Research And Application Of Intelligent Help System For Instrument Software

With the development of computer technology,artificial intelligence technologies such as deep learning are also advancing rapidly,and the application of artificial intelligence is becoming more and more extensive.In the field of instrumentation,important experiments such as circuit diagram drawing,simulation,and data processing have also been gradually transferred to computers.Computer software related to the professional field is constantly updated with more and more functions.The numerous functions of the software directly lead to an increase in the learning cost of users,and problems such as low utilization of software functions have also appeared.Therefore,the application of artificial intelligence technology such as deep learning to guide users to learn and use related software will be able to reduce the software learning costs of practitioners,improve work efficiency,and promote the development of the industry.After analyzing the research status of human-machine dialogue system,deep learning natural language processing,real scene omission recovery,and software help system at home and abroad,this paper proposes an intelligent help system based on real scene information,and analyzes the real scene omission recovery in the intelligent software help system,then constructs an omission recovery model based on real scene information and an model of the intelligent software help system,and uses deep learning and other technologies to conduct experiments.In the help system development process,using HOOK technology,deep learning OCR recognition technology,and deep learning BERT model.Through experiments such as program development,parameter configuration,model training,etc,real scene information of the help system is obtained,including software button names,button functions,operation steps,software displayed on the current interface of the computer,software currently running on the computer,and buttons currently clicked by the mouse,and use the obtained button information to build a button tree using the tree structure;due to the lack of existing deep learning data sets,this paper proposes A method to automatically generate a data set is completed by defining rules for omission and recovery,combined with real scene information,to complete the automatic generation of deep learning data sets.In addition,in terms of data set construction,crawling technology is also used to crawl data on related websites,in order to expand the data set;this paper uses the Rasa open source framework to help the system text dialogue,through data preprocessing,strategy configuration,custom actions based on real scene information,etc,the training of the Rasa model is completed,and it is generated in the form of a front-end interface text dialog;the mouse single-step demonstration function of the help system is designed and the function is realized through program development,which makes the guidance of the help system more intuitive.Finally,the intelligent software help system is applied to the circuit diagram design and simulation process,and the prototype system of the intelligent software help system is developed for Multisim software.Through the guidance method combining text dialogue and mouse single-step demonstration,it helps users to use Multisim software to complete the design of the Chebyshev low-pass filter,it verifies the feasibility of the help system model.