Remote grinding database management system of user-foundation-process-knowledge progressive structure and efficient low-consumption intelligent grinding method

[0031] DETAILED DESCRIPTION figure 1 , Detailing a remote grinding database management system for a user-foundation-process-knowledge process, the user-foundation-process-knowledge-based remote grinding database management system top-term utilization program development environment LabVIEW Grinding the database management system, the front processor (1-5) and the post-processor (1-6), using data management software SQL Server management underlayer grinding user data (1-1), grinding processing basic data (1- 2), grinding process dynamic data (1-3) and grinding process knowledge data (1-4), the program development environment LabVIEW and data management software SQL Server interface is implemented by LabVIEW Open Software Toolkit Labsql.

[0032]The user-foundation-process - the underlying data of the remote grinding database management system of the knowledge process structure includes four layers of delivery data management structure, the first layer data structure is grinding user data (1-1), specifically user Permissions Authorize and track grinding user data, the user rights include database users (1-1-1), database designers (1-1-2), database maintenance (1-1-3) and database Advanced Managers (1-1-4), the second layer data structure is grinding processing base data (1-2), including grinding machine data (1-2-1), abrasive data (1-2-2) , Grinding liquid data (1-2-3) and grinding processing target data (1-2-4), the third layer data structure is the dynamic data of the grinding process (1-3), including the spindle power real-time monitoring data. (1-3-1) and feature extraction from the spindle power real-time monitoring data (1-3-1) obtains spindle power characteristic data (1-3-2), the spindle power feature data (1-3- 2) includes initial threshold power (1-3-2-1), net material removal energy (1-3-2-2), net material removal power peak (1-3-2-3), processing energy Consumption (1-3-2-4), processing time (1-3-2-5), the fourth layer data structure is grinding process knowledge data (1-4), including optimal grinding process parameters (1- 4-1), the most superior sand wheel trimming strategy (1-4-2), grinding wheel passivation state threshold power (1-4-3) and threshold specific to milling energy (1-4-4), grinding burns threshold power (1-4-5).

[0033] The remote grinding database management system of the user-foundation-process-knowledge process is included, including two processors, pre-processors (1-5), and rear processors (1-6), the front processor (1 -5) Includes server-side application interfaces (1-5-1), mobile client application interface (1-5-2) and network service cloud (1-5-3), in the server-side application interface (1-5-1) Realize the management and grinding processing basic data (1-2) management, requiring database users (1-1-1) to manually edit, input, or import regular paradigms .Txt, .excel, .tdms, .jpg, .bmp format file, the mobile client application interface (1-5-2) implements grinding process dynamic data (1-3) management, requires database Users (1-1-1) specify the spindle power real-time monitoring data (1-3-1) to store .TDMS or .LVM format storage, and extract data (1-3-1) from the spindle power in real time Spindle power characteristics (1-3-2), realize grinding process knowledge data (1-4) management in network service cloud (1-5-3), the server-side application interface (1-5-1) , Mobile client application interface (1-5-2) and network service cloud (1-5-3) three inter-three data transfer is implemented by TCP / IP protocol, the remote grinding database management system post-processor (1 -6) Including database query, insertion, editing, deletion, update, constraint, threshold alarm, and data protection basic functions (1-6-1), data matching function (1-6-2), dynamic stream data compression processing function ( 1-6-3), power signal feature extraction (1-6-4), and intelligent decision optimization functions (1-6-5).

[0034] DETAILED DESCRIPTION 2: Combined with figure 2 Detailed description of a high-efficiency low-cost smart grinding method using a remote grinding database management system using a user-foundation-process-knowledge process, including the following steps:

[0035] Step 1 (S2.1): Database user (1-1-1) Enter the ground processing base data (1-2) in the server-side application interface (1-5-1);

[0036] Step 2 (S2.2): Call the data matching function (1-6-2), automatically compare the network service cloud (1-5-3), suitable for grinding processing object data (1-2-4) Excellent grinding process parameters (1-4-1) and the best sand wheel trim strategy (1-4-2), if the information match fails, jump to step 3 (S2.3), if the information matches success, jump to Step 7 (S2.7);

[0037] Step 3 (S2.3): Remote grinding database management system feeds the system authority to the database designer (1-1-2), performing a full-factor grinding process;

[0038] Step 4 (S2.4): The remote grinding database management system feeds the system authority to the database user (1-1-1), and the experimental data sample is constructed according to the full factor grinding and processing experiment.

[0039] Step 5 (S2.5): Remote grinding database management system feeds the system authority to the database designer (1-1-2), call intelligent decision optimization functions (1-6-5), processing energy consumption (1- 3-2-4) and the machining time (1-3-2-5) for the target for efficient low grinding process decision, intelligent acquisition process knowledge data (1-4), and serve the cloud in the network (1- 5-3) Storage grinding process knowledge data (1-4);

[0040] Step 6 (S2.6): Remote grinding database management system feeds system authority to database users (1-1-1);

[0041] Step 7 (S2.7): Network service cloud (1-5-3) passes the grinding process knowledge data (1-4) to the mobile client application interface (1-5-2) through the TCP / IP Data Transfer Protocol (1-5-2) );

[0042] Step 8 (S2.8): Grinding is performed according to the optimal grinding process parameters (1-4-1), the optimal sand wheel trimming strategy (1-4-2).

[0043] Step 9 (S2.9): Mobile Client Application Interface (1-5-2) Monitor the spindle power signal in grinding processing in real time, call dynamic stream data compression processing (1-6-3) to the spindle power signal After compression processing, stored as a spindle power real-time monitoring data (1-3-1), and call the power signal feature extraction function (1-6-4) to extract the spindle power characteristic data (1-3-2);

[0044] Step 10 (S2.10): Call data matching function (1-6-2), perform initial threshold power (1-3-2-1), net material removal energy (1-3-2-2) To determine whether the grinding wheel is passivated, if the grinding wheel is passivated, if the grinding wheel is passed, if the grinding wheel is passed, if the grinding wheel is passed down to step 11 (S2.11) If the grinding wheel is not passivated, the net material removal power peak (1-3-2-3) is compared with the grinding burn threshold power (1-4-5), and it is determined whether or not the grinding burns occur, if not adjacent to occur After grinding, returning to step 8 (S2.8) continues to perform grinding processing; if grinding burn occurs, jump to step 12 (S2.12);

[0045] Step 11 (S2.11): Call the intelligent decision optimization function (1-6-5), get the grinding wheel to improve the optimization strategy, and return to step 8 (S2.8) to adjust the best sand wheel trimming strategy in real time (1-4-2) Grinding, and temporarily store the optimized optimal sand wheel trimming strategy (1-4-2) to mobile client application interface (1-5-2);

[0046] Step 12 (S2.12): Call the intelligent decision optimization function (1-6-5), get the grinding process parameter optimization strategy, and return to step 8 (S2.8) Real-time adjustment optimal grinding process parameters (1-4 -1), perform grinding, and temporarily store the optimized optimal grinding process parameters (1-4-1) to the mobile client application interface (1-5-2);

[0047] Step 13 (S2.13): Remote grinding database management system feeds system permissions into database advanced administrators (1-1-4), reviewing the temporary storage mobile client application interface (1-5-2) Optimal grinding process parameters (1-4-1) and the best sand wheel trimming strategy (1-4-2);

[0048] Step 14 (S2.14): If the audit fails, delete the temporary data, if the audit is successful, the remote grinding database management system feeds the system authority to the database maintenance person (1-1-3), updating the network service cloud ( 1-5-3) The optimal grinding process parameters (1-4-1) and the best sand wheel trimming strategy (1-4-2).