CN112462730A - Fault diagnosis method for underwater glider - Google Patents
Fault diagnosis method for underwater glider Download PDFInfo
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- CN112462730A CN112462730A CN202011071409.4A CN202011071409A CN112462730A CN 112462730 A CN112462730 A CN 112462730A CN 202011071409 A CN202011071409 A CN 202011071409A CN 112462730 A CN112462730 A CN 112462730A
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- 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
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0267—Fault communication, e.g. human machine interface [HMI]
- G05B23/027—Alarm generation, e.g. communication protocol; Forms of alarm
Abstract
The invention relates to a fault diagnosis method for an underwater glider. The method comprises the following steps: time sequence step of data request: loading an underwater glider controlled equipment list, and sending equipment data to be detected to a fault analysis module one by one; and (3) fault analysis: the fault analysis module analyzes the acquired equipment state data and outputs a fault level; and fault early warning: and outputting early warning response according to the fault level. The method designs a set of complete data request time sequence, combines the existing instruction response set of the data management module to sequentially acquire corresponding information, and effectively analyzes the faults in the aspects of GPS fault, current and voltage, working time, automatic navigation state, submergence depth, task execution state, flow field abnormity, in-situ circling, performance attenuation of an execution mechanism and the like and gives early warning to a user.
Description
Technical Field
The invention relates to the technical field of underwater glider control, in particular to a fault diagnosis method for an underwater glider.
Background
The underwater glider is a pre-programmed underwater vehicle which realizes underwater gliding by adjusting the buoyancy and the posture of the underwater glider, and the formation of the underwater glider is different from other types of underwater robots in cooperative control. The underwater glider formation method has the characteristics of low cost, simplicity in operation and control, flexibility in operation mode and the like, and the underwater glider formation is widely applied to high-precision long-time continuous observation in a specific sea area at present.
Because the underwater glider group can only carry out indirect interaction after asynchronous water outlet so as to complete data recovery and instruction updating, the health degree information such as attitude, endurance and the like of the underwater glider group and the potential failure risk prediction need to be analyzed item by item aiming at specified parameters by an experienced operator by using monitoring software, and when the controlled glider sleeve exceeds a certain order of magnitude, the speed of manual item-by-item analysis cannot be matched with the working efficiency of a glider team, so that the space-time resolution of an observation result is influenced. On the other hand, when the operator uses the monitoring software to perform analysis, the operator is interfered by a series of interferences such as equipment switching, parameter adjustment, data transmission, communication state conversion and the like, so that the probability of influencing a fault analysis result due to misoperation, data chaos and the like is greatly improved. Meanwhile, due to direct contact with relatively sensitive monitoring software, the exposure probability of sensitive data can be increased by artificial fault analysis. In addition, the artificial fault analysis result is difficult to be simultaneously displayed to users in different fields, so that the accuracy of the analysis method and the result is difficult to be comprehensively improved.
Disclosure of Invention
Aiming at the fault diagnosis of an underwater glider group, an automatic fault analysis and early warning method based on an underwater glider data management system is researched. Firstly, the fault of the underwater glider is divided into three levels of 'normal', 'warning' and 'abnormal'. "Normal" means that the state parameters of the underwater glider completely accord with the normal range and do not have larger sudden change; "warning" represents that the state parameter of the underwater glider exceeds the normal range and does not exceed 120% of the normal range, and sudden data sudden change caused by the reason that the system cannot judge whether the equipment is caused by the equipment or the change of the surrounding sea area environment occurs; "abnormal" means that the state parameter of the underwater glider exceeds 120% of the normal value range, and a fault of a definite cause occurs in the equipment itself.
The technical scheme adopted by the invention for realizing the purpose is as follows: a fault diagnosis method of an underwater glider comprises the following steps:
time sequence step of data request: loading an underwater glider controlled equipment list, and acquiring equipment data to be detected one by one for fault analysis;
and (3) fault analysis: the fault analysis module analyzes the acquired equipment state data and outputs a fault level;
and fault early warning: and outputting early warning response according to the fault level.
The data request timing step includes:
applying for a controlled device list, wherein the controlled device list is empty, acquiring core information of all devices, analyzing to obtain the number M of the controlled devices, and sequentially and repeatedly executing: and acquiring control information of the Nth controlled device, acquiring energy information of the Nth device, and acquiring track navigation information of the Nth device until all device information is acquired for fault analysis.
The faults of the underwater glider are divided into three levels of 'normal', 'warning' and 'abnormal':
"normal" represents that the state parameter of the underwater glider accords with the threshold value range under the normal working state, and indicates that no larger sudden change occurs;
the warning represents that the state parameter of the underwater glider exceeds the threshold range in the normal working state and does not exceed the preset percentage of the normal threshold range, and represents that sudden data sudden change which cannot be judged by a system occurs;
"abnormal" represents a preset percentage of the state parameter of the underwater glider exceeding the normal value range, and indicates that the equipment per se has a fault.
The fault early warning of the underwater glider adopts the following mode:
and sending the state value of each equipment data to a front-end display interface for displaying, and coloring fault data of different levels in different colors.
The fault early warning of the underwater glider also adopts the following mode:
and inputting a short message and a mail address, and sending the fault early warning information to a user of the front-end interface through the short message and the mail.
A fault diagnosis system for an underwater glider, comprising: the method comprises a land base station fault analysis module, a cloud data request module and a fault early warning module, wherein each module comprises a processing unit, a storage unit and a communication unit, the storage unit stores a program, and the processing unit loads the program and executes the steps of the fault diagnosis method of the underwater glider as claimed in any one of claims 1 to 5.
The data request module loads an underwater glider controlled equipment list and sends the equipment data to be detected to the fault analysis module one by one;
the fault analysis module analyzes the acquired equipment state data and outputs a fault level;
and the fault early warning module outputs early warning response according to the fault level.
And the data request module is communicated with the underwater glider through the iridium satellite to acquire the list information of the controlled equipment.
The invention has the following beneficial effects and advantages:
1. the method designs a set of complete data request time sequence, combines the existing instruction response set of a data management module to sequentially acquire corresponding information, and performs fault analysis on the aspects of GPS fault, current and voltage, working time, automatic navigation state, submergence depth, task execution state, flow field abnormity, in-situ circling, performance attenuation of an execution mechanism and the like.
2. The method disclosed by the invention is used for distributing the underwater gliders in the year for 97 times in total, wherein the large-scale networking observation experiment in south China sea ranges from 7-month and 11-month to 10-month and 15-month in 2019, and the online monitoring equipment is maximally carried out for 53 times. And (3) performing fault analysis on the equipment in the experiment more than 29000 times by using a fault analysis module, stably operating the system for more than 300 days, accurately analyzing the equipment abnormity for 10 times, warning for 24 times, wherein the analysis fault number covers more than 95% of the total fault number of the equipment, and the error rate is lower than 2% of the analysis fault number.
Drawings
FIG. 1 is a diagram of a fault analysis module architecture for the method of the present invention;
FIG. 2 is a data request timing workflow of the method of the present invention;
FIG. 3 is a fault analysis module interface of the method of the present invention;
FIG. 4 is a display interface of a failure analysis early warning web page of the method of the present invention;
FIG. 5 shows the real-time display effect of the early warning result of the observation fault of the underwater glider team according to the method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Aiming at the fault diagnosis of an underwater glider group, the invention researches an automatic fault analysis and early warning method based on an underwater glider data management system. Firstly, the fault of the underwater glider is divided into three levels of 'normal', 'warning' and 'abnormal'. "Normal" means that the state parameters of the underwater glider completely accord with the normal range and do not have larger sudden change; "warning" represents that the state parameter of the underwater glider exceeds the normal range and does not exceed 120% of the normal range, and sudden data sudden change caused by the reason that the system cannot judge whether the equipment is caused by the equipment or the change of the surrounding sea area environment occurs; "abnormal" means that the state parameter of the underwater glider exceeds 120% of the normal value range, and a fault of a definite cause occurs in the equipment itself. The failure level division and response mode are shown in table 1.
TABLE 1
As shown in fig. 1, the fault analysis and early warning method is divided into three modules, namely an "underwater glider data management module", a "fault analysis module", and a "fault early warning module". The underwater glider data management module is deployed on the monitoring server, monitors the designated network port, analyzes the received instruction and feeds back the corresponding result to the designated user according to the authority. The fault analysis module is deployed on a computer with network communication capacity, interacts with the data management module through the Internet/local area network, analyzes the acquired equipment state data, and feeds back an analysis result to the data management module for recording. The fault early warning module is deployed in the Ali cloud server, and when the fault early warning module is displayed to a user through a webpage, an analysis result reaching an abnormal state is sent to the user through a short message.
According to the method, a set of complete data request time sequence is designed under an underwater glider data management and fault analysis module, corresponding information is sequentially acquired by combining the existing instruction response set of the data management module, and fault analysis is performed on the aspects of GPS fault, current and voltage, working time, automatic navigation state, submergence depth, task execution state, flow field abnormity, in-situ hovering, performance attenuation of an execution mechanism and the like.
Data request timing:
as shown in fig. 2, it is a data request timing workflow of the method of the present invention: the sequence steps according to the data request of the underwater glider data request module are as follows: applying for the controlled list of equipment, the controlled equipment list is empty, acquires all equipment core information, resolves and obtains controlled equipment number M, sets N as 1, if N is less than or equal to M, repeatedly executes: and acquiring control information of the Nth controlled device, acquiring energy information of the Nth device, acquiring track navigation information of the Nth device, feeding back analysis results of all devices until N is M, and waiting for 20 minutes.
Responding to the data content:
[ core information ]: the method comprises the core information of all equipment, including equipment name, serial number, voltage, preposed task ending time, current task starting time, set timeout time, expected water outlet time and the like.
[ control information ]: the system comprises the information of the number, name, mission number, mission starting position, mission starting time, abnormal information, target point, automatic navigation state, course angle, speed, depth, health information, data transmission information, sensor configuration information, waypoint information, working mode, equipment standard voltage, predicted water outlet time and the like of the applied equipment.
[ energy information ]: including the name and number of the device being applied, and information on the minimum voltage, maximum current, and actuator time consumption for approximately ten cycles.
[ navigation information ]: including the name and number of the applied device, and the distance of nearly ten cycles, the task start point GPS and the task end point GPS information.
The GPS fault analysis method comprises the following steps: when the lower computer feeds back that the GPS is invalid, the abnormality is directly judged. And when the difference between the GPS position when the task is finished and the GPS position when the task is started is not more than 100 meters, judging that the vehicle is a warning. The rest are judged to be normal.
The voltage fault analysis method comprises the following steps: and determining that the condition is lower than 80% of the standard voltage as abnormal. The case of higher than 80% of the standard voltage and lower than 85% of the standard voltage, and the case of combining the submergence depth and the nearly ten times of continuous decrease of the lowest voltage are judged as warnings. And judging the other conditions to be normal.
The working time abnormity analysis method comprises the following steps: and judging the condition that the working time exceeds the set timeout time as abnormal. And judging the condition that the working time exceeds the expected water outlet time and does not exceed the set overtime time as warning. And judging the rest conditions as normal.
The automatic navigation fault analysis method comprises the following steps: and judging that the monitoring system and the aerodone airborne system are in the automatic navigation state at the same time to be normal. And judging that the situation that one of the onboard systems of the glider is in the automatic sailing state by the monitoring system as a warning. This fault has no abnormal state.
The diving depth anomaly analysis method comprises the following steps: and judging that the current diving depth is less than 60% of the set target depth as abnormal. A case where the depth is greater than 60% and lower than 80% of the set target depth is determined as warning. The rest is normal.
The task progress abnormity analysis method comprises the following steps: and judging the condition that the number of the current target waypoint is less than the total waypoint number-1 as normal. And judging the condition that the target waypoint number is the total number of waypoints or the total number is-1 as warning. This fault has no abnormal state.
The flow field abnormity analysis method comprises the following steps: and obtaining the average value of the equipment navigation distances of nearly 10 times, and judging the equipment navigation distances to be abnormal when the average value is less than 60% of the navigation distances in theoretical still water. And judging that the condition that the navigation distance is more than 60% and less than 80% of the theoretical still water is a warning. And judging the condition of more than 80% of the navigation distance in the theoretical still water as normal.
The method for analyzing the spiral abnormity comprises the following steps: and calculating the distance between the GPS and the target waypoint after the task finishes for 5 times, and judging the condition that the current standard deviation is lower than 80% of the theoretical standard deviation to be abnormal. The case higher than 80% and lower than 90% of the theoretical standard deviation is determined as warning. And judging the rest conditions to be normal.
The actuator attenuation analysis method comprises the following steps: and (5) calculating the action speed of the executing mechanism in unit time by combining the action time of 5 tasks of the executing mechanism with the submergence depth and the target displacement. And judging the condition that the speed is obviously reduced (the time consumption is obviously increased for more than 15 seconds) for 3 times of tasks in 5 times of succession as abnormal. The time taken for 3 consecutive increases exceeding 10 seconds and below 15 planes is determined as warning. And judging the rest conditions to be normal.
The fault analysis module is deployed in the monitoring server and is mutually accessed with the monitoring system software through the local area network. The software interface is shown in fig. 3:
the software appearance contains three parts, a failure analysis statistic part positioned at the top layer, a failure analysis detailed information part positioned at the lower left and a software configuration part positioned at the lower right.
The fault analysis and statistics part is used for carrying out statistics on fault analysis carried out each time and comprises statistical information such as analysis times, abnormal times, network and power state monitoring times of monitoring equipment and the like.
The fault analysis detailed information part can display the received and transmitted data content in the actual operation process of the software, and display the status information of fault analysis progress, results and the like, and the information of short message mail alarm and the like.
The software configuration part can configure the serial port used by the used short message sending module, the short message target telephone number, the mail target mailbox and the configuration of whether to alarm when encountering abnormity.
And after the fault analysis module analyzes the fault, the result is transmitted back to the glider data management module and is recorded into the database. When a user accesses a designated webpage through a network, the data management module displays a fault analysis result to the user according to the authority of the user, and sends a data item with an abnormal analysis result to the user through a short message and an email. As shown in fig. 4:
taking row data with the sequence number 2 as an example, the data item with the green background represents an item which is determined to be normal in the fault analysis result, and comprises items such as a GPS, a voltage, a successful submergence, a submergence depth, a strong current, a spiral and a motor working time; the data of the yellow background represents warning items which are determined to be important in the fault analysis result, and the automatic navigation warning represents that the equipment cancels the automatic navigation and needs to be confirmed by monitoring personnel; the data items with red backgrounds represent items with obvious anomalies in the fault analysis results, wherein the working time exceeds the set maximum timeout time, and monitoring personnel are required to intervene in the operation.
The green and yellow background items in fig. 4 are displayed in the web page, and are updated every 20 minutes without triggering a short message or email alarm. On the basis of webpage display, the red background item can simultaneously send the corresponding fault details to a designated telephone and a designated mailbox through a short message and an email, and the fault details are sent once every 20 minutes until the intervention of a worker.
The underwater glider is distributed for 97 times in total in the year, wherein the large-scale networking observation experiment in the south China sea ranges from 11 days in 7 months to 15 days in 10 months in 2019, and 53 times of online monitoring equipment are maximally arranged. The failure analysis module is used for carrying out failure analysis on the equipment in the experiment for more than 29000 times, the system stably runs for more than 300 days, the equipment abnormity is accurately analyzed for 10 times, the warning is carried out for 24 times, the number of the analyzed failures covers more than 95% of the total number of the equipment failures, the error rate is lower than 2% of the total number of the analyzed failures, and the real-time display effect of the observation failure early warning result of the underwater glider team in the experiment process is shown in figure 5. The yellow term indicated in the figure is a warning term, with no red outlier. For example, the data in the third row in the figure shows that the warning for the submergence depth of the equipment with the number of 1000J019 exists and needs to be noticed. Data item content "798/1000" indicates that the set target submergence depth is 1000 meters, whereas the actual submergence depth only reaches 798 meters. Since the diving depth does not affect the whole observation task, the diving depth is defined as a warning level, and short messages and mails do not need to be reminded.
In conclusion, the invention provides a fault diagnosis method for an underwater glider.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (8)
1. A fault diagnosis method of an underwater glider is characterized by comprising the following steps:
time sequence step of data request: loading an underwater glider controlled equipment list, and acquiring equipment data to be detected one by one for fault analysis;
and (3) fault analysis: the fault analysis module analyzes the acquired equipment state data and outputs a fault level;
and fault early warning: and outputting early warning response according to the fault level.
2. The method of claim 1, wherein the step of requesting the data in a time sequence comprises:
applying for a controlled device list, wherein the controlled device list is empty, acquiring core information of all devices, analyzing to obtain the number M of the controlled devices, and sequentially and repeatedly executing: and acquiring control information of the Nth controlled device, acquiring energy information of the Nth device, and acquiring track navigation information of the Nth device until all device information is acquired for fault analysis.
3. The method for diagnosing the fault of the underwater glider according to claim 1, wherein the fault of the underwater glider is classified into three levels of "normal", "warning", and "abnormal":
"normal" represents that the state parameter of the underwater glider accords with the threshold value range under the normal working state, and indicates that no larger sudden change occurs;
the warning represents that the state parameter of the underwater glider exceeds the threshold range in the normal working state and does not exceed the preset percentage of the normal threshold range, and represents that sudden data sudden change which cannot be judged by a system occurs;
"abnormal" represents a preset percentage of the state parameter of the underwater glider exceeding the normal value range, and indicates that the equipment per se has a fault.
4. The method for diagnosing the fault of the underwater glider according to claim 1, wherein the fault early warning of the underwater glider is performed by the following method:
and sending the state value of each equipment data to a front-end display interface for displaying, and coloring fault data of different levels in different colors.
5. The method for diagnosing the fault of the underwater glider according to claim 1, wherein the fault early warning of the underwater glider is further performed by:
and inputting a short message and a mail address, and sending the fault early warning information to a user of the front-end interface through the short message and the mail.
6. The fault diagnosis system of an underwater glider according to any one of claims 1 to 5, comprising: the method comprises a land base station fault analysis module, a cloud data request module and a fault early warning module, wherein each module comprises a processing unit, a storage unit and a communication unit, the storage unit stores a program, and the processing unit loads the program and executes the steps of the fault diagnosis method of the underwater glider as claimed in any one of claims 1 to 5.
7. The fault diagnosis system of an underwater glider according to claim 6, wherein:
the data request module loads an underwater glider controlled equipment list and sends the equipment data to be detected to the fault analysis module one by one;
the fault analysis module analyzes the acquired equipment state data and outputs a fault level;
and the fault early warning module outputs early warning response according to the fault level.
8. The system of claim 7, wherein the data request module obtains the list information of the controlled devices by communicating with the underwater glider through an iridium satellite.
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