Abstract: This paper introduces the types of FF fieldbus intelligent instruments and function block technology. It presents the configuration methods and precautions for FF intelligent instruments in common control loops, and explains the advantages and characteristics of FF intelligent instruments. Keywords: FF fieldbus; Intelligent instrument; Function block ; Configuration 1 Introduction The development of fieldbus technology has promoted the digitization, intelligence, and networking of field instruments. Since China's "Ninth Five-Year Plan" for key technologies, the development of HART and FF protocol intelligent instruments and systems has progressed rapidly and achieved relevant results. However, because fieldbus is a new technology, and FF intelligent instruments have many configuration parameters, the requirements for the professional knowledge and technical level of field commissioning and maintenance personnel have increased. Therefore, this article introduces FF smart instruments and their configuration technology from the perspective of practical application, so as to facilitate the promotion and application of FF smart instruments. 2 FF Smart Instruments FF smart instruments are instruments with functions such as sensing measurement, digital communication, automatic compensation, automatic diagnosis, distributed control, and information storage. At present, the most common types and uses of FF fieldbus smart instruments in the world are as follows. (1) IF meter, also known as "current signal to fieldbus signal transmitter", converts 4-20mA current signal into fieldbus signal, which is used to connect the traditional 4-20mA output analog instrument to the fieldbus control system. It is suitable for the transformation of enterprise control system, which can protect the user's original available analog instrument resources to a large extent and reduce user investment. (2) FI meter, also known as "fieldbus to current signal transmitter", converts fieldbus signals into 4-20mA current signals. It is used to connect fieldbus control equipment with instruments that require 4-20mA current input signals. It is also a control signal conversion device for fieldbus and 4-20mA current control actuators and control devices. It is suitable for connecting fieldbus control systems with 4-20mA electrical converters or electric regulating valves. It is beneficial to retain usable actuators in the transformation of enterprise control systems. (3) TT meter, also known as "fieldbus temperature transmitter", converts PT100, CU50 and other thermal resistance signals into fieldbus signals. It is suitable for the acquisition of temperature signals in fieldbus control systems. (4) PT meter (LD), also known as "fieldbus intelligent pressure transmitter", converts pressure signals into fieldbus signals. It is suitable for the acquisition of pressure, flow, liquid level and other signals in fieldbus control systems. (5) FP meter, also known as "fieldbus to pneumatic signal converter", converts the input signal received from the bus into a 3-15psi air pressure signal and connects it to a non-fieldbus type pneumatic valve positioner to replace the analog electro-pneumatic converter and control the pneumatic valve in the system. (6) FY meter, also known as "fieldbus pneumatic valve positioner", converts the fieldbus signal into the corresponding pressure output to control the valve to the required position and realize the positioning control of the pneumatic valve. 3 Function Blocks A function block is a complete composition of parameters, algorithms and events. It is defined by input parameters, output parameters, internal parameters and operation algorithms, and is identified by a tag and an OD index. The execution of a function block is either periodically scheduled or event-driven. The external connection structure of a function block is universal, with a set of input parameters on the left and a set of output parameters on the right. Different function blocks are mainly different in terms of the internal execution algorithm and the functions implemented. The FF fieldbus smart instrument contains 10 standard function blocks, as shown in Table 1. 4. FF Instrument Configuration Technology 4.1 Function Block Connections The key to configuring a fieldbus control system is configuring the function block parameters in the fieldbus devices, combining and connecting function blocks, and adjusting function block scheduling parameters. This section uses PID control and cascade control, which are widely used in the process industry, as examples to introduce the FF intelligent instrument configuration method. During configuration, the input parameter of one function can only be connected to the output parameter of another function block, and the output parameter can only be connected to the input parameter of another function block. The function block connections for PID control and cascade control are shown in Figures 1 and 2. 4.2 Configuration of Main Function Block Parameters This section uses the cascade control of coke oven gas main pipe pressure and flow in a coking plant as an example to introduce the configuration of the main parameters of the FF intelligent instrument function blocks. The cascade control of coke oven gas main pipe pressure and flow adjusts the opening of the main pipe flap by detecting the pressure and flow of the main gas pipe. Pressure control is the main loop, and flow control is the secondary loop. The control loop instruments and detection parameters are shown in Table 2. Referring to Figure 2, the parameter configurations of each function block are shown in Tables 3-5. FF intelligent instruments exhibit strong anti-interference capabilities, remote calibration, self-diagnostic functions, and convenient connection in control systems, and have broad application prospects. 4.4 Configuration Precautions (1) Each time the instrument function block parameters are modified, the target mode of the function block must first be selected as OOS (Out Of Service). The parameters can only be changed when the actual mode of the instrument is in OOS. After the change, the target mode of the function block should be selected as Auto or other required states. (2) When the actual mode of the PID function block is "IMAN" or switching between "IMAN" and "AUTO", it indicates that there is a problem with the communication between the PID and AO function blocks. This can be eliminated by adjusting the scheduling interval of the function blocks. (3) If the device comes online with a temporary address, it indicates that the device has a conflict with the address of other devices on the bus. Changing its address to an unused available address on the bus will solve the problem. (4) Functional blocks such as AI, AO, and PID that are useful to the system must be added to the function block scheduling application and downloaded to the instrument. Otherwise, the actual mode of the function block will not be able to leave the OOS state and enter Auto0.9559. When the optimal classification matrix is ​​obtained, the original data is divided into 7 categories: {1}, {2, b, c}, {3}, {4}, {5}, {6, a}, {7}. The classification matrix at this time is as follows: Further calculations are performed on the above classification results to obtain the final classification matrix and the final cluster center: Final classification matrix: In the final cluster: According to the above analysis, the diagnostic results are: Data a indicates that the angle limiter is malfunctioning, and data b and c indicate that the control board has a fault. Based on this, engineers can formulate methods and steps to troubleshoot the fault, thereby quickly eliminating the discovered fault. It can be seen that this method is easy to implement in real-time and intelligent fault diagnosis. Case studies show that the theoretical calculations and field inspection results are consistent. This demonstrates that the method has good practical application prospects and provides a good approach for fault diagnosis of complex systems. 3. Conclusion This paper discusses a new method for fault diagnosis of the electric transmission device of a self-propelled rocket launcher. This method, through fuzzy theory, can utilize uncertain or incomplete knowledge from human subjectivity and practical experience, thereby successfully and accurately classifying and determining the fault type. In rocket launcher training, once a fault occurs, this method can quickly and accurately determine the fault type. Operators can then take appropriate measures to quickly eliminate the fault based on the fault type, greatly improving the technical support capability of the rocket launcher and yielding significant economic and military benefits.