LIU Xiao-li, FEI Ren-yuan 2, WANG Min 2, SHI Yan-peng 3 (1. Beijing Institute of Mechanical and Electronic Engineering, Beijing University, Beijing, China The filtering of the vibration signal in the instrument environment is processed by the wavelet intelligent analysis method, which is a new direction in the field of diagnosis.The whole analysis process adopts discrete wavelet transform (DWT) dual channel filtering, optional window function, signal time domain, spectrum In other methods, and calculating the vibration intensity sliding average, as shown, the use of the on-site operating state shows that the introduction of wavelet transform signal processing method brings more accurate and comprehensive signal analysis results.
The use of discrete wavelet transform to process the vibration signal is a typical two-channel full reconstruction filter bank. The signal X(z) is filtered by the filters G, (z) and G(z) in the two channels in the analysis section and then extracted by â€œseparating 1 by 1â€ to obtain the scale and resolution of 1/2 respectively. The approximation signal (low-pass signal) and detail signal (high-pass signal). In the synthesis part, the low-pass approximation signal and the high-pass detail signal are doubled to 1 (the resolution still remains 1/2) through the interpolation operation in the two channels, and finally the original signal XT is added, as shown.
The spectrum processing of the vibration signal by the dual-channel filter is processed by the LabVIEW wavelet analysis package, which can fully reflect the relationship among the vibration signal in time, frequency, and amplitude.
1.3 The realization of long-distance communication technology With the development of Internet technology, the development of the virtual instrument must also develop in the direction of the network. Future instrument testing work often needs to be conducted in the network, so the network virtual instrument will have unlimited development prospects. DataSocket technology is NI's original network real-time communication technology. It eliminates complicated TCPP programming and real-time data transmission, providing advanced scientific research methods for remote monitoring and control. The formation of an intelligent measurement and control network usually has two modes: C/S mode (client/server mode) and B/S mode (browser/server mode). The C/S mode data transmission has good real-time performance. The data can be processed and stored at the remote site with great flexibility. Due to the database technology, the B/S model has a large amount of data storage and is easy to query.
In the remote fault diagnosis, the vibration signal changes rapidly, the data is required to be analyzed at the remote end, and the C/S mode is easily used. For signals such as pressure and temperature that do not require remote processing, the B/S mode is easy to use. The research and development system will organically combine the two to give full play to their respective advantages for remote monitoring.
National Instruments DataSocket Technology is a new technology for online real-time high-speed data exchange programming for measurement and automation engineering. It overcomes the shortcomings of slow transmission speeds and greatly simplifies the programming of the Internet's measurement and control data exchange. The DataSocket Server can connect to the maximum number of client programs and the maximum number of data items that can be created, create user groups and users, set user permission to create data items and read and write data items, and facilitate the formation of intelligent monitoring and control networks. DataSocketServer is also an independently running applet that supervises the exchange of data between various privileges set in DataSocketManager and client programs.
Each computer can read the data on the server. Run the DataSocketServer on the measurement side, and then, as needed, the data is written to one or more of the following items. The client can read the data items of the required VW over the network to obtain real-time measurement data.
1.4 Signaling (Semaphore) Implementation of Parallel Execution Resource Allocation In parallel execution, the user encounters a shared resource with several VI calls at the same time. In this system, the online monitoring system collects data periodically, and the remote analysis and processing system also The data needs to be calculated and stored at regular intervals. In this way, if the resource is accessed by several VIs asynchronously or in an inappropriate order, the system may be damaged. This problem is called the phenomenon of race.
To achieve long-range transfer of large amounts of data, a more reliable and convenient method is to use global variables. Global variables also bring troublesome shared resources. When we need to maintain a global variable database, there may be many VIs that need to access the database. The moment exists in the "read, update, write" cycle. These issues have no protection in the built-in LabVIEW global variables. This program uses signals to protect data global variable access permissions. It follows a standard sequence of events: creating a signal, waiting for the signal to work, running a critical section, and then releasing the signal. The elimination signal tells other users that they should stop using it. Because signalling provides a way to protect code-critical sections, code-critical sections do not allow simultaneous access from parallel invocation VIs. In this way, the contradiction between reading the data of each unit from the on-site monitoring system and updating the data on-site is well solved.
2 The main achievements of the system (sepends on the specific requirements of industrial field unit fault diagnosis, extends the LabVffiW system that complies with laboratory signal monitoring and analysis, and establishes monitoring systems such as data acquisition, database storage, signal analysis, and fault diagnosis. Improves system reliability and measurement accuracy; (2) Under virtual environment, the requirements for long-distance communication under network communication have been successfully achieved, and online remote monitoring requirements have been met; (3) Due to the large amount of data sampled on site, in order to avoid the emergence of the phenomenon of race state, The method of semaphore to realize the parallel execution of resource allocation is proposed, and the diagnostic database is ideally established. (4) The intelligent signal processing method of time-frequency analysis is introduced to achieve the expected effect of the theory applied in practice; (5)) Realize the scene Report generation and printing of monitoring data can print production reports and failure reports according to site requirements, and provide modern scientific management methods for production departments.
3 Conclusion Through the above description, we can understand the realization of virtual instrument technology to achieve machine monitoring and fault analysis methods, the introduction of wavelet analysis methods, can further improve the accuracy of fault diagnosis, especially for on-site industrial monitoring requirements, accurate diagnosis The method is even more important. As a graphical programming software, LabVIEW is a powerful and convenient programming tool for the development of virtual test systems. In the development of large-scale unit monitoring systems, we must pay particular attention to the rational allocation of system resources and the avoidance of the phenomenon of unexpected phenomena. With the development of computer technology, networked condition monitoring and fault diagnosis have achieved certain results, and remote network monitoring and analysis technologies have received increasing attention. According to research in this area at home and abroad, this system needs to be further improved and strengthened. The appearance of some new intelligent network analysis methods will further enhance the monitoring and diagnosis effect and speed.
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