A fault alarm method of a charging device

Abstract

The application relates to a fault alarm method of a charging device, which comprises the following steps: acquiring data of the charging pile device in real time; judging whether there is fault data or abnormal heartbeat packet data in the acquired data, and if yes, alarm is performed; if no, whether the device is abnormal is judged according to the state information of the device, and if yes, alarm is performed; if no, whether there is abnormal risk in a period of time is judged according to historical order data in combination with device portrait data, and if yes, alarm is performed; if no, no alarm is performed. Compared with the prior art, the application has the advantages of considering real-time information and long-term state information, comprehensive detection and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent charging piles, in particular to a fault alarm method of a charging device. BACKGROUND

[0002] The existing charging pile alarm mainly relies on the fault uploaded by the device itself to alarm, acquires sensor information through a hardware device sensor, and if a fault occurs, the fault code is sent to the cloud, and the cloud alarms in the background management system. This method first requires the integrity of the hardware device at the sensor level. If the hardware sensor is not complete, the fault of the device that has not been collected cannot be effectively alarmed in time.

[0003] At the same time, for the ground lock and ground conditions in the entire charging process, the mechanical interface of the charging interface, etc. cannot be data collected, such as ground damage, cannot park, surrounding environmental pollution, road blockage, line grounding, ground lock damage, human driving, fuel car occupation, etc. cannot be effectively alarmed in time. And the existing alarm method only alarms the real-time received data, and cannot analyze the use of the charging pile for a period of time, and the practicability is insufficient. SUMMARY

[0004] The purpose of the present application is to overcome the defects of the prior art and provide a fault alarm method of a charging device.

[0005] The purpose of the present application can be achieved by the following technical solutions:

[0006] A fault alarm method of a charging device, comprising the following steps:

[0007] S1, acquiring data of the charging pile device in real time;

[0008] S2, judging whether there is fault data or abnormal heartbeat packet data in the acquired data, if yes, alarming; if no, executing step S3;

[0009] S3, judging whether the device has an abnormality according to the state information of the device, if yes, alarming; if no, judging whether there is an abnormal risk in a period of time according to the historical order data and combining the device portrait data, if yes, alarming; if no, not alarming.

[0010] Further, in the step S3 of judging whether there is an abnormal risk in a period of time, the abnormal risk includes a device usage rate abnormal risk and a short order quantity abnormal risk.

[0011] Further, the judgment steps of the usage rate abnormal risk are as follows:

[0012] S301, initializing the charging duration of the charging device every first time period;

[0013] S302, dividing the charging duration of the first time period by the total duration of a week to obtain the device usage rate in each first time period;

[0014] S303, calculating the value of the device usage rate in the current first time period divided by the device usage rate in the previous first time period, and if the value is greater than a first threshold value, an alarm is given.

[0015] Further, the first threshold value ranges from 140% to 160%.

[0016] Further, the judgment of short order quantity abnormal risk is as follows:

[0017] S311, obtaining the time of each order of the device, and calculating the average order time of the device, and if the value of the order time divided by the average order time is less than a second threshold value, the order is set as a short order;

[0018] S312, judging whether the number of short orders in the current first time period of the device exceeds the value of the total order quantity of the site to which the device belongs multiplied by a third threshold value, and if yes, step S313 is executed; if no, it is determined that there is no abnormal risk;

[0019] S313, obtaining the ratio of the number of short orders of the device to the total order quantity of the site as a first ratio, obtaining the ratio of the number of short orders of the device to the total order quantity of the site before a second time period as a second ratio, calculating the value of the first ratio divided by the second ratio, and if the value is greater than a fourth threshold value, an alarm is given.

[0020] Further, the first time period is one week.

[0021] Further, the second time period is one year.

[0022] Further, the second threshold value ranges from 0.5 to 0.7, the third threshold value ranges from 0.7 to 0.9, and the fourth threshold value ranges from 140% to 160%.

[0023] Further, the standard for judging the abnormality of the heartbeat message data is the last heartbeat message data of the recording device, and if the last heartbeat message data exceeds 2-10 minutes, it is determined that the heartbeat message data is abnormal.

[0024] Further, in step S3, according to the state information of the device, it is judged whether the device has an abnormality, wherein the state information includes the number of offline times, the number of disconnections and the number of recharging times.

[0025] Compared with the prior art, the present application has the following advantages:

[0026] 1. Compared to existing charging pile alarm methods on the market, this invention, in addition to detecting and alarming the real-time status of the equipment, also evaluates the equipment's status over a period of time by acquiring historical information and profiles. It vertically judges equipment faults over time, taking into account both real-time and long-term conditions, making the charging equipment alarm more practically valuable for comprehensive planning. Furthermore, in terms of specific equipment judgment, it analyzes fault information and heartbeat message data one by one, and also performs logical judgments on status information such as offline counts, making detection more comprehensive and alarm determination more scientific.

[0027] 2. When determining the long-term status, this invention judges the usage rate and short order volume, initializes relevant information weekly, and combines data from previous years and weeks for judgment, making the anomaly judgment periodic and easier for personnel to maintain. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the process of the present invention.

[0029] Figure 2 This is a flowchart of the usage rate anomaly detection method of the present invention.

[0030] Figure 3 This is a flowchart illustrating the abnormal judgment of the number of short orders in this invention. Detailed Implementation

[0031] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0032] This embodiment provides a fault alarm method for charging equipment, such as Figure 1 As shown, the specific steps include:

[0033] Step S1: Acquire data from the charging pile equipment in real time.

[0034] Step S2: Determine whether there is faulty data or abnormal heartbeat message data in the acquired data. If so, issue an alarm; otherwise, proceed to step S3.

[0035] Step S3: Based on the device status information, determine whether the device is abnormal. If so, issue an alarm; otherwise, based on historical order data and device profile data, determine whether there is any abnormal risk within a certain period of time. If so, issue an alarm; otherwise, do not issue an alarm.

[0036] Among them, the abnormal risks involved in step S3 include abnormal equipment utilization risk and abnormal short order volume risk.

[0037] The steps for judging the risk of abnormal usage are as follows: Figure 2 As shown, the specific steps include:

[0038] Step S301: Initialize the charging duration of the charging device every first time period;

[0039] Step S302: Divide the charging time of the first time period by the total duration of a week to obtain the device utilization rate within each first time period;

[0040] Step S303: Calculate the current device utilization rate in the first time period divided by the device utilization rate in the previous first time period. If the value is greater than a first threshold, an alarm is triggered. In this embodiment, the first threshold is preferably 150%.

[0041] The steps for judging the risk of abnormal short order volume are as follows: Figure 3 As shown, the specific steps include:

[0042] Step S311: Obtain the time of each order from the device and calculate the average time of historical orders from the device. If the value of the order time divided by the average order time is lower than the second threshold, then the order is set as a short order.

[0043] Step S312: Determine whether the number of short orders for the device in the current first time period exceeds the total number of orders of the site to which the device belongs multiplied by the third threshold. If yes, proceed to step S313; otherwise, determine that there is no abnormal risk.

[0044] Step S313: Obtain the ratio of the number of short orders of the device to the total number of orders of the site as the first ratio, obtain the ratio of the number of short orders of the device to the total number of orders of the site before the second time period as the second ratio, calculate the value of the first ratio divided by the second ratio, and if it is greater than the fourth threshold, then issue an alarm.

[0045] In this embodiment, the first time period is one week, the second time period is one year, the second threshold is preferably 0.618, the third threshold is preferably 0.8, and the fourth threshold is preferably 150%.

[0046] In this embodiment, the device status information includes the number of times it went offline, the number of times it lost connection, and the number of times it was recharged.

[0047] The complete fault alarm method in this embodiment can be expanded as follows:

[0048] Step 1: Real-time access to data from the charging gun device.

[0049] Step 2: Determine the data type of the connected charging gun device.

[0050] Step 3: If the data is from a charging device malfunction, proceed to Step 4. If the data is from a heartbeat, proceed to Step 5. If the data is from other sources, proceed to Step 7.

[0051] Step 4: Analyze the fault type data, issue an alarm to the device, and the overall process ends.

[0052] Step 5: Maintain the devices with heartbeats, record the last heartbeat message data of the devices, and start a thread to periodically check the last heartbeat message data of the devices under maintenance. If the heartbeat message data times out (in this embodiment, heartbeat message data timeout means more than 10 seconds), proceed to step 6.

[0053] Step 6: Issue an alarm to the device and delete the information about the charging device maintained in memory. The entire process ends here.

[0054] Step 7: Group the devices by charging gun. If the data obtained in Step 3 is the charging gun device status information, proceed to Step 8. If the data is the charging gun order information data, proceed to Step 14.

[0055] Step 8: Determine the status of the charging gun device. If it is offline, open a short window and proceed to step 9; if it is plugged in but not charging, open a short window and proceed to step 11; the duration of the short window is 10 seconds.

[0056] Step 9: Determine whether the charging gun device is still offline in the next short window. If it is offline, increment the offline count by 1 and proceed to step 10. If it is not offline, end the short window, set the offline count to 0, and proceed to step 8.

[0057] Step 10: Determine whether the number of offline attempts exceeds the set threshold. In this embodiment, it is preferably 3 times. If it exceeds the threshold, it indicates that the device is in an abnormal state. The device will issue an alarm and set the number of offline attempts to 0, end the short window, and the overall process will end.

[0058] Step 11: Determine whether the next short window is in an idle or charging state. If it is in an idle state, increment the disconnection count by 1 and proceed to Step 12. If it is in a charging state, increment the recharging count by 1 and proceed to Step 13.

[0059] Step 12: Determine whether the number of disconnections exceeds the set threshold. In this embodiment, it is preferably 3 times. If it exceeds the threshold, it means that the device is in an abnormal state. The device will issue an alarm and set the number of disconnections to 0, end the short window, and the whole process ends.

[0060] Step 13: Determine whether the number of recharges exceeds the set threshold. In this embodiment, it is preferably 5 times. If it exceeds the threshold, it indicates that the device is in an abnormal state. The device will issue an alarm and set the number of recharges to 0, end the short window, and the overall process will end.

[0061] Step 14: Divide the order information data into two identical data streams and push them downstream. One data stream executes Step 15 to determine abnormal usage rate; the other data stream executes Step 17 to determine abnormal short order count.

[0062] Step 15: Initialize the device's charging time every Wednesday, and store the total charging time for the whole week each week. Then proceed to Step 16.

[0063] Step 16: Divide the total weekly charging time by the total weekly time to obtain the device utilization rate. At the same time, correlate the device profile data to determine the ratio of this week's utilization rate to last week's utilization rate. If it is greater than 150%, it indicates an abnormal risk, and the device will issue an alarm.

[0064] Step 17: Calculate the time from the start of each order to the end of the order.

[0065] Step 18: Obtain the average effective duration of historical charging orders for the charging device, and determine whether the duration of this order is less than 61.8% of the historical average duration of the charging device. If so, set the order as a short order; otherwise, skip the short order exception judgment for this order.

[0066] Step 19: Initialize the weekly short order volume data every Wednesday and store the short order count for the device every week.

[0067] Step 20: Aggregate the charging guns by charging station and determine whether the current number of short orders for the device exceeds 80% of the total number of orders for the station this week. If yes, proceed to step 21; otherwise, skip the short order anomaly check for this order.

[0068] Step 21: Obtain the percentage of short orders for the same period of the previous year for this device, and determine whether the percentage of short orders this week divided by the percentage of the same period last year is greater than 150%. If so, it indicates that there is an abnormal risk in the device, the device will issue an alarm, and the process will end.

[0069] This embodiment also proposes a fault alarm device for charging equipment, including a memory and a processor; the memory is used to store a computer program; the processor is used to implement the above-mentioned fault alarm method for charging equipment when the computer program is executed.

[0070] This embodiment further proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the fault alarm method for the charging device mentioned in this embodiment. This program can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be—but is not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0071] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A fault alarm method for a charging device, characterized in that, Includes the following steps: S1. Real-time acquisition of data from charging pile equipment; S2. Determine whether there is faulty data or abnormal heartbeat message data in the acquired data. If so, issue an alarm; otherwise, proceed to step S3. S3. Based on the equipment status information, determine whether the equipment is abnormal. If so, issue an alarm. If not, based on historical order data and equipment profile data, determine whether there is any abnormal risk within a certain period of time. If so, issue an alarm. If not, do not issue an alarm. In step S3, determining whether there is any abnormal risk within a certain period of time includes abnormal risks of equipment utilization rate and abnormal risks of short order volume. The steps for determining the risk of abnormal short order volumes are as follows: S311. Obtain the time of each order from the device and calculate the average time of historical orders from the device. If the order time divided by the average order time is lower than the second threshold, then set the order as a short order. S312. Determine whether the number of short orders for the device in the current first time period exceeds the total number of orders of the site to which the device belongs multiplied by the third threshold. If yes, proceed to step S313; otherwise, determine that there is no abnormal risk. S313. Obtain the ratio of the number of short orders of the device to the total number of orders of the site as the first ratio, obtain the ratio of the number of short orders of the device to the total number of orders of the site before the second time period as the second ratio, calculate the value of the first ratio divided by the second ratio, and if it is greater than the fourth threshold, then issue an alarm. The first time period is one week, the second time period is one year, the second threshold range is 0.5 to 0.7, the third threshold range is 0.7 to 0.9, and the fourth threshold range is 140% to 160%.

2. The fault alarm method for a charging device according to claim 1, characterized in that, The steps for determining the risk of abnormal usage rates are as follows: S301. Initialize the charging duration of the charging device every first time period; S302. Divide the charging time of the first time period by the total duration of a week to obtain the device utilization rate within each first time period; S303. Calculate the current equipment utilization rate in the first time period divided by the equipment utilization rate in the previous first time period. If it is greater than the first threshold, then issue an alarm.

3. The fault alarm method for a charging device according to claim 2, characterized in that, The first threshold ranges from 140% to 160%.

4. The fault alarm method for a charging device according to claim 1, characterized in that, The standard for judging abnormal heartbeat message data is the last heartbeat message data recorded by the recording device. If the last heartbeat message data is more than 2 to 10 minutes old, it is judged as abnormal heartbeat message data.

5. The fault alarm method for a charging device according to claim 1, characterized in that, In step S3, the device status information is used to determine whether there is any abnormality in the device. The status information includes the number of times the device went offline, the number of times it disconnected, and the number of times it was recharged.

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