CN114624578A - Aggregation analysis and diagnosis device and method for action characteristics of high-voltage switch equipment - Google Patents
Aggregation analysis and diagnosis device and method for action characteristics of high-voltage switch equipment Download PDFInfo
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- CN114624578A CN114624578A CN202210215261.XA CN202210215261A CN114624578A CN 114624578 A CN114624578 A CN 114624578A CN 202210215261 A CN202210215261 A CN 202210215261A CN 114624578 A CN114624578 A CN 114624578A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
- G01R31/3271—Testing of circuit interrupters, switches or circuit-breakers of high voltage or medium voltage devices
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
- G01R31/3271—Testing of circuit interrupters, switches or circuit-breakers of high voltage or medium voltage devices
- G01R31/3272—Apparatus, systems or circuits therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/327—Testing of circuit interrupters, switches or circuit-breakers
- G01R31/3271—Testing of circuit interrupters, switches or circuit-breakers of high voltage or medium voltage devices
- G01R31/3275—Fault detection or status indication
Abstract
The invention discloses a polymerization analysis diagnosis device for the action characteristics of high-voltage switch equipment, which comprises a giant magnetoresistance displacement sensor, a current sensor group and a vibration sensor, wherein the giant magnetoresistance displacement sensor, the current sensor group and the vibration sensor are electrically connected with an intelligent acquisition and analysis terminal; the giant magnetoresistance displacement sensor is used for acquiring the displacement of the spring operating mechanism, the current sensor group is used for acquiring the current of the opening coil, the current of the closing coil and the current of the energy storage motor, and the vibration sensor is used for acquiring the vibration condition of the mechanism; the intelligent acquisition and analysis terminal is used for acquiring data, processing the data and sending the data to the big data platform server, and the data platform server is used for comparing the data acquired twice before to generate an alarm event and pushing the alarm event to the electric power operation and maintenance personnel. The invention realizes the real-time monitoring of the action characteristics of the high-voltage switch equipment and simultaneously carries out health life assessment on the mechanical part of the high-voltage switch equipment.
Description
Technical Field
The invention belongs to the technical field of analysis and diagnosis of high-voltage switchgear operating characteristics, and particularly relates to an aggregation analysis and diagnosis device and method for the operating characteristics of high-voltage switchgear.
Background
The high-voltage circuit breaker is mainly used for controlling and protecting a power system, can be used for putting a part of power equipment or lines into or out of operation according to the operation requirements of a power grid, and can also be used for quickly cutting off a fault part from the power grid when the power equipment or lines have faults, so that the normal operation of the fault-free part in the power grid and the safety of equipment and operation maintenance personnel are ensured.
However, most of the faults of the existing high-voltage circuit breakers occur in mechanical mechanisms, mainly relating to an operating mechanism, a monitoring device, an auxiliary device and the like, are mostly caused by poor mechanical characteristics, such as separation rejection, closing rejection or misoperation, and because most of transformer substations are unmanned, accidents caused by switch equipment often occur.
Traditionally, the maintenance of circuit breakers has been preventive maintenance on a regular basis, which has a number of disadvantages, such as: have a relatively fixed and conservative maintenance cycle; the reliability of the circuit breaker after maintenance is possibly reduced due to human factors; the operating condition of the circuit breaker cannot be reflected in real time; faults that may exist between scheduled overhauls cannot be discovered in time.
Disclosure of Invention
The method aims at solving the problem that the reliability of the breaker after maintenance is reduced because the breaker in the prior art is periodically and preventively maintained; the running condition of the circuit breaker cannot be reflected in real time; the invention also provides a device and a method for analyzing and diagnosing the action characteristic of high-voltage switch equipment in a polymerization manner.
In order to achieve the technical purpose, the technical scheme adopted by the invention is as follows:
a polymerization analysis diagnosis device for action characteristics of high-voltage switch equipment comprises a giant magnetoresistance displacement sensor, a current sensor group, a vibration sensor, an intelligent acquisition and analysis terminal and a big data platform server, wherein the giant magnetoresistance displacement sensor, the current sensor group and the vibration sensor are electrically connected with the intelligent acquisition and analysis terminal, and the intelligent acquisition and analysis terminal is connected with the big data platform server through a wireless network; the giant magnetoresistance displacement sensor is used for acquiring the displacement of the spring operating mechanism, the current sensor group is used for acquiring the current of the opening coil, the current of the closing coil and the current of the energy storage motor, and the vibration sensor is used for acquiring the vibration condition of the mechanism; the intelligent acquisition and analysis terminal is used for acquiring data, processing the data and sending the data to the big data platform server, and the data platform server is used for comparing the data acquired twice before to generate an alarm event and pushing the alarm event to the electric power operation and maintenance personnel.
The diagnosis device selectively collects the currents of the opening coil and the closing coil and the current of the energy storage motor, carries out digital processing and analysis on the current waveform of the currents, is attached with detection of other mechanical characteristics such as contact stroke, over stroke and overshoot of the circuit breaker, completes monitoring of the high-voltage circuit breaker operating mechanism, and utilizes a mass real-time database of a background to realize state evaluation of the circuit breaker by means of an intelligent method, thereby realizing online monitoring and health diagnosis of the high-voltage circuit breaker.
Furthermore, the current sensor group comprises a first current sensor, a second current sensor and a third current sensor, the first current sensor is used for collecting the current of the opening coil, the second current sensor is used for collecting the current of the closing coil, and the third current sensor is used for collecting the current of the energy storage motor.
A high-voltage switch equipment action characteristic aggregation analysis diagnosis method comprises the following steps:
s1, collecting the opening current, the closing current and the energy storage motor current on the high-voltage switch by adopting a current sensor group to obtain current curves of the opening current, the closing current and the energy storage motor current;
s2, collecting current signals of a switching-off coil and a switching-on coil, and collecting displacement and mechanism vibration conditions of a spring operating mechanism of the high-voltage switch by adopting a giant magnetoresistance displacement sensor and a vibration sensor to obtain a mechanical characteristic curve and a mechanism vibration curve;
s3, generating a comtrade file format by using the collected current curve, mechanical characteristic curve and mechanism vibration curve, and submitting the comtrade file format to a cloud computing center of a large data platform server through a network;
s4, carrying out coaxiality comparison on the switching-on and switching-off current curves of the previous two times by the cloud computing center of the big data platform server through the current curves, and judging the characteristic state; carrying out coaxiality comparison on qualified current curves of the outgoing opening and closing switches through the current curves, and judging the characteristic state; comparing the coaxiality of the current curves of the energy storage motor in the previous two times through the current curve of the energy storage motor, and judging the characteristic state; judging the characteristic state through trend analysis of the mechanical characteristic curve and the mechanical characteristic curves of the equipment in the previous two times; judging the characteristic state through trend analysis of the mechanical characteristic curve and a delivery mechanical characteristic qualified curve of the equipment; judging the characteristic state through the trend analysis of the mechanism vibration curve and the mechanism vibration curves of the previous two times of the equipment;
and S5, diagnosing the health state of the high-voltage switch equipment according to the aggregation analysis, namely forming multi-parameter characteristic event information through the characteristic state of multi-parameter waveform comparison, comparing the characteristic event information with a threshold value in a high-voltage switch equipment health evaluation library, generating an alarm event, and pushing the alarm event to electric power operation and maintenance staff.
Further, the current curves of the opening current and the closing current obtain the state characteristics of the circuit breaker: by extracting time characteristic parameters in a current waveform: the electromagnet movement time t1, the contact action time t2 and the switch auxiliary contact cutting time t3 represent the closing characteristic time, and the state characteristic of the circuit breaker is judged according to the three time characteristic parameters.
Further, the current curve of the current of the energy storage motor obtains the state characteristics of the energy storage motor: by extracting time characteristic parameters in the current waveform of the energy storage motor: at the time of t1, the energy storage motor receives a power-on command, and the energy storage motor starts to start without load; at the time t2, the motor rotates without load, and the current tends to be stable from the time t 2; at the time of t3, the energy storage motor starts to release energy, the closing spring is pulled to do work, and at t3, the rigidity state of the spring and the lubrication degree of the energy storage shaft are obtained according to the current curve of the energy storage motor current.
Further, mechanical characteristic curve: when a main shaft of the circuit breaker rotates, a giant magnetoresistance arranged on the main shaft is driven to rotate, the sensor acquires deflection of a magnetic induction line, change of a contact stroke is obtained by measuring a deflection angle of the magnetic induction line, a stroke time characteristic curve of the circuit breaker is obtained, a sampling interval is obtained by subtracting two adjacent time values, a contact stroke corresponding to the sampling interval is obtained according to the stroke time curve, and the corresponding contact movement speed is obtained by dividing the stroke by the corresponding sampling interval.
Compared with the prior art, the invention has the following beneficial effects:
the invention realizes the real-time monitoring of the action characteristics of the high-voltage switch equipment, and simultaneously evaluates the health service life of the mechanical part of the high-voltage switch equipment, avoids accidents caused by the high-voltage switch equipment, and improves the safety and the stability of a power grid. The equipment maintenance and repair cost is saved, and the power failure loss caused by the mechanical fault of the circuit breaker is reduced.
By adopting the on-line monitoring means of the circuit breaker, the running state of the circuit breaker can be known in real time, the early fault characteristics of the circuit breaker can be found in time, the maintainer intervenes in advance to eliminate the fault, the occurrence of accidents is avoided, and the maintenance cost is saved. The online monitoring of the power equipment is a premise for realizing the predictive maintenance of the equipment, is a key for ensuring the safe and reliable operation of the equipment, and is also a significant supplement and new development of the traditional offline preventive test.
Drawings
Fig. 1 is a block diagram of the structure of an aggregation analysis diagnostic device for the operating characteristics of a high-voltage switchgear according to the present invention;
fig. 2 is a flowchart of an aggregate analysis and diagnosis method for the operating characteristics of the high-voltage switchgear according to the present invention.
The notation in the figure is: 10-giant magnetoresistance displacement sensor, 20-current sensor group, 30-vibration sensor, 40-intelligent acquisition and analysis terminal, 50-big data platform server, 201-first current sensor, 202-second current sensor and 203-third current sensor.
Detailed Description
In order to facilitate understanding of those skilled in the art, the present invention is further described below with reference to the following examples and the accompanying drawings, which are not intended to limit the present invention.
As shown in fig. 1, the aggregation analysis and diagnosis device for the action characteristics of the high-voltage switch equipment comprises a giant magnetoresistance displacement sensor 10, a current sensor group 20, a vibration sensor 30, an intelligent acquisition and analysis terminal 40 and a big data platform server 50, wherein the giant magnetoresistance displacement sensor 10, the current sensor group 20 and the vibration sensor 30 are electrically connected with the intelligent acquisition and analysis terminal 40, and the intelligent acquisition and analysis terminal 40 is connected with the big data platform server 50 through a wireless network; the giant magnetoresistance displacement sensor 10 is used for collecting the displacement of the spring operating mechanism, the current sensor group 20 is used for collecting the current of a switching-off coil, the current of a switching-on coil and the current of an energy storage motor, and the vibration sensor 30 is used for collecting the vibration condition of the mechanism; the intelligent acquisition and analysis terminal 40 is used for acquiring data, processing the data and sending the data to the big data platform server 50, and the data platform server is used for comparing the data acquired in the previous two times to generate an alarm event and pushing the alarm event to the electric power operation and maintenance staff.
The diagnosis device selectively collects the currents of the opening coil and the closing coil and the current of the energy storage motor, carries out digital processing and analysis on the current waveform, is attached with detection of other mechanical characteristics such as contact stroke, over stroke and overshoot of the circuit breaker, completes monitoring on the high-voltage circuit breaker operating mechanism, and utilizes a background massive real-time database to realize state evaluation on the circuit breaker by means of an intelligent method, thereby realizing online monitoring and health diagnosis on the high-voltage circuit breaker.
The current sensor group 20 includes a first current sensor 201, a second current sensor 202 and a third current sensor 203, the first current sensor 201 is used for collecting the current of the opening coil, the second current sensor 202 is used for collecting the current of the closing coil, and the third current sensor 203 is used for collecting the current of the energy storage motor.
As shown in fig. 2, a method for aggregate analysis and diagnosis of operating characteristics of a high-voltage switchgear includes the steps of:
s1, collecting the opening current, the closing current and the energy storage motor current on the high-voltage switch by adopting the current sensor group 20 to obtain current curves of the opening current, the closing current and the energy storage motor current;
s2, collecting current signals of a switching-off coil and a switching-on coil, and collecting displacement and mechanism vibration conditions of a spring operating mechanism of the high-voltage switch by adopting a giant magnetoresistance displacement sensor 10 and a vibration sensor 30 to obtain a mechanical characteristic curve and a mechanism vibration curve;
s3, generating a comtrade file format from the collected current curve, mechanical characteristic curve and mechanism vibration curve, and submitting the comtrade file format to a cloud computing center of the big data platform server 50 through a network;
s4, carrying out the coaxiality comparison of the current curves of the two previous switching-on and switching-off operations by the cloud computing center of the big data platform server 50 through the current curves, and judging the characteristic state; carrying out coaxiality comparison on qualified current curves of the outgoing opening and closing switches through the current curves, and judging the characteristic state; comparing the coaxiality of the current curves of the energy storage motor in the previous two times through the current curve of the energy storage motor, and judging the characteristic state; judging the characteristic state through trend analysis of the mechanical characteristic curve and the mechanical characteristic curves of the equipment in the previous two times; judging the characteristic state through trend analysis of the mechanical characteristic curve and a delivery mechanical characteristic qualified curve of the equipment; judging the characteristic state through the trend analysis of the mechanism vibration curve and the mechanism vibration curves of the previous two times of the equipment;
and S5, diagnosing the health state of the high-voltage switch equipment according to the aggregation analysis, namely forming multi-parameter characteristic event information through the characteristic state of multi-parameter waveform comparison, performing threshold value comparison on the characteristic event information in a high-voltage switch equipment health evaluation library, generating an alarm event, and pushing the alarm event to electric power operation and maintenance staff.
The state characteristics of the circuit breaker are obtained by the current curves of the opening current and the closing current: by extracting time characteristic parameters in a current waveform: the electromagnet movement time t1, the contact action time t2 and the switch auxiliary contact cutting time t3 represent the closing characteristic time, and the state characteristic of the circuit breaker is judged according to the three time characteristic parameters.
Acquiring the state characteristics of the energy storage motor by using a current curve of the current of the energy storage motor: by extracting time characteristic parameters in the current waveform of the energy storage motor: at the time of t1, the energy storage motor receives a power-on command, and the energy storage motor starts to start without load; at the time t2, the motor rotates without load, and the current tends to be stable from the time t 2; at the time of t3, the energy storage motor starts to release energy, the closing spring is pulled to do work, and at t3, the rigidity state of the spring and the lubrication degree of the energy storage shaft are obtained according to the current curve of the energy storage motor current. The criterion of the characteristic points is as follows: the waveform can be clearly divided into 5 stages according to the movement of the core, as shown below.
Stage 1: t is t0-t 1. The coil is energized at time t0 and the electromagnet core begins to move by time t 1. t0 is the time of the breaker opening/closing command, and is the starting point of the breaker opening/closing action timing; t1 is the time when the current and flux in the coil rise enough to drive the core, i.e. the core starts to move. This phase is characterized by an exponential rise in current and a standstill of the core. The time of this phase is related to the control supply voltage and the coil resistance.
And (2) stage: t is t1-t 2. The core moves and the current drops. t2 is the valley point of the control current, which represents that the core has touched the load of the operating machine, thus significantly slowing down or stopping the motion.
And (3) stage: t is t2-t 3. The core stops moving and the current rises exponentially until the contacts start to operate at time t 3.
And (4) stage: t is t3-t 4. The current reaches an approximately steady state in this phase.
And (5) stage: t is t4-t 5. And in the current breaking stage, the auxiliary switch is broken, an arc is generated between the contacts of the auxiliary switch and is elongated, the voltage of the arc is rapidly increased, and the current is rapidly reduced until the arc is extinguished.
According to the waveform analysis, the time characteristic parameters in the waveform correspond to the movement event of the iron core, the electromagnet movement time t1, the contact action time t2 and the switch auxiliary contact cut-off time t3, the closing characteristic time is represented, and the state characteristic of the circuit breaker is judged according to the three time characteristic parameters.
The criterion of the characteristic point is as follows: the waveform can be clearly divided into 4 stages as follows.
Stage 1: t is t0-t 1. The energy storage motor is electrified at the time t0, and the motor starts to rotate at the time t 1. t0 is the time when the energy storage command of the circuit breaker is issued, and is the starting point of energy storage timing of the circuit breaker; t1 is the time when the current is sufficient to drive the motor to rotate, i.e. the motor starts to compress the spring. This phase is characterized by an exponential rise in current and by the absence of rotor rotation. The time of this phase is related to the control supply voltage and the motor resistance.
And (2) stage: t is t1-t 2. The motor rotates the compression spring, the current continuously fluctuates, and t2 is the peak point of the control current, which represents that the motor has finished storing energy, so the current has a significant rise.
And (3) stage: t-t 2-t 3. After the energy storage is finished, the motor idles, no spring resistance exists, and the current drops to a stable value.
The circuit breaker of the spring operating mechanism and the energy storage motor play very important roles, and the realization of the function of the circuit breaker depends on the working state of the energy storage motor to a great extent. When the closing action of the breaker is finished, the energy storage loop is switched on, and the spring starts to work so as to store energy required by opening and closing.
Mechanical characteristic curve: when a main shaft of the circuit breaker rotates, a giant magnetoresistance mounted on the main shaft is driven to rotate, a sensor acquires deflection of a magnetic induction line, change of a contact stroke is obtained by measuring a deflection angle of the magnetic induction line, a stroke time characteristic curve of the circuit breaker is obtained, a sampling interval is obtained by subtracting two adjacent time values, a contact stroke corresponding to the sampling interval is obtained according to the stroke time characteristic curve, and the corresponding contact movement speed is obtained by dividing the stroke by the corresponding sampling interval.
Compared with the prior art, the invention has the following beneficial effects:
the invention realizes the real-time monitoring of the action characteristics of the high-voltage switch equipment, and simultaneously evaluates the health service life of the mechanical part of the high-voltage switch equipment, avoids accidents caused by the high-voltage switch equipment, and improves the safety and the stability of a power grid. The maintenance cost of equipment and the maintenance cost are saved, and the power failure loss caused by the mechanical fault of the circuit breaker is reduced.
By adopting the on-line monitoring means of the circuit breaker, the running state of the circuit breaker can be known in real time, the early fault characteristics of the circuit breaker can be found in time, the maintainer intervenes in advance to eliminate the fault, the occurrence of accidents is avoided, and the maintenance cost is saved. The online monitoring of the power equipment is a premise for realizing the predictive maintenance of the equipment, is a key for ensuring the safe and reliable operation of the equipment, and is also a significant supplement and new development of the traditional offline preventive test.
The present application provides a device and a method for aggregate analysis and diagnosis of operating characteristics of a high voltage switchgear. The description of the specific embodiments is only intended to facilitate the understanding of the method of the present application and its core concepts. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
Claims (6)
1. The aggregation analysis and diagnosis device for the action characteristics of the high-voltage switch equipment is characterized by comprising a giant magnetoresistance displacement sensor (10), a current sensor group (20), a vibration sensor (30), an intelligent acquisition and analysis terminal (40) and a big data platform server (50), wherein the giant magnetoresistance displacement sensor (10), the current sensor group (20) and the vibration sensor (30) are electrically connected with the intelligent acquisition and analysis terminal (40), and the intelligent acquisition and analysis terminal (40) is connected with the big data platform server (50) through a wireless network; the giant magnetoresistance displacement sensor (10) is used for collecting the displacement of the spring operating mechanism, the current sensor group (20) is used for collecting the current of a brake separating coil, the current of a brake closing coil and the current of an energy storage motor, and the vibration sensor (30) is used for collecting the vibration condition of the mechanism; the intelligent acquisition and analysis terminal (40) is used for acquiring data, processing the data and sending the data to the big data platform server (50), and the data platform server is used for comparing the data acquired in the previous two times to generate an alarm event and pushing the alarm event to the electric power operation and maintenance staff.
2. The device for aggregate analysis and diagnosis of action characteristics of high-voltage switchgear according to claim 1, wherein the current sensor group (20) comprises a first current sensor (201), a second current sensor (202) and a third current sensor (203), the first current sensor (201) is used for collecting a switching-off coil current, the second current sensor (202) is used for collecting a switching-on coil current, and the third current sensor (203) is used for collecting an energy storage motor current.
3. An aggregation analysis and diagnosis method for the action characteristics of high-voltage switch equipment is characterized by comprising the following steps:
s1, collecting the opening current, the closing current and the energy storage motor current on the high-voltage switch by adopting a current sensor group (20) to obtain current curves of the opening current, the closing current and the energy storage motor current;
s2, collecting current signals of a switching-off coil and a switching-on coil, and collecting displacement and mechanism vibration conditions of a spring operating mechanism of the high-voltage switch by adopting a giant magnetoresistance displacement sensor (10) and a vibration sensor (30) to obtain a mechanical characteristic curve and a mechanism vibration curve;
s3, generating a comtrade file format by using the collected current curve, mechanical characteristic curve and mechanism vibration curve, and submitting the comtrade file format to a cloud computing center of a big data platform server (50) through a network;
s4, carrying out coaxiality comparison on the switching-on/off current curves of the first two times through the current curves by the cloud computing center of the big data platform server (50), and judging the characteristic state; carrying out coaxiality comparison on qualified current curves of the outgoing opening and closing switches through the current curves, and judging the characteristic state; comparing the coaxiality of the current curves of the energy storage motor in the previous two times through the current curve of the energy storage motor, and judging the characteristic state; judging the characteristic state through trend analysis of the mechanical characteristic curve and the mechanical characteristic curves of the equipment in the previous two times; judging the characteristic state through trend analysis of the mechanical characteristic curve and a delivery mechanical characteristic qualified curve of the equipment; judging the characteristic state through the trend analysis of the mechanism vibration curve and the mechanism vibration curves of the previous two times of the equipment;
and S5, diagnosing the health state of the high-voltage switch equipment according to the aggregation analysis, namely forming multi-parameter characteristic event information through the characteristic state of multi-parameter waveform comparison, performing threshold value comparison on the characteristic event information in a high-voltage switch equipment health evaluation library, generating an alarm event, and pushing the alarm event to electric power operation and maintenance staff.
4. The method for aggregate analysis and diagnosis of the operating characteristics of the high-voltage switchgear according to claim 3, wherein the current curves of the opening current and the closing current are used to obtain the state characteristics of the circuit breaker: by extracting time characteristic parameters in a current waveform: the electromagnet movement time t1, the contact action time t2 and the switch auxiliary contact cutting time t3 represent the closing characteristic time, and the state characteristic of the circuit breaker is judged according to the three time characteristic parameters.
5. The method for aggregate analysis and diagnosis of the operating characteristics of the high-voltage switchgear according to claim 4, wherein the current curve of the current of the energy storage motor obtains the state characteristics of the energy storage motor: by extracting time characteristic parameters in the current waveform of the energy storage motor: at the time of t1, the energy storage motor receives a power-on command, and the energy storage motor starts to start without load; at the time t2, the motor rotates without load, and the current tends to be stable from the time t 2; at the time of t3, the energy storage motor starts to release energy, the closing spring is pulled to do work, and at t3, the rigidity state of the spring and the lubrication degree of the energy storage shaft are obtained according to the current curve of the energy storage motor current.
6. The method for aggregate analysis and diagnosis of the operating characteristics of the high-voltage switchgear according to claim 5, characterized in that the mechanical characteristic curve: when a main shaft of the circuit breaker rotates, a giant magnetoresistance mounted on the main shaft is driven to rotate, a sensor acquires deflection of a magnetic induction line, change of a contact stroke is obtained by measuring a deflection angle of the magnetic induction line, a stroke time characteristic curve of the circuit breaker is obtained, a sampling interval is obtained by subtracting two adjacent time values, a contact stroke corresponding to the sampling interval is obtained according to the stroke time characteristic curve, and the corresponding contact movement speed is obtained by dividing the stroke by the corresponding sampling interval.
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| CN110501637A (en) * | 2019-09-23 | 2019-11-26 | 贵州电网有限责任公司 | A kind of high-tension switch gear acting characteristic polymerization analysis diagnostic device and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110501637A (en) * | 2019-09-23 | 2019-11-26 | 贵州电网有限责任公司 | A kind of high-tension switch gear acting characteristic polymerization analysis diagnostic device and method |
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