Electric power system fault early warning monitoring method and system based on intelligent sensor

Abstract

The invention discloses an electric power system fault early warning monitoring method and system based on an intelligent sensor, and particularly relates to the technical field of sensors, and the method comprises the steps: obtaining a first electric power text of a target enterprise; preprocessing the first power text to obtain a first key text corresponding to the first power text; performing data selection on the first key text; calculating and analyzing the first key text to obtain a corresponding first key text safety value; obtaining an intelligent power model, and calculating the first key text security value according to the intelligent power model to obtain a comprehensive text security value; and comparing the comprehensive text safety value with a preset comprehensive safety text threshold value, and transmitting a judged digital signal to a corresponding feedback mode to a manager. According to the method, the accuracy and comprehensiveness of the power system are improved, data errors are reduced, a more intuitive effect is presented, it is finally ensured that faults of the power system can be accurately monitored, and the comprehensiveness and safety of the method are ensured.

Description

Technical Field

[0001] The present invention relates to the field of sensor technology, and more specifically, to a method and system for early warning monitoring of power system faults based on intelligent sensors. Background Art

[0002] The application of smart sensors in power systems requires the support of many background technologies. The development of sensor technology, including high-precision measurement, miniaturization and integration, and wireless communication technology, provides accurate and convenient data collection for power systems. The demand for intelligent power systems, such as fault warning and diagnosis, energy management and optimization, and adaptation to the development of smart grids, has prompted smart sensors to play an important role. In terms of data analysis and processing technology, big data, artificial intelligence, and cloud computing technologies can process the large amount of data generated by smart sensors, provide support for decision-making in power systems, and realize intelligent control and optimized operation.

[0003] The existing intelligent sensor power system fault early warning monitoring method mainly includes data collection step, data analysis step and fault assessment step. The data collection step mainly collects relevant data of the power system through various intelligent sensors; the data analysis step converts complex power system data into intuitive analysis results to make the system operation status clearer. The fault assessment step accurately evaluates the existing analysis results by comparing historical data to determine whether there is a fault risk in the power system.

[0004] However, there are still some shortcomings in its actual use. For example, in the data collection step, the power system data is collected through various intelligent sensors, which is easily interfered by power factors, resulting in inaccurate data. For example, electromagnetic interference may affect the accuracy of the sensor, causing deviations in the collected voltage, current and other data; in the data analysis step, the collected data is processed, but when the existing technology analyzes complex power system data, there will be deviations in the analysis results and omissions of data, resulting in data gaps, which reduces the reference value of the power system data; the existing system lacks comprehensive data to measure the key indicators of power system operation, making the evaluation not comprehensive and objective, increasing the difficulty and risk of decision-making, and bringing troubles to power system management. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for early warning monitoring of power system faults based on intelligent sensors, which solves the problems raised in the above-mentioned background technology through the field of sensor technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a power system fault early warning monitoring method based on intelligent sensors, comprising:

[0007] S1: in response to the operation of the smart sensor of the target enterprise, obtaining a first power text of the target enterprise;

[0008] S2: preprocessing the first power text of the target enterprise, obtaining a first key text corresponding to the first power text, determining the first key text as the target text, dividing the target text into sub-texts, and numbering the sub-texts in sequence as i=1, 2, ..., n;

[0009] S3: performing a preprocessing operation on the first power text of the target enterprise to obtain a first key text, and performing data selection on the first key text;

[0010] S4: The first key text is calculated and analyzed to obtain a corresponding first key text safety value; including a voltage characteristic calculation unit, a current characteristic calculation unit, a vibration characteristic calculation unit and an insulation characteristic calculation unit;

[0011] S5: Acquire a smart power model, and calculate the first key text safety value according to the smart power model to obtain a comprehensive text safety value; including a smart power unit;

[0012] S6: comparing the comprehensive text safety value with a preset comprehensive safety text threshold and transmitting the determined digital signal to a corresponding feedback method for processing;

[0013] S7: According to the digital signal, a preset intelligent feedback method is sent to the corresponding manager of the target enterprise.

[0014] Preferably, the first key text specifically includes: node voltage distortion rate is recorded as dj, voltage sag depth is recorded as dy, node voltage phase difference is recorded as dx, current mutation amount is recorded as lt, current harmonic distortion rate is recorded as lv, current imbalance is recorded as lb, vibration displacement is recorded as zx, vibration frequency bandwidth is recorded as zk, vibration acceleration is recorded as za, insulation resistance change rate is recorded as jd, insulation breakdown voltage value is recorded as jc and insulation medium loss angle value is recorded as jz.

[0015] Preferably, the voltage characteristic calculation unit is used to establish a mathematical model of voltage characteristic coefficient values, select and import the data of the first key text into the mathematical model of voltage characteristic coefficient values, and calculate the voltage characteristic coefficient values ​​of each sub-text, which is specifically expressed as:

[0016]

[0017] DA i Indicates the voltage characteristic coefficient value of the i-th subtext, dj i Indicates the node voltage distortion rate of the i-th subtext, dy i Indicates the voltage sag depth of the i-th subtext, dxi represents the node voltage phase difference of the i-th subtext, and n represents the number of subtexts.

[0018] Preferably, the current characteristic calculation unit is used to establish a mathematical model of the current characteristic coefficient value, select and import the data of the first key text into the mathematical model of the current characteristic coefficient value, and calculate the current characteristic coefficient value of each sub-text, which is specifically expressed as:

[0019]

[0020] LA i represents the current characteristic coefficient value of the i-th subtext, lt i represents the current mutation amount of the i-th subtext, lv i Indicates the current harmonic distortion rate of the i-th subtext, lb i Indicates the current unbalance degree of the i-th subtext.

[0021] Preferably, the vibration characteristic calculation unit is used to establish a mathematical model of vibration characteristic coefficient values, select and import the data of the first key text into the mathematical model of vibration characteristic coefficient values, and calculate the vibration characteristic coefficient values ​​of each sub-text, which is specifically expressed as:

[0022]

[0023] ZA i represents the vibration characteristic coefficient value of the i-th subtext, zx max represents the vibration displacement of the target text, zk i represents the vibration frequency bandwidth of the i-th subtext, za i represents the vibration acceleration of the ith subtext, and n represents the number of subtexts.

[0024] Preferably, the insulation characteristic calculation unit is used to establish a mathematical model of insulation characteristic coefficient values, select and import the data of the first key text into the mathematical model of insulation characteristic coefficient values, and calculate the insulation characteristic coefficient values ​​of each sub-text, which is specifically expressed as:

[0025]

[0026] J A i Indicates the insulation characteristic coefficient value of the i-th subtext, jd i Indicates the insulation resistance change rate of the i-th subtext, jc i Indicates the insulation breakdown voltage value of the i-th subtext, jz i Indicates the dielectric loss angle value of the i-th subtext, jz i The value range of is (0°, 90°).

[0027] Preferably, the intelligent power unit is used to establish an intelligent power model, import the first key text safety value into the intelligent power model, and calculate the comprehensive text safety value, which is specifically expressed as:

[0028]

[0029] Where P represents the comprehensive text security value, μ i represents the first key text security value of the i-th subtext, μ a The mean of the first key text safety value of the target text, DA i Indicates the voltage characteristic coefficient value of the i-th subtext, LA i represents the current characteristic coefficient value of the i-th subtext, ZA i Indicates the vibration characteristic coefficient value of the i-th subtext, JA i Indicates the insulation characteristic coefficient value of the i-th subtext, α 1 , α 2 , α 3 , α 4 represents the weight coefficient, λ 1 The value range is 0.23 to 0.26, λ 2 The value range is 0.22 to 0.23, λ 3 The value range is 0.25 to 0.29, λ 4 The value range is 0.14 to 0.27, where ζ represents other influencing factors of the comprehensive text security value, where i = 1, 2, ..., n.

[0030] Preferably, the preset comprehensive safety text threshold is a value based on the reasonable evaluation of power information by the system in previous years; the specific determination is as follows:

[0031] B1: If the comprehensive text safety value is greater than the preset comprehensive safety text threshold, a fault signal is issued;

[0032] B2: If the comprehensive text safety value is less than the preset comprehensive safety text threshold, a safety signal is issued.

[0033] To achieve the above object, the present invention provides the following technical solution: a power system fault early warning monitoring system based on intelligent sensors, comprising the following modules:

[0034] A power information acquisition module, in response to the operation of the smart sensor of the target enterprise, acquires a first power text of the target enterprise;

[0035] The power information preprocessing module performs a preprocessing operation on the first power text of the target enterprise, obtains the first key text corresponding to the first power text, determines the first key text as the target text, divides the target text into sub-texts, and numbers the sub-texts in sequence as i=1, 2, ..., n;

[0036] An electric power text selection module performs a preprocessing operation on the first electric power text of the target enterprise to obtain a first key text, and performs data selection on the first key text;

[0037] The power information analysis module calculates and analyzes the first key text to obtain a corresponding first key text safety value; including a voltage characteristic calculation unit, a current characteristic calculation unit, a vibration characteristic calculation unit and an insulation characteristic calculation unit;

[0038] A comprehensive analysis module, which obtains an intelligent power model, calculates the first key text safety value according to the intelligent power model to obtain a comprehensive text safety value and transmits it to the determination module; including an intelligent power unit;

[0039] A discrimination module compares the comprehensive text safety value with a preset comprehensive safety text threshold and transmits the judged digital signal to the feedback module for processing;

[0040] The feedback module performs a preset intelligent feedback method according to the digital signal and sends it to the corresponding management personnel of the target enterprise.

[0041] Technical effects and advantages of the present invention:

[0042] 1. The present invention obtains the first power text of the target enterprise in response to the operation of the intelligent sensor of the target enterprise through the express information acquisition module, and determines it as the target text, and filters out each subtext from the target text, which is helpful to improve the integrity of the subsequent power information analysis; it is used to perform a preprocessing operation on the first power text of the target enterprise to obtain the first key text, thereby improving the quality of power data, removing abnormal values, and ensuring that the data is accurate and reliable;

[0043] 2. The present invention selects data for the first key text, and then calculates the first key text using a mathematical model to obtain the first key text safety value, thereby discovering the faults that exist in the power information system, which helps to provide an important guarantee for the early warning decision-making analysis of power information by the subsequent system, and helps to improve the stability of power information monitoring; obtains an intelligent power model, and calculates the first key text safety value according to the intelligent power model to obtain a comprehensive text safety value, which helps to present a more intuitive effect and the accuracy of power data to management personnel;

[0044] 3. The present invention compares the comprehensive text safety value with the preset comprehensive safety text threshold and transmits the judged digital signal to the corresponding feedback method for processing, which helps to improve the accuracy of early warning analysis of power information; the feedback method can detect the digital signal sent by the system in real time. Once a fault signal is received, the system will feed back the processing result to the management personnel, and the management personnel will intelligently optimize and adjust the power information; it helps to improve the comprehensiveness and safety of power information analysis; BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the structure of the method of the present invention.

[0046] Figure 2 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] As attached Figure 1 Shown in the figure is a power system fault early warning monitoring method based on intelligent sensors, including steps S1-S7.

[0049] S1: In response to the operation of a smart sensor of a target enterprise, a first power text of the target enterprise is obtained.

[0050] In this embodiment, it should be specifically explained that the managers of the target enterprise can perform intelligent sensor operations on the corresponding information terminal devices. The types of information terminal devices mainly include: mobile terminals, computer terminals, tablet terminals, etc.; managers have a variety of ways to detect target power data, including but not limited to: text, audio, images, etc. The managers obtain the corresponding power text through the corresponding information terminal devices. The system operates through the intelligent sensors of the target enterprise and performs fault warning detection and analysis on the power system based on the first power text of the target enterprise. This embodiment does not limit the information terminal devices and the methods of power data.

[0051] S2: Preprocess the first power text of the target enterprise, obtain the first key text corresponding to the first power text, determine the first key text as the target text, divide the target text into sub-texts, and number the sub-texts in sequence as i=1, 2,..., n.

[0052] In this embodiment, specifically, the specific steps of preprocessing the first power text of the target enterprise are as follows:

[0053] A1: Cleaning of the first power text: Remove special characters, punctuation marks, and numbers, and convert the case to make the target text all uppercase or all lowercase.

[0054] A2: Stop word removal: Remove common words that contribute less to the analysis of the first power text, such as "of", "to", "is", "in", etc.

[0055] A3: Text standardization: According to the Z-score standardization method, perform data standardization processing on the first power text to obtain the first key text.

[0056] S3: After performing preprocessing operations on the first power text of the target enterprise to obtain the first key text, perform data selection on the first key text.

[0057] In this embodiment, specifically, the first key text specifically includes: the node voltage distortion rate denoted as dj, the voltage sag depth denoted as dy, the node voltage phase difference denoted as dx, the current mutation denoted as lt, the current harmonic distortion rate denoted as lv, the current unbalance degree denoted as lb, the vibration displacement denoted as zx, the vibration frequency bandwidth denoted as zk, the vibration acceleration denoted as za, the insulation resistance change rate denoted as jd, the insulation breakdown voltage value denoted as jc, and the insulation dielectric loss angle value denoted as jz.

[0058] In this embodiment, specifically, the node voltage distortion rate is obtained by collecting signals through voltage sensors installed at each node and analyzing them through fast Fourier transform; the voltage sag depth is monitored in real time by voltage sensors installed at the access points of key equipment and important load nodes; the node voltage phase difference is calculated using phase measuring instruments installed at different nodes; the current mutation is obtained by monitoring the difference between adjacent sampling moments in real time by current sensors installed in the current circuits of transmission lines and equipment; the current harmonic distortion rate is obtained by collecting signals through current sensors and analyzing them through fast Fourier transform, installed at the main transmission lines and the inlets of large equipment; the current unbalance degree is calculated by measuring the three-phase current through current sensors at each node; the vibration displacement, vibration frequency bandwidth, and vibration acceleration are measured by vibration sensors, vibration analyzers, and acceleration sensors respectively, installed at key parts of power equipment and parts prone to vibration; the insulation resistance change rate is measured and calculated by a measuring device installed regularly on the insulation part of power equipment; the insulation breakdown voltage value is measured on a laboratory or on-site test device for insulation withstand voltage test; the insulation dielectric loss angle value is measured on the insulation part of power equipment by a special measuring instrument.

[0059] S4: The first key text is calculated and analyzed to obtain a corresponding first key text safety value; including a voltage characteristic calculation unit, a current characteristic calculation unit, a vibration characteristic calculation unit and an insulation characteristic calculation unit.

[0060] In this embodiment, it should be specifically explained that the first key text safety value includes the voltage characteristic coefficient value of each sub-text, the current characteristic coefficient value of each sub-text, the vibration characteristic coefficient value of each sub-text and the insulation characteristic coefficient value of each sub-text.

[0061] In this embodiment, it should be specifically explained that the voltage characteristic calculation unit is used to establish a mathematical model of the voltage characteristic coefficient value, select and import the data of the first key text into the mathematical model of the voltage characteristic coefficient value, and calculate the voltage characteristic coefficient value of each sub-text, which is specifically expressed as:

[0062]

[0063] DA i Indicates the voltage characteristic coefficient value of the i-th subtext, dj i Indicates the node voltage distortion rate of the i-th subtext, dy i Indicates the voltage sag depth of the i-th subtext, dx i represents the node voltage phase difference of the i-th subtext, and n represents the number of subtexts.

[0064] In this embodiment, it should be specifically explained that the current characteristic calculation unit is used to establish a mathematical model of the current characteristic coefficient value, select the data of the first key text and import it into the mathematical model of the current characteristic coefficient value, and calculate the current characteristic coefficient value of each sub-text, which is specifically expressed as:

[0065]

[0066] LA i represents the current characteristic coefficient value of the i-th subtext, lt i represents the current mutation amount of the i-th subtext, lv i Indicates the current harmonic distortion rate of the i-th subtext, lb i Indicates the current unbalance degree of the i-th subtext.

[0067] In this embodiment, it should be specifically explained that the vibration characteristic calculation unit is used to establish a mathematical model of the vibration characteristic coefficient value, select the data of the first key text and import it into the mathematical model of the vibration characteristic coefficient value, and calculate the vibration characteristic coefficient value of each sub-text, which is specifically expressed as:

[0068]

[0069] ZA irepresents the vibration characteristic coefficient value of the i-th subtext, zx max represents the vibration displacement of the target text, zk i represents the vibration frequency bandwidth of the i-th subtext, za i represents the vibration acceleration of the ith subtext, and n represents the number of subtexts.

[0070] In this embodiment, it should be specifically explained that the insulation characteristic calculation unit is used to establish a mathematical model of the insulation characteristic coefficient value, select and import the data of the first key text into the mathematical model of the insulation characteristic coefficient value, and calculate the insulation characteristic coefficient value of each sub-text, which is specifically expressed as:

[0071]

[0072] J A i Indicates the insulation characteristic coefficient value of the i-th subtext, jd i Indicates the insulation resistance change rate of the i-th subtext, jc i Indicates the insulation breakdown voltage value of the i-th subtext, jz i Indicates the dielectric loss angle value of the i-th subtext, jz i The value range of is (0°, 90°).

[0073] S5: Acquire a smart power model, and calculate the first key text safety value according to the smart power model to obtain a comprehensive text safety value; including a smart power unit.

[0074] In this embodiment, it should be specifically explained that the intelligent power unit is used to establish an intelligent power model, import the first key text safety value into the intelligent power model, and calculate the comprehensive text safety value, which is specifically expressed as:

[0075]

[0076] Where P represents the comprehensive text security value, μ i represents the first key text security value of the i-th subtext, μ a The mean of the first key text safety value of the target text, DA i Indicates the voltage characteristic coefficient value of the i-th subtext, LA i represents the current characteristic coefficient value of the i-th subtext, ZA i Indicates the vibration characteristic coefficient value of the i-th subtext, JA i Indicates the insulation characteristic coefficient value of the i-th subtext, α 1 , α 2 , α 3 , α 4 represents the weight coefficient, λ 1The value range is 0.23 to 0.26, λ 2 The value range is 0.22 to 0.23, λ 3 The value range is 0.25 to 0.29, λ 4 The value range is 0.14 to 0.27, where ζ represents other influencing factors of the comprehensive text security value, where i = 1, 2, ..., n.

[0077] S6: Compare the comprehensive text safety value with the preset comprehensive safety text threshold and transmit the determined digital signal to the corresponding feedback method for processing.

[0078] In this embodiment, it should be specifically noted that the preset comprehensive safety text threshold is a value based on a reasonable evaluation of power information by the system in previous years; the specific determination is as follows:

[0079] B1: If the comprehensive text safety value is greater than the preset comprehensive safety text threshold, a fault signal is issued;

[0080] B2: If the comprehensive text safety value is less than the preset comprehensive safety text threshold, a safety signal is issued;

[0081] S7: According to the digital signal, a preset intelligent feedback method is sent to the corresponding manager of the target enterprise.

[0082] In this embodiment, it is specifically necessary to explain that the preset intelligent feedback modes are: text reply, image reply and audio reply.

[0083] As attached Figure 2 As shown, this embodiment provides a power system fault early warning monitoring system based on intelligent sensors, including the following modules:

[0084] A power information acquisition module, in response to the operation of the smart sensor of the target enterprise, acquires a first power text of the target enterprise;

[0085] The power information preprocessing module performs a preprocessing operation on the first power text of the target enterprise, obtains the first key text corresponding to the first power text, determines the first key text as the target text, divides the target text into sub-texts, and numbers the sub-texts in sequence as i=1, 2, ..., n;

[0086] An electric power text selection module performs a preprocessing operation on the first electric power text of the target enterprise to obtain a first key text, and performs data selection on the first key text;

[0087] The power information analysis module calculates and analyzes the first key text to obtain a corresponding first key text safety value; including a voltage characteristic calculation unit, a current characteristic calculation unit, a vibration characteristic calculation unit and an insulation characteristic calculation unit;

[0088] A comprehensive analysis module, which obtains an intelligent power model, calculates the first key text safety value according to the intelligent power model to obtain a comprehensive text safety value and transmits it to the determination module; including an intelligent power unit;

[0089] A discrimination module compares the comprehensive text safety value with a preset comprehensive safety text threshold and transmits the judged digital signal to the feedback module for processing;

[0090] The feedback module performs a preset intelligent feedback method according to the digital signal and sends it to the corresponding management personnel of the target enterprise.

[0091] The present invention obtains the first power text of the target enterprise in response to the operation of the intelligent sensor of the target enterprise through the express information acquisition module, and determines it as the target text, and filters out each subtext from the target text, which is helpful to improve the integrity of the power information analysis later; it is used to perform a preprocessing operation on the first power text of the target enterprise to obtain the first key text, thereby improving the quality of power data, removing abnormal values, and ensuring that the data is accurate and reliable; thereafter, data selection is performed on the first key text, and then the first key text is calculated by a mathematical model to obtain the first key text safety value, thereby discovering the existence of faults in the power information system, which is helpful to provide an important guarantee for the early warning decision analysis of the power information by the subsequent system, and is helpful to provide The stability of high power information monitoring is improved; an intelligent power model is obtained, and a comprehensive text safety value is calculated from the first key text safety value according to the intelligent power model, which helps to present a more intuitive effect and the accuracy of power data to management personnel; by comparing the comprehensive text safety value with the preset comprehensive safety text threshold and transmitting the judged digital signal to the corresponding feedback method for processing, it helps to improve the accuracy of early warning analysis of power information; the digital signal emitted by the system can be discovered in real time through the feedback method. Once a fault signal is received, the system will feed back the processing result to the management personnel, and the management personnel will intelligently optimize and adjust the power information; it helps to improve the comprehensiveness and safety of power information analysis.

[0092] Secondly, in the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0093] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A power system fault early warning monitoring method based on intelligent sensors, characterized in that: include: S1: in response to the operation of the smart sensor of the target enterprise, obtaining a first power text of the target enterprise; S2: preprocessing the first power text of the target enterprise, obtaining a first key text corresponding to the first power text, determining the first key text as the target text, dividing the target text into sub-texts, and numbering the sub-texts in sequence as i=1, 2, ..., n; S3: performing a preprocessing operation on the first power text of the target enterprise to obtain a first key text, and performing data selection on the first key text; S4: Calculate and analyze the first key text to obtain a corresponding first key text security value; It includes a voltage characteristic calculation unit, a current characteristic calculation unit, a vibration characteristic calculation unit and an insulation characteristic calculation unit; S5: Acquire a smart power model, and calculate the first key text safety value according to the smart power model to obtain a comprehensive text safety value; including a smart power unit; S6: comparing the comprehensive text safety value with a preset comprehensive safety text threshold and transmitting the determined digital signal to a corresponding feedback method for processing; S7: According to the digital signal, a preset intelligent feedback method is sent to the corresponding manager of the target enterprise.

2. The method for early warning and monitoring of power system faults based on intelligent sensors according to claim 1 is characterized in that: The first key text specifically includes: node voltage distortion rate is recorded as dj, voltage sag depth is recorded as dy, node voltage phase difference is recorded as dx, current mutation amount is recorded as lt, current harmonic distortion rate is recorded as lv, current imbalance is recorded as lb, vibration displacement is recorded as zx, vibration frequency bandwidth is recorded as zk, vibration acceleration is recorded as za, insulation resistance change rate is recorded as jd, insulation breakdown voltage value is recorded as jc and insulation medium loss angle value is recorded as jz.

3. The method for early warning and monitoring of power system faults based on intelligent sensors according to claim 1 is characterized in that: The voltage characteristic calculation unit is used to establish a mathematical model of voltage characteristic coefficient values, select and import the data of the first key text into the mathematical model of voltage characteristic coefficient values, and calculate the voltage characteristic coefficient values ​​of each sub-text, which is specifically expressed as: DA i Indicates the voltage characteristic coefficient value of the i-th subtext, dj i Indicates the node voltage distortion rate of the i-th subtext, dy i Indicates the voltage sag depth of the i-th subtext, dx i represents the node voltage phase difference of the i-th subtext, and n represents the number of subtexts.

4. The method for early warning and monitoring of power system faults based on intelligent sensors according to claim 1 is characterized in that: The current characteristic calculation unit is used to establish a mathematical model of the current characteristic coefficient value, select and import the data of the first key text into the mathematical model of the current characteristic coefficient value, and calculate the current characteristic coefficient value of each sub-text, which is specifically expressed as: LA i represents the current characteristic coefficient value of the i-th subtext, lt i represents the current mutation amount of the i-th subtext, lv i Indicates the current harmonic distortion rate of the i-th subtext, lb i Indicates the current unbalance degree of the i-th subtext.

5. The method for early warning and monitoring of power system faults based on intelligent sensors according to claim 1 is characterized in that: The vibration characteristic calculation unit is used to establish a mathematical model of vibration characteristic coefficient values, select and import the data of the first key text into the mathematical model of vibration characteristic coefficient values, and calculate the vibration characteristic coefficient values ​​of each sub-text, which is specifically expressed as: ZA i represents the vibration characteristic coefficient value of the i-th subtext, zx max represents the vibration displacement of the target text, zk i represents the vibration frequency bandwidth of the i-th subtext, za i represents the vibration acceleration of the ith subtext, and n represents the number of subtexts.

6. The method for early warning and monitoring of power system faults based on intelligent sensors according to claim 1, characterized in that: The insulation characteristic calculation unit is used to establish a mathematical model of insulation characteristic coefficient values, select and import the data of the first key text into the mathematical model of insulation characteristic coefficient values, and calculate the insulation characteristic coefficient values ​​of each sub-text, which is specifically expressed as: J A i Indicates the insulation characteristic coefficient value of the i-th subtext, jd i Indicates the insulation resistance change rate of the i-th subtext, jc i Indicates the insulation breakdown voltage value of the i-th subtext, jz i Indicates the dielectric loss angle value of the i-th subtext, jz i The value range of is (0°, 90°).

7. The method for early warning and monitoring of power system faults based on intelligent sensors according to claim 1, characterized in that: The smart power unit is used to establish a smart power model, import the first key text safety value into the smart power model, and calculate the comprehensive text safety value, which is specifically expressed as: Where P represents the comprehensive text security value, μ i represents the first key text security value of the i-th subtext, μ a The mean of the first key text safety value of the target text, DA i Indicates the voltage characteristic coefficient value of the i-th subtext, LA i represents the current characteristic coefficient value of the i-th subtext, ZA i Indicates the vibration characteristic coefficient value of the i-th subtext, JA i represents the insulation characteristic coefficient value of the i-th sub-text, α1, α2, α3, α4 represent weight coefficients, λ1 ranges from 0.23 to 0.26, λ2 ranges from 0.22 to 0.23, λ3 ranges from 0.25 to 0.29, λ4 ranges from 0.14 to 0.27, where ζ represents other influencing factors of the comprehensive text security value, where i = 1, 2, ..., n.

8. The method for early warning and monitoring of power system faults based on intelligent sensors according to claim 1, characterized in that: The preset comprehensive safety text threshold is a value based on the reasonable evaluation of power information by the system in previous years; the specific determination is as follows: B1: If the comprehensive text safety value is greater than the preset comprehensive safety text threshold, a fault signal is issued; B2: If the comprehensive text safety value is less than the preset comprehensive safety text threshold, a safety signal is issued.

9. A power system fault early warning monitoring system based on intelligent sensors, characterized in that: A method for early warning and monitoring power system faults based on intelligent sensors for implementing any one of claims 1 to 8 above comprises the following modules: A power information acquisition module, in response to the operation of the smart sensor of the target enterprise, acquires a first power text of the target enterprise; The power information preprocessing module performs a preprocessing operation on the first power text of the target enterprise, obtains the first key text corresponding to the first power text, determines the first key text as the target text, divides the target text into sub-texts, and numbers the sub-texts in sequence as i=1, 2, ..., n; An electric power text selection module performs a preprocessing operation on the first electric power text of the target enterprise to obtain a first key text, and performs data selection on the first key text; The power information analysis module calculates and analyzes the first key text to obtain a corresponding first key text safety value; It includes a voltage characteristic calculation unit, a current characteristic calculation unit, a vibration characteristic calculation unit and an insulation characteristic calculation unit; A comprehensive analysis module obtains an intelligent power model, calculates the first key text safety value according to the intelligent power model to obtain a comprehensive text safety value and transmits it to the determination module; Includes intelligent power unit; A discrimination module compares the comprehensive text safety value with a preset comprehensive safety text threshold and transmits the judged digital signal to the feedback module for processing; The feedback module performs a preset intelligent feedback method according to the digital signal and sends it to the corresponding management personnel of the target enterprise.

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