CN112532433A - Universal network equipment fault analysis method based on ping and current characteristics - Google Patents
Universal network equipment fault analysis method based on ping and current characteristics Download PDFInfo
- Publication number
- CN112532433A CN112532433A CN202011302531.8A CN202011302531A CN112532433A CN 112532433 A CN112532433 A CN 112532433A CN 202011302531 A CN202011302531 A CN 202011302531A CN 112532433 A CN112532433 A CN 112532433A
- Authority
- CN
- China
- Prior art keywords
- network
- current
- equipment
- network equipment
- value
- 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.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0803—Configuration setting
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0823—Errors, e.g. transmission errors
- H04L43/0829—Packet loss
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0852—Delays
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
Abstract
The invention provides a universal network equipment fault analysis method based on ping and current characteristics, which comprises the steps of carrying out periodic current collection, calibration and analysis on an IO power supply port through a front-end management host, carrying out fault detection and analysis on network terminal equipment according to an equipment current empirical value, a network packet loss rate and network delay, and carrying out equipment fault alarm reporting and automatic restart processing according to user configuration. The method can realize the monitoring of the faults of the general network equipment, and can greatly improve the operation and maintenance efficiency of the network equipment through the functions of remote acquisition, alarming, control, restart recovery and the like, avoid manual inspection and save the operation and maintenance cost.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of network equipment monitoring, in particular to a universal network equipment fault analysis method based on ping and current characteristics.
[ background of the invention ]
In recent years, in order to meet the requirements of increasingly complex public security situations, governments all over the world have vigorously promoted the construction of video monitoring systems. Video monitoring points are set in places such as public security complex places, sections with frequent cases, main streets, key parts, important intersections, bayonets and the like, a video monitoring network covering the whole city and villages and towns is gradually formed, and the social efficiency of the monitoring system is effectively exerted. The use of the video private network monitoring system greatly improves the capability of timely discovering and disposing various illegal crimes and provides first-hand site data for detecting the illegal crimes; secondly, the traffic management capability is strengthened powerfully; thirdly, various illegal criminal activities are frightened effectively, and the safety of people is improved. The public security organization intuitively understands and masters the regional public security dynamics by browsing, video playback, data downloading and application monitoring video, and comprehensively improves the response capability and monitoring strength for dealing with emergency cases, group events and major security activities.
In the snow project and the skynet project, besides the video monitoring equipment, other network equipment such as network light supplement lamp equipment and wifi probes are deployed in many places. Since different network devices have different message formats, communication protocols and service characteristics, if each network device performs message characteristic analysis, the service characteristic analysis is not practical or necessary. However, for the front-end management host dedicated to operation and maintenance management of the video monitoring front-end terminal device, hierarchical fault detection is required according to the emphasis of the service. The core service device is used for performing special service analysis on the core service device, and is used for performing universal characteristic analysis on the general device. Therefore, in order to improve the operation and maintenance efficiency of the video monitoring front-end management device, the fault detection and analysis of the universal network device is also important, and a universal network device fault analysis method based on ping and current characteristics is provided.
[ summary of the invention ]
The invention aims to solve the problems in the prior art, and provides a universal network equipment fault analysis method based on ping and current characteristics, which can monitor the fault of the universal network equipment, improve the operation and maintenance efficiency of the network equipment and save the operation and maintenance cost.
In order to achieve the purpose, the invention provides a universal network equipment fault analysis method based on ping and current characteristics, which sequentially comprises the following steps:
s1, configuring access equipment parameter information: parameter configuration is carried out on access equipment accessed to an IO power supply port on a front-end management host through a central platform;
s2, automatic collection of starting current and automatic learning of experience values: starting an automatic current acquisition mode and an automatic experience value learning function of the access equipment through the central platform, periodically acquiring an effective current value of the network equipment by the front-end management host, and performing data analysis through the central platform to obtain a current experience value range;
s3, issuing the fault detection parameters, the fault reporting parameters and the current experience values to the front-end management host through the central platform;
s4, power supply fault detection: the front end management host compares and analyzes the access equipment parameters, the current empirical value range, the fault detection parameters and the current effective value of the network equipment which is periodically collected according to the user, if the power supply is normal, the step S5 is carried out to start the network fault detection, otherwise, the front end management host determines whether the equipment needs to be restarted according to the user configuration;
s5, network fault detection: the method comprises the steps of carrying out unified detection through a central platform, firstly storing configuration information of network equipment into a network equipment fault detection data table, then starting a group of network fault detection threads, periodically sending an ICMP message to the network equipment, reporting a suspected network abnormity alarm if the network packet loss rate and the network delay of the network equipment exceed a threshold value configured by a user, and determining whether the equipment needs to be restarted or not according to the user configuration.
Preferably, the step S1 of configuring the parameters includes: the device type, the device name, the brand model, the rated power, the error range, the power switch, the switching time, the ip address, the login user name and the password (optional) and the like.
Preferably, in step S2, the front-end management host collects the current effective value of the network device every 200ms through 485 (the current effective value is collected every 20ms inside the IO power supply detection), and generates a maximum value, a minimum value, and an average value; and then reporting data to a central platform every 10 minutes for data analysis to obtain the current empirical value range (maximum value and minimum value) of the brand model specification.
Preferably, in step S3, the fault detection parameters include: the method comprises the steps of detecting an enabling switch, detecting a network detection period, detecting a network packet loss rate, detecting a network delay and the like.
Preferably, in step S3, the fault reporting parameter includes alarm reporting information and whether the fault is restarted, and the alarm reporting information includes an alarm type, an alarm name, a severity level, whether to report, a remark description, and the like.
Preferably, in step S3, the empirical current value includes a maximum current value and a minimum current value.
Preferably, in step S4, if the collected current effective value does not fall within the empirical value range, it indicates that the network device is powered abnormally, and the counter is incremented by one; and if the power supply of the network equipment is abnormal for 3 times continuously, reporting that the power supply of the network equipment is abnormal, and judging whether the equipment needs to be restarted according to user configuration.
Preferably, in step S5, the main fields of the network device failure detection data table include a host number, a slot number, a port number, a device type, a device name, an IP address, a network packet loss rate, a network delay, a user name, and a password (which may be selected according to actual requirements).
Preferably, in step S5, the network failure detection thread uses a thread pool, and the number of threads can be automatically increased and decreased.
The invention carries out periodic current collection, calibration and analysis on the IO power supply port through the front-end management host, carries out fault detection and analysis on network terminal equipment according to the equipment current empirical value, the network packet loss rate and the network delay, and carries out equipment fault alarm reporting and automatic restart processing according to user configuration. For general network equipment, fault detection is respectively carried out from two aspects of network and power supply, and inhibition processing is carried out according to service priority. Therefore, during configuration, the network fault detection parameters and the power failure detection parameters need to be configured respectively. And the priority of the power supply abnormality alarm of the network equipment is greater than that of the network abnormality alarm, so that a suppression relation exists during alarm reporting.
The invention has the beneficial effects that:
firstly, errors caused by environmental factors and current acquisition components can be calibrated through automatic learning and configuration of current empirical values, and therefore false alarm is prevented.
And secondly, judging whether the network equipment is normal in power supply aspect by capturing the real-time current value of the network equipment and comparing the real-time current value with the work experience value.
And thirdly, periodically sending an ICMP message to the network equipment, and counting the network packet loss rate and the network delay to judge whether the network equipment is normal in the aspect of network communication.
And fourthly, the operation and maintenance efficiency of the network equipment can be greatly improved through the functions of remote acquisition, alarming, control, restart recovery and the like, manual inspection is avoided, and the operation and maintenance cost is saved.
The features and advantages of the present invention will be described in detail by embodiments in conjunction with the accompanying drawings.
[ description of the drawings ]
FIG. 1 is a system layout framework of the present invention;
FIG. 2 is a flow chart of parameter configuration of the present invention;
FIG. 3 is a flow chart of the current collection and empirical value auto-learning of the present invention;
FIG. 4 is a flow chart of the device power anomaly detection of the present invention;
fig. 5 is a flow chart of the device network anomaly detection of the present invention.
[ detailed description ] embodiments
One, environment building and configuration
First, the RJ45 port (WAN port) of the head end management host 1 is connected to the optical modem (as shown in fig. 1). And secondly, connecting an IO expansion power supply board card (such as IO _ P8_ AC220VB) to a 485 bus of the front-end management host 1 through 485. The power supplies of network device 1 and network device 2 are then plugged into power supply port 1 and power supply port 2, respectively, in the IO _ P8_ AC220VB board. And then the network ports of the network device 1 and the network device 2 are respectively connected to the LAN1 port and the LAN2 port of the front end management host 1. And finally, configuring information of the host and the central platform, wherein the information comprises the host ip, a mask, a gateway, the central platform ip, a logic board in the IO _ P8_ AC220VB, the network device 1 and the basic configuration of the network device in the IO board.
Secondly, testing whether the network equipment is normal or not
Switching the network equipment to a normal working mode, for example, turning on a light supplement lamp and turning on the lamp, and starting video recording by a camera; and then, detecting the current and voltage values of the network equipment 1 and the network equipment 2 through a multimeter, and if the obtained values are consistent with the specification, indicating that the power supply is normal.
And respectively ping the network device 1 and the network device 2 from the central platform server and the front end management host 1, if the both ok and the service are normal, the network is basically normal.
Thirdly, collecting and automatically learning current experience values of network equipment
Due to the influence of the actual working environment and the error of the current detection component, the actual standby current and the working current have certain deviation from the specification of the equipment. Therefore, calibration by empirical values of current is required. Since the network device has been verified as normal in step two, current value sampling and empirical value auto-learning and configuration follows.
And C, switching the network equipment to a working mode to operate for 24 hours to 48 hours to obtain a group of current sampling values of the equipment with the brand model in the working mode, and comparing and processing the current sampling values according to the current reference values and the deviation range obtained by measurement in the step II to obtain current experience values in the working mode. Note that: (1) the input voltage needs a voltage stabilizer, and the mains supply is basically normal. (2) The system runs under the environment of the front end management host machine such as nominal magnetic field, air pressure, temperature, humidity and the like.
Fourthly, configuring empirical values and configuring fault detection parameters
And issuing the current experience values learned by the network device 1 and the network device 2 in the step three to the front-end management host 1. Then, parameters of the fault such as a fault detection enabling switch, a detection period, debounce times, an alarm name, an alarm type, an alarm level, whether an alarm is reported or not, whether a fault is automatically processed or not and the like are configured into the front-end management host 1. And storing network detection parameters such as host serial number, slot number, port number, equipment type, ip address, network packet loss rate, network delay and the like into a data table.
Fifth, fault detection
The IO _ P8_ AC220VB board has 8 power ports of AC220VB, and each power port supports output voltage and current detection. When the system starts the fault detection of the network equipment, 64 values in a current oscillogram are collected every 20ms at the IO power supply board card side, and an effective current value is calculated according to the 64 values. At the moment, the front-end management host reads a group of current values in the IO _ P8_ AC220VB every 200ms through 485, namely, 10 effective current values are acquired by one network device and are compared according to current experience values, if the current values are not within the experience value range, a fault counter is increased by one, and if the count of the fault calculator reaches the fault detection debounce times, a suspected network device power supply abnormity alarm is reported, and self-repairing processing is carried out according to user configuration.
If the power supply is normal, the central platform can automatically start a group of threads according to the network equipment fault detection data table, and can adjust the number of the threads in the thread pool according to the dynamic change of the data table. Each thread reads N IP addresses once (which can be set, defaulted to 50), one IP address is sent once per second, 3 ICMP requests are sent once, 3 times in succession, each time 1 second is timed out. And polling a period for 150 seconds, if the network packet loss rate and the network delay of the network equipment exceed the threshold value configured by the user in continuous 3 periods, reporting a suspected network abnormality alarm, and restarting the network equipment according to the user configuration.
The above embodiments are illustrative of the present invention, and are not intended to limit the present invention, and any simple modifications of the present invention are within the scope of the present invention.
Claims (9)
1. A general network equipment fault analysis method based on ping and current characteristics is characterized in that: the method sequentially comprises the following steps:
s1, configuring access equipment parameter information: parameter configuration is carried out on access equipment accessed to an IO power supply port on a front-end management host through a central platform;
s2, automatic collection of starting current and automatic learning of experience values: starting an automatic current acquisition mode and an automatic experience value learning function of the access equipment through the central platform, periodically acquiring an effective current value of the network equipment by the front-end management host, and performing data analysis through the central platform to obtain a current experience value range;
s3, issuing the fault detection parameters, the fault reporting parameters and the current experience values to the front-end management host through the central platform;
s4, power supply fault detection: the front end management host compares and analyzes the access equipment parameters, the current empirical value range, the fault detection parameters and the current effective value of the network equipment which is periodically collected according to the user, if the power supply is normal, the step S5 is carried out to start the network fault detection, otherwise, the front end management host determines whether the equipment needs to be restarted according to the user configuration;
s5, network fault detection: the method comprises the steps of carrying out unified detection through a central platform, firstly storing configuration information of network equipment into a network equipment fault detection data table, then starting a group of network fault detection threads, periodically sending an ICMP message to the network equipment, reporting a suspected network abnormity alarm if the network packet loss rate and the network delay of the network equipment exceed a threshold value configured by a user, and determining whether the equipment needs to be restarted or not according to the user configuration.
2. The method of claim 1, wherein the method comprises the following steps: in step S1, parameter configuration is performed, including: the device type, the device name, the brand model, the rated power, the error range, the power switch, the switching time, the ip address, the login user name and the password.
3. The method of claim 1, wherein the method comprises the following steps: in step S2, the front-end management host acquires the current effective value of the network device every 200ms through 485 circuits, and generates a maximum value, a minimum value, and an average value; and then reporting data to a central platform every 10 minutes for data analysis to obtain the current experience value range of the brand model specification.
4. The method of claim 1, wherein the method comprises the following steps: in step S3, the fault detection parameters include: detecting an enabling switch, a network detection period, a network packet loss rate and network delay.
5. The method of claim 1, wherein the method comprises the following steps: in step S3, the fault reporting parameter includes alarm reporting information and whether the fault is restarted, where the alarm reporting information includes an alarm type, an alarm name, a severity level, whether to report, and a remark description.
6. The method of claim 1, wherein the method comprises the following steps: in step S3, the current empirical values include a current maximum value and a current minimum value.
7. A method for analyzing faults of a general network device based on ping and current characteristics as claimed in any one of claims 1 to 6, wherein: in step S4, if the collected current effective value does not fall within the empirical value range, it indicates that the network device is abnormally powered, and the counter is incremented by one; and if the power supply of the network equipment is abnormal for 3 times continuously, reporting that the power supply of the network equipment is abnormal, and judging whether the equipment needs to be restarted according to user configuration.
8. The method of claim 1, wherein the method comprises the following steps: in step S5, the main fields of the network device fault detection data table include a host number, a slot number, a port number, a device type, a device name, an IP address, a network packet loss rate, a network delay, a user name, and a password.
9. The method of claim 1, wherein the method comprises the following steps: in step S5, the network failure detection thread uses a thread pool.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011302531.8A CN112532433B (en) | 2020-11-19 | 2020-11-19 | Universal network equipment fault analysis method based on ping and current characteristics |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011302531.8A CN112532433B (en) | 2020-11-19 | 2020-11-19 | Universal network equipment fault analysis method based on ping and current characteristics |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112532433A true CN112532433A (en) | 2021-03-19 |
| CN112532433B CN112532433B (en) | 2023-04-07 |
Family
ID=74981481
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011302531.8A Active CN112532433B (en) | 2020-11-19 | 2020-11-19 | Universal network equipment fault analysis method based on ping and current characteristics |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112532433B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116319501A (en) * | 2023-05-25 | 2023-06-23 | 深圳市英创立电子有限公司 | Network system for obtaining equipment operation parameters |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100102631A1 (en) * | 2008-10-24 | 2010-04-29 | Shih-Chien Chiou | Apparatus power restart method in response to network connection status |
| CN103220173A (en) * | 2013-04-09 | 2013-07-24 | 北京搜狐新媒体信息技术有限公司 | Alarm monitoring method and alarm monitoring system |
| US20150304372A1 (en) * | 2012-11-29 | 2015-10-22 | Dolby Laboratories Licensing Corporaton | Systems for Providing Services in a Voice Conferencing Environment |
| CN205353706U (en) * | 2015-12-22 | 2016-06-29 | 成都史塔克智能科技有限公司 | Electrical equipment failure monitoring system |
| CN107356883A (en) * | 2017-08-09 | 2017-11-17 | 安徽科力信息产业有限责任公司 | A kind of signal lamp failure detection means and method based on current effective value |
| CN108988961A (en) * | 2018-07-10 | 2018-12-11 | 西华大学 | A kind of radio monitoring operation management system |
| CN109412880A (en) * | 2017-08-17 | 2019-03-01 | 中车株洲电力机车研究所有限公司 | A kind of communication device initiated abnormal test method of train network |
| CN111010533A (en) * | 2019-11-04 | 2020-04-14 | 华南理工大学 | Method and system for automatically reporting power supply and network connection state of AR camera |
| CN111082999A (en) * | 2019-12-31 | 2020-04-28 | 国网四川省电力公司泸州供电公司 | Self-induction self-rescue PDU (Power distribution Unit) of network equipment and self-induction self-rescue method thereof |
| CN111830846A (en) * | 2020-07-24 | 2020-10-27 | 贵州电网有限责任公司 | Power distribution network fault testing method and system based on simulation testing platform |
-
2020
- 2020-11-19 CN CN202011302531.8A patent/CN112532433B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100102631A1 (en) * | 2008-10-24 | 2010-04-29 | Shih-Chien Chiou | Apparatus power restart method in response to network connection status |
| US20150304372A1 (en) * | 2012-11-29 | 2015-10-22 | Dolby Laboratories Licensing Corporaton | Systems for Providing Services in a Voice Conferencing Environment |
| CN103220173A (en) * | 2013-04-09 | 2013-07-24 | 北京搜狐新媒体信息技术有限公司 | Alarm monitoring method and alarm monitoring system |
| CN205353706U (en) * | 2015-12-22 | 2016-06-29 | 成都史塔克智能科技有限公司 | Electrical equipment failure monitoring system |
| CN107356883A (en) * | 2017-08-09 | 2017-11-17 | 安徽科力信息产业有限责任公司 | A kind of signal lamp failure detection means and method based on current effective value |
| CN109412880A (en) * | 2017-08-17 | 2019-03-01 | 中车株洲电力机车研究所有限公司 | A kind of communication device initiated abnormal test method of train network |
| CN108988961A (en) * | 2018-07-10 | 2018-12-11 | 西华大学 | A kind of radio monitoring operation management system |
| CN111010533A (en) * | 2019-11-04 | 2020-04-14 | 华南理工大学 | Method and system for automatically reporting power supply and network connection state of AR camera |
| CN111082999A (en) * | 2019-12-31 | 2020-04-28 | 国网四川省电力公司泸州供电公司 | Self-induction self-rescue PDU (Power distribution Unit) of network equipment and self-induction self-rescue method thereof |
| CN111830846A (en) * | 2020-07-24 | 2020-10-27 | 贵州电网有限责任公司 | Power distribution network fault testing method and system based on simulation testing platform |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116319501A (en) * | 2023-05-25 | 2023-06-23 | 深圳市英创立电子有限公司 | Network system for obtaining equipment operation parameters |
| CN116319501B (en) * | 2023-05-25 | 2023-09-05 | 深圳市英创立电子有限公司 | Network system for obtaining equipment operation parameters |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112532433B (en) | 2023-04-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103200050B (en) | The hardware state monitoring method and system of server | |
| WO2018126645A1 (en) | Communication network management method and apparatus therefor | |
| CN108828406A (en) | The fault recognition method and its system of non-intrusion type user power utilization | |
| CN110988557B (en) | Equipment fault detection device based on real-time current detection | |
| CN105450472A (en) | Method and device for automatically acquiring states of physical components of servers | |
| CN110045178B (en) | Wind power comprehensive lightning protection monitoring method | |
| CN110954849B (en) | Abnormity detection system and method for electrical equipment and monitoring terminal | |
| CN111381163A (en) | Motor group fault early warning method and device | |
| CN107704359A (en) | A kind of monitoring system of big data platform | |
| CN112532433B (en) | Universal network equipment fault analysis method based on ping and current characteristics | |
| CN110988560A (en) | Medical equipment fault detection system and method based on real-time current | |
| CN110752959A (en) | Intelligent substation process layer physical link fault positioning system | |
| CN110333493A (en) | A kind of weather radar transmitter failure detection system and method | |
| CN117135343A (en) | Fault analysis method, device, equipment and storage medium | |
| CN115276235A (en) | Intelligent management system and method for transformer substation safety monitoring | |
| CN113300918A (en) | Fault detection method of intelligent lamp pole, terminal device and storage medium | |
| CN107306213A (en) | Diagnostic method and diagnostic device for network | |
| CN113379082A (en) | Cloud intelligent monitoring energy-saving and operation and maintenance management platform for clean industrial environment and equipment | |
| CN113327741A (en) | Front end structure for monitoring oil-filled transformer in real time | |
| CN112865312A (en) | Power dispatching system and power data processing method | |
| CN212965187U (en) | Electronic equipment monitoring system | |
| WO2014173127A1 (en) | Communication network monitoring method, device and system in electric power system | |
| CN112557939A (en) | Explosion flash lamp fault analysis method based on current characteristic analysis | |
| CN117233515B (en) | Method and system for measuring state of outlet pressing plate | |
| CN216792879U (en) | Interactive terminal |
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 |