CN107807342B - Insulation defect detection device and method for current transformer - Google Patents
Insulation defect detection device and method for current transformer Download PDFInfo
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- CN107807342B CN107807342B CN201711044458.7A CN201711044458A CN107807342B CN 107807342 B CN107807342 B CN 107807342B CN 201711044458 A CN201711044458 A CN 201711044458A CN 107807342 B CN107807342 B CN 107807342B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
- G01R35/02—Testing or calibrating of apparatus covered by the other groups of this subclass of auxiliary devices, e.g. of instrument transformers according to prescribed transformation ratio, phase angle, or wattage rating
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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
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1218—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing using optical methods; using charged particle, e.g. electron, beams or X-rays
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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
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1263—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
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Abstract
The embodiment of the invention provides an insulation defect detection device and method for a current transformer, wherein the insulation defect detection device comprises: the quantum sensor is arranged near the current transformer; a laser generator for emitting laser light to the quantum sensor to excite the quantum sensor; the microwave transceiver is used for transmitting microwave signals to the quantum sensor and receiving the microwave signals fed back by the quantum sensor; the electronic spin resonance spectrometer is used for starting the laser generator and the microwave transceiver and obtaining the distribution characteristics of the electric field and/or the magnetic field intensity of the current transformer in space according to the fed-back microwave signals; and the processor is used for judging whether the current transformer has a defect according to the distribution characteristics of the detected electric field and/or magnetic field intensity and determining the defect type of the defect when judging that the current transformer has the defect. The insulation defect detection device can detect the electric field and magnetic field distribution characteristics of the current transformer and judge the defect type of the current transformer.
Description
Technical Field
The invention relates to a current transformer, in particular to an insulation defect detection device and method for the current transformer.
Background
The electric equipment is an important component element in the power system, and the normal and stable operation of the electric equipment is an important basis for the safe and reliable operation of the power system. However, raw materials, design, manufacturing processes, transportation, installation, etc. cause flaws in insulation problems. If the problems of local overheating, local discharge and the like can not be found in time, the problems of local overheating, local discharge and the like can be generated in the operation process, even the equipment can be caused to fire and explode, and the power grid and personal safety are seriously influenced. At present, state detection means under the running state of electrical equipment such as a sleeve, a transformer and the like mainly comprise infrared temperature measurement and relative dielectric loss factor measurement. Infrared temperature measurement can sensitively find current-induced heat defects and overall voltage-induced heat defects, but serious defects in a small-range concentration type are difficult to find, and the defects can develop rapidly and cause malignant faults; the relative dielectric loss factor measurement needs to modify the equipment end screen, increases the running risk of the equipment, and is difficult to find the serious defects of the small-range concentration type by the measurement technology.
Disclosure of Invention
The invention aims to provide an insulation defect detection device and method for a current transformer, which can detect the distribution characteristics of an electric field and a magnetic field of the current transformer and judge the defect type of the current transformer.
In order to achieve the above object, embodiments of the present invention provide an insulation defect detection apparatus for a current transformer, which may include:
the quantum sensor is arranged near the current transformer;
a laser generator for emitting laser light to the quantum sensor to excite the quantum sensor;
the microwave transceiver is used for transmitting microwave signals to the quantum sensor and receiving the microwave signals fed back by the quantum sensor;
the electronic spin resonance spectrometer is used for starting the laser generator and the microwave transceiver and obtaining the distribution characteristics of the electric field and/or the magnetic field intensity of the current transformer in space according to the fed-back microwave signals;
a processor for:
judging whether the current transformer has a defect according to the distribution characteristics of the detected electric field and/or magnetic field intensity, and determining the defect type of the defect under the condition that the current transformer has the defect.
Alternatively, the quantum sensor may comprise diamond.
Optionally, the insulation defect detecting device may further include an alarm. The processor may also be configured to activate the alarm if the defect type is determined to be a serious defect.
Optionally, the processor may be further configured to: comparing the distribution characteristics with a pre-stored distribution model of the electric field and/or magnetic field intensity in space, and judging whether the current transformer has a defect or not and the defect type of the defect under the condition that the defect exists according to the comparison result.
Alternatively, the distribution model may be a distribution model modeled using a neural network.
Alternatively, the neural network may be a radial basis function neural network.
Optionally, the insulation defect detecting device may further include: and the display is used for displaying at least the defect type of the current transformer.
The embodiment of the invention also provides an insulation defect detection method for detecting the current transformer, which can comprise the following steps:
the laser generator emits laser to a quantum sensor disposed near the current transformer to excite the quantum sensor;
the microwave transceiver transmits microwave signals to the quantum sensor and receives the microwave signals fed back by the quantum sensor;
the electron spin resonance spectrometer obtains the distribution characteristics of the electric field and/or magnetic field intensity of the current transformer in space according to the fed-back microwave signals;
the processor judges whether the current transformer has defects according to the distribution characteristics, and determines the defect type of the defects under the condition that the current transformer has the defects.
Optionally, the determining, by the processor, whether the current transformer has a defect according to the distribution characteristics and determining a defect type of the defect if the current transformer has the defect may include:
comparing the distribution characteristics with a pre-stored distribution model of the electric field and/or magnetic field intensity in space;
judging whether the current transformer has defects or not according to the comparison result, and judging the defect type of the defects under the condition that the defects exist.
Alternatively, the quantum sensor may comprise diamond.
According to the technical scheme, the insulation defect detection device and the insulation defect detection method can detect the electric field and/or magnetic field distribution characteristics of the current transformer, and judge whether the current transformer has defects or not and the defect types under the condition of the defects by comparing the detected electric field and/or magnetic field intensity distribution characteristics with the preset electric field and/or magnetic field intensity distribution characteristics.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain, without limitation, the embodiments of the invention. In the drawings:
fig. 1 is a flowchart of an insulation defect detection method for a current transformer according to an embodiment of the present invention;
fig. 2 is a schematic view of an insulation defect detection apparatus for a current transformer according to an embodiment of the present invention;
fig. 3 is a block diagram of an insulation defect detecting apparatus for a current transformer according to an embodiment of the present invention;
fig. 4 is a block diagram of an insulation defect detecting apparatus for a current transformer according to an embodiment of the present invention; and
fig. 5 is a block diagram of an insulation defect detecting apparatus for a current transformer according to an embodiment of the present invention.
Description of the reference numerals
10. Current transformer 20 and quantum sensor
30. Laser generator 40 and microwave transceiver
50. Electron spin resonance spectrometer 60 and processor
70. Alarm 80 and display
Detailed Description
The following describes specific embodiments of the present invention in detail with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
Fig. 1 is a flowchart of an insulation defect detection method for a current transformer according to an embodiment of the present invention. In the drawings, the insulation defect detection method may include the steps of:
in step S10, a quantum sensor is provided. In the present embodiment, the quantum sensor may be provided on a circular ring having a center axis of the current transformer as a center and a predetermined distance as a radius as shown in fig. 2. In this embodiment, the predetermined distance may be determined according to the accuracy of the electric field and/or magnetic field strength actually required to be detected. In addition, the quantum sensor may be disposed on a different horizontal plane (assuming that the current transformer is disposed vertically).
In step S11, the laser generator emits laser light to the quantum sensor disposed near the current transformer to excite the quantum sensor. In this embodiment, an electron spin resonance spectrometer may be used to control the laser generator to emit laser light to the current transformer to excite the quantum sensor.
In step S12, the microwave transceiver transmits a microwave signal to the quantum sensor and receives a microwave signal fed back by the quantum sensor. In this embodiment, the electron spin resonance spectrometer may be used to control the microwave transceiver to emit microwaves to the quantum sensor and receive microwave signals fed back by the quantum sensor through the microwave transceiver.
In step S13, the electron spin resonance spectrometer obtains the distribution characteristics of the electric field and/or magnetic field intensity of the current transformer in space according to the fed-back microwave signal; in this embodiment, an electron spin resonance spectrometer may be used to determine the electric field and/or magnetic field strength at the location through the microwave frequency of the fed-back signal, and the distribution characteristics of the electric field and/or magnetic field strength of the current transformer in space may be determined in combination with the setting position of the quantum sensor.
In step S14, the processor determines whether the current transformer has a defect according to the distribution characteristics and determines a defect type of the defect if the current transformer has the defect. In this embodiment, the detected distribution characteristics of the electric field and/or magnetic field strength may be compared with a pre-stored spatially distributed model of the electric field and/or magnetic field strength, for example, to determine whether the current transformer is defective under the distribution characteristics of the electric field and/or magnetic field strength. In this embodiment, the distribution model of the electric and/or magnetic field strength may be established by learning a large number of current transformer samples. Still further, the specific defect type of the current transformer can be determined according to a spatially distributed model of the electric field and/or magnetic field strength established through a large number of sample studies. Thus, the working personnel can conveniently make effective measures on the current transformer. In addition, a part of the distribution model of the electric field and/or magnetic field intensity established through a large number of sample learning can be selected as the early warning defect. When the current transformer is determined to have the early warning defect, the current transformer is likely to be problematic in a short time, so that workers can conveniently and timely make early warning, and accidents are avoided. Furthermore, in order to improve the operation efficiency, the above-described distribution model of the electric field and/or the magnetic field intensity established by the large number of sample learning may be, for example, a distribution model modeled using a neural network, and further, the neural network may be an RBF (Radial Basis Function ) neural network.
Fig. 3 is a block diagram of an insulation defect detecting apparatus for a current transformer according to an embodiment of the present invention. In fig. 3, the insulation defect detecting apparatus includes:
the quantum sensor 20 may be disposed near the current transformer 10. In one example, the quantum sensor 20 may be disposed on a circular ring having a center axis of the current transformer 10 as a center and a predetermined distance as a radius as shown in fig. 2. The predetermined distance may be determined based on the accuracy of the actual desired detected electric and/or magnetic field strength. The number of quantum sensors 20 may be determined based on the accuracy of the electric and/or magnetic field strength actually required to be detected. In an embodiment of the present invention, the quantum sensor 20 may include diamond.
A laser generator 30, the laser generator 30 being connected to the electron spin resonance spectrometer 50 for emitting laser light to the quantum sensor 20 to excite the quantum sensor 20.
And a microwave transceiver 40, wherein the microwave transceiver 40 is connected with the electron spin resonance spectrometer 50, and is used for transmitting microwave signals to the quantum sensor 20 and receiving the microwave signals fed back by the quantum sensor, and finally transmitting the fed-back microwave signals to the electron spin resonance spectrometer 50.
An electron spin resonance spectrometer 50, the electron spin resonance spectrometer 50 being connected to the processor 60 for detecting the frequency of the fed back microwave signal, from which the spatial distribution characteristics of the electric and/or magnetic field strength of the current transformer 10 are obtained.
A processor 60 for: the spatially distributed characteristics of the electric field and/or magnetic field strength of the current transformer 10 are received from the electron spin resonance spectrometer 50, and it is determined whether the current transformer 10 is defective or not according to the distributed characteristics of the electric field and/or magnetic field strength and a defect type is determined in case that it is determined that the current transformer 10 is defective.
Upon detection, the electron spin resonance spectrometer 50 controls the activation of the laser generator 30 to emit laser light to the quantum sensor 20. The quantum sensors 20 are disposed on a circular ring having a predetermined distance as a radius around the central axis of the current transformer 10, and the number of the quantum sensors 20 may be, for example, 4, and the radius of the circular ring may be, for example, 1 cm. Those skilled in the art will also appreciate that the number of quantum sensors 20 may be other values and the radius of the circle may be other values, as desired for practical measurement accuracy. The quantum sensor 20 (in this embodiment, the quantum sensor 20 may include diamond.) is polarized by free electrons in a nitrogen-vacancy (NV) color center structure under irradiation of laser light. At this time, the microwave transceiver 40 transmits a microwave signal to the quantum sensor 20. The quantum sensor 20 induces electron spin resonance under the influence of the electric and/or magnetic field of the current transformer 10 and a microwave signal. At this time, the quantum sensor 20 reflects a feedback microwave signal having the same frequency as the self electron spin resonance. The microwave transceiver 40 receives the fed-back microwave signal and transmits the fed-back microwave signal to the electron spin resonance spectrometer 50. The electron spin resonance spectrometer 50 calculates the electric and/or magnetic field strength of the current transformer 10 by detecting the frequency of the fed-back microwave signal. The processor 60 receives the distribution characteristics of the electric field and/or magnetic field intensity from the electron spin resonance spectrometer 50 and determines whether the current transformer 10 is defective or not based on the detected distribution characteristics of the electric field and/or magnetic field intensity and determines the type of defect if the current transformer 10 is determined to be defective.
The quantum sensor 20 is based on quantum precision relative to prior art measurement techniquesThe measurement technique is based on manipulation of single molecules, which is very sensitive to physical characteristics reflected by the internal electronic polarization of the object under test. Thus, the quantum sensor 20 may measure up to 200mV/m (millivolts per meter) for an electric field and up to 10 for a magnetic field -13 T/m (tesla per meter) to obtain a spatially fine distribution model of the electric and/or magnetic field of the device under test while in operation.
The processor 60 may be a general purpose processor, a special purpose processor, a conventional processor, a Digital Signal Processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) circuits, any other type of Integrated Circuit (IC), a state machine, or the like. In this embodiment, the processor 60 may be a quantum detection analysis system. Although the foregoing lists several examples of processors, these examples of processors are not limiting on the technical solution of the present invention, and those skilled in the art will understand that other processors are also applicable.
Fig. 4 is a block diagram of an insulation defect detection apparatus for a current transformer 10 according to an embodiment of the present invention. The insulation defect detecting apparatus for the current transformer 10 shown in fig. 3 is different in that the insulation defect detecting apparatus may further include: an alarm 70, the alarm 70 being coupled to the processor 20 and being operable to be activated to alert personnel. The processor 60 may also be used to activate the alarm 70 in the event that it is determined that the current transformer 10 is of a serious defect. For example, when the processor 60 determines that the current transformer 10 has a defect, it further determines the defect type of the current transformer 10, and determines whether the defect type belongs to a serious defect. In case that the defect type is judged to be a serious defect, the alarm 70 is activated to inform the worker of making a corresponding measure, thereby avoiding occurrence of an accident. The alarm 70 may be an LED lamp, a buzzer, a voice device, etc., and those skilled in the art will recognize that other alarms are suitable.
Fig. 5 is an insulation defect detection apparatus for a current transformer 10 according to an embodiment of the present invention. The insulation defect detecting device for the current transformer 10 shown in fig. 4 is different in that the insulation defect detecting device may further include: a display 80, the display 80 being connectable to the processor 60 and being operable to display at least a type of defect of the current transformer 10. For example, when the processor 60 detects that the current transformer 10 is defective, the type of defect of the current transformer 10 is further detected. At this time, the processor 60 prompts the worker for the type of the defect through the display 80 to allow the worker to take a measure in advance. When the processor 60 determines that the defect type belongs to a serious defect, the processor 60 can prompt a worker to take measures in time through the display 80 on the one hand; on the other hand, the staff may also be prompted by means of an alarm 70. In this way, accidents caused by negligence of staff are avoided through the two alarms. The display 80 may be an LED, OLED display, or the like, and those skilled in the art will recognize that other displays may be suitable.
In one embodiment of the present invention, based on the insulation defect detection apparatus for the current transformer 10 as shown in fig. 5, the processor 60 may be further configured to: comparing the detected distribution characteristics of the electric field and/or magnetic field intensity with a distribution model of the electric field and/or magnetic field intensity in space, which is established through a large number of sample study, and judging whether the current transformer 10 has defects under the distribution characteristics of the electric field and/or magnetic field intensity according to the comparison result. And further comparing the distribution characteristics of the detected electric field and/or magnetic field intensity with a spatial distribution model of the electric field and/or magnetic field established through a large number of sample studies when the defects are detected, so as to identify the defect type of the defects.
In one embodiment of the present invention, the distribution model may be modeled using a neural network based on the insulation defect detection device for the current transformer 10 as shown in fig. 5, further, the neural network may be an RBF (Radial Basis Function ) neural network. Methods of modeling a distribution model using neural networks may be known to those skilled in the art, the details of which are not set forth herein.
The insulation defect detecting device for the current transformer 10 shown in fig. 1 is performed with the insulation defect detecting device for the current transformer 10 shown in fig. 5. During operation, the quantum sensor 20 may be disposed in proximity to the current transformer 10. In one example, the quantum sensor 20 may be disposed on a circular ring having a center axis of the current transformer 10 as a center and a predetermined distance as a radius as shown in fig. 2. The number of quantum sensors 20 may be, for example, 6 and the radius of the circle may be, for example, 1 cm. Those skilled in the art will also appreciate that the number of quantum sensors 20 may be other values and the radius of the circle may be other values, as desired for practical measurement accuracy. The quantum sensor 20 (in this embodiment, the quantum sensor 20 may include diamond.) polarizes electrons in a nitrogen-vacancy (NV) color center structure under irradiation of laser light. The electron spin resonance spectrometer 50 controls the microwave transceiver 40 to emit microwave signals to the quantum sensor 20. The quantum sensor 20 causes electron spin resonance under the electric and/or magnetic field of the current transformer 10 and the microwave signal and reflects the microwave signal having the same frequency as the resonance frequency. The microwave transceiver 40 receives the fed-back microwave signal and transmits the fed-back microwave signal to the electron spin resonance spectrometer 50. The electron spin resonance spectrometer 50 calculates the electric and/or magnetic field intensity of the current transformer 10 by detecting the frequency of the fed-back microwave signal and determines the distribution characteristics of the electric and/or magnetic field intensity by the set position of each quantum sensor 20. Modeling by RBF neural network in processor 60 creates a spatially distributed model of the electric and/or magnetic field strength of current transformer 10 in a variety of defect case states through a number of sample studies. The processor 60 compares the received spatial distribution characteristics of the electric field and/or magnetic field intensity of the actual current transformer 10 with the spatial distribution model of the electric field and/or magnetic field intensity established through a large number of sample studies, and determines whether the current transformer 10 has defects according to the comparison result. If the current transformer 10 is defective, the processor 60 notifies the operator by activating an alarm 70. In addition, the processor 60 may further compare the spatial distribution characteristics of the electric field and/or magnetic field strength of the current transformer 10 detected with the spatial distribution model of the electric field and/or magnetic field strength established through a plurality of sample studies, so as to determine the type of the defect. The processor 60 displays the presence of a defect in the current transformer 10 and the corresponding type of defect via the display 80. The operator may also pre-select one or more of the spatial distribution models of the electric field and/or magnetic field strengths of the various defects established through the plurality of sample studies as serious defects, and if the defects belong to the serious defects, the processor 60 prompts the operator that the current transformer 10 has the serious defects through the display 80. At the same time, the processor 60 activates the alarm 80 to notify the worker, thereby avoiding accidents due to the negligence of the worker.
Still further, the operator may set pre-warning defects in a spatially distributed model of the electric and/or magnetic field strengths of the various defects established by the large number of sample studies, based on the nature of the occurrence of the serious defect, which indicates that the current transformer 10 is likely to be about to have the serious defect. Therefore, when the processor 60 compares the defect of the current transformer 10 as the early warning defect, the early warning can be made to the staff through the display 80, so that the accident is avoided in advance.
Through the technical scheme, the insulation defect detection device and method for the current transformer provided by the invention have the following advantages:
1. and measuring the current transformer by using a quantum sensor based on a quantum precision measurement technology. The problem that the whole state of the current transformer can only be measured in the prior art is solved by comparing the spatial distribution model of the electric field and/or magnetic field intensity established through a large number of sample learning with the spatial distribution characteristics of the detected electric field and/or magnetic field intensity of the current transformer, and the detection of the local small-range defects of the current transformer is realized.
2. Through setting up early warning defect and serious defect, when detecting early warning defect, can instruct the staff to make preparation in advance, avoided the emergence of accident. When serious defects are detected, workers can be timely prompted, and further deterioration of accidents is avoided.
3. The specific position of the defect of the current transformer 10 can be positioned by detecting the current transformer 10 in a local small range, so that the current transformer 10 is convenient to maintain.
The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the embodiments of the present invention are not limited to the specific details of the foregoing embodiments, and various simple modifications may be made to the technical solutions of the embodiments of the present invention within the scope of the technical concept of the embodiments of the present invention, and all the simple modifications belong to the protection scope of the embodiments of the present invention.
In addition, the specific features described in the above embodiments may be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the various possible combinations of embodiments of the invention are not described in detail.
In addition, any combination of the various embodiments of the present invention may be made between the various embodiments, and should also be regarded as disclosed in the embodiments of the present invention as long as it does not deviate from the idea of the embodiments of the present invention.
Claims (3)
1. A method for detecting an insulation defect of a current transformer, characterized in that an insulation defect detection device comprises:
a quantum sensor disposed in the vicinity of the current transformer;
a laser generator for emitting laser light to the quantum sensor to excite the quantum sensor;
the microwave transceiver is used for transmitting microwave signals to the quantum sensor and receiving the microwave signals fed back by the quantum sensor;
the electronic spin resonance spectrometer is used for starting the laser generator and the microwave transceiver and obtaining the distribution characteristics of the electric field and/or magnetic field intensity of the current transformer in space according to the fed-back microwave signals;
the processor is used for judging whether the current transformer has a defect according to the distribution characteristics and determining the defect type of the defect under the condition that the current transformer has the defect;
the method comprises the following steps:
a laser generator emits laser light to a quantum sensor disposed near the current transformer to excite the quantum sensor;
the microwave transceiver transmits microwave signals to the quantum sensor and receives the microwave signals fed back by the quantum sensor;
the electron spin resonance spectrometer obtains the distribution characteristics of the electric field and/or magnetic field intensity of the current transformer in space according to the fed-back microwave signals;
and the processor judges whether the current transformer has a defect according to the distribution characteristics and determines the defect type of the defect under the condition that the current transformer has the defect.
2. The method of claim 1, wherein the processor determining whether the current transformer is defective based on the distribution characteristics and determining a defect type of the defect if the current transformer is determined to be defective comprises:
comparing the distribution characteristics with a pre-stored distribution model of electric field and/or magnetic field intensity in space;
judging whether the current transformer has defects or not and judging the defect type of the defects under the condition that the defects exist according to the comparison result.
3. The method of claim 1, wherein the quantum sensor comprises diamond.
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| CN105158709B (en) * | 2015-08-05 | 2017-12-22 | 北京航空航天大学 | One kind is based on embedded NV‑The magnetic field measuring device of colour center diamond |
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