connotation and profound philosophy. It will surely provide a powerful tool for solving major micro-technical problems such as automatic assembly of material molecules, high-speed gene sequencing and efficient protein structure prediction. It will also open up brilliant prospects for the virtualization, networking and intelligence of instruments and meters. The matter-element extension method is based on the comparison and optimization of a variety of known general decisions, based on the needs of incompatible contradictions generated at various levels and stages, and then breaks through routine and expansive creative decision-making Skills, grasp the key strategies, maximize the satisfaction of the main system, incompatible contradictions into a compatible relationship, so as to achieve the overall best decision goal. It is a powerful means of resolving minor contradictions, solving major contradictions and key problems in complex systems, and will also make a significant contribution to the development of instrumentation's virtualization, networking and intelligence. Data fusion technology is a technical method for allocating different weights to the data measured by multiple information sources according to their importance and credibility in the entire system, and comprehensively calculating the overall optimal representation value of the characteristic attribute. It is an optimized measurement and characterization technology for the properties of complex things, which is of great significance to the research and development of high technology. In short, the intelligent technology in today's world is developing rapidly and comprehensively. Second, the application of intelligent technology in instrumentation and measurement The application of intelligent automation technology is infiltrating into the instrumentation industry. (1) Application in the improvement of instrumentation structure and performance First of all, intelligent automation technology has opened up broad prospects for the application of instrumentation and measurement related fields. Using intelligent software and hardware, each instrument or meter can accurately analyze and process current and previous data information at any time, properly abstract the measurement process from low, medium and high levels to improve the existing measurement system The performance and efficiency of the system extend the functions of traditional measurement systems, such as the use of intelligent technologies such as neural networks, genetic algorithms, evolutionary calculations, and chaos control, so that instruments and meters can achieve high-speed, high-efficiency, Multi-Function, high flexibility and other performance. Secondly, it is also possible to use microprocessors, microcontrollers and other microchip technologies in different instruments of distributed systems to design fuzzy control programs, set critical values ​​for various measurement data, and apply fuzzy inference techniques with fuzzy rules to deal with things. Various fuzzy relations make various types of fuzzy decisions. Its advantage is that it does not need to establish a mathematical model of the controlled object, nor a large amount of test data. It only needs to summarize the appropriate control rules based on experience, apply the offline calculation and on-site debugging of the chip, and produce an accurate one according to our needs and accuracy. Analyze and control actions on time. Especially in sensor measurement, the application of intelligent automation technology is more extensive. Using software to implement signal filtering, such as fast Fourier transform, short-time Fourier transform, wavelet transform and other technologies, is an effective way to simplify hardware, improve the signal-to-noise ratio, and improve the dynamic characteristics of the sensor, but it needs to determine the dynamic mathematical model of the sensor, and the high order The real-time performance of the filter is poor. Using neural network technology, high-performance autocorrelation filtering and adaptive filtering can be achieved. Make full use of the powerful self-learning, self-adaptive and self-organizing capabilities of artificial neural network technology, association, memory function and black box mapping characteristics between the input and output of nonlinear complex relationships, regardless of applicability and fast real-time All will greatly exceed the complex functional formula, which can make full use of multi-sensor resources and comprehensively obtain more accurate and credible conclusions. Among them, real-time and non-real-time, fast-changing and slow-changing, fuzzy and deterministic data information may support or contradict each other. At this time, the object features are extracted and fused until the final decision is made to make a correct judgment. Will be difficult. So neural network or fuzzy logic will become the most worthwhile method. For example, the gas sensor array is used for mixed gas identification. In the signal processing method, a self-organizing mapping network and a BP network can be used to classify first, then identify the components, and transform the whole process of the traditional method into a piecewise simulation. To reduce the complexity of the algorithm and improve the recognition rate. As another example, the difficulty of detecting and identifying food taste signals was once a major obstacle for research and development organizations. Now wavelet transform can be used for data compression and feature extraction, and then the data is input into the fuzzy neural network trained by genetic algorithm, which greatly improves the recognition rate of simple compound flavor. As another example, in the field of fabric quality assessment, flexible manipulator handling of tactile signals, and machine fault diagnosis, intelligent automation technology has also achieved a large number of successful examples. (2) Application in virtual instrument structure design The combination of instrumentation and measurement technology and computer technology has not only greatly improved the accuracy of measurement and the level of intelligent automation, especially the rapid development of computer hardware softening and software modularization of virtual instruments, as well as its unification with networked system resource programs Optimizing the performance configuration has created more and more superior conditions for the rapid improvement of the intelligent level of instruments and meters. In the design of instrumentation structures, instrument manufacturers used to provide users with intelligent virtual instrument plug-and-play instrument drivers in the form of source code. In order to simplify the end user's operation and development process, they have continuously improved operating efficiency, programming quality and Programming flexibility, related instrument manufacturers are based on the VXI plug-and-play bus instrument driver standard. Hedge-trimmer machine mainly includes gasoline engine, transmission mechanism, handle, switch and Blade mechanism, etc. The gasoline engine power drives the blade mechanism to work through the transmission mechanism, the main handle is located at the rear of the machine, the front handle is installed at the front of the machine housing, and the front handle can rotate at a certain Angle, which is characterized by: The main handle is connected with the main body of the machine through the telescoping rod, and the main handle is connected with the telescoping rod or the telescoping rod and the main body of the machine is connected by a rotating mechanism, the hedgerows machine also includes a pair of side handles, the two side handles are also connected by the telescoping rod and the telescoping mechanism is installed on the machine, and the machine is connected by the rotating mechanism. The operator can choose the grip mode, rotation Angle and expansion length of the handle according to the needs and use habits. The operation is simple, convenient, and the work efficiency is high, and the packaging size is small. Single Blade Hedge Trimmer,Hedge shears,Hedge Trimmer Shaoxing Haotuo Machinery CO., LTD. , https://www.haotuochinatools.com