DSDO115A 3BSE018298R1  | 控制模块   | DSDI110AV1 3BSE018295R1

　　型号:DSDO115A 3BSE018298R1

　　类别:控制模块

　　成色:全新/非全新

　　快递:顺丰/德邦

　　质保:一年

　　货期:现货

　　产品净深:350 mm

　　产品净高:20 mm

　　产品净宽:255 mm

　　产品净重:0.44 kg

　　DSDO115A 3BSEO18298R1 ABB DCS系统 控制模块中，仪器仪表作为其构成元素，它的技术进展是跟随控制系统技术的发展而发展的。目前，控制理论已发展到智能控制的新阶段，自动化仪器

　　仪表的智能化就成为必然了。

　　仪器仪表的智能化主要归结于微处理器和人工智能技术的发展与应用。

　　例如运用神经网络、选传算法、进化计算、混沌控制等智能技术，使仪器仪表实现高速、高效、多功能、高机动灵活等性能。

　　再如，运用模糊规则的模糊推理技术，对事物的各种模糊关系进行各种类型的模糊决策。

　　又如，用软件实现信号滤波，如快速傅立叶变换、短时傅立叶变换、小波变换等技术，是简化硬件，提高信噪比，改善传感器动态特性的有效途径.

　　还如，充分利用人工神经网络技术强有力的自学习、自适应、自组织能力，联想、记忆功能以及对非线件复杂关系的输入、输出间的里箱映射特件等,。

　　Model :DSDO115A 3BSE018298R1

　　Category: Control module

　　Finish: New/not new

　　Express: SF Express/Debon

　　Warranty: One year

　　Delivery time: from stock

　　Product depth :350 mm

　　Product height :20 mm

　　Product net width :255 mm

　　Net weight: 0.44kg

　　DSDO115A 3BSEO18298R1 ABB DCS system control module, instrumentation as its constituent elements, its technical progress is to follow the development of control system technology and development. At present, control theory has developed to a new stage of intelligent control, automated instruments

　　The intelligence of the instrument becomes inevitable.

　　The intelligence of instrumentation is mainly attributed to the development and application of microprocessor and artificial intelligence technology.

　　For example, intelligent technologies such as neural network, selective transmission algorithm, evolutionary computing, chaos control are used to make instruments achieve high speed, high efficiency, multi-function, high mobility and flexibility.

　　Another example is to use fuzzy reasoning technology of fuzzy rules to make various types of fuzzy decisions for various fuzzy relations of things.

　　For another example, using software to realize signal filtering, such as fast Fourier transform, short-time Fourier transform, wavelet transform and other technologies, is an effective way to simplify hardware, improve signal-to-noise ratio, and improve the dynamic characteristics of sensors.

　　Also, make full use of the strong self-learning, self-adaptation, self-organization ability of artificial neural network technology, association, memory function, and the box mapping feature between the input and output of the complex relationship between non-linear parts.