CN116257019B - PLC (programmable logic controller) management method and system based on cloud - Google Patents
PLC (programmable logic controller) management method and system based on cloud Download PDFInfo
- Publication number
- CN116257019B CN116257019B CN202310538373.3A CN202310538373A CN116257019B CN 116257019 B CN116257019 B CN 116257019B CN 202310538373 A CN202310538373 A CN 202310538373A CN 116257019 B CN116257019 B CN 116257019B
- Authority
- CN
- China
- Prior art keywords
- plc
- temperature
- rise rate
- data
- cloud
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/05—Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
- G05B19/054—Input/output
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/10—Plc systems
- G05B2219/14—Plc safety
- G05B2219/14078—If fault in next cycle persists, declare channel faulty
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Programmable Controllers (AREA)
Abstract
The invention discloses a cloud-based PLC management method and system, which comprises the steps of collecting temperature data of a tested PLC during operation, collecting event execution completion rate of the tested PLC during operation if the temperature of the PLC is normal, testing the event execution of the PLC if faults exist, obtaining event test results, judging the state of the PLC according to the deviation of the event execution test results and standard results, correcting the PLC if the state is available, and carrying out temperature test and control on the PLC after the correction is completed, thereby completing fault detection and management of the PLC. By the technical scheme provided by the invention, the real-time management of the PLC can be realized, and the normal operation of the PLC is ensured.
Description
Technical Field
The invention relates to the field of PLC, in particular to a cloud-based PLC management method and system.
Background
To prevent potential safety hazards that may exist with industrial control systems, some industrial control systems deploy SCADA systems. The SCADA system is a data acquisition and monitoring system, integrates a data acquisition system, a data transmission system and a human-machine interface design HMI software, and is mainly used for controlling scattered equipment to perform centralized data acquisition so as to provide centralized monitoring and control. SCADA systems typically collect on-site control information, transmit the information to a computer system, and display the information in the form of images or text, allowing an operator to monitor and control the entire production line system in real time within a monitoring room, and control any individual system to perform related operations or tasks based on the complexity and related settings of each system. The SCADA system has higher requirements on the operator's attendance and experience, while modern industrial production requires more automation and intelligence, reducing the degree of dependence on operators. How to realize the automatic state detection and the self-adaptive monitoring adjustment of multiple PLCs in an industrial control system becomes a problem to be solved.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a PLC management method based on a cloud, which comprises the following steps:
acquiring temperature data of a tested PLC during operation, acquiring operation temperature and temperature fluctuation according to the acquired temperature data, and if the difference value between the operation temperature and the standard temperature is within a set difference value threshold value range and the temperature fluctuation is within a temperature fluctuation threshold value range, enabling the temperature of the PLC to be normal, and entering a step two; otherwise, enter step five;
step two, collecting event execution completion rate of the tested PLC during operation, judging whether faults exist in the PLC according to the difference value of the collected event execution completion rate and the design event execution completion rate, if so, entering step three, otherwise, entering step five;
step three, performing event execution test on the PLC to obtain an event test result, judging the state of the PLC according to the deviation between the event execution test result and a standard result, if the state is the available state, entering a step four, otherwise, replacing the PLC;
step four, acquiring corresponding standard data from a cloud data server according to the batch and model of the PLC, correcting the PLC according to the acquired standard data, and entering a step five after the correction is completed;
fifthly, performing temperature test and control on the PLC, detecting the temperature of the PLC through a temperature sensor module, and obtaining the temperature rise rate of the PLC according to the temperature of the PLC detected by the temperature sensor module after the set test is used for a long time, wherein if the temperature rise rate of the PLC is not greater than a set temperature rise rate threshold value, the temperature of the PLC is normal;
if the temperature rising rate of the PLC is larger than the set temperature rising rate threshold value, adjusting the heat dissipation power of the radiator to ensure that the temperature rising rate of the PLC is within the set temperature rising rate threshold value range, and completing the temperature test and control of the PLC;
and step six, completing the fault detection and management of the PLC.
Further, the step of acquiring the operation temperature and the temperature fluctuation according to the acquired temperature data comprises the step of acquiring the average temperature in the set PLC operation time according to the acquired temperature data in the set PLC operation time, namely the operation temperature of the PLC; the temperature fluctuation is the ratio of the difference value between the highest value and the lowest value in the acquired temperature data to the set PLC operation duration.
Further, the event execution completion rate is: and if the peak value deviation of the signal output after the signal is subjected to the PLC and the standard output signal corresponding to the signal input into the PLC is within a set error range, completing the execution of the event, and obtaining the completion rate of the execution of the event according to the completion times of the execution of the event in the acquired times of the execution of the event.
Further, the event execution test is performed on the PLC to obtain an event test result, and the state of the PLC is judged according to the deviation between the event execution test result and the standard result:
through inputting the PLC test signal, the peak value deviation of the signal output after passing through the PLC and the standard output signal corresponding to the input PLC test signal, if the deviation is within the set adjustable threshold value range, the PLC is in an available state, otherwise, the PLC is in an unavailable state.
Further, according to the batch and model of the PLC, the corresponding standard data is obtained from the cloud data server, and the PLC is corrected according to the obtained standard data, which is that:
and according to the acquired standard data, adjusting the PLC output to ensure that the peak value deviation of the output signal and the standard signal is within a set error range, and completing the PLC correction.
The cloud-based PLC management system applying the cloud-based PLC management method comprises a data processor, a data memory, an output signal peak value acquisition device, a temperature detection device, a power control device, a communication device, a display module, a temperature rise rate acquisition module and a heat dissipation module; the data memory, the output signal peak value acquisition device, the temperature detection device, the power control device, the communication device, the display module and the temperature rise rate acquisition module are respectively connected with the data processor; the heat dissipation module is connected with the power control device.
The output signal peak value acquisition device is used for acquiring output signal peak values when the PLC works;
the temperature detection device is used for collecting temperature data of the PLC;
the power control device is used for adjusting the power of the heat dissipation module;
the display device is used for displaying the acquired parameters;
the temperature rise rate judging module is used for calculating the temperature rise rate and comparing the temperature rise rate with a set temperature rise rate threshold value.
Preferably, the temperature detection device comprises a temperature sensor module; the temperature sensor module is connected with the data processor and is used for detecting the temperature of the PLC.
Preferably, the temperature rise rate judging module comprises a temperature rise rate calculating module and a temperature rise rate judging device; the temperature rise rate calculation module and the temperature rise rate judgment device are respectively connected with the data processor;
the temperature rise rate calculation module calculates the temperature rise rate by adopting the following formula:
therein, whereinFor PLC pass operation duration->Post temperature, < >>Is the temperature at the time of PLC acquisition.
The beneficial effects of the invention are as follows: by the technical scheme provided by the invention, the real-time monitoring of the PLC can be realized, and the stable operation of the PLC is ensured.
Drawings
Fig. 1 is a schematic flow chart of a cloud-based PLC management method;
fig. 2 is a schematic diagram of a cloud-based PLC management system.
Detailed Description
The technical solution of the present invention will be described in further detail with reference to the accompanying drawings, but the scope of the present invention is not limited to the following description.
For the purpose of making the technical solution and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the particular embodiments described herein are illustrative only and are not intended to limit the invention, i.e., the embodiments described are merely some, but not all, of the embodiments of the invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present invention. It is noted that relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The features and capabilities of the present invention are described in further detail below in connection with the examples.
As shown in fig. 1, a cloud-based PLC management method includes the following steps:
acquiring temperature data of a tested PLC during operation, acquiring operation temperature and temperature fluctuation according to the acquired temperature data, and if the difference value between the operation temperature and the standard temperature is within a set difference value threshold value range and the temperature fluctuation is within a temperature fluctuation threshold value range, enabling the temperature of the PLC to be normal, and entering a step two; otherwise, enter step five;
step two, collecting event execution completion rate of the tested PLC during operation, judging whether faults exist in the PLC according to the difference value of the collected event execution completion rate and the design event execution completion rate, if so, entering step three, otherwise, entering step five;
step three, performing event execution test on the PLC to obtain an event test result, judging the state of the PLC according to the deviation between the event execution test result and a standard result, if the state is the available state, entering a step four, otherwise, replacing the PLC;
step four, acquiring corresponding standard data from a cloud data server according to the batch and model of the PLC, correcting the PLC according to the acquired standard data, and entering a step five after the correction is completed;
fifthly, performing temperature test and control on the PLC, detecting the temperature of the PLC through a temperature sensor module, and obtaining the temperature rise rate of the PLC according to the temperature of the PLC detected by the temperature sensor module after the set test is used for a long time, wherein if the temperature rise rate of the PLC is not greater than a set temperature rise rate threshold value, the temperature of the PLC is normal;
if the temperature rising rate of the PLC is larger than the set temperature rising rate threshold value, adjusting the heat dissipation power of the radiator to ensure that the temperature rising rate of the PLC is within the set temperature rising rate threshold value range, and completing the temperature test and control of the PLC;
and step six, completing the fault detection and management of the PLC.
The method comprises the steps that the operation temperature and temperature fluctuation are obtained according to the collected temperature data, wherein the average temperature in the set PLC operation time is obtained according to the collected temperature data in the set PLC operation time, and the average temperature is the operation temperature of the PLC; the temperature fluctuation is the ratio of the difference value between the highest value and the lowest value in the acquired temperature data to the set PLC operation duration.
The event execution completion rate is as follows: and if the peak value deviation of the signal output after the signal is subjected to the PLC and the standard output signal corresponding to the signal input into the PLC is within a set error range, completing the execution of the event, and obtaining the completion rate of the execution of the event according to the completion times of the execution of the event in the acquired times of the execution of the event.
The event execution test is carried out on the PLC to obtain an event test result, and the state of the PLC is judged according to the deviation between the event execution test result and the standard result:
through inputting the PLC test signal, the peak value deviation of the signal output after passing through the PLC and the standard output signal corresponding to the input PLC test signal, if the deviation is within the set adjustable threshold value range, the PLC is in an available state, otherwise, the PLC is in an unavailable state.
According to the batch and model of the PLC, corresponding standard data are obtained from a cloud data server, and the PLC is corrected according to the obtained standard data, wherein the correction is as follows:
and according to the acquired standard data, adjusting the PLC output to ensure that the peak value deviation of the output signal and the standard signal is within a set error range, and completing the PLC correction.
The cloud-based PLC management system applying the cloud-based PLC management method comprises a data processor, a data memory, an output signal peak value acquisition device, a temperature detection device, a power control device, a communication device, a display module, a temperature rise rate acquisition module and a heat dissipation module; the data memory, the output signal peak value acquisition device, the temperature detection device, the power control device, the communication device, the display module and the temperature rise rate acquisition module are respectively connected with the data processor; the heat dissipation module is connected with the power control device.
The output signal peak value acquisition device is used for acquiring output signal peak values when the PLC works;
the temperature detection device is used for collecting temperature data of the PLC;
the power control device is used for adjusting the power of the heat dissipation module;
the display device is used for displaying the acquired parameters;
the temperature rise rate acquisition module is used for calculating the temperature rise rate and comparing the temperature rise rate with a set temperature rise rate threshold.
The temperature detection device comprises a temperature sensor module; the temperature sensor module is connected with the data processor and is used for detecting the temperature of the PLC.
The temperature rise rate acquisition module comprises a temperature rise rate calculation module and a temperature rise rate judgment device; the temperature rise rate calculation module and the temperature rise rate judgment device are respectively connected with the data processor;
the temperature rise rate calculation module calculates the temperature rise rate by adopting the following formula:
therein, whereinFor PLC pass operation duration->Post temperature, < >>Is the temperature at the time of PLC acquisition.
The foregoing is merely a preferred embodiment of the invention, and it is to be understood that the invention is not limited to the form disclosed herein but is not to be construed as excluding other embodiments, but is capable of numerous other combinations, modifications and environments and is capable of modifications within the scope of the inventive concept, either as taught or as a matter of routine skill or knowledge in the relevant art. And that modifications and variations which do not depart from the spirit and scope of the invention are intended to be within the scope of the appended claims.
Claims (8)
1. The PLC management method based on the cloud is characterized by comprising the following steps of:
acquiring temperature data of a tested PLC during operation, acquiring operation temperature and temperature fluctuation according to the acquired temperature data, and if the difference value between the operation temperature and the standard temperature is within a set difference value threshold value range and the temperature fluctuation is within a temperature fluctuation threshold value range, enabling the temperature of the PLC to be normal, and entering a step two; otherwise, enter step five;
step two, collecting event execution completion rate of the tested PLC during operation, judging whether faults exist in the PLC according to the difference value of the collected event execution completion rate and the design event execution completion rate, if so, entering step three, otherwise, entering step five;
step three, performing event execution test on the PLC to obtain an event test result, judging the state of the PLC according to the deviation between the event execution test result and a standard result, if the state is the available state, entering a step four, otherwise, replacing the PLC;
step four, acquiring corresponding standard data from a cloud data server according to the batch and model of the PLC, correcting the PLC according to the acquired standard data, and entering a step five after the correction is completed;
fifthly, performing temperature test and control on the PLC, detecting the temperature of the PLC through a temperature sensor module, and obtaining the temperature rise rate of the PLC according to the temperature of the PLC detected by the temperature sensor module after the set test is used for a long time, wherein if the temperature rise rate of the PLC is not greater than a set temperature rise rate threshold value, the temperature of the PLC is normal;
if the temperature rising rate of the PLC is larger than the set temperature rising rate threshold value, adjusting the heat dissipation power of the radiator to ensure that the temperature rising rate of the PLC is within the set temperature rising rate threshold value range, and completing the temperature test and control of the PLC;
and step six, completing the fault detection and management of the PLC.
2. The cloud-based PLC management method according to claim 1, wherein the acquiring the operating temperature and the temperature fluctuation according to the collected temperature data includes acquiring an average temperature within a set PLC operating time period according to the collected temperature data, which is an operating temperature of the PLC; the temperature fluctuation is the ratio of the difference value between the highest value and the lowest value in the acquired temperature data to the set PLC operation duration.
3. The cloud-based PLC management method of claim 2, wherein the event execution completion rate is: and if the peak value deviation of the peak value of the signal output after the signal is subjected to the PLC is within a set error range with the peak value of the standard output signal corresponding to the signal input into the PLC, completing the execution of the event, and obtaining the event execution completion rate according to the event execution completion times in the acquired event execution times.
4. The cloud-based PLC management method according to claim 3, wherein the performing an event execution test on the PLC to obtain an event test result, and determining a state of the PLC according to a deviation between the event execution test result and a standard result:
and obtaining the peak value deviation between the peak value of the signal output after passing through the PLC and the peak value of the standard output signal corresponding to the input PLC test signal by inputting the PLC test signal, if the deviation is within the set adjustable threshold range, the PLC is in an available state, and otherwise, the PLC is in an unavailable state.
5. The cloud-based PLC management method according to claim 4, wherein the obtaining corresponding standard data from the cloud data server according to the batch and model of the PLC, and correcting the PLC according to the obtained standard data is:
and according to the acquired standard data, adjusting the PLC output to ensure that the peak deviation between the peak value of the output signal and the peak value of the standard signal is within a set error range, thereby completing the PLC correction.
6. The management system applying the cloud-based PLC management method according to any one of claims 1 to 5, which is characterized by comprising a data processor, a data memory, an output signal peak value acquisition device, a temperature detection device, a power control device, a communication device, a display module, a temperature rise rate acquisition module and a heat dissipation module; the data memory, the output signal peak value acquisition device, the temperature detection device, the power control device, the communication device, the display module and the temperature rise rate acquisition module are respectively connected with the data processor; the heat dissipation module is connected with the power control device
The output signal peak value acquisition device is used for acquiring output signal peak values when the PLC works;
the temperature detection device is used for collecting temperature data of the PLC;
the power control device is used for adjusting the power of the heat dissipation module;
the display module is used for displaying the acquired parameters;
the temperature rise rate acquisition module is used for calculating the temperature rise rate and comparing the temperature rise rate with a set temperature rise rate threshold.
7. The cloud-based PLC management system of claim 6, wherein said temperature sensing means comprises a temperature sensor module; the temperature sensor module is connected with the data processor and is used for detecting the temperature of the PLC.
8. The cloud-based PLC management system of claim 7, wherein the temperature rise rate obtaining module comprises a temperature rise rate calculating module and a temperature rise rate judging device; the temperature rise rate calculation module and the temperature rise rate judgment device are respectively connected with the data processor;
the temperature rise rate calculation module calculates the temperature rise rate by adopting the following formula:
therein, whereinFor PLC pass operation duration->Post temperature, < >>Is the temperature at the time of PLC acquisition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310538373.3A CN116257019B (en) | 2023-05-15 | 2023-05-15 | PLC (programmable logic controller) management method and system based on cloud |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310538373.3A CN116257019B (en) | 2023-05-15 | 2023-05-15 | PLC (programmable logic controller) management method and system based on cloud |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116257019A CN116257019A (en) | 2023-06-13 |
| CN116257019B true CN116257019B (en) | 2023-08-04 |
Family
ID=86688360
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310538373.3A Active CN116257019B (en) | 2023-05-15 | 2023-05-15 | PLC (programmable logic controller) management method and system based on cloud |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116257019B (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012113408A (en) * | 2010-11-22 | 2012-06-14 | Koyo Electronics Ind Co Ltd | Multiple plc management system |
| CN104834264A (en) * | 2015-04-22 | 2015-08-12 | 青岛四方车辆研究所有限公司 | PLC detection system and method of Railway carriage control chamber |
| CN108693825A (en) * | 2018-04-23 | 2018-10-23 | 西门子工厂自动化工程有限公司 | The detection method and device of PLC input/output modules |
| CN108845563A (en) * | 2018-06-26 | 2018-11-20 | 北京工业大学 | A kind of method and system for testing PLC program and PLC monitoring software |
| CN109947087A (en) * | 2019-04-17 | 2019-06-28 | 湖南优利泰克自动化系统有限公司 | PLC input/output module test method, device, system and computer equipment |
| CN110501965A (en) * | 2019-07-18 | 2019-11-26 | 浙江工业大学 | Based on the acquisition of Embedded remote PLC data and early warning system |
| CN110941524A (en) * | 2018-09-21 | 2020-03-31 | 广达电脑股份有限公司 | Heat dissipation management method and system using management controller in computing device |
| CN111007796A (en) * | 2019-12-31 | 2020-04-14 | 郑州信大捷安信息技术股份有限公司 | PLC safety real-time monitoring method and system |
| CN114035555A (en) * | 2021-11-19 | 2022-02-11 | 武汉润致新电子科技有限公司 | PLC controller fault detection system |
| CN115963775A (en) * | 2023-03-15 | 2023-04-14 | 深圳华龙讯达信息技术股份有限公司 | PLC state monitoring system and method based on characteristic signal data |
-
2023
- 2023-05-15 CN CN202310538373.3A patent/CN116257019B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012113408A (en) * | 2010-11-22 | 2012-06-14 | Koyo Electronics Ind Co Ltd | Multiple plc management system |
| CN104834264A (en) * | 2015-04-22 | 2015-08-12 | 青岛四方车辆研究所有限公司 | PLC detection system and method of Railway carriage control chamber |
| CN108693825A (en) * | 2018-04-23 | 2018-10-23 | 西门子工厂自动化工程有限公司 | The detection method and device of PLC input/output modules |
| CN108845563A (en) * | 2018-06-26 | 2018-11-20 | 北京工业大学 | A kind of method and system for testing PLC program and PLC monitoring software |
| CN110941524A (en) * | 2018-09-21 | 2020-03-31 | 广达电脑股份有限公司 | Heat dissipation management method and system using management controller in computing device |
| CN109947087A (en) * | 2019-04-17 | 2019-06-28 | 湖南优利泰克自动化系统有限公司 | PLC input/output module test method, device, system and computer equipment |
| CN110501965A (en) * | 2019-07-18 | 2019-11-26 | 浙江工业大学 | Based on the acquisition of Embedded remote PLC data and early warning system |
| CN111007796A (en) * | 2019-12-31 | 2020-04-14 | 郑州信大捷安信息技术股份有限公司 | PLC safety real-time monitoring method and system |
| CN114035555A (en) * | 2021-11-19 | 2022-02-11 | 武汉润致新电子科技有限公司 | PLC controller fault detection system |
| CN115963775A (en) * | 2023-03-15 | 2023-04-14 | 深圳华龙讯达信息技术股份有限公司 | PLC state monitoring system and method based on characteristic signal data |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116257019A (en) | 2023-06-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109001649B (en) | Intelligent power supply diagnosis system and protection method | |
| US20180107196A1 (en) | Method of Detecting Home Appliance Bus Control System | |
| CN108474806B (en) | System and method for monitoring manufacturing | |
| CN104390657B (en) | A kind of Generator Unit Operating Parameters measurement sensor fault diagnosis method and system | |
| US10496051B2 (en) | Event analyzing device, event analyzing system, event analyzing method, and non-transitory computer readable storage medium | |
| US20170131705A1 (en) | Field device, field device system, and diagnostic method | |
| US20070043539A1 (en) | Abnormality monitoring system and abnormality monitoring method | |
| CN111542791B (en) | Facility diagnosis method using facility diagnosis system | |
| US11181890B2 (en) | Control system, information processing device, and anomaly factor estimation program | |
| CN113552840A (en) | Machining control system | |
| KR102483811B1 (en) | Abnormal status monitoring and controlling system for automated process | |
| CN114037673B (en) | Hardware connection interface monitoring method and system based on machine vision | |
| CN108388237B (en) | Fault diagnosis method, device, equipment and medium for discrete manufacturing equipment | |
| CN110941558B (en) | Intelligent office remote operation and maintenance method and system | |
| CN109240253B (en) | Online equipment diagnosis and preventive maintenance method and system | |
| TWI586943B (en) | Enhanced-fft online machine vibration measurement system and method | |
| CN113253711B (en) | Ceramic manufacturing method based on Internet of things, cloud server, industrial control equipment and system | |
| CN116257019B (en) | PLC (programmable logic controller) management method and system based on cloud | |
| CN112650068B (en) | Household fault detection method and device based on intelligent current sensor | |
| CN107194034B (en) | GPR-based equipment damage detection method and system | |
| CN110703721B (en) | Method and device for monitoring a production process | |
| CN102915032A (en) | Method for detecting state of electronic control system and diagnosing faults | |
| CN112579665A (en) | Energy equipment control method and device and energy equipment | |
| TWM584502U (en) | Equipment utilization rate and abnormality detection system | |
| CN107045325B (en) | Control method and device based on object characteristic value |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |