CN108805300A - Numerically controlled machine remote live collaboration fault diagnosis and maintenance system - Google Patents

Abstract

The present invention relates to a remote real-time cooperative fault diagnosis and maintenance system for CNC machine tools. The remote fault diagnosis system is established by using LabVIEW virtual instrument technology, Node.js background server technology, streaming media technology and iOS mobile terminal technology to enable data collection, transmission and processing Integrated into a shared platform, the work of fault diagnosis experts is freed from the limitations of space and conditions, and the collected data is sent to a remote cloud server in real time through the network, and then stored and distributed by the cloud server. For real-time collaboration, a collaborative communication platform has been built to support real-time online text communication and picture and file sharing between on-site engineers and remote experts. At the same time, during on-site engineering, mobile devices are used to collect multimedia data such as pictures and videos of the fault site and send them to the cloud server. Remote diagnostic experts can view various multimedia data in real time. In addition, the system uses HTTPS encryption technology to ensure the safe transmission of data.

Description

Remote Real-time Collaborative Fault Diagnosis and Maintenance System for CNC Machine Tool

technical field

The invention relates to a CNC machine tool maintenance technology, in particular to a remote real-time collaborative fault diagnosis and maintenance system for a CNC machine tool based on cloud service technology.

Background technique

In the process of debugging and using CNC machine tools, fault diagnosis is a very important part, and it is one of the main factors that limit the normal operation of CNC machine tools. During the working process of CNC machine tools, they are subjected to various effects such as heat, force, friction, and wear. Their operating states are very complicated, and failures are inevitable. Therefore, it is necessary to make a quick and efficient judgment after a fault occurs, and take corresponding measures to solve the fault to avoid more serious economic losses due to the fault. This can greatly improve the operating reliability of the machine tool equipment, thereby improving the The productivity of the equipment and the entire enterprise.

Although many institutions and researchers have made considerable contributions and researches on the remote diagnosis of CNC machine tools, at this stage, relatively few companies in my country have launched remote diagnosis systems, and the expected results have not been obtained in the application. The reasons for this include: (1) lack of real-time performance: the real-time transmission of a large number of characteristic signal data at the fault site cannot be guaranteed; (2) lack of collaboration: it is difficult for remote diagnostic experts to communicate and collaborate effectively with field engineers in real time (3) Lack of intuition: It is difficult for remote diagnosis experts to judge the cause of machine failure based on machine tool operating data and sensor data, and requires more intuitive media data such as pictures, videos, etc. Auxiliary diagnosis; (4) Lack of security: due to the openness of the Internet, competitors are likely to use network system loopholes to steal business secrets and bring losses to the enterprise.

Compared with the traditional fault diagnosis in the past, the advantages of remote real-time collaborative diagnosis are reflected in enabling enterprises to obtain technical support immediately after a machine tool fails, and at the same time, CNC machine tool diagnosis experts can get first-hand information on enterprise equipment more quickly and effectively. data without having to visit the fault site. It provides a multi-faceted fault information sharing platform, communicates with machine tool operation site personnel, diagnostic experts, management departments and equipment manufacturers in a timely manner, serves the process of machine tool manufacturing, operation and maintenance, and makes full use of high-speed networks as information transmission carriers , Realized the collection, transmission and sharing of real-time faulty machine tool information, which greatly shortened the time for fault diagnosis.

The function of the remote real-time collaborative diagnosis system for CNC machine tools is to remotely diagnose the accidents and faults of CNC machine tools that occur in different places, mainly through the cooperation of on-site maintenance personnel and remote diagnosis experts. According to the status signal, fault information and on-site multimedia audio-visual signal of the running machine tool, the remote diagnosis experts can formulate the maintenance solution for the corresponding faulty equipment in time. The on-site maintenance personnel can adjust and repair the faulty equipment under the guidance of the remote diagnosis expert. until troubleshooting. Therefore, remote real-time collaborative diagnosis technology is a new technical field formed by the fusion of computer network technology, communication technology, signal processing technology, sensor monitoring technology, streaming media technology and other technologies.

The remote real-time collaborative diagnosis system of CNC machine tools provides a wide area network-supported fault collaborative diagnosis environment for multiple technicians and maintenance experts associated with tasks in different regions, enabling them to perform efficient and accurate diagnosis of a maintenance case at the same time and guide equipment maintenance . Specifically, it is the combination of signal processing and computer network programming technology. On the one hand, under the real-time guidance of remote experts, on-site maintenance personnel install sensors on faulty machine tools, and send the real-time collected signal data to the cloud server for further analysis. The cloud server performs the necessary data processing; on the other hand, multiple remote experts can view the maintenance site video and sensor real-time data through the web browser and guide the maintenance work of the on-site engineers, so as to realize rapid fault diagnosis and timely maintenance. To achieve the above requirements, the main functional requirements of the system design include: fault case tracking management, fault machine tool equipment characteristic signal collection and real-time display, fault site multimedia signal collection and sharing, fault site video real-time monitoring, online fault diagnosis communication platform, user manage.

Therefore, the main purpose and significance of researching the remote real-time collaborative diagnosis system of CNC machine tools is: 1) Diagnosis experts can complete fault diagnosis across regions, which improves the timeliness, accuracy and reliability of diagnosis; The case database trains enterprise technicians to improve their machine tool maintenance practice; 3) remote diagnosis can realize the sharing of diagnostic data and diagnostic knowledge worldwide; 4) diagnostic experts of scientific research institutions can obtain valuable on-site experience and data, Enrich theoretical and technical research.

Contents of the invention

The present invention is aimed at the importance of remote diagnosis of CNC machine tools, and proposes a remote real-time collaborative fault diagnosis and maintenance system for CNC machine tools, which realizes the integration of data collection, transmission and processing into a shared platform, and supports on-site engineers and remote experts. Real-time online text communication and picture and file sharing, remote diagnosis experts can view various multimedia data in real time, and ensure the safe transmission of data.

The technical solution of the present invention is: a remote real-time collaborative fault diagnosis and maintenance system for CNC machine tools, including three layers of upper and lower interaction,

The first layer of data layer: provide fault case data, storage and modification of sensor historical data, user-related data storage, and remote diagnosis data acquisition system for temperature sensors, current sensors, and vibration sensors to monitor vibration signals, current signals, and temperature signals of CNC machine tools , each signal is collected through the DAQ data acquisition card, the remote diagnosis data acquisition system transmits the data to the remote diagnosis cloud server system, and the cloud fault list is obtained according to the interface provided by the cloud server system;

The second layer of application logic layer: responsible for data processing and transmission between cloud server, remote sensor and fault diagnosis browser, including remote diagnosis cloud server system and remote diagnosis video monitoring streaming media server system, remote diagnosis mobile terminal system to realize streaming media Data acquisition, real-time acquisition and streaming of video signals at the fault site, remote diagnosis video monitoring streaming media server system adopts real-time mode, media file data is transmitted in the form of stream, stream data is cached in the client memory, real-time playback stream Data, realize playing while downloading;

The third layer of customer layer: directly enter the address through the web browser, realize the communication with the on-site maintenance engineer and diagnose the machine tool.

The remote diagnostic data acquisition system obtains the fault list of the cloud server, and then the on-site maintenance engineer selects the corresponding fault case to carry out the data collection work. The remote diagnostic data acquisition system Labview uses the HTTP protocol to communicate with the cloud server to obtain the fault list data. The HTTP network toolkit and Socket network toolkit under the cloud server realize the acquisition of the cloud fault list and the real-time transmission of sensor data according to the interface provided by the cloud server.

The remote diagnosis cloud server system adopts B/S architecture and adopts the model-view-controller design pattern; in the data layer, the Mongoose framework is used to operate the MongoDB database; the front-end logic and page effects of the cloud server based on Node.js adopt HTML5+CSS3+Bootstrap+AngularJS +Jquery+WebSocket to achieve; the background of the cloud server uses the Node.js-based web framework Express.

The remote diagnosis video monitoring streaming media server system adopts streaming media technology to realize audio and video data collection at the fault site, streaming transmission at the streaming media server end and audio and video acquisition at the remote expert playback end;

Audio and video data collection: collect the sound and image of the machine tool at the fault site, convert the collected audio and video data into byte codes, mix and compress them, and finally package them into audio and video formats, which is the so-called audio and video compression coding; the compressed audio and video data Video data, converted into code stream and then pushed to the streaming media server;

The stream transmission on the streaming media server side distributes and transmits the audio and video streams on the maintenance site to all viewers;

Acquisition of streaming media data at the playback end: the remote expert obtains the streaming media data of the streaming media server, and then parses, decodes, and plays the stream.

Described remote diagnosis mobile terminal system adopts Model-View-Controller framework, is divided into 5 parts, is interface UI layer, control layer, data layer, network layer and tool layer respectively;

Interface The UI layer is responsible for displaying various interfaces and is the expresser of data;

The control layer is the core, responsible for controlling the coordination between other layers and event control;

The data layer is responsible for data model definition and data persistence, chooses an appropriate way to store different data types and characteristics, and provides an appropriate interface to the outside world to store or extract data;

The network layer is responsible for encapsulating network requests, related services, and data processing and exposing a unified interface to the outside world.

The beneficial effect of the present invention is that: the remote real-time cooperative fault diagnosis and maintenance system of CNC machine tools of the present invention utilizes LabVIEW virtual instrument technology, Node. Acquisition, transmission and processing are integrated into a shared platform, freeing the work of fault diagnosis experts from the constraints of space and conditions, and sending the collected data to a remote cloud server in real time through the network, and then stored and distributed by the cloud server . For real-time collaboration, this system builds a collaborative communication platform to support real-time online text communication and picture and file sharing between on-site engineers and remote experts. At the same time, during on-site engineering, mobile devices can be used to collect multimedia data such as pictures and videos of the fault site and send them to the cloud server. Remote diagnostic experts can view various multimedia data in real time. In addition, the system uses HTTPS encryption technology to ensure the safe transmission of data.

Description of drawings

Fig. 1 is the function frame diagram of remote real-time cooperative fault diagnosis and maintenance system of numerical control machine tool of the present invention;

Fig. 2 is a system architecture diagram of the present invention;

Fig. 3 is a technical framework diagram of the cloud server of the present invention;

Fig. 4 is the key process of streaming media system of the present invention;

FIG. 5 is a software architecture diagram of the mobile terminal of the present invention.

Detailed ways

Fig. 1 is the functional frame diagram of the remote real-time collaborative fault diagnosis and maintenance system of CNC machine tools of the present invention. The main operating objects of the present invention are fault diagnosis and maintenance of various CNC machine tool models. The system adopts a three-layer system architecture, and the first layer is data The service layer mainly provides fault case data, storage and modification of sensor historical data, and user-related data storage; the second layer is the application logic layer, also known as the middle layer, responsible for the communication between cloud servers, remote sensors, and fault diagnosis browsers. Data processing and transmission; the third layer is the client layer. This system does not need to install the client program remotely, and can communicate with the on-site maintenance engineer and diagnose the machine tool remotely by directly inputting the address in the browser. Specifically, in order to realize the above system architecture, the present invention includes four subsystems. The data acquisition system mainly monitors vibration signals, current signals, temperature signals, etc.; the remote diagnosis cloud server system is mainly to realize fault case management, fault pictures, videos, File upload and sharing, real-time transmission of sensor data, and real-time communication; remote diagnostic video surveillance streaming media system is mainly to realize audio and video data collection, streaming media server-side streaming, and streaming media data acquisition at the playback end; remote diagnostic mobile terminal system, the system Based on the iOS mobile device platform, it realizes the shooting and uploading of fault scene pictures and videos, the collection and transmission of real-time streaming media signals, the display of fault lists and detailed information, and the push notification of the latest fault information.

The specific architecture of the whole system is shown in Figure 2. Specifically, it can be divided into three layers of upper and lower interaction. The first layer is the data layer, including MongoDB database and File file storage; data interaction with the middle layer mainly provides Fault case data, storage and modification of sensor historical data, and user-related data storage; the second layer of application logic layer, also known as the middle layer, includes remote diagnosis cloud server system and remote diagnosis video monitoring streaming media server system, responsible for cloud server, Data processing and transmission between remote sensors and fault diagnosis browser (client layer). This system is oriented to fault diagnosis of various CNC machine tool models. Therefore, external sensors and data acquisition equipment are used, and existing data acquisition cards, Sensors and LabVIEW virtual instruments realize the data collection of machine tool characteristic signals and transmit them to the cloud server. At the same time, in order to obtain on-site real-time video, streaming media data collection equipment is required. Therefore, a remote diagnosis client software system is designed on the mobile terminal to support fault diagnosis. Real-time collection and streaming of on-site video signals. At the same time, the software has functions such as failure case display, photo and video shooting and uploading, and failure information push reminder. . The third layer is the client layer. This system does not need to install the client program remotely. You can directly enter the address in the web browser to communicate with the on-site maintenance engineer and diagnose the machine tool remotely.

In order to achieve the above purpose, the data layer includes a remote diagnosis data acquisition system, which can not only transmit data to the remote diagnosis cloud server system, but also realize the acquisition of the cloud fault list according to the interface provided by the cloud server; the application logic layer includes the remote diagnosis cloud server System and remote diagnosis video monitoring streaming media server system; remote diagnosis mobile terminal system is to realize streaming media data collection, support real-time collection and streaming of video signals at the fault site, and the software has fault case display, photo and video shooting and uploading , fault information push reminder and other functions. in:

1. Remote diagnosis data acquisition system: use the virtual instrument integrated development environment Labview to develop data acquisition software, obtain cloud server fault case list data through HTTP protocol, and use streaming socket to send real-time data to cloud server.

Selection of remote diagnostic data source signals: There are many types and quantities of characteristic signals generated by CNC machine tools during work. In remote diagnosis, it is obviously not feasible to monitor all status signals, so the one that best reflects the characteristics of the machine tool should be selected. The signal is used as the basis for diagnosis, so as to achieve efficient and accurate fault diagnosis. The principle of data source signal selection can generally be used as characteristic parameters, and should have the following characteristics: (1) Sensitivity: The characteristic parameters should reflect the working state of the machine tool to the maximum extent. In the case of slight changes in the operating state of the machine tool, the characteristic parameters can Large changes can be produced, and can objectively reflect the state of the machine tool equipment; (2) Reliability: The characteristic parameters should show a certain law as much as possible with the state change of the machine tool under test, and have high reproducibility; (3) ) Feasibility: The measurement of characteristic parameters should be realistic and feasible, so as to be easily detected by sensors. In the present invention, combined with the existing hardware conditions, the system selects signals such as current, vibration and temperature to monitor the working status of the machine tool and its motor.

In the present invention, the selection of remote diagnostic data acquisition hardware includes temperature sensors, current sensors, vibration sensors, and DAQ data acquisition cards.

In the present invention, the remote diagnosis data acquisition software design is firstly the acquisition of the Labview failure case list, and the failure diagnosis must be aimed at a certain independent failure case, so it must also be aimed at a specific case in the process of collecting data, which requires the acquisition of cloud The fault list of the server, and then the on-site maintenance engineer selects the corresponding fault case for data collection. The Labview of this system uses the HTTP (HyperText Transfer Protocol) protocol to communicate with the cloud server to obtain the fault list data. HTTP is located in the application layer of the OSI seven-layer network model, and has the advantages of simplicity, speed, and flexibility. Using the HTTP network toolkit and Socket network toolkit under LabVIEW, according to the interface provided by the cloud server, the acquisition of the cloud fault list and the real-time transmission of sensor data are realized. Secondly, LabVIEW sensor data is processed before sending sensor data to the server. Before sending sensor data to the server, the server must be notified of the fault cases corresponding to these data. Therefore, this acquisition system uses the GET request of the HTTP protocol to send the fault case id to the server, and the server will Be able to understand the fault cases corresponding to the following monitoring data. Finally, Labview sends the sensor data. We used the HTTP protocol to exchange data with the cloud server before, but HTTP is stateless. Every time the client and server perform an HTTP operation, a connection is established, but the connection is interrupted after the task is over. Less than high real-time requirements. The collected sensor signal is a continuous signal, obviously HTTP is not suitable for such a scene, so we need to use the Socket interface. In the network model, it is the interface of the middle software abstraction layer between the application layer and the transport layer. The Socket interface defines a lot of network connection APIs, so that programmers can easily use them to develop applications on the TCP/IP network.

2. Remote diagnosis cloud server system: It needs to meet the functional requirements and performance requirements. The functional requirements include: fault case management, fault-related pictures, videos, file upload and sharing, real-time sensor data, and real-time communication. Performance requirements include: real-time, openness, and scalability.

In the present invention, the remote diagnosis cloud server system adopts B/S architecture. In order to reduce the coupling degree between the UI layer, logic layer and data layer, the cloud server system adopts Model-View-Controller (Model-View-Controller) design mode, the overall architecture is shown in Figure 3.

In the data layer, we use the Mongoose framework to operate the MongoDB database. Mongoose is a framework for creating relationships between JavaScript objects and databases, and can be used to connect Node.js and MongoDB.

The front-end logic and page effects of the Node.js-based cloud server are mainly realized by HTML5+CSS3+Bootstrap+AngularJS+Jquery+WebSocket. HTML+CSS completes page typesetting, WebSocket completes real-time data transmission, AngularJS+Jquery is used for dynamic binding of page data, and Ajax technology is used to ensure timely response to user interaction, so as to achieve good user interaction effect.

The background of the cloud server adopts Express, a web framework based on Node.js. The Express framework does a lot of underlying work for us in request parsing, so that we can focus on the coding of business logic and improve the efficiency of development. The Express framework is also based on the MVC (Model-View-Controller) design pattern, and supports RESTful-style Web applications and routing management.

3. The remote diagnosis video monitoring streaming media system adopts real-time mode, which is the so-called streaming media technology. The media file data is transmitted in the form of streaming, and the streaming data is cached in the client memory, and then the streaming data is played in real time, realizing The effect of playing while downloading. In the remote maintenance system of CNC machine tools, in order to allow maintenance experts to remotely guide the maintenance process in real time, the system uses streaming media technology to collect audio and video data at the fault site and push them to the server, and the front end of the web page can pull real-time Audio and video data.

The architecture design of the streaming media system considers the following scenarios: maintenance personnel repair at the machine tool failure site, output the audio and video information of the failure site to the network through the camera and microphone, and many machine tool maintenance experts watch the maintenance process in real time through the Internet in various places. There are several key points here: audio and video data collection at the fault site, streaming transmission at the streaming media server, and audio and video acquisition at the playback end of the remote expert.

(1) Audio and video data collection, first of all, the sound and image of the machine tool at the fault site must be collected, which is the so-called audio and video collection; the collected audio and video data needs to be converted into byte codes, mixed and compressed, and finally packaged into some kind of audio and video The format is the so-called audio and video compression coding; the encoded and compressed audio and video data cannot be directly transmitted on the network, and needs to be converted into some kind of code stream such as RTMP, and then pushed to the streaming media server.

(2) The stream transmission on the streaming media server side distributes and transmits the audio and video streams on the maintenance site to all viewers.

(3) Acquisition of streaming media data at the playback end, the remote expert obtains the streaming media data of the streaming media server, and then parses, decodes and plays the stream.

Therefore, according to the analysis of the above key points, the key flow of the streaming media system is shown in Figure 4.

First of all, the selection of the transmission protocol of the remote diagnosis streaming media system, in order to realize the transmission of media stream data between each end, each end must abide by the relevant application layer protocol. As a key component of the streaming media system, the streaming media transmission protocol plays an indispensable role in the streaming media system. Currently, the common streaming media real-time transmission protocols include HTTP (HyperText Transfer Protocol)-FLV protocol, RTMP (Real Time Messaging Protocol) protocol and HLS (HTTP Live Streaming) protocol.

Secondly, the server of the remote diagnosis video surveillance streaming media system, the streaming media server provides users with an audio and video streaming data distribution platform, it is mainly responsible for receiving streaming media data and buffering it in memory for other terminals to pull streaming media data. The streaming media server implements functions such as receiving, caching, transferring and transmitting streaming media data. Typical streaming media servers include SRS, CRTMP, nginx-rtmp, Red5, FMS, etc. By comparison, in this system we choose the Nginx-RTMP streaming media server with superior performance and good stability. The key steps for the deployment of the streaming media server are: download and install nginx, download and install the extended rtmp module of Nginx, after the installation is complete, we enter the command to check the version number of nginx in the terminal, and configure the RTMP module.

Finally, realize the front-end playback of the remote diagnosis webpage. On the player of the front-end webpage, we choose Video.js. Video.js is a web player class library that supports playing video through HTML5, and it will automatically switch to Flash playback if HTML5 is not supported. It is very simple to use Viedeo.js to play the video stream of RTMP protocol. We only need to specify its video address and the size and position of the player to easily obtain the video stream of the server.

4. Remote diagnosis mobile terminal system, developed and designed remote diagnosis client software on the iOS mobile terminal, the software supports real-time collection and streaming of video signals at the fault site, and the software has fault case display, photo and video shooting and uploading , fault information push reminder and other functions.

In order to reduce the coupling of each logical level in the software, the terminal software adopts the MVC (Model-View-Controller) architecture. The entire terminal software can be roughly divided into five parts, namely the interface UI layer, control layer, data layer, and network layer. and tool layers. The specific architecture is shown in Figure 5.

The data layer is responsible for data model definition and data persistence. For different data types and characteristics, we need to choose an appropriate way to store and provide an appropriate interface to the outside world to store or extract data.

Interface The UI layer is mainly responsible for displaying various interfaces and is the expresser of data. When designing this layer, attention should be paid to reflect the data as comprehensively and beautifully as possible, and to adapt to devices of different sizes.

The control layer is the core of the entire terminal software design, and it is mainly responsible for controlling the coordination between other layers and event control. First of all, when an event occurs (such as a user click), it controls to get the corresponding data from the data layer or initiate a request using the network layer. After obtaining the data, it hands the data to the interface layer for display. It can be said that the control layer plays the role of steward of the data flow, controlling the data flow of the entire terminal software.

The network layer is responsible for encapsulating network requests, related services, and data processing and exposing a unified interface to the outside world. The focus of network layer design is the unified management of HTTP requests, and the unified control and data analysis of request parameters and result callbacks.

Claims (5)

1. a kind of numerically controlled machine remote live collaboration fault diagnosis and maintenance system, which is characterized in that three including upper-lower interactive Layer,

First layer data Layer：Fault case data, the storage of sensor historic data and modification, user related data is provided to deposit It stores up, temperature sensor, current sensor, vibrating sensor monitor Vibration of Computerized Numerical Control Machine respectively in remote diagnosis data collecting system Signal, current signal, temperature signal acquire each signal by DAQ data collecting cards, and remote diagnosis data collecting system is by data It is transmitted to remote diagnosis cloud server system, the interface provided according to cloud server system realizes obtaining for high in the clouds error listing It takes；

Second layer application logical layer：The data processing being responsible between cloud server, distance sensor and fault diagnosis browser And transmission, including remote diagnosis cloud server system and remote diagnosis video monitoring streaming media server system, remote diagnosis Mobile terminal system realizes stream medium data acquisition, the real-time acquisition of fault in-situ vision signal and plug-flow, remote diagnosis video It monitors stream media server system and uses real-time mode, media file data is to be transmitted in the form of streaming, stream data cache In client's end memory, flow data is played in real time, is realized and is played when downloading；

Third layer client layer：Directly by web browser input address, the communication with FE field engineering teacher is realized and to lathe Diagnosis.

2. numerically controlled machine remote live collaboration fault diagnosis and maintenance system according to claim 1, which is characterized in that described Remote diagnosis data collecting system obtains the error listing of cloud server, and then FE field engineering teacher selects corresponding failure Case carries out data collection task, and remote diagnosis data collecting system Labview is carried out using http protocol and cloud server It communicates to obtain error listing data, using the http network kit and Socket network tool packets under LabVIEW, according to cloud The interface that server provides is held to realize the real-time Transmission of the acquisition and sensing data of high in the clouds error listing.

3. numerically controlled machine remote live collaboration fault diagnosis and maintenance system according to claim 1, which is characterized in that described Remote diagnosis cloud server system uses B/S frameworks, and pattern is designed using model-view-controller；In data Layer, use Mongoose frames operate MongoDB databases；The logic and the page of the front end of Cloud Server based on Node.js are imitated Fruit is realized using HTML5+CSS3+Bootstrap+AngularJS+Jquery+WebSocket；After cloud server Platform uses the web page frame Express based on Node.js.

4. numerically controlled machine remote live collaboration fault diagnosis and maintenance system according to claim 1, which is characterized in that described Remote diagnosis video monitoring streaming media server system use stream media technology, realize fault in-situ audio, video data acquisition, The audio and video that the steaming transfer and Remote at streaming media server end play end obtain；

Audio, video data acquires：The sound and image of fault in-situ lathe are acquired, the audio, video data after acquisition is converted into byte Code is mixed and is compressed, and is finally packaged into audio and video format, is exactly so-called audiovisual compression coding；Compressed sound is encoded to regard Frequency evidence is converted into code stream and then plug-flow to streaming media server；

The audio/video flow distribution of maintenance sites is transferred to all viewers by the steaming transfer at streaming media server end；

The stream medium data for playing end obtains：Remote obtains the stream medium data of streaming media server, and then convection current carries out Parsing decoding plays.

5. numerically controlled machine remote live collaboration fault diagnosis and maintenance system according to claim 1, which is characterized in that described Remote diagnosis mobile terminal system uses Model-View-Controller frameworks, is divided into 5 parts, is interface UI respectively Layer, control layer, data Layer, network layer and tool layer；

Interface UI layers is responsible for the various interfaces of displaying, is the expresser of data；

Control layer is core, is responsible for controlling the co-ordination between other each layers and event control；

Data Layer is responsible for the work of data model definitions and data persistence, and for different data type and characteristic, selection is closed Suitable mode is stored, and is supplied to extraneous suitable interface to store or extract data；

Network layer is responsible for being encapsulated the processing of network request, related service, data and to the unified interface of extraneous exposure.