CN112484767A - Automatic fault diagnosis method and device for icing equipment - Google Patents
Automatic fault diagnosis method and device for icing equipment Download PDFInfo
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Abstract
The invention discloses an automatic fault diagnosis method and device for icing equipment, wherein the method comprises the steps of processing and analyzing data received by an icing monitoring system, judging whether the equipment has a fault according to an analysis result, and judging the type and the reason of the fault if the equipment has the fault; providing a maintenance scheme corresponding to the fault type according to the judged fault type and reason; the fault types comprise equipment offline, data acquisition abnormity and image acquisition abnormity. The invention can lead the background of the icing detection system to directly pre-judge the possible failure reason of the equipment according to the data uploaded by the icing equipment and provide a suggested maintenance scheme, thereby effectively reducing the time of manual investigation, reducing the consumption of human resources and avoiding the occurrence of failure statistics and artificial misjudgment as much as possible.
Description
Technical Field
The invention relates to the technical field of equipment diagnosis, in particular to an automatic diagnosis method and device for faults of icing equipment.
Background
The existing transmission line icing monitoring devices are all uniformly connected to the backstage of the icing monitoring system in each area in a wireless mode. The system can only simply judge whether the device is off-line or not, has no data and the like, but cannot automatically diagnose and analyze specific fault types, fault reasons and the like, has high false alarm rate and cannot comprehensively judge all data. Whether the device does fail or not basically needs to be checked one by depending on manual work, and related personnel fill the failure into a corresponding report form. Along with the increase of the ice coating device year by year, the corresponding workload is increased gradually, a large amount of manpower is consumed to check the corresponding faults in the ice season every year, and however, the conditions of omission or human judgment errors are inevitable.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides an automatic fault diagnosis method and device for icing equipment, which are used for autonomously judging whether faults exist in an icing terminal and distinguishing corresponding fault types and fault reasons.
In order to achieve the purpose, the technical scheme of the invention is as follows:
in a first aspect, an embodiment of the present invention provides an automatic fault diagnosis method for an icing device, where data acquired by the icing device is transmitted to an icing monitoring system for a power transmission line, and the method includes:
processing and analyzing the data received by the ice coating monitoring system, judging whether equipment fails according to an analysis result, and if so, judging the type and reason of the failure;
providing a maintenance scheme corresponding to the fault type according to the judged fault type and reason;
the fault types comprise equipment offline, data acquisition abnormity and image acquisition abnormity.
In a second aspect, an embodiment of the present invention provides an automatic diagnosing apparatus for ice coating equipment failure, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method when executing the computer program.
In a third aspect, the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the method described above.
Compared with the prior art, the invention has the beneficial effects that:
according to the automatic fault diagnosis method for the icing equipment, the background of the icing detection system can directly pre-judge the possible fault reasons of the equipment according to the data uploaded by the icing equipment, and a suggested maintenance scheme is provided, so that the manual troubleshooting time can be effectively shortened, the human resource consumption is reduced, and the fault statistics missing and the occurrence of human misjudgment are avoided as much as possible.
Drawings
Fig. 1 is a flowchart of an automatic fault diagnosis method for an ice coating apparatus according to embodiment 1 of the present invention;
FIG. 2 is a flow chart of an apparatus offline determination;
FIG. 3 is a flow chart illustrating the process of determining the reason for the offline status of the device;
FIG. 4 is a flow chart of data collection abnormality determination;
FIG. 5 is a flow chart of the temperature sensor abnormality determination;
FIG. 6 is a flow chart of wind speed sensor abnormality determination;
FIG. 7 is a flow chart of the wind direction sensor abnormality determination;
FIG. 8 is a flow chart of abnormality determination of the tension sensor;
FIG. 9 is a flowchart of image failure determination;
FIG. 10 is a flowchart of image black failure determination;
fig. 11 is a schematic composition diagram of an automatic diagnosing apparatus for ice coating equipment failure according to embodiment 2 of the present invention.
Detailed Description
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1:
as the data acquired by the icing equipment is transmitted to the transmission line icing monitoring system, the method for automatically diagnosing the fault of the icing equipment provided by the embodiment is mainly deployed on the background of the transmission line icing detection system, and as shown in fig. 1, the method for automatically diagnosing the fault of the icing equipment provided by the embodiment specifically comprises the following steps:
101. processing and analyzing the data received by the ice coating monitoring system, judging whether equipment fails according to an analysis result, and if so, judging the type and reason of the failure;
102. providing a maintenance scheme corresponding to the fault type according to the judged fault type and reason;
103. the fault types comprise equipment offline, data acquisition abnormity and image acquisition abnormity.
Therefore, the method for automatically diagnosing the fault of the icing equipment can enable the background of the icing detection system to directly pre-judge the possible fault reason of the equipment according to the data uploaded by the icing equipment, and provide a suggested maintenance scheme, so that the time for manual troubleshooting can be effectively reduced, the human resource consumption can be reduced, and the fault statistics and the occurrence of artificial misjudgment can be avoided as much as possible.
Specifically, the method for determining the offline fault of the device is as follows:
if the system does not receive the heartbeat data returned by the device after a certain time A (unit of minutes), the equipment can be considered to be in an off-line state. The default parameter a (in minutes) is set empirically by the operation and maintenance personnel and is typically 15-30 minutes.
The specific judgment method is as follows:
as shown in fig. 2, the system automatically records the heartbeat interval, the acquisition interval, the online time and the sleep time in the device configuration information, which are respectively a, b, c and d (unit minute). When d is 0, it represents that the device has no sleep state.
And when d is equal to 0, judging according to the values of a and b, taking the interval as a reference (generally, a is equal to 1, b is equal to 10, 15 and 20), adding A minutes as a time criterion 1, taking the data type of the interval with a short interval as a type criterion 1, and if b is greater than a, judging that the device is off-line if the heartbeat data (the type criterion 1) is not received after the time of b + A minutes (the time criterion 1).
When d is greater than 0, d + a minutes is used as a time criterion 2, and the collected data, the heartbeat data and the sleep notification information are simultaneously used as a type criterion 2, for example: and if any collected data, heartbeat data and sleep notification information are not received within d + A minutes, the equipment is considered to be offline.
Therefore, whether the equipment is in the offline fault or not can be accurately and efficiently judged by the method
The judgment of the offline fault reason of the equipment comprises the following steps:
if all or most of the equipment is offline, whether the background server network has problems or not needs to be checked, the proportion can be set, and when the online equipment is offline in a certain percentage, a maintenance scheme suggestion is given: and checking whether the server, the system background and the network have faults or not.
As shown in fig. 3, a device battery voltage low voltage protection judgment value B (usually 12V, which can be set) is set, the device battery voltage is checked, when the battery voltage is less than B, the battery trend is checked, if the battery voltage is decreased all the time or only slightly increased (not exceeding 13V) within C days (usually 10 days, which can be set), and the offline time point is not more than 30 days from the initial installation time (which can be set), it is determined that the power supply system solar panel is oriented incorrectly, or the battery is in a fault or the charging and discharging function is abnormal;
checking the battery voltage of the equipment, checking the battery trend when the battery voltage is less than B, and judging that the equipment is off-line possibly due to low-voltage protection of the battery if the battery voltage is reduced all the time or only slightly increased (not exceeding 13V) within C days (usually 10 days, which can be set), and the off-line time point is more than 30 days (which can be set) away from the initial installation time;
checking the battery voltage of the equipment, and checking the battery when the battery voltage is less than B;
checking the battery voltage of the equipment, when the battery voltage is greater than B, checking the signal intensity, and judging whether the field signal is weak or not to cause the equipment to be off-line when the signal intensity is less than 50 percent (can be set);
if the battery voltage is greater than B and the signal intensity is greater than 50% (which can be set), judging that the communication card or the master control fault possibly causes the equipment to be off-line;
the equipment offline fault maintenance method proposal comprises the following steps:
the offline time is not more than 30 days from the initial installation time, the orientation of the solar panel of the power supply system is judged to be incorrect or the battery is in fault or the charging and discharging function is abnormal, and the system provides a maintenance proposal: and (4) preparing a solar panel, a battery and a charge-discharge controller, and checking and repairing the power supply system on site.
And (3) judging that the low-voltage protection of the battery causes the equipment to be off-line and the equipment does not return to be on-line beyond D days (usually 7 days which can be set), and giving a maintenance scheme suggestion by the system: and (5) checking the master control and power supply system, and replacing or repairing the fault component. If the system gives a maintenance plan recommendation within D days: and (5) temporarily not maintaining, and recovering after the equipment is charged.
And judging that the weak signal causes the equipment to be offline, four maintenance proposal suggestions are given: attempting to replace the large gain antenna; notifying an operator of the enhanced signal; attempting to change operators; and confirming the tower position without the signal, and suggesting tower replacement installation.
Judging whether the communication card or the master control fault causes the offline, and providing 2 maintenance proposal suggestions: inquiring the state of the communication card, and confirming that the phenomena of arrearage, no number, service closing and the like do not exist; and confirming the problem of the non-communication card, and replacing the main control unit.
When the device is determined to be in the online state, entering a determination of data collection abnormality, as shown in fig. 4-8, where the determination of data collection abnormality includes:
judging whether all sensors on the equipment are abnormal;
if the data uploaded by the equipment are all 0, retrieving tension/inclination angle and meteorological data, and judging whether the data are synchronous or not, if not, judging that all acquisition abnormalities are caused by faults of a single sensor or a plurality of sensors; if yes, judging all acquisition abnormalities caused by main control faults or single sensor faults;
if not all 0, see the following judgment method.
The temperature data is in abnormal values for a long time, the threshold value can be set, in a south net area, the high-temperature threshold value is usually set to be 50 ℃ (can be set), the low-temperature threshold value is set to be-30 ℃, and when the sensor is in the temperature for a long time (usually 48h, can be set), the temperature sensor is judged to be in fault.
If the humidity data is 0 for a long time (usually 48h, which can be set), judging that the humidity sensor is in fault;
if the wind speed data remains unchanged for a long time (generally 48h, which can be set) but is not equal to 0, judging that the wind speed sensor is in fault;
if the wind speed data is 0 for a long time (usually 7 days, and can be set), and the wind direction is kept unchanged, the wind speed sensor is judged to be in fault
If the wind direction data is kept unchanged but not equal to 0 for a long time (generally 48h, which can be set), and the wind speed is kept unchanged, judging that the wind direction sensor is in fault;
if the wind direction data is 0 for a long time (usually 7 days, which can be set), and the wind speed is kept unchanged, judging that the wind direction sensor is in failure;
the long-term (usually 24h, settable) data of the tension sensor is 0, and the fault of the tension sensor is judged;
when the ice coating period is in (background system setting, usually 10 months to 3 months of the second year), the measured data of the tension sensor is more than e (set according to experience, the common coefficient is 2.5-5, and the pertinence setting is carried out according to the tower position tower type and the tension data during ice coating of the previous year) multiplied by original tension data (tension data during initial installation, which is not ice coating period data during installation, and if the ice coating period data needs the non-ice coating period of the second year), the data of the tension sensor is judged to be larger;
when the ice coating is in the non-ice coating period, if the measured data of the tension sensor is larger than f (set according to experience, the common coefficient is 2) multiplied by the original tension value, the data of the tension sensor is judged to be larger;
when the original tension value of the tension sensor is larger than Ekg (set according to experience), the tension sensor is started, the measurement data of the tension sensor is smaller than g (set according to experience, the common coefficient is 0.5, and the setting is carried out according to the data of the past year, the tower type and the tower position) multiplied by the original tension value, and the data of the tension sensor is judged to be smaller.
The intermittent data of the tension sensor is 0 (not all 0), and when the data which is uploaded every day and exceeds a certain proportion F (set according to experience and default of 30%) of the tension sensor with the same address code is 0, the jumping of the tension sensor is judged.
The method for maintaining the abnormity of the collected data of the equipment comprises the following steps:
all data acquisition is abnormal (0) and synchronization is confirmed to be abnormal, and a maintenance scheme proposal is given: when a small amount of spare parts are in a non-power-off state, the tower is put on the tower to find out the accurate reasons of the fault, the fault can be maintained directly on site, and the spare parts with the fault need to be maintained in a power-off state;
all data acquisition is abnormal (0) and is confirmed to be caused by one or more sensor faults, and a maintenance suggestion is given: replacing a faulty weather (tension) sensor;
temperature, humidity, wind speed, wind direction trouble, give the maintenance suggestion: replacing a faulty meteorological sensor;
the method comprises the following steps of (1) giving maintenance suggestions due to the fact that the tension sensor has faults, large data and small data: and replacing the failed tension sensor.
When the device is determined to be in the online state, determining that the image acquisition is abnormal, as shown in fig. 9-10, where the determining of the image acquisition abnormality includes: the judging method comprises the following steps:
and (3) uploading no data for a long time (generally 48h, which can be set), automatically sending an instruction to the system to retrieve the photographing schedule, and if the photographing schedule does not exist, automatically resetting the preset default photographing schedule by the system and automatically and remotely repairing the fault. If the shooting time table exists, judging that the device camera or the master control image snapshot module has a fault;
the method comprises the following steps of (1) continuously judging that a plurality of image files are less than G (usually 50k according to experience), judging that an uploaded image is incomplete or a black image, and simultaneously judging signal strength which is less than 60% (can be set), and judging that images cannot be transmitted due to camera failure or master control image snapshot module failure or signal problems; if the signal intensity is larger than 60% (can be set), only judging that the camera is in fault or the main control image snapshot module is in fault.
Therefore, whether the image acquisition is abnormal in fault can be accurately and efficiently judged by the method.
The image data abnormity maintenance method suggestion comprises the following steps:
if the system does not have the schedule, the system automatically re-issues the default schedule, after the system receives the front-end reply and the master control re-inquires the schedule again to confirm the schedule, the master control gives an instruction to display the re-issued schedule; if the front end does not reply after sending or the query schedule is still empty after replying, and the same is still true after trying for multiple times, a maintenance suggestion is given: and (5) replacing the master control when the master control fails.
If the camera or the master control image snapshot module of the device is judged to have faults, a maintenance suggestion is given: and replacing the fault device after the master control and the camera are checked on site.
In conclusion, the invention can comprehensively judge the accurate fault reason of the device according to the data of the equipment, can directly pre-judge the possible fault reason of the equipment, and provides a suggested maintenance scheme, thereby effectively reducing the time of manual troubleshooting, reducing the consumption of human resources and avoiding the occurrence of fault statistics and false judgment as much as possible.
Implementation 2:
referring to fig. 11, the automatic diagnosing apparatus for ice coating equipment failure according to the present embodiment includes a processor 111, a memory 112, and a computer program 113 stored in the memory 112 and capable of running on the processor 111, such as an automatic diagnosing program for ice coating equipment failure. The processor 111, when executing the computer program 113, implements the steps of embodiment 1 described above, such as the steps shown in fig. 1.
Illustratively, the computer program 113 may be divided into one or more modules/units, which are stored in the memory 112 and executed by the processor 111 to accomplish the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 113 in the automatic diagnosing apparatus for ice coating equipment failure.
The automatic fault diagnosis device for the icing equipment can be computing equipment such as a desktop computer, a notebook computer, a palm computer and a cloud server. The automatic diagnosing device for the fault of the ice coating equipment can include, but is not limited to, a processor 111 and a memory 112. It will be understood by those skilled in the art that fig. 5 is merely an example of an automatic diagnosing apparatus for failure of an ice coating device, and does not constitute a limitation of the automatic diagnosing apparatus for failure of an ice coating device, and may include more or less components than those shown in the drawings, or may combine some components, or different components, for example, the automatic diagnosing apparatus for failure of an ice coating device may further include an input/output device, a network access device, a bus, etc.
The Processor 111 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable Gate Array (FPGA) or other programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 112 may be an internal storage element of the automatic diagnosing apparatus for diagnosing faults of the ice coating equipment, such as a hard disk or a memory of the automatic diagnosing apparatus for diagnosing faults of the ice coating equipment. The memory 112 may also be an external storage device of the automatic diagnosing apparatus for ice coating equipment, such as a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the automatic diagnosing apparatus for ice coating equipment. Further, the memory 112 may also include both an internal storage unit and an external storage device of the automatic diagnosing apparatus for a malfunction of the ice coating device. The memory 112 is used for storing the computer program and other programs and data required by the automatic diagnosing apparatus for failure of the ice coating equipment. The memory 112 may also be used to temporarily store data that has been output or is to be output.
Example 3:
the present embodiment provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the steps of the method of embodiment 1.
The computer-readable medium can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Further, the computer readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
The above embodiments are only for illustrating the technical concept and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention accordingly, and not to limit the protection scope of the present invention accordingly. All equivalent changes or modifications made in accordance with the spirit of the present disclosure are intended to be covered by the scope of the present disclosure.
Claims (10)
1. A fault automatic diagnosis method for icing equipment is characterized in that data collected by the icing equipment is transmitted to an icing monitoring system of a power transmission line, and the method comprises the following steps:
processing and analyzing the data received by the ice coating monitoring system, judging whether equipment fails according to an analysis result, and if so, judging the type and reason of the failure;
providing a maintenance scheme corresponding to the fault type according to the judged fault type and reason;
the fault types comprise equipment offline, data acquisition abnormity and image acquisition abnormity.
2. The method for automatically diagnosing the faults of the icing equipment according to claim 1, wherein the mode of judging the fault type of the equipment as the equipment offline mode is as follows:
and if the icing monitoring system does not receive heartbeat data returned by the icing equipment after the set time A is exceeded, judging that the equipment is in an off-line state, wherein the unit of A is minutes.
3. The method for automatically diagnosing the faults of the icing equipment as claimed in claim 2, wherein the method for judging the equipment to be in the off-line state comprises the following steps:
the icing monitoring system automatically records heartbeat intervals, acquisition intervals, online time and dormancy time in equipment configuration information, wherein the heartbeat intervals, the acquisition intervals, the online time and the dormancy time are respectively a, b, c and d, and the unit is minutes; when d is 0, representing that the equipment has no dormant state;
when d is equal to 0, judging according to the values of a and b, taking the long interval as a reference, adding A minutes as a time criterion 1, taking the data type of the short interval as a type criterion 1, and if b is larger than a, judging that the device is off-line if the heartbeat data is not received after b + A minutes;
and when d is greater than 0, taking d + A minutes as a time criterion 2, taking the collected data, the heartbeat data and the sleep notification information as a type criterion 2 at the same time, and considering the equipment to be offline if any collected data, heartbeat data and sleep notification information are not received within d + A minutes.
4. The method for automatically diagnosing the faults of the icing equipment as claimed in claim 3, wherein the mode of judging the reasons of the offline faults of the equipment is as follows:
if all the equipment is offline or exceeds the set proportion, checking whether the background server network has problems, and when the online equipment exceeding the set proportion is offline, giving a maintenance proposal: checking whether the server, the system background and the network have faults or not;
setting a device battery voltage low-voltage protection judgment value B, checking the device battery voltage, checking the battery trend when the battery voltage is less than B, and judging that a power supply system solar panel of the device faces incorrectly or the battery fails or the charging and discharging functions are abnormal if the battery voltage is reduced all the time or only slightly increased within C days, the increase amplitude does not exceed a set value, and the distance between an offline time point and initial installation time does not exceed set time;
checking the battery voltage of the equipment, checking the battery trend when the battery voltage is less than B, and if the battery voltage is always reduced or only slightly increased within C days, the increasing amplitude does not exceed a set value, and the distance from the offline time point to the initial installation time exceeds the set value, judging that the equipment is possibly offline due to low-voltage protection of the battery;
checking the battery voltage of the equipment, and checking the battery when the battery voltage is less than B;
checking the battery voltage of the equipment, when the battery voltage is greater than B, checking the signal intensity, and if the signal intensity is less than a set value, judging that the equipment is off-line due to weak field signals;
if the battery voltage is greater than B and the signal strength is greater than the set value, it is determined that the equipment is off-line due to communication card or master control failure.
5. The method for automatically diagnosing the faults of the icing equipment as claimed in claim 1, wherein when the equipment is judged to be in an online state, the judgment of the abnormity of the collected data is entered, and the judgment of the abnormity of the collected data comprises the following steps:
judging whether all sensors on the equipment are abnormal;
if the data uploaded by the equipment are all 0, retrieving tension/inclination angle and meteorological data, and judging whether the data are synchronous or not, if not, judging that all acquisition abnormalities are caused by faults of a single sensor or a plurality of sensors; if yes, judging all acquisition abnormalities caused by main control faults or single sensor faults;
if the data uploaded by the equipment are not all 0, the following judgment is carried out:
if the temperature data is in an abnormal value for a long time, judging that the temperature sensor has a fault, wherein the long time is the set time;
if the humidity data is 0 for a long time, judging that the humidity sensor has a fault; the long term is the set time;
if the wind speed data is kept unchanged for a long time but is not equal to 0, judging that the wind speed sensor has a fault; the long term is the set time;
if the wind speed data is 0 for a long time and the wind direction is kept unchanged, judging that the wind speed sensor has a fault; the long term is the set time;
if the wind direction data keeps unchanged for a long time but is not equal to 0 and the wind speed keeps unchanged, judging that the wind direction sensor has a fault; the long term is the set time;
if the wind direction data is 0 for a long time and the wind speed is kept unchanged, judging that the wind direction sensor has a fault; the long term is the set time;
judging the fault of the tension sensor when the long-term data of the tension sensor is 0; the long term is the set time;
when the ice-covering period is in, the measured data of the tension sensor is larger than e multiplied by the original tension data, the data of the tension sensor is judged to be larger, and e is a coefficient;
when the ice coating is in the non-icing period, if the measured data of the tension sensor is larger than f multiplied by the original tension value, the data of the tension sensor is judged to be larger, and f is a coefficient;
when the original tension value of the tension sensor is larger than Ekg, the tension sensor is started, and the measurement data of the tension sensor is smaller than g multiplied by the original tension value, the data of the tension sensor is judged to be smaller, and g is a coefficient;
the intermittent data of the tension sensor is 0, and when the tension sensor with the same address code uploaded every day exceeds a set proportion F (the data is 0), the jump of the tension sensor is judged.
6. The method of claim 5, wherein the collected data anomaly maintenance protocol comprises:
all data acquisition is abnormal and synchronization is confirmed to be abnormal, and a maintenance scheme proposal is given: when the spare parts are in a non-power-off state, the tower is put on the tower to find out the accurate reasons of the faults, the faults can be maintained directly on site, and the power-off maintenance is needed for maintaining the fault spare parts;
all data acquisition is abnormal and the data is confirmed to be caused by one or more sensor faults, and a maintenance suggestion is given: replacing a faulty meteorological sensor;
temperature, humidity, wind speed, wind direction trouble, give the maintenance suggestion: replacing a faulty meteorological sensor;
the method comprises the following steps of (1) giving maintenance suggestions due to the fact that the tension sensor has faults, large data and small data: and replacing the failed tension sensor.
7. The method for automatically diagnosing the faults of the icing equipment as claimed in claim 2, wherein when the equipment is judged to be in an online state, the judgment of abnormal image acquisition is entered, and the judgment of the abnormal image acquisition comprises the following steps:
the image is uploaded without data within the set time, the icing monitoring system automatically sends an instruction to retrieve the photographing time table, and if the photographing time table is not available, the icing monitoring system automatically resets the preset default photographing time table and automatically and remotely repairs the fault; if the shooting time table exists, judging that the device camera or the master control image snapshot module has a fault;
judging whether the uploaded picture is incomplete or a black picture and judging the signal intensity at the same time when a plurality of continuous image files are smaller than a set value G, and judging whether the image cannot be transmitted due to the fault of a camera or the fault or signal problem of a master control image capturing module when the signal intensity is smaller than the set value; if the signal intensity is larger than the set value, only the fault of the camera or the fault of the master control image snapshot module is judged.
8. The method of claim 7, wherein the image capture anomaly maintenance protocol comprises:
if the icing monitoring system does not have the schedule, the icing monitoring system automatically re-issues the default schedule, and after the system receives the front-end reply and the master control re-inquires the schedule again to confirm the schedule, the master control gives an instruction to display the re-issued schedule; if the front end does not reply after sending or the query schedule is still empty after replying, and the same is still true after trying for multiple times, a maintenance suggestion is given: the master control is replaced when the master control fails;
if the camera or the master control image snapshot module of the device is judged to have faults, a maintenance suggestion is given: and replacing the fault device after the master control and the camera are checked on site.
9. An automatic fault diagnosis device for an ice coating plant, comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor implements the steps of the method according to any one of claims 1 to 8 when executing said computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.
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