CN116578486A - Intelligent manufacturing industrial software debugging system based on cloud computing - Google Patents
Intelligent manufacturing industrial software debugging system based on cloud computing Download PDFInfo
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Abstract
The application discloses an intelligent manufacturing industrial software debugging system based on cloud computing, which relates to the technical field of intelligent manufacturing, and solves the technical problems that the optimal operation parameters of abnormal equipment cannot be confirmed in time and excessive manpower is consumed, according to the acquired operation parameters, abnormal equipment is confirmed, then parameter testing is carried out on the abnormal equipment, different preset test intervals are extracted from a storage unit, according to the different preset test intervals, then according to the output parameters, the energy conversion ratio is confirmed, after the optimal test interval is confirmed, the power value in the test interval is retested, thus a group of optimal operation input power values is confirmed, the operation input power values are adopted, the abnormal equipment is debugged, so that the optimal abnormal equipment processing effect is achieved, normal operation of the abnormal equipment is enabled, and then whether maintenance is needed for the abnormal equipment is judged according to the operation result, so that the overall debugging effect of the whole industrial equipment is improved.
Description
Technical Field
The application belongs to the technical field of intelligent manufacturing, and particularly relates to an intelligent manufacturing industrial software debugging system based on cloud computing.
Background
Intelligent manufacturing, which originates from research of artificial intelligence, is generally considered to be the sum of knowledge and intelligence, the former being the basis of intelligence, and the latter being the ability to acquire and use knowledge solutions.
The application of patent publication No. CN115328054A discloses an intelligent manufacturing industrial software debugging system based on cloud computing, which belongs to the technical field of intelligent manufacturing, and the system is beneficial to accurately evaluating non-equipment factors in the working process of intelligent manufacturing industrial software by analyzing and acquiring the influence of equipment aging and damage, is also beneficial to timely finding out the problems of low abnormal production efficiency and low production yield in equipment production, is fast locked and maintained, is also beneficial to finding out the conditions of high abnormal production efficiency and high production yield in equipment production, is beneficial to finding out good production progress, is beneficial to timely adjusting the whole production environment by a user, and fully utilizes the factors beneficial to production efficiency and yield; according to the method and the device, when the industrial software is on line, part of parameters of the industrial software can be accurately predicted according to the actual running time and maintenance conditions, running errors in the initial stage of the industrial software on line are reduced, and accuracy is improved.
For the intelligent manufacturing equipment operation monitoring process, corresponding manufacturing equipment is generally marked as abnormal equipment according to the operation parameters of specific equipment, subsequent dispatch personnel maintain and debug the abnormal equipment, and normal operation of the abnormal equipment is guaranteed.
Disclosure of Invention
The present application aims to solve at least one of the technical problems existing in the prior art; therefore, the application provides an intelligent manufacturing industrial software debugging system based on cloud computing, which is used for solving the technical problems that the optimal operation parameters of abnormal equipment cannot be confirmed in time and the manpower is excessively consumed.
To achieve the above object, an embodiment according to a first aspect of the present application provides an intelligent manufacturing industrial software debugging system based on cloud computing, including a data acquisition end, a software debugging center, and a display unit;
the software debugging center comprises a data self-adaptive analysis unit, an abnormal equipment confirmation unit, an equipment parameter test unit, an equipment debugging unit, a storage unit, a productivity monitoring unit and an analysis processing unit;
the data acquisition end is used for acquiring working parameters of different equipment in the intelligent manufacturing industry and transmitting the acquired working parameters into the software debugging center, wherein the working parameters comprise equipment yield parameters and equipment operation parameters;
the data self-adaptive analysis unit performs self-adaptive analysis on different devices according to the acquired working parameters, generates an abnormal signal according to an analysis result, and transmits the generated abnormal signal to the abnormal device confirmation unit, wherein the specific mode is as follows:
determining a group of monitoring periods T, wherein T is a preset value, and marking the device productivity parameters of different devices in the monitoring periods T as CS i Wherein i represents a different device;
capacity parameters CS of a plurality of groups of equipment i Carrying out mean value processing to obtain a mean value JZ to be processed;
capacity parameters CS of a plurality of groups of equipment i Performing difference processing with the average value JZ to obtain a plurality of difference values CZ to be processed i ；
Several groups of differences CZ to be processed i Comparing with a preset parameter Y1, wherein Y1 is a preset value, and when CZ i If Y1 is not more than or equal to, not performing any processing, otherwise, generating an abnormal signal and transmitting the generated abnormal signal to an abnormal equipment confirmation unit;
the abnormal equipment confirming unit marks the appointed equipment as abnormal equipment according to the abnormal signal sent by the data self-adaptive analysis unit;
the device parameter testing unit determines marked abnormal devices, performs split power testing on the abnormal devices, extracts a preset power testing interval from the storage unit, confirms an energy conversion ratio according to the testing data, and confirms an optimal power testing interval according to the energy conversion ratio, wherein the specific mode is as follows:
extracting preset different power test intervals from the storage unit, wherein the different power test intervals comprise a plurality of different input power test values, randomly inputting the input power test values of the corresponding power test intervals to the abnormal equipment, and marking the input power test values as SR i And records the output power parameter of the corresponding abnormal equipment and marks the output power parameter as SC i ；
By NY i ＝SC i ÷SR i Obtaining an energy conversion ratio NY corresponding to the input power test value of the equipment i Then, for a plurality of groups of energy conversion ratios NY in the power test interval i After the confirmation, a plurality of groups of energy conversion ratios NY belonging to the same section are confirmed i Binding to obtain interval binding data packages;
testing other power test intervals to obtain interval binding data packets belonging to different intervals;
energy conversion ratio NY inside section binding data package of different sections i Average value processing is carried out to obtain a to-be-processed conversion ratio average value J k Wherein k represents different interval binding data packets, and then different conversion ratio average values J are processed k Internal extraction maximum J kmax And the average value J of the conversion ratio to be processed kmax The corresponding power test interval is confirmed, and the confirmed power test interval is transmitted to the equipment debugging unit;
the device debugging unit is used for debugging the input power of the appointed abnormal device according to the confirmed optimal power test interval, and confirming the optimal operation input power value according to a debugging result, wherein the specific mode is as follows:
defining a group of monitoring periods P according to the confirmed power test interval;
sequentially limiting power test values in the power test interval, recording corresponding power output values, analyzing the fluctuation times of the power output values in the monitoring period P according to the confirmed monitoring period P, and extracting the power test value corresponding to the minimum fluctuation times;
if only one group of the determined power test values exists, the determined power test values are directly marked as the optimal operation input power values;
if the determined power test values have a plurality of groups, extracting the maximum value from the plurality of groups of power test values, and marking the maximum value as the optimal operation input power value;
and taking the confirmed optimal operation input power value as the operation parameter of the corresponding abnormal equipment, and debugging the operation parameter of the abnormal equipment.
Preferably, the capacity monitoring unit monitors the capacity of the plurality of groups of abnormal devices after the debugging is completed, and transmits the monitored capacity parameters of the abnormal devices to the analysis processing unit.
Preferably, the analysis processing unit confirms the abnormal equipment productivity parameter determined in unit time according to the monitored abnormal equipment productivity parameter, compares the abnormal equipment productivity parameter with a preset value in the storage unit after confirmation, and generates a corresponding processing signal according to a comparison result, and the specific mode is as follows:
marking the productivity parameter of the abnormal equipment in unit time as CN m Wherein m represents different abnormal devices;
extracting preset value Y2 from the storage unit, when CN m And when the value is less than Y2, generating a maintenance signal, transmitting the maintenance signal into a display unit for display, and otherwise, not performing any processing.
Compared with the prior art, the application has the beneficial effects that: according to the acquired working parameters, confirming the abnormal equipment, subsequently carrying out parameter testing on the abnormal equipment, extracting different preset test intervals from the storage unit, confirming different output parameters according to the different preset test intervals, confirming the energy conversion ratio according to the output parameters, after confirming the optimal test interval, retesting the power value in the test interval, confirming a group of optimal operation input power values, subsequently debugging the abnormal equipment by adopting the operation input power values, thereby achieving the optimal abnormal equipment processing effect, enabling the abnormal equipment to normally operate, and subsequently judging whether the abnormal equipment needs maintenance according to the operation result, thereby improving the integral debugging effect of the whole industrial equipment.
Drawings
Fig. 1 is a schematic diagram of a principle frame of the present application.
Detailed Description
The technical solutions of the present application will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1
Referring to fig. 1, the application provides an intelligent manufacturing industrial software debugging system based on cloud computing, which comprises a data acquisition end, a software debugging center and a display unit;
the data acquisition end is electrically connected with the input end of the software debugging center, and the software debugging center is electrically connected with the input end of the display unit;
the software debugging center comprises a data self-adaptive analysis unit, an abnormal equipment confirming unit, an equipment parameter testing unit, an equipment debugging unit, a storage unit, a productivity monitoring unit and an analysis processing unit, wherein the data self-adaptive analysis unit is electrically connected with the input end of the abnormal equipment confirming unit, the abnormal equipment confirming unit is electrically connected with the input end of the equipment parameter testing unit, the equipment parameter testing unit is electrically connected with the input end of the equipment debugging unit, the equipment parameter testing unit is in bidirectional connection with the storage unit, the equipment debugging unit is electrically connected with the input end of the productivity monitoring unit, and the productivity monitoring unit is electrically connected with the input end of the analysis processing unit;
the data acquisition end is used for acquiring working parameters of different equipment in the intelligent manufacturing industry and transmitting the acquired working parameters into the software debugging center, wherein the working parameters comprise equipment yield parameters and equipment operation parameters;
the data self-adaptive analysis unit performs self-adaptive analysis on different devices according to the acquired working parameters, generates an abnormal signal according to an analysis result, and transmits the generated abnormal signal to the abnormal device confirmation unit, wherein the specific mode of performing self-adaptive analysis is as follows:
determining a group of monitoring periods T, wherein T is generally 24h, T is a preset value, the specific value is determined by an operator according to experience, and the equipment productivity parameters of different equipment in the monitoring periods T are marked as CS i Wherein i represents a different device;
capacity parameters CS of a plurality of groups of equipment i Carrying out mean value processing to obtain a mean value JZ to be processed;
capacity parameters CS of a plurality of groups of equipment i Performing difference processing with the average value JZ to obtain a plurality of difference values CZ to be processed i ；
Several groups of differences CZ to be processed i Comparing with a preset parameter Y1, wherein Y1 is a preset value, the specific value is determined by an operator according to experience, and when CZ is performed i And when Y1 is not more than or equal to, not performing any processing, otherwise, generating an abnormal signal, and transmitting the generated abnormal signal into an abnormal equipment confirmation unit.
The abnormal equipment confirming unit marks the appointed equipment as abnormal equipment according to the abnormal signal sent by the data self-adaptive analysis unit;
the device parameter testing unit determines marked abnormal devices, performs split power testing on the abnormal devices, extracts a preset power testing interval from the storage unit, confirms an energy conversion ratio according to the testing data, and confirms an optimal power testing interval according to the energy conversion ratio, wherein the specific mode for performing the split power testing is as follows:
extracting preset different power test intervals from the storage unit, wherein the different power test intervals comprise a plurality of different input power test values, and performing power test on abnormal equipment by adopting the different power test intervals to different directionsThe normal equipment randomly inputs the input power test value of the corresponding power test interval and marks the input power test value as SR i And records the output power parameter of the corresponding abnormal equipment and marks the output power parameter as SC i In the actual application process, when the corresponding equipment is used, input parameters and output parameters generally exist;
by NY i ＝SC i ÷SR i Obtaining an energy conversion ratio NY corresponding to the input power test value of the equipment i Then, for a plurality of groups of energy conversion ratios NY in the power test interval i After the confirmation, a plurality of groups of energy conversion ratios NY belonging to the same section are confirmed i Binding to obtain interval binding data packages;
testing other power test intervals to obtain interval binding data packets belonging to different intervals;
energy conversion ratio NY inside section binding data package of different sections i Average value processing is carried out to obtain a to-be-processed conversion ratio average value J k Wherein k represents different interval binding data packets, and then different conversion ratio average values J are processed k Internal extraction maximum J kmax And the average value J of the conversion ratio to be processed kmax And confirming the corresponding power test interval, and transmitting the confirmed power test interval into the equipment debugging unit.
The device debugging unit is used for debugging the input power of the appointed abnormal device according to the confirmed power test interval, and confirming the optimal operation input power value according to the debugging result, wherein the specific mode for debugging is as follows:
defining a group of monitoring periods P according to the confirmed power test interval, wherein P is a preset value, the specific value of the P is drawn by an operator according to experience, and the value of the P is generally 2min;
sequentially limiting power test values in the power test interval, recording corresponding power output values, analyzing the fluctuation times of the power output values in the monitoring period P according to the confirmed monitoring period P, and extracting the power test value corresponding to the minimum fluctuation times;
if only one group of the determined power test values exists, the determined power test values are directly marked as the optimal operation input power values;
if the determined power test values have a plurality of groups, extracting the maximum value from the plurality of groups of power test values, and marking the maximum value as the optimal operation input power value;
and taking the confirmed optimal operation input power value as the operation parameter of the corresponding abnormal equipment, and debugging the operation parameter of the abnormal equipment.
Example two
In the implementation process of this embodiment, compared to the first embodiment, the embodiment includes the first embodiment, which is specifically different from the first embodiment in that:
the capacity monitoring unit monitors the capacity of the debugged groups of abnormal equipment and transmits the capacity parameters of the monitored abnormal equipment to the analysis processing unit;
the analysis processing unit confirms the capacity parameters of the abnormal equipment determined in unit time according to the monitored capacity parameters of the abnormal equipment, compares the capacity parameters with preset values in the storage unit after confirmation, and generates corresponding processing signals according to comparison results, wherein the specific mode of comparison is as follows:
marking the productivity parameter of the abnormal equipment in unit time as CN m Wherein m represents different abnormal devices, and the specific value of the unit time is empirically drawn by an operator;
extracting preset value Y2 from the storage unit, wherein the specific value of Y2 is empirically determined by an operator, and when CN is obtained m And when the value is less than Y2, generating a maintenance signal, transmitting the maintenance signal into a display unit for display, and otherwise, not performing any processing.
The display unit is used for maintaining the appointed abnormal equipment according to the maintenance signal and re-debugging or maintaining equipment parameters generated by the abnormal equipment.
The partial data in the formula are all obtained by removing dimension and taking the numerical value for calculation, and the formula is a formula closest to the real situation obtained by simulating a large amount of collected data through software; the preset parameters and the preset threshold values in the formula are set by those skilled in the art according to actual conditions or are obtained through mass data simulation.
The working principle of the application is as follows: confirming abnormal equipment in advance according to the acquired working parameters, subsequently carrying out parameter testing on the abnormal equipment, extracting different preset test intervals from the storage unit, confirming different output parameters according to the different preset test intervals, confirming the energy conversion ratio according to the output parameters, carrying out retesting on the power values in the test intervals after confirming the optimal test intervals, confirming a group of optimal operation input power values, subsequently debugging the abnormal equipment by adopting the operation input power values, so as to achieve the optimal abnormal equipment processing effect, enabling the abnormal equipment to normally operate, and subsequently judging whether the abnormal equipment needs maintenance according to the operation result, so that the integral debugging effect of the whole industrial equipment is improved.
The above embodiments are only for illustrating the technical method of the present application and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present application may be modified or substituted without departing from the spirit and scope of the technical method of the present application.
Claims (7)
1. The intelligent manufacturing industrial software debugging system based on cloud computing is characterized by comprising a data acquisition end, a software debugging center and a display unit;
the software debugging center comprises a data self-adaptive analysis unit, an abnormal equipment confirmation unit, an equipment parameter test unit, an equipment debugging unit, a storage unit, a productivity monitoring unit and an analysis processing unit;
the data acquisition end is used for acquiring working parameters of different equipment in the intelligent manufacturing industry and transmitting the acquired working parameters into the software debugging center, wherein the working parameters comprise equipment yield parameters and equipment operation parameters;
the data self-adaptive analysis unit performs self-adaptive analysis on different equipment according to the acquired working parameters, generates an abnormal signal according to an analysis result, and transmits the generated abnormal signal to the abnormal equipment confirmation unit;
the abnormal equipment confirming unit marks the appointed equipment as abnormal equipment according to the abnormal signal sent by the data self-adaptive analysis unit;
the device parameter testing unit is used for determining marked abnormal devices, carrying out split power testing on the abnormal devices, extracting a preset power testing interval from the storage unit, confirming an energy conversion ratio according to the testing data, and confirming an optimal power testing interval according to the energy conversion ratio;
the device debugging unit is used for debugging the input power of the appointed abnormal device according to the confirmed optimal power test interval, and confirming the optimal operation input power value according to a debugging result.
2. The cloud computing-based intelligent manufacturing industrial software debugging system according to claim 1, wherein the data adaptive analysis unit performs adaptive analysis on different devices in the following specific ways:
determining a group of monitoring periods T, wherein T is a preset value, and marking the device productivity parameters of different devices in the monitoring periods T as CS i Wherein i represents a different device;
capacity parameters CS of a plurality of groups of equipment i Carrying out mean value processing to obtain a mean value JZ to be processed;
capacity parameters CS of a plurality of groups of equipment i Performing difference processing with the average value JZ to obtain a plurality of difference values CZ to be processed i ；
Several groups of differences CZ to be processed i Comparing with a preset parameter Y1, wherein Y1 is a preset value, and when CZ i And when Y1 is not more than or equal to, not performing any processing, otherwise, generating an abnormal signal, and transmitting the generated abnormal signal into an abnormal equipment confirmation unit.
3. The cloud computing-based intelligent manufacturing industrial software debugging system according to claim 2, wherein the device parameter testing unit performs the split power test on the abnormal device in the following specific ways:
extracting preset different power test intervals from the storage unit, wherein the different power test intervals comprise a plurality of different input power test values, randomly inputting the input power test values of the corresponding power test intervals to the abnormal equipment, and marking the input power test values as SR i And records the output power parameter of the corresponding abnormal equipment and marks the output power parameter as SC i ；
By NY i ＝SC i ÷SR i Obtaining an energy conversion ratio NY corresponding to the input power test value of the equipment i Then, for a plurality of groups of energy conversion ratios NY in the power test interval i After the confirmation, a plurality of groups of energy conversion ratios NY belonging to the same section are confirmed i Binding to obtain interval binding data packages;
testing other power test intervals to obtain interval binding data packets belonging to different intervals;
energy conversion ratio NY inside section binding data package of different sections i Average value processing is carried out to obtain a to-be-processed conversion ratio average value J k Wherein k represents different interval binding data packets, and then different conversion ratio average values J are processed k Internal extraction maximum J kmax And the average value J of the conversion ratio to be processed kmax And confirming the corresponding power test interval, and transmitting the confirmed power test interval into the equipment debugging unit.
4. The intelligent manufacturing industrial software debugging system based on cloud computing as claimed in claim 3, wherein the device debugging unit is configured to debug the input power of the specified abnormal device in the following specific manner:
defining a group of monitoring periods P according to the confirmed power test interval;
sequentially limiting power test values in the power test interval, recording corresponding power output values, analyzing the fluctuation times of the power output values in the monitoring period P according to the confirmed monitoring period P, and extracting the power test value corresponding to the minimum fluctuation times;
if only one group of the determined power test values exists, the determined power test values are directly marked as the optimal operation input power values;
if the determined power test values have a plurality of groups, extracting the maximum value from the plurality of groups of power test values, and marking the maximum value as the optimal operation input power value;
and taking the confirmed optimal operation input power value as the operation parameter of the corresponding abnormal equipment, and debugging the operation parameter of the abnormal equipment.
5. The cloud computing-based intelligent manufacturing industrial software debugging system according to claim 4, wherein the capacity monitoring unit monitors capacity of the plurality of sets of abnormal devices after completion of debugging, and transmits the monitored capacity parameters of the abnormal devices to the analysis processing unit.
6. The cloud computing-based intelligent manufacturing industrial software debugging system according to claim 1, wherein the analysis processing unit confirms the abnormal equipment productivity parameter determined in unit time according to the monitored abnormal equipment productivity parameter, compares the abnormal equipment productivity parameter with a preset value in the storage unit after confirmation, and generates a corresponding processing signal according to a comparison result.
7. The cloud computing-based intelligent manufacturing industrial software debugging system according to claim 6, wherein the specific way for the analysis processing unit to compare the abnormal equipment productivity parameter with the preset value in the storage unit is as follows:
marking the productivity parameter of the abnormal equipment in unit time as CN m Wherein m represents different abnormal devices;
extracting preset value Y2 from the storage unit, when CN m When < Y2, generate dimensionThe protection signal is transmitted to the display unit for display, otherwise, no processing is performed.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310549981.4A CN116578486A (en) | 2023-05-16 | 2023-05-16 | Intelligent manufacturing industrial software debugging system based on cloud computing |
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| CN202310549981.4A CN116578486A (en) | 2023-05-16 | 2023-05-16 | Intelligent manufacturing industrial software debugging system based on cloud computing |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117408575A (en) * | 2023-12-13 | 2024-01-16 | 深圳市安科讯电子制造有限公司 | Intelligent management method and platform for energy product production |
| CN117850279A (en) * | 2024-01-12 | 2024-04-09 | 汗青数据咨询有限公司 | Intelligent control system based on information system integration |
-
2023
- 2023-05-16 CN CN202310549981.4A patent/CN116578486A/en not_active Withdrawn
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117408575A (en) * | 2023-12-13 | 2024-01-16 | 深圳市安科讯电子制造有限公司 | Intelligent management method and platform for energy product production |
| CN117408575B (en) * | 2023-12-13 | 2024-03-29 | 深圳市安科讯电子制造有限公司 | Intelligent management method and platform for energy product production |
| CN117850279A (en) * | 2024-01-12 | 2024-04-09 | 汗青数据咨询有限公司 | Intelligent control system based on information system integration |
| CN117850279B (en) * | 2024-01-12 | 2024-06-25 | 汗青数据咨询有限公司 | Intelligent control system based on information system integration |
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Application publication date: 20230811 |