Cable well fault early warning method, device, equipment, medium and product

Abstract

The embodiment of the invention provides a cable well fault early warning method, device and equipment, a medium and a product, and is applied to the technical field of smart power grids. The method is applied to a cable well fault early warning system, the system comprises a plurality of sensors, a lower computer and an upper computer, and the method comprises the following steps: collecting monitoring data of the plurality of sensors in a cable well and environment data corresponding to the cable well based on the lower computer; when the monitoring data and the environment data meet a preset adjustment condition, updating an initial early warning value of each sensor based on the monitoring data and the environment data to obtain an updated target early warning value; performing abnormality verification on each sensor based on the monitoring data and the target early warning value to obtain an abnormality verification result; and sending the exception verification result to an upper computer, and sending early warning information based on the upper computer when the exception verification result indicates that an exception exists. The method achieves the technical effect of improving the fault early warning precision of the cable well.

Description

Technical Field

[0001] This application relates to the field of smart grid technology, and in particular to a method, device, equipment, medium and product for early warning of cable well faults. Background Technology

[0002] As urbanization progresses, and with the requirements for beautifying main traffic arteries and ensuring the safe operation of power lines, overhead power lines are gradually being replaced by underground cable lines, resulting in a continuous increase in the number of cable wells and consequently, greater difficulty in their operation and maintenance.

[0003] In the existing technology, the main methods for detecting faults in cable wells are: using camera devices or sensor devices to obtain the underground status information of the cable well, and using a pre-set judgment threshold in combination with the underground status information to determine whether there is a fault in the cable well, and then carrying out corresponding fault warnings and handling.

[0004] Because existing technologies rely on fixed thresholds for early warning, they suffer from low accuracy in early warning of cable well faults. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, medium, and product for early warning of cable well faults, in order to improve the technical accuracy of early warning of cable well faults.

[0006] In a first aspect, embodiments of this application provide a cable well fault early warning method, applied to a cable well fault early warning system. The system includes multiple sensors, a lower-level computer, and a higher-level computer. The method includes:

[0007] The monitoring data from multiple sensors in the cable well, as well as the corresponding environmental data of the cable well, are collected by the lower-level computer.

[0008] When the monitoring data and environmental data meet the preset adjustment conditions, the initial warning value of each sensor is updated based on the monitoring data and environmental data to obtain the updated target warning value;

[0009] Anomaly verification is performed on each sensor based on monitoring data and target warning values ​​to obtain anomaly verification results;

[0010] The anomaly verification result is sent to the host computer. When the anomaly verification result indicates that an anomaly exists, the host computer issues an early warning message.

[0011] The environmental data includes ambient temperature and ambient humidity.

[0012] In one possible implementation, the preset adjustment conditions include at least one of the following:

[0013] The ambient temperature exceeds the preset temperature range;

[0014] The ambient humidity exceeds the preset humidity range;

[0015] There are at least two sensors whose monitoring data are greater than the initial warning value corresponding to the sensor;

[0016] There are instances where the monitoring data from any sensor exceeds the initial warning value more than the preset number of times.

[0017] In one possible implementation, the initial warning value of each sensor is updated based on monitoring data and environmental data to obtain the updated target warning value, including:

[0018] Based on the type of each sensor, determine the preset warning value adjustment strategy for each sensor;

[0019] Based on monitoring data, environmental data, and the preset warning value adjustment strategy for each sensor, the target warning value after each sensor is updated is calculated.

[0020] In one possible implementation, anomaly verification is performed on each sensor based on monitoring data and target warning values ​​to obtain anomaly verification results, including:

[0021] For each sensor, when the sensor's monitoring data exceeds the sensor's target warning value, it is determined that the sensor's monitoring data is abnormal, and the type of abnormality is determined according to the type of sensor.

[0022] Anomaly verification results are generated based on the anomaly type corresponding to the abnormal monitoring data.

[0023] In one possible implementation, the anomaly verification result is sent to a host computer. When the anomaly verification result indicates the presence of an anomaly, a warning message is issued by the host computer, including:

[0024] The warning level corresponding to each anomaly type in the anomaly verification result is determined based on a preset anomaly mapping list.

[0025] The warning method for each type of anomaly is determined based on the warning level;

[0026] Warning messages are issued according to the warning method corresponding to each type of anomaly.

[0027] In one possible implementation, the method further includes:

[0028] Acquire historical monitoring data for each sensor;

[0029] Calculate the mean or rate of change of the historical monitoring data for each sensor;

[0030] The initial warning value of each sensor is updated based on the mean or rate of change to obtain the updated target warning value.

[0031] In one possible implementation, the system further includes a communication module, and the method further includes:

[0032] Based on the communication quality of the main communication unit in the lower-level machine monitoring communication module;

[0033] When the communication quality of the main communication unit is lower than a preset threshold, the current communication unit of the communication module will be switched to the backup communication unit.

[0034] The main communication unit and backup communication unit of the communication module are used to transmit the monitoring data of each sensor to the lower-level machine and to send the abnormal verification results generated by the lower-level machine to the upper-level machine.

[0035] Secondly, embodiments of this application provide a cable well fault early warning device, comprising:

[0036] The acquisition module is used to collect monitoring data from multiple sensors in the cable well, as well as the corresponding environmental data of the cable well, based on the lower-level computer.

[0037] The first processing module is used to update the initial warning value of each sensor based on the monitoring data and environmental data when the monitoring data and environmental data meet the preset adjustment conditions, so as to obtain the updated target warning value.

[0038] The second processing module is used to perform anomaly verification on each sensor based on monitoring data and target warning values, and obtain anomaly verification results.

[0039] The third processing module is used to send the anomaly verification result to the host computer. When the anomaly verification result indicates that there is an anomaly, the host computer issues an early warning message.

[0040] The environmental data includes ambient temperature and ambient humidity.

[0041] In one possible implementation, the preset adjustment conditions include at least one of the following:

[0042] The ambient temperature exceeds the preset temperature range;

[0043] The ambient humidity exceeds the preset humidity range;

[0044] There are at least two sensors whose monitoring data are greater than the initial warning value corresponding to the sensor;

[0045] There are instances where the monitoring data from any sensor exceeds the initial warning value more than the preset number of times.

[0046] In one possible implementation, the first processing module is further configured to:

[0047] Based on the type of each sensor, determine the preset warning value adjustment strategy for each sensor;

[0048] Based on monitoring data, environmental data, and the preset warning value adjustment strategy for each sensor, the target warning value after each sensor is updated is calculated.

[0049] In one possible implementation, the second processing module is further configured to:

[0050] For each sensor, when the sensor's monitoring data exceeds the sensor's target warning value, it is determined that the sensor's monitoring data is abnormal, and the type of abnormality is determined according to the type of sensor.

[0051] Anomaly verification results are generated based on the anomaly type corresponding to the abnormal monitoring data.

[0052] In one possible implementation, the third processing module is further configured to:

[0053] The warning level corresponding to each anomaly type in the anomaly verification result is determined based on a preset anomaly mapping list.

[0054] The warning method for each type of anomaly is determined based on the warning level;

[0055] Warning messages are issued according to the warning method corresponding to each type of anomaly.

[0056] In one possible implementation, the first processing module is further configured to:

[0057] Acquire historical monitoring data for each sensor;

[0058] Calculate the mean or rate of change of the historical monitoring data for each sensor;

[0059] The initial warning value of each sensor is updated based on the mean or rate of change to obtain the updated target warning value.

[0060] In one possible implementation, the system number further includes a communication module, and the device further includes a fourth processing module for:

[0061] Based on the communication quality of the main communication unit in the lower-level machine monitoring communication module;

[0062] When the communication quality of the main communication unit is lower than a preset threshold, the current communication unit of the communication module will be switched to the backup communication unit.

[0063] The main communication unit and backup communication unit of the communication module are used to transmit the monitoring data of each sensor to the lower-level machine and to send the abnormal verification results generated by the lower-level machine to the upper-level machine.

[0064] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0065] The memory stores instructions that the computer executes;

[0066] The processor executes computer execution instructions stored in memory, causing the processor to perform the possible implementations described in the second aspect above.

[0067] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the possible implementations described in the second aspect above.

[0068] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the possible implementations described in the second aspect above.

[0069] This application provides a method, apparatus, equipment, medium, and product for early warning of cable well faults. The method is applied to a cable well fault early warning system, which includes multiple sensors, a lower-level computer, and a higher-level computer. The method acquires monitoring data from multiple sensors and environmental data of the cable well through the lower-level computer; compares the environmental data, monitoring data, and preset adjustment conditions; when the preset adjustment conditions are met, a threshold update is triggered, updating the initial early warning value of each sensor based on the monitoring data and environmental data, obtaining the updated target early warning value for each sensor; performs anomaly verification on the monitoring data and environmental data using the lower-level computer and the updated target early warning value, obtaining anomaly verification results; and provides early warning of cable well faults using the higher-level computer and the anomaly verification results. Compared with existing technologies, this application dynamically updates the early warning value of each sensor using collected monitoring data and environmental data, reducing the probability of false early warnings due to environmental factors, thereby improving the accuracy of early warnings. Attached Figure Description

[0070] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0071] Figure 1 Schematic diagram of the cable well fault early warning system provided in this application Figure 1 ;

[0072] Figure 2 Flowchart of the cable well fault early warning method provided in this application Figure 1 ;

[0073] Figure 3Flowchart of the cable well fault early warning method provided in this application Figure 2 ;

[0074] Figure 4 Schematic diagram of the cable well fault early warning system provided in this application Figure 2 ;

[0075] Figure 5 Flowchart of the cable well fault early warning method provided in this application Figure 3 ;

[0076] Figure 6 This is a schematic diagram of the structure of the cable well fault early warning device provided in this application;

[0077] Figure 7 A schematic diagram of the structure of the electronic device provided in this application.

[0078] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0079] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0080] In existing technologies, the main methods for detecting faults in cable wells are as follows: using various types of sensor devices to acquire the underground status information of the cable well; analyzing the underground status information to obtain various types of real-time monitoring values; determining whether each type of monitoring value meets the warning conditions of the warning threshold based on the warning threshold corresponding to each type of monitoring value; and when the warning conditions are met, sending warning information to the terminal of the operation and maintenance management personnel, thereby prompting the operation and maintenance management personnel to conduct fault investigation and handling of the cable well.

[0081] However, existing early warning methods use fixed early warning thresholds. When the external environment of the cable well changes, the average change in the monitored values ​​increases, leading to frequent early warnings or missed early warnings. Therefore, existing technologies suffer from low accuracy in early warning of cable well faults.

[0082] To address the aforementioned technical problems, this application proposes the following technical concept: Compared to the existing method of using fixed warning thresholds for cable well fault early warning, this application dynamically updates the warning threshold by combining environmental data and monitoring data from the cable well. Specifically: a lower-level computer collects monitoring data from multiple sensors in the cable well in real time, as well as corresponding environmental data; the lower-level computer determines whether the monitoring data and environmental data meet preset adjustment conditions, i.e., whether the sensor warning values ​​need to be updated; when the preset adjustment conditions are met, the warning value is updated using the monitoring data and environmental data, and anomaly verification is performed on the monitoring data based on the updated warning value; when the anomaly verification indicates an anomaly, the upper-level computer issues a warning message, thereby improving the accuracy of cable well fault early warning by dynamically updating the warning value.

[0083] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0084] Figure 1 Schematic diagram of the cable well fault early warning system provided in this application Figure 1 ,like Figure 1 As shown, the system includes: multiple sensors 101, a host computer 102, a slave computer 103, and a communication module 104.

[0085] The system includes multiple sensors 101 for real-time monitoring and generating monitoring data in the cable well; a lower-level computer 102 for acquiring the real-time monitoring data from the multiple sensors and the corresponding environmental data of the cable well; the lower-level computer 102 is also used to dynamically update the warning value corresponding to each sensor 101 based on the monitoring data and environmental data, and to perform anomaly verification on the monitoring data based on the warning value, generating anomaly verification results; the main communication unit or backup communication unit of the communication module 104 is used to transmit the monitoring data of the sensors to the lower-level computer, and to transmit the anomaly verification results of the lower-level computer 102 to the upper-level computer 103 when the anomaly verification results indicate an anomaly; the upper-level computer 103 is used to issue warning information based on the anomaly verification results.

[0086] Figure 2 Flowchart of the cable well fault early warning method provided in this application Figure 1 ,like Figure 2 As shown, this method is applied to, for example Figure 1 The cable well fault early warning system shown includes the following method:

[0087] S201. Based on the lower-level computer, collect monitoring data from multiple sensors in the cable well, as well as the corresponding environmental data of the cable well.

[0088] In this step, environmental data includes ambient temperature and humidity. Multiple sensors are used, including pressure sensors, level sensors, six-axis sensors, and gas sensors; correspondingly, the types of monitored data include: manhole cover stress, manhole cover displacement, liquid level height, and various gas concentrations.

[0089] Alternatively, one possible implementation method for collecting monitoring data from multiple sensors in a cable well based on a lower-level computer is as follows:

[0090] S2011. Acquire analog signals from multiple sensors based on the lower-level machine.

[0091] In this step, the data acquisition frequency varies depending on the type of sensor. A high acquisition frequency is used when the sensor is dealing with rapidly changing data, and a low acquisition frequency is used when the sensor is dealing with slowly changing data.

[0092] For example, when collecting monitoring data from a liquid level sensor, the acquisition frequency can be set to 1 Hz; when collecting monitoring data from a six-axis sensor, the acquisition frequency can be set to 10 Hz.

[0093] It should be noted that the sampling frequency setting in this embodiment is only an illustrative example and does not limit the actual sampling frequency.

[0094] S2012. Based on the lower-level computer, the analog signal is converted into the corresponding digital signal to obtain the monitoring data corresponding to each sensor.

[0095] In this step, the monitoring data can be obtained in the following ways: the sensor outputs an analog signal, such as current and voltage; the analog signal is amplified and filtered; the processed analog signal is converted into a digital signal; the digital signal is converted into actual physical quantities, such as pressure, displacement and gas concentration; the processed actual physical quantities are calibrated; and the calibrated data is determined as the monitoring data.

[0096] For example, a pressure sensor outputs a voltage signal of 0-5 volts (V), corresponding to a pressure range of 0-30 kN; a level sensor outputs a current signal of 4-20 milliamperes (mA), corresponding to a liquid level of 0-2 meters (m); and a gas sensor outputs a voltage signal of 0-3.3V, corresponding to a gas concentration of 0-5%. The lower-level computer uses amplifier and filter circuits to condition the analog signals; amplifies weak signals; and removes high-frequency noise from the analog signals. The conditioned analog signals are converted to digital signals via analog-to-digital conversion, and the data signals are calibrated to obtain the monitoring data corresponding to each sensor.

[0097] S202. When the monitoring data and environmental data meet the preset adjustment conditions, update the initial warning value of each sensor based on the monitoring data and environmental data to obtain the updated target warning value.

[0098] In this step, the preset adjustment conditions are used to indicate sudden changes in environmental parameters, continuous anomalies in monitoring data, and coordinated anomalies in multiple sensors.

[0099] Optionally, the preset adjustment conditions include at least one of the following:

[0100] The ambient temperature exceeds the preset temperature range.

[0101] The ambient humidity exceeds the preset humidity range.

[0102] There are at least two sensors whose monitoring data are greater than the initial warning value corresponding to the sensor.

[0103] There are instances where the monitoring data from any sensor exceeds the initial warning value more than the preset number of times.

[0104] For example, the preset temperature range is set to 0 degrees Celsius (°C) to 40°C; the preset humidity range is set to 20% to 80%; the initial warning value of the pressure sensor is set to 10kN; the initial warning value of the liquid level sensor is set to 0.8m; the initial warning value of the methane sensor is set to 0.5%, and the preset number of times the initial warning value can be exceeded is set to three times per hour.

[0105] Scenario triggering preset adjustment conditions can be as follows: A cable well experiences overheating due to underground cable overload, causing the ambient temperature to rise to 45°C, exceeding the upper limit of the preset temperature range; this confirms that the preset adjustment conditions are met. Heavy rain causes water seepage into the cable well, causing humidity to surge to 85%, exceeding the upper limit of the preset humidity range; this confirms that the preset adjustment conditions are met. A cable well cover deforms due to an external impact, with the pressure sensor detecting 15kN, and the water level inside the well rising to 1.2m; the lower-level computer determines that both the pressure and level sensors are exceeding their limits, confirming that the current monitoring data meets the preset adjustment conditions. The lower-level computer records the time when the gas concentration in the cable well exceeds the initial warning value. Based on the records, it determines whether the methane gas concentration has exceeded the initial warning value more than 3 times in the past hour; if it has, the monitoring data triggers the preset adjustment conditions.

[0106] Optionally, one possible way to update the initial warning value of each sensor based on monitoring data and environmental data to obtain the updated target warning value is to calculate the updated target warning value based on the change range of the monitoring data and the change range of the environmental data.

[0107] It should be noted that the calculation of the target warning value in this step is as follows: Figure 3 Further explanation will be provided in the embodiments shown, and will not be repeated here.

[0108] S203. Based on the monitoring data and target warning values, perform anomaly verification on each sensor to obtain the anomaly verification results.

[0109] In this step, the anomaly verification method involves comparing the monitoring data with the target warning value to determine if the monitoring data exceeds the target warning value; or calculating the average value of the monitoring data over the preset time period based on the monitoring data and historical monitoring data recorded within that time period, and determining if the average value of the monitoring data exceeds the target warning value. If it is determined that the monitoring data exceeds the target warning value or the average value of the monitoring data exceeds the target warning value, an anomaly is identified in the current monitoring data. Based on the sensor type corresponding to the anomaly, the anomaly type is determined, and the anomaly verification result is obtained.

[0110] The anomaly verification results include at least one anomaly, and each anomaly can be a single anomaly or a compound anomaly. A single anomaly refers to an anomaly that is related to monitoring data from only one sensor, while a compound anomaly refers to an anomaly that is related to monitoring data from at least two sensors.

[0111] For example: if the manhole cover displacement corresponding to the six-axis sensor and the water immersion height corresponding to the liquid level sensor both exceed the target warning value, the anomaly type is determined as a composite anomaly "structural seepage anomaly"; if the methane concentration and liquid level both exceed the target warning value, the anomaly type is determined as a composite anomaly "gas leakage accompanied by water accumulation"; if the manhole cover pressure corresponding to the pressure sensor exceeds the target warning value, the anomaly type is determined as a single anomaly "cable well cover pressure exceeding limit".

[0112] S204. Send the anomaly verification result to the host computer. When the anomaly verification result indicates that an anomaly exists, issue an early warning message based on the host computer.

[0113] In this step, the early warning information includes: the anomaly verification result, the monitoring data corresponding to the anomaly verification result, the location and marking of the cable well cover, and the time when the anomaly occurred.

[0114] Optionally, communication between multiple sensors, the host computer, and the slave computer can be achieved by the slave computer detecting the current communication quality of the communication module and switching the current communication unit of the communication module according to the communication quality. One possible implementation of switching the communication unit is as follows:

[0115] S2041. Based on the lower-level machine monitoring communication module, monitor the communication quality of the main communication unit.

[0116] In this step, the communication quality can be represented by: communication delay, bit error rate, and signal strength.

[0117] For example, when the main communication unit is an RS-485 bus, communication quality can be represented by the bit error rate. RS-485 is a serial communication standard used for long-distance, interference-resistant data transmission in industrial environments. When the main communication unit is a Bluetooth network, communication quality can be represented by communication latency.

[0118] S2042. When the communication quality of the main communication unit is lower than a preset threshold, the current communication unit of the communication module is switched to the backup communication unit.

[0119] In this step, the main communication unit and the backup communication unit of the communication module are used to transmit the monitoring data of each sensor to the lower-level computer, and to send the anomaly verification results generated by the lower-level computer to the upper-level computer. The upper-level computer can be a microcontroller deployed inside the cable well or a server deployed around the cable well; the lower-level computer can be a server deployed around the cable well or a mobile terminal.

[0120] For example, when the current main communication unit is an RS-485 bus, but due to severe electromagnetic interference downhole, the bit error rate rises to 5%, exceeding the preset threshold of 2%, then it is determined that the current communication quality is low, and the current communication unit of the communication module is switched to the backup communication unit.

[0121] It should be noted that when the communication module in this embodiment transmits data between the sensor, the host computer, and the slave computer, it needs to consider the data integrity, timeliness, and effectiveness during the transmission process; the range of the applied voltage of the cable well fault early warning system is calculated based on the data transmission loss rate of the cable well fault early warning system under different voltages, so as to determine the voltage range suitable for data transmission.

[0122] For example, the voltage range applied to the cable well fault early warning system is set to 0.40V~0.60V. This voltage range is further subdivided into seven sub-levels, along with the data transmission loss rate of the cable well fault early warning system at each voltage level. The voltage values ​​are (0.30V, 0.35V, 0.40V, 0.45V, 0.50V, 0.55V, 0.60V), and the corresponding loss rates are (100%, 100%, 85%, 37%, 0%, 0%, 0%). Therefore, the suitable monitoring voltage range can be determined to be 0.40V~0.55V. The 0.40V~0.55V voltage range can be further subdivided for detection, ultimately resulting in a voltage range above 0.48V. That is, the suitable monitoring voltage range for the cable well fault early warning system is greater than or equal to 0.48V.

[0123] The cable well fault early warning method provided in this application acquires monitoring data from multiple sensors and environmental data of the cable well via a lower-level computer. It compares the environmental data, monitoring data, and preset adjustment conditions. When the preset adjustment conditions are met, a threshold update is triggered, updating the initial early warning value of each sensor based on the monitoring data and environmental data to obtain the updated target early warning value for each sensor. The lower-level computer and the updated target early warning value are used to perform anomaly verification on the monitoring data and environmental data, obtaining anomaly verification results. Finally, an early warning of cable well faults is issued via a higher-level computer and the anomaly verification results. Compared with existing technologies, this application dynamically updates the early warning value of each sensor using collected monitoring data and environmental data, reducing the probability of false early warnings due to environmental factors, thereby improving the accuracy of early warnings.

[0124] Figure 3 Flowchart of the cable well fault early warning method provided in this application Figure 2 Based on the above embodiments, the implementation of fault warning in steps S202 to S204 of this embodiment will be explained in further detail, such as... Figure 3 As shown, the method includes:

[0125] S301. Based on the type of each sensor, determine the preset warning value adjustment strategy for each sensor.

[0126] In this step, because the influencing conditions corresponding to the monitoring data of each sensor are different, the preset warning value adjustment strategies for each sensor are different.

[0127] For example, the concentrations of various gases in a cable well are related to the ambient temperature and humidity of the cable well, so the effects of temperature and humidity need to be considered when adjusting the warning values ​​of the gas sensors; the liquid level in a cable well is related to rainfall, so the real-time rainfall in the area where the cable well is located needs to be considered when adjusting the warning values ​​of the liquid level sensors; the displacement of the cable well cover is related to the liquid level inside the cable well, so the current liquid level in the cable well needs to be considered when adjusting the warning values ​​of the six-axis sensors.

[0128] S302. Based on monitoring data, environmental data, and the preset warning value adjustment strategy for each sensor, calculate the target warning value after each sensor is updated.

[0129] In this step, the preset warning value adjustment strategy for the pressure sensor is as follows: based on the initial warning value of pressure, the material expansion coefficient of the cable well cover, the current ambient temperature, and the reference temperature corresponding to the initial warning value, the updated target warning value is calculated. The preset warning value adjustment strategy for the six-axis sensor is as follows: when there is an anomaly in the liquid level of the cable well, the target warning value corresponding to the displacement is tightened to a predefined value. The preset warning value adjustment strategy for the liquid level sensor is as follows: based on the current rainfall, the target warning value corresponding to the liquid level is raised in stages. The preset warning value adjustment strategy for the gas sensor is as follows: when there is a sudden change in temperature and humidity, the target warning value is calculated based on the magnitude of the temperature and humidity change, the initial warning value, and the temperature and humidity change coefficient.

[0130] For example, when updating the warning value for a pressure sensor: the initial warning value is 15kN, the reference temperature corresponding to the initial warning value is 25°C, the ambient temperature is 35°C, the material expansion coefficient is 0.05, and the threshold is increased by 0.5% for every 1°C increase in temperature; the calculated target warning value is 15.75kN.

[0131] When updating the warning value for the liquid level sensor: the initial warning value corresponding to the liquid level sensor is 1.0m; the rainfall obtained from the real-time meteorological data is 30mm / h, the rainfall level corresponding to the rainfall is 2, the correlation coefficient between the liquid level height and the rainfall level is set to 0.2, and the calculated target warning value is 1.4m.

[0132] When updating the warning value for a six-axis sensor, the displacement threshold is tightened to ±0.02m when the liquid level exceeds the initial warning value of the liquid level sensor.

[0133] When updating the warning values ​​for gas sensors, the initial warning value for the methane sensor is 0.5%, and the initial warning value for the carbon monoxide sensor is 0.0024%. When both the methane and carbon monoxide concentrations exceed their respective initial warning values, it is determined that there is an anomaly in multiple gases. The warning values ​​for all gases can be reduced by 20%. The final calculated target warning value for the methane sensor is 0.4%, and the target warning value for the carbon monoxide sensor is 0.00192%.

[0134] Optionally, the calculation method for the target warning value also includes:

[0135] S3021. Obtain historical monitoring data corresponding to each sensor.

[0136] In this step, the historical monitoring data of each sensor can be stored in the cache of the lower-level machine or in a preset database.

[0137] For example, one possible way to implement historical monitoring data of the lake area is to read the historical monitoring data corresponding to each sensor in the past 24 hours from the cache of the lower-level machine; or, according to the address of the preset database stored in the cache of the lower-level machine, read the historical monitoring data corresponding to each sensor in the past 24 hours from the preset database.

[0138] S3022. Calculate the mean or rate of change of the historical monitoring data of each sensor.

[0139] In this step, the mean refers to the average value of historical monitoring data, and the rate of change refers to the rate of increase or decrease of historical monitoring data.

[0140] S3023. Update the initial warning value of each sensor based on the mean or rate of change to obtain the updated target warning value.

[0141] In this step, the target warning value is calculated based on the mean as follows: the standard deviation is calculated based on the mean and historical monitoring data, and the updated target warning value is obtained based on the mean and standard deviation; the target warning value is calculated based on the rate of change as follows: the target warning value is obtained based on the rate of change, the initial warning value, and the time span between the current value and the last warning value update.

[0142] It should be noted that when adjusting the warning value based on the mean or rate of change, the upper and lower limits of the warning value adjustment should be considered to avoid warning errors caused by the warning value being too high or too low.

[0143] S303. For each sensor, when the sensor's monitoring data exceeds the sensor's target warning value, determine that the sensor's monitoring data is abnormal, and determine the type of abnormality based on the sensor type.

[0144] In this step, the types of anomalies include: multiple single anomalies, as well as complex anomalies formed by combinations of multiple single anomalies. For example: excessive gas concentration, excessive concentration of multiple gases, abnormal manhole cover displacement, abnormal liquid leakage, and abnormal manhole cover pressure overload.

[0145] For example, if the displacement of the manhole cover corresponding to the six-axis sensor exceeds the target warning value, the anomaly type is determined as a single anomaly "manhole cover displacement anomaly"; if the carbon monoxide concentration and methane concentration both exceed the target warning value, the anomaly type is determined as a compound anomaly "multiple gas concentrations exceeding the standard".

[0146] S304. Generate anomaly verification results based on the anomaly type corresponding to the abnormal monitoring data.

[0147] In this step, the anomaly verification results include: the anomaly types corresponding to multiple sensors, the monitoring data corresponding to multiple sensors, and the location and marking of the manhole cover of the cable well.

[0148] The location and marking of the cable well cover are used to determine the location of the faulty cable well, and the monitoring data is used to further analyze the fault of the cable well to determine the fault resolution strategy.

[0149] S305. Determine the warning level corresponding to each abnormal type in the abnormal verification result based on the preset abnormal mapping list.

[0150] In this step, the warning level is used to limit the warning method. The level of the warning determines which warning method is used to send the warning information.

[0151] For example, when the anomaly type is excessive methane concentration, the corresponding warning level is high; when the anomaly type is slow liquid level rise, the corresponding warning level is low.

[0152] S306. Determine the warning method corresponding to each type of anomaly based on the warning level.

[0153] According to the example in S305, when the warning level is high, the corresponding warning method can be: light-emitting diode (LED) prompt and buzzer prompt; when the warning level is low, the corresponding warning method can be: push warning information through a mobile terminal application.

[0154] S307. Issue warning information for each type of anomaly using the corresponding warning method.

[0155] In this step, the warning information can be issued in the following ways: through various alarm devices connected to the host computer, or by pushing warning information to a mobile terminal.

[0156] For example, various alarm devices connected to the host computer can be: LED lights, displays, and buzzers.

[0157] Based on the above embodiments, this application also provides a cable well fault early warning system. Figure 4 Schematic diagram of the cable well fault early warning system provided in this application Figure 2 ,like Figure 4 As shown, the system includes:

[0158] Pressure sensor 401 is used to monitor the stress on the cable manhole cover. When the pressure on the cable manhole cover exceeds its own withstand threshold, it will cause direct damage to the cable manhole cover. Pressure sensor 401 is used to collect the pressure on the surface of the cable manhole cover in real time.

[0159] Liquid level sensor 402 is used to detect the liquid level in the cable well. If the liquid in the cable well is not removed in time, it can easily corrode the cable lines and even cause phase-to-phase short circuits. Liquid level sensor 402 can output an analog electrical signal in the form of voltage difference based on changes in the liquid level in the cable well, which is then transmitted to the lower-level computer 407 for data processing.

[0160] The six-axis sensor 403 is used to monitor the displacement of cable manhole covers. The six-axis sensor primarily senses changes in acceleration in various directions within a three-dimensional space. When the cable manhole cover shifts position, it generates acceleration in the direction of the shift. By analyzing the direction of acceleration, the movement trajectory of the cable manhole cover can be obtained, thus determining the type of potential displacement hazard. The six-axis sensor 403 is in a dormant state when no acceleration change is detected, at which point its power consumption is almost zero. Once acceleration is detected, the six-axis sensor 403 is activated, transmitting the generated data to the lower-level computer 407 for processing in the form of analog electrical signals.

[0161] The methane sensor 404, carbon monoxide sensor 405, and hydrogen sulfide sensor 406 are used to detect the concentrations of methane, hydrogen sulfide, and carbon monoxide, respectively. These three gas sensors operate on the same principle: they output a corresponding current based on the detected gas concentration, and then transmit this current as an analog electrical signal to the lower-level computer 407 for data processing.

[0162] The lower-level computer 407 is used to acquire environmental data of the cable well, process the data based on the environmental data and monitoring data from multiple sensors, update the sensor warning values ​​and verify the anomalies in the monitoring data, and send the anomaly verification results to the upper-level computer 408.

[0163] The host computer 408 is used to determine whether to issue a warning message based on the anomaly verification result, and combines the LED light 410, the display screen 411, and the buzzer 412 to send the warning message.

[0164] The communication module 409 is used to realize communication between the sensor, the host computer 408 and the slave computer 407.

[0165] LED light 410, display screen 411, and buzzer 412 are used to provide early warning when there is an abnormality in the cable well.

[0166] Figure 5 Flowchart of the cable well fault early warning method provided in this application Figure 3 ,exist Figure 4 Based on the illustrated embodiment, this method further elaborates on the method for early warning of cable well faults, such as... Figure 5 As shown, the method includes:

[0167] A1. Check whether the current multiple sensors meet the monitoring conditions.

[0168] In this step, it is necessary to determine the operating status of multiple sensors to see if they are all in normal operating condition. If a sensor malfunctions, it is necessary to replace or repair it in a timely manner to ensure that the sensors can perform real-time data monitoring of the cable well.

[0169] A2. When multiple sensors meet the monitoring conditions, collect monitoring data.

[0170] A3. Perform data analysis on the monitoring data based on the lower-level machine.

[0171] A4. The lower-level machine transmits the data analysis results to the upper-level machine.

[0172] A5. The host computer determines whether the data reception is complete.

[0173] In this step, after the lower-level machine transmits the data analysis results to the upper-level machine, the upper-level machine needs to determine whether the received data is complete. If it is determined that the data reception is incomplete, the upper-level machine can retrieve the data from the lower-level machine again.

[0174] A6. When the data is complete, determine whether there is an anomaly based on the received data.

[0175] A7. Trigger an alert when an anomaly is detected.

[0176] A8. Display the monitoring data on the screen connected to the host computer.

[0177] In this step, the information displayed on the screen may also include: the manhole cover markings and location information of the cable well, and the anomaly verification results when there is an anomaly in the cable well.

[0178] Figure 6 This is a structural schematic diagram of the cable well fault early warning device provided in this application, as shown below. Figure 6 As shown, the cable well fault early warning device provided in this embodiment includes:

[0179] The acquisition module 601 is used to collect monitoring data from multiple sensors in the cable well and the corresponding environmental data of the cable well based on the lower-level computer.

[0180] The first processing module 602 is used to update the initial warning value of each sensor based on the monitoring data and environmental data when the monitoring data and environmental data meet the preset adjustment conditions, so as to obtain the updated target warning value.

[0181] The second processing module 603 is used to perform anomaly verification on each sensor based on monitoring data and target warning values, and obtain anomaly verification results.

[0182] The third processing module 604 is used to send the anomaly verification result to the host computer, and to issue a warning message based on the host computer when the anomaly verification result indicates that an anomaly exists.

[0183] The environmental data includes ambient temperature and ambient humidity.

[0184] In one possible implementation, the preset adjustment conditions include at least one of the following:

[0185] The ambient temperature exceeds the preset temperature range.

[0186] The ambient humidity exceeds the preset humidity range.

[0187] There are at least two sensors whose monitoring data are greater than the initial warning value corresponding to the sensor.

[0188] There are instances where the monitoring data from any sensor exceeds the initial warning value more than the preset number of times.

[0189] In one possible implementation, the first processing module 602 is further configured to:

[0190] Based on the type of each sensor, determine the preset warning value adjustment strategy for each sensor.

[0191] Based on monitoring data, environmental data, and the preset warning value adjustment strategy for each sensor, the target warning value after each sensor is updated is calculated.

[0192] In one possible implementation, the second processing module 603 is further configured to:

[0193] For each sensor, when the sensor's monitoring data exceeds the sensor's target warning value, it is determined that the sensor's monitoring data is abnormal, and the type of abnormality is determined according to the type of sensor.

[0194] Anomaly verification results are generated based on the anomaly type corresponding to the abnormal monitoring data.

[0195] In one possible implementation, the third processing module 604 is further used for:

[0196] The warning level corresponding to each anomaly type in the anomaly verification results is determined based on a preset anomaly mapping list.

[0197] The warning method corresponding to each type of anomaly is determined based on the warning level.

[0198] Warning messages are issued according to the warning method corresponding to each type of anomaly.

[0199] In one possible implementation, the first processing module 602 is further configured to:

[0200] Obtain historical monitoring data for each sensor.

[0201] For each sensor, calculate the mean or rate of change of the sensor's historical monitoring data.

[0202] The initial warning value of each sensor is updated based on the mean or rate of change to obtain the updated target warning value.

[0203] In one possible implementation, the system number further includes a communication module, and the device further includes a fourth processing module 605 for:

[0204] Based on the lower-level machine monitoring communication module, the communication quality of the main communication unit is monitored.

[0205] When the communication quality of the main communication unit is lower than a preset threshold, the current communication unit of the communication module will be switched to the backup communication unit.

[0206] The main communication unit and backup communication unit of the communication module are used to transmit the monitoring data of each sensor to the lower-level machine and to send the abnormal verification results generated by the lower-level machine to the upper-level machine.

[0207] The cable well fault early warning device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0208] Figure 7 A schematic diagram of the structure of the electronic device provided in this application. Figure 7 As shown, the electronic device provided in this embodiment includes at least one processor 701 and a memory 702. Optionally, the device further includes a communication component 703. The processor 701, memory 702, and communication component 703 are connected via a bus 704.

[0209] In the specific implementation process, at least one processor 701 executes computer execution instructions stored in memory 702, causing at least one processor 701 to execute the above-mentioned cable well fault early warning method.

[0210] The specific implementation process of processor 701 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0211] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0212] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0213] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0214] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described cable well fault early warning method.

[0215] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the aforementioned cable well fault early warning method.

[0216] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0217] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0218] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0219] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0220] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0221] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0222] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0223] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for early warning of cable well faults, characterized in that, An application is made in a cable well fault early warning system, the system comprising multiple sensors, a lower-level computer, and a higher-level computer, the method comprising: The monitoring data from multiple sensors in the cable well, as well as the corresponding environmental data of the cable well, are collected by the lower-level computer. When the monitoring data and the environmental data meet the preset adjustment conditions, the initial warning value of each sensor is updated based on the monitoring data and the environmental data to obtain the updated target warning value; Based on the monitoring data and the target warning value, anomaly verification is performed on each sensor to obtain the anomaly verification result; The anomaly verification result is sent to the host computer, and when the anomaly verification result indicates that an anomaly exists, an early warning message is issued based on the host computer; The environmental data includes ambient temperature and ambient humidity.

2. The method according to claim 1, characterized in that, The preset adjustment conditions include at least one of the following: The ambient temperature exceeds the preset temperature range; The ambient humidity exceeds the preset humidity range; There are at least two sensors whose monitoring data are greater than the initial warning value corresponding to the sensor; There are instances where the monitoring data from any sensor exceeds the initial warning value more than the preset number of times.

3. The method according to claim 2, characterized in that, The process of updating the initial warning value of each sensor based on the monitoring data and the environmental data to obtain the updated target warning value includes: Based on the type of each sensor, determine the preset warning value adjustment strategy for each sensor; Based on the monitoring data, the environmental data, and the preset warning value adjustment strategy for each sensor, the target warning value after the update for each sensor is calculated.

4. The method according to any one of claims 1 to 3, characterized in that, The anomaly verification is performed on each sensor based on the monitoring data and the target early warning value to obtain the anomaly verification result, including: For each sensor, when the monitoring data of the sensor exceeds the target warning value of the sensor, it is determined that the monitoring data of the sensor is abnormal, and the type of abnormality is determined according to the type of the sensor; Anomaly verification results are generated based on the anomaly type corresponding to the abnormal monitoring data.

5. The method according to claim 4, characterized in that, The step of sending the anomaly verification result to the host computer, and issuing a warning message based on the host computer when the anomaly verification result indicates the existence of an anomaly, includes: The warning level corresponding to each anomaly type in the anomaly verification result is determined based on a preset anomaly mapping list; The warning method for each type of anomaly is determined based on the warning level; Warning messages are issued according to the warning method corresponding to each type of anomaly.

6. The method according to claim 1, characterized in that, The method further includes: Acquire historical monitoring data for each sensor; For each sensor, calculate the mean or rate of change of the historical monitoring data of that sensor; The initial warning value of each sensor is updated based on the mean or rate of change to obtain the updated target warning value.

7. The method according to claim 1, characterized in that, The system further includes a communication module, and the method further includes: The lower-level machine monitors the communication quality of the main communication unit in the communication module. When the communication quality of the main communication unit is lower than a preset threshold, the current communication unit of the communication module is switched to the backup communication unit. The main communication unit and the backup communication unit of the communication module are used to transmit the monitoring data of each sensor to the lower-level machine, and to send the abnormal verification results generated by the lower-level machine to the upper-level machine.

8. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

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