CN110823863A - Method, device and equipment for detecting algae on surface of insulating material - Google Patents
Method, device and equipment for detecting algae on surface of insulating material Download PDFInfo
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- CN110823863A CN110823863A CN201911052804.5A CN201911052804A CN110823863A CN 110823863 A CN110823863 A CN 110823863A CN 201911052804 A CN201911052804 A CN 201911052804A CN 110823863 A CN110823863 A CN 110823863A
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- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/71—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light thermally excited
Abstract
The invention discloses a detection method of algae on the surface of an insulating material, which comprises the following steps: acting laser pulses with preset power density on an actually measured insulating material, and collecting spectral data of the actually measured insulating material; comparing the spectral data of the actually measured insulating material through a preset standard spectral database, and judging whether the surface of the actually measured insulating material is covered with algae or not; and when the measured insulating material surface is covered with algae, analyzing the species and the density of the algae on the measured insulating material surface. The invention also discloses a device and equipment for detecting the algae on the surface of the insulating material, which can quickly and accurately detect the type and density of the algae covered by the actually measured insulating material by acquiring the spectral data of the actually measured insulating material, and provide a foundation for maintaining the safety and stability of the power equipment.
Description
Technical Field
The invention relates to the field of spectral analysis methods, in particular to a method, a device and equipment for detecting algae on the surface of an insulating material.
Background
In the transmission line, the insulator plays the dual role of mechanical connection and electrical insulation between a wire and an iron tower. In practical application, the insulator is influenced by emissions of factories, traffic, agriculture, mines, life and the like, natural dust falls off and the like during operation, and thus, the surface of the insulator gradually accumulates fouling substances. Especially in forests and mountains in warm and humid areas, microbial spores float in the atmosphere, and when the environment is proper, the spores are easy to breed on the surface of the insulator and gradually become large-area algae, moss or lichen. Microorganisms such as algae grow on the surface of the composite insulating material serving as power transmission and transformation equipment, and influence the electrical property, mechanical property, hydrophobic property and physical and chemical properties of the composite insulating material, so that the electrical system is threatened to operate stably, safely and reliably. In a humid environment, pollution flashover discharge of insulator materials can occur, so that pollution flashover accidents occur, and huge losses are brought to economic development and life of people.
In the prior art, parameters of algae coverage area proportion and unit area growth thickness are represented by using a visual inspection method or an image shooting analysis method, or the detection of algae species and density is realized by using a traditional detection method such as an equivalent salt deposit density method, a leakage current method and the like. However, in the process of implementing the invention, the inventor finds that the prior art has at least the following problems: because the pollution condition on the surface of the insulator is complex, certain errors may exist in the image shooting analysis method for judging the pollution components through the pollution colors; the traditional detection method has the defects of long detection period, manpower and material resource consumption and the like. Therefore, a technical method capable of directly identifying the algae type on the surface of the insulator and representing the accurate distribution of the algae type is urgently needed.
Disclosure of Invention
The embodiment of the invention aims to provide a method, a device and equipment for detecting algae on the surface of an insulating material, which can quickly and accurately detect the type and density of algae covered by an actually measured insulating material by acquiring spectral data of the actually measured insulating material, and provide a basis for maintaining the safety and stability of power equipment.
In order to achieve the above object, an embodiment of the present invention provides a method for detecting algae on the surface of an insulating material, including:
acting laser pulses with preset power density on an actually measured insulating material, and collecting spectral data of the actually measured insulating material;
comparing the spectral data of the actually measured insulating material through a preset standard spectral database, and judging whether the surface of the actually measured insulating material is covered with algae or not;
and when the measured insulating material surface is covered with algae, analyzing the species and the density of the algae on the measured insulating material surface.
As an improvement of the above scheme, the step of establishing the standard spectrum database comprises the following steps:
obtaining an uncovered algae insulating material and a plurality of covered algae insulating materials; wherein the species and density of algae covered on the surface of each algae-covered insulating material are known and are different from each other;
acting the laser pulse with the preset power density on each insulating material, and collecting the spectral data of each insulating material;
and training the spectral data of each insulating material to obtain the standard spectral database.
As an improvement of the above solution, the training of the spectrum data of each of the insulating materials to obtain the standard spectrum database includes:
determining characteristic element spectral line data corresponding to each of the covered algae insulation materials based on a NIST database;
importing the corresponding relation between each characteristic element spectral line data and the corresponding algae species and density of the covered algae insulating material into a preset fitting model for fitting so as to obtain the standard spectral database through training; the characteristic element spectral line data comprise characteristic element types, spectral line intensities of characteristic elements and spectral line intensity ratios of different characteristic elements.
As an improvement of the above solution, the determining the characteristic element spectral line data corresponding to each of the covered algae insulating materials based on the NIST database specifically includes:
comparing the spectral data of each of the covered algae insulation materials with the spectral data of the uncovered algae insulation material for the same class of insulation material to determine peaks in the spectral data of the covered algae insulation material;
matching the peaks in the spectral data with the elemental spectral line information in the NIST database to determine characteristic elemental spectral line data corresponding to each of the coated algae insulation.
As an improvement of the above scheme, the preset fitting model includes, but is not limited to, a univariate fitting model, a multivariate fitting model, and a random forest fitting model.
As an improvement of the above scheme, the method for collecting the spectrum data of the actually measured insulating material by applying the laser pulse with the preset power density to the actually measured insulating material specifically includes:
acquiring a region with a preset shape and a preset size on the surface of the actually measured insulating material as an action region of laser pulse;
bombarding a plurality of uniformly distributed action points in the action area by using the laser pulse with the preset power density to obtain original spectrum data of the actually measured insulating material;
and preprocessing the original spectrum data, and removing the interference of background spectrum data to obtain the spectrum data of the actually measured insulating material.
The embodiment of the invention also provides a detection device for the algae on the surface of the insulating material, which comprises an acquisition module, a judgment module and an analysis module;
the acquisition module is used for acting on the actually measured insulating material by using a laser pulse with preset power density to acquire spectral data of the actually measured insulating material;
the judging module is used for comparing the spectral data of the actually measured insulating material through a preset standard spectral database and judging whether the surface of the actually measured insulating material is covered with algae or not;
the analysis module is used for analyzing the species and the density of algae on the surface of the actually measured insulating material when the covered algae of the actually measured insulating material.
The embodiment of the invention also provides equipment for detecting the algae on the surface of the insulating material, which is characterized by comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to realize the method for detecting the algae on the surface of the insulating material.
Compared with the prior art, the method, the device and the equipment for detecting the algae on the surface of the insulating material disclosed by the invention have the advantages that the spectral data of the actually measured insulating material surface is obtained through the laser-induced breakdown spectroscopy technology and is analyzed through the preset standard spectral database, so that whether the actually measured insulating material surface is covered with the algae or not is judged, and the type and the density of the covered algae are obtained. The analysis efficiency of the condition that the insulating material covers the algae can be improved, the type and the density of the actually measured insulating material covering the algae can be detected quickly and accurately, and a foundation is provided for maintaining the safety and the stability of the power equipment.
Drawings
FIG. 1 is a schematic flow chart of a method for detecting algae on the surface of an insulating material according to an embodiment of the present invention;
FIG. 2 is a schematic flowchart illustrating steps of establishing a standard spectrum database in a method for detecting algae on the surface of an insulating material according to an embodiment of the present invention;
FIGS. 3(a) and 3(b) are graphs of spectral data of covered algae silicone rubber and uncovered algae silicone rubber at different wavelengths in a method for detecting algae on the surface of an insulating material according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an apparatus for detecting algae on the surface of an insulating material according to a second embodiment of the present invention;
fig. 5 is a schematic structural diagram of an apparatus for detecting algae on the surface of an insulating material according to a third embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Referring to fig. 1, a schematic flow chart of a method for detecting algae on the surface of an insulating material according to an embodiment of the present invention is shown. In a first embodiment of the present invention, a method for detecting algae on a surface of an insulating material is performed through steps S11 to S13:
s11, acting laser pulses with preset power density on the actually measured insulating material, and collecting spectral data of the actually measured insulating material;
acquiring an actually measured insulating material needing to be subjected to detection of covered algae condition, wherein the insulating material is classified according to manufacturing materials and can be an electric porcelain insulator, a glass insulator, a composite insulator and the like, and the covered algae condition indicates whether the surface of the insulating material is covered with algae or not and the type and density of the algae if the surface is covered with the algae. By utilizing a laser-induced breakdown spectroscopy technology, generating laser pulses with extremely high power density, acting the laser pulses on the measured insulating material, generating plasma on the surface of the measured insulating material through induction, and collecting plasma spectral data to obtain spectral data of the measured insulating material.
Preferably, step S11 is specifically executed by steps S111 to S113:
s111, acquiring a region with a preset shape and a preset size on the surface of the actually measured insulating material, and taking the region as an action region of laser pulse;
specifically, a region with a certain shape and size is preset on the measured insulating material as an active region of the laser pulse, for example, a square region of 5cm × 5cm is selected on the measured insulating material as the active region, so as to perform laser pulse induced breakdown on the active region.
And S112, bombarding a plurality of uniformly distributed action points in the action area by using the laser pulse with the preset power density to obtain the original spectrum data of the actually measured insulating material.
For example, when a square area of 5cm × 5cm is selected as the action area on the actually measured insulating material, four vertices and a midpoint of the square area may be selected as the action points, the action points are bombarded by using the laser pulse with the preset power density, plasma is induced, and plasma spectrum data is collected, that is, original spectrum data of the actually measured insulating material is obtained.
It can be understood that the above mentioned selection of the action region and the action point of the laser pulse is only an example, in practical applications, the action region and the action point may be set according to the shape and size of the selected actually measured insulating material, the manufacturing material, and other factors, for example, a circle with a diameter of 5cm or a rectangle with a suitable size may be selected as the action region of the laser pulse, and the beneficial effects obtained by the present invention are not affected.
S113, preprocessing the original spectrum data, and removing interference of background spectrum data to obtain spectrum data of the actually measured insulating material.
And collecting background spectrum data in the original spectrum data, and removing the background spectrum data through software such as matlab and the like to obtain the spectrum data of the actually measured insulating material.
Preferably, the collection of the spectral data of the actually measured insulating material can be realized by pre-constructing a laser induced breakdown spectroscopy device, namely a remote LIBS device. The laser induced breakdown spectroscopy device comprises a laser, a light path system, a controller, a spectrometer and the like, and laser pulses with the preset power density meeting requirements can be generated by selecting proper laser energy and adjusting proper light receiving angle and spectrometer delay time, so that spectral data with high signal-to-noise ratio and signal-to-back ratio can be obtained. In practical application, the laser energy, the light receiving angle and the spectrometer delay time may be specifically set according to the actual condition of the actually measured insulating material to obtain the optimal spectral data, which is not specifically limited herein.
S12, comparing the spectral data of the actually measured insulating material through a preset standard spectral database, and judging whether the surface of the actually measured insulating material is covered with algae or not;
and S13, when the surfaces of the measured insulation materials are covered with algae, analyzing the types and the densities of the algae on the surfaces of the measured insulation materials.
One or more standard spectral databases may be constructed in advance according to different insulating materials to store the corresponding relationship between the spectral data of a plurality of insulating materials covering algae and the species and density of algae covered on the surface thereof. It is understood that the standard spectrum database further stores the corresponding spectrum data of the insulation material without covering algae, so that when the spectrum data of the measured insulation material is collected, whether the surface of the measured insulation material is covered with algae can be judged by comparing the spectrum data with the standard spectrum database. And when the fact that the surface of the actually measured insulating material is covered with algae is judged, the type and the density of the algae covered on the surface of the actually measured insulating material are further analyzed and obtained through the standard spectrum database.
Further, referring to fig. 2, a flow chart of steps for establishing a standard spectrum database in the method for detecting algae on the surface of an insulating material according to an embodiment of the present invention includes steps S21 to S23:
s21, obtaining uncovered algae insulating materials and a plurality of covered algae insulating materials; wherein the species and density of algae covered on the surface of each algae-covered insulating material are known and are different from each other;
to construct the standard spectral data, it is trained with a large number of known algae-covered condition insulating materials as training data sets to build the standard spectral database. Wherein, the algae covering condition indicates whether the surface of the insulating material is covered with algae or not, and if so, the type and density of the algae, and in the training data set, the type and density of the algae covered on the surface of the insulating material covered with the algae are known, so that the establishment of a standard database is carried out.
It should be noted that the standard spectrum database may be divided according to specific manufacturing materials of the insulating material, so as to construct a plurality of standard spectrum databases corresponding to different types of insulating materials, and when analyzing the algae covering condition of the actually measured insulating material, the corresponding standard spectrum database is selected as needed; and a standard spectrum database can be constructed, the corresponding relation between the spectrum data of the insulating material and the algae covering condition on the surface of the insulating material under the condition of storing different types of insulating materials is stored, and when the algae covering condition of the insulating material is actually measured, the analysis and judgment are automatically carried out corresponding to the different types of insulating materials, so that the beneficial effects obtained by the invention are not influenced.
S22, acting the laser pulse with the preset power density on each insulating material, and collecting the spectral data of each insulating material;
similarly, in the same process as the process of analyzing and detecting the algae covered condition of the actually measured insulating material, when the standard spectrum database is established, the laser-induced breakdown spectroscopy equipment still needs to be established by using the laser-induced breakdown spectroscopy technology, and the laser pulse with the extremely high power density and the preset power density is generated by selecting the appropriate laser energy and adjusting the appropriate light receiving angle and the spectrometer delay time. Selecting a region with a preset shape and a preset size on the surface of each insulating material as an action region of laser pulse; bombarding a plurality of uniformly distributed action points in the action area by using the laser pulse with the preset power density, inducing to generate plasma, collecting the spectral data of the plasma, and obtaining the spectral data with higher signal-to-noise ratio and signal-to-back ratio of each insulating material by removing background spectral data and other operations.
And S23, training the spectrum data of each insulating material to obtain the standard spectrum database.
Specifically, the standard spectral database is constructed by acquiring uncovered algae insulation and a number of covered algae insulations of known species and density, collecting spectral data for each of the insulations, and training.
Preferably, the step S23 of training the spectrum data of each of the insulating materials to obtain the standard spectrum database includes steps S231 to S232:
s231, determining characteristic element spectral line data corresponding to each covered algae insulating material based on an NIST database; the characteristic element spectral line data comprise characteristic element types, spectral line intensities of characteristic elements and spectral line intensity ratios of different characteristic elements.
Preferably, the spectral data of each said covered algae insulation is compared to the spectral data of said uncovered algae insulation for the same class of insulation to determine peaks in the spectral data of each said covered algae insulation;
matching the peaks in the spectral data with the elemental spectral line information in the NIST database to determine characteristic elemental spectral line data corresponding to each of the coated algae insulation.
Specifically, by comparing the spectral data of each covered algae insulating material with the spectral data of the uncovered algae insulating material, the peak in the spectral data of each covered algae insulating material is determined and matched with the element spectral line information in the NIST database, so that a suitable analysis element is selected as the characteristic element of the covered algae insulating material. The characteristic element species include, but are not limited to, magnesium, calcium, aluminum, sodium, copper, and iron. The characteristic element of each covered algae insulating material can be one or a plurality of, and is selected by determining the corresponding spectral data peak according to the difference between the characteristic element and the uncovered algae insulating material.
Taking a silicone rubber insulating material as an example, spectral data of the insulating material covered with the algae silicone rubber and the insulating material not covered with the algae silicone rubber are obtained by the method under the same condition, and referring to fig. 3(a) and fig. 3(b), the spectral data of the covered algae silicone rubber and the insulating material not covered with the algae silicone rubber under different wavelengths in the detection method for algae on the surface of the insulating material provided by the embodiment of the invention are shown. And performing superposition comparison on the spectral data of the two to determine the wave peak of the spectral data of the covered algae silicone rubber, and matching the wave peak in the spectral data with the element spectral line information in the NIST database to determine the characteristic element spectral line data corresponding to the covered algae silicone rubber. Referring to fig. 3, it can be seen that the difference between the spectral data of the algainizing silicone rubber and the spectral data of the non-algainizing silicone rubber is large, wherein the spectral line intensity of Mg and Fe elements in the covered algae part is higher than that in the uncovered algae part, so that the characteristic element types in the covered algae on the surface of the silicone rubber insulating material are determined to be Mg and Fe.
After the characteristic elements are determined, the spectral line intensities of the characteristic elements and the spectral line intensity ratios of different characteristic elements can be further determined to serve as the characteristic element spectral line data of the covered algae insulating material, so that the corresponding relation can be conveniently established with the algae species and the density of the covered algae insulating material, and a precise and complete standard spectral database can be established.
It is understood that the above is only taken as an example of the silicone rubber insulating material, and in practical application, the above method is also applicable to other types of insulating materials, such as glass insulating materials, electric porcelain insulating materials and the like, without affecting the beneficial effects achieved by the present invention.
And S232, importing the corresponding relation between each characteristic element spectral line data and the corresponding alga type and density of the covering alga insulating material into a preset fitting model for fitting so as to train and obtain the standard spectral database.
Specifically, the characteristic element spectral line data is used as an independent variable, the corresponding alga type and density of the covering alga insulating material are used as dependent variables, and fitting is carried out through a corresponding fitting model, so that the standard spectral database is obtained through training. The preset fitting model comprises but is not limited to a univariate fitting model, a multivariate fitting model and a random forest fitting model.
The embodiment of the invention provides a method for detecting algae on the surface of an insulating material, which comprises the steps of obtaining spectral data of the surface of an actually-measured insulating material through a laser-induced breakdown spectroscopy technology, and analyzing the spectral data through a preset standard spectral database, so as to judge whether the surface of the actually-measured insulating material is covered with the algae, and obtain the type and the density of the covered algae. The analysis efficiency of the condition that the insulating material covers the algae can be improved, the type and the density of the actually measured insulating material covering the algae can be detected quickly and accurately, and a foundation is provided for maintaining the safety and the stability of the power equipment.
Example two
Fig. 4 is a schematic structural diagram of a detection apparatus for detecting algae on the surface of an insulating material according to a second embodiment of the present invention. The second detection device 20 for detecting algae on the surface of the insulating material, provided by the embodiment of the invention, comprises an acquisition module 21, a judgment module 22 and an analysis module 23;
the acquisition module 21 is configured to act on an actually measured insulating material with a laser pulse of a preset power density, and acquire spectral data of the actually measured insulating material;
the judging module 22 is configured to compare the spectral data of the actually measured insulating material with a preset standard spectral database, and judge whether the surface of the actually measured insulating material is covered with algae;
the analysis module 23 is configured to analyze the species and density of algae on the surface of the measured insulation material when the insulation material covers the algae.
It should be noted that, the detection apparatus for detecting algae on the surface of an insulating material provided in the second embodiment of the present invention is used for executing all the process steps of the detection method for detecting algae on the surface of an insulating material provided in the first embodiment, and the working principles and beneficial effects of the two are in one-to-one correspondence, so that details are not repeated.
The second embodiment of the invention provides a detection device for algae on the surface of an insulating material, which is characterized in that a collection module acquires spectral data of the actually measured insulating material surface through a laser-induced breakdown spectroscopy technology, and a judgment module compares the spectral data with a preset standard spectral database so as to judge whether the actually measured insulating material surface is covered with algae or not, and an analysis module 23 outputs the type and density of the covered algae on the actually measured insulating material surface. The device can improve the analysis efficiency to the insulating material covers the alga condition, detects fast accurately the kind and the density that actually measure insulating material covers the alga provide the basis for maintaining power equipment's safety and stability.
EXAMPLE III
Fig. 5 is a schematic structural diagram of a detection apparatus for detecting algae on the surface of an insulating material according to a third embodiment of the present invention. The third embodiment of the present invention provides a detection apparatus 30 for algae on the surface of an insulating material, which includes a processor 31, a memory 32, and a computer program stored in the memory and configured to be executed by the processor, such as a method for constructing the standard spectrum database. The processor, when executing the computer program, implements the steps in the above-described method embodiment for constructing the standard spectral database, such as steps S21 to S23 shown in fig. 2. Alternatively, the processor implements the functions of the modules in the above embodiments of the apparatus when executing the computer program, for example, the apparatus for detecting algae on the surface of an insulating material according to the second embodiment.
Illustratively, the computer program may be divided into one or more modules, which are stored in the memory 32 and executed by the processor 31 to accomplish the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program in the detection apparatus 30 for algae on the surface of the insulation material. For example, the computer program may be divided into the acquisition module 21, the determination module 22 and the analysis module 23, and the specific functions of each module are as follows:
the acquisition module 21 is configured to act on an actually measured insulating material with a laser pulse of a preset power density, and acquire spectral data of the actually measured insulating material;
the judging module 22 is configured to compare the spectral data of the actually measured insulating material with a preset standard spectral database, and judge whether the surface of the actually measured insulating material is covered with algae;
the analysis module 23 is configured to analyze the species and density of algae on the surface of the measured insulation material when the insulation material covers the algae.
The detection device 30 for algae on the surface of the insulating material can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The detection device 30 for algae on the surface of the insulating material can include, but is not limited to, a processor 31 and a memory 32. It will be understood by those skilled in the art that the schematic illustration is merely an example of the detecting device 30 for algae on the surface of an insulating material, and does not constitute a limitation of the detecting device 30 for algae on the surface of an insulating material, and may include more or less components than those illustrated, or some components in combination, or different components, for example, the detecting device 30 for algae on the surface of an insulating material may further include input and output devices, network access devices, buses, and the like.
The Processor 31 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, and the processor 31 is the control center of the apparatus 30 for detecting algae on the surface of the insulation material, and various interfaces and lines are used to connect the various parts of the apparatus 30 for detecting algae on the surface of the insulation material.
The memory 32 may be used to store the computer programs and/or modules, and the processor may implement the various functions of the apparatus 30 for detecting algae on the surface of an insulating material by running or executing the computer programs and/or modules stored in the memory and invoking the data stored in the memory. The memory 32 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 32 may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein, the integrated module of the detection device 30 for algae on the surface of the insulating material can be stored in a computer readable storage medium if the module is realized in the form of a software functional unit and sold or used as a separate product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc.
It should be noted that the above-described embodiments of the detection apparatus for detecting algae on the surface of an insulating material are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (8)
1. A method for detecting algae on the surface of an insulating material is characterized by comprising the following steps:
acting laser pulses with preset power density on an actually measured insulating material, and collecting spectral data of the actually measured insulating material;
comparing the spectral data of the actually measured insulating material through a preset standard spectral database, and judging whether the surface of the actually measured insulating material is covered with algae or not;
and when the measured insulating material surface is covered with algae, analyzing the species and the density of the algae on the measured insulating material surface.
2. The method for detecting algae on the surface of the insulating material according to claim 1, wherein the step of establishing the standard spectrum database comprises the steps of:
obtaining an uncovered algae insulating material and a plurality of covered algae insulating materials; wherein the species and density of algae covered on the surface of each algae-covered insulating material are known and are different from each other;
acting the laser pulse with the preset power density on each insulating material, and collecting the spectral data of each insulating material;
and training the spectral data of each insulating material to obtain the standard spectral database.
3. The method according to claim 2, wherein the training of the spectral data of each of the insulating materials to obtain the standard spectral database comprises:
determining characteristic element spectral line data corresponding to each of the covered algae insulation materials based on a NIST database; the characteristic element spectral line data comprise characteristic element types, spectral line intensities of characteristic elements and spectral line intensity ratios of different characteristic elements;
and importing the corresponding relation between each characteristic element spectral line data and the corresponding algae species and density of the covered algae insulating material into a preset fitting model for fitting so as to train and obtain the standard spectral database.
4. The method according to claim 3, wherein the determining the characteristic element spectral line data corresponding to each of the covered algae insulation materials based on the NIST database specifically comprises:
comparing the spectral data of each of the covered algae insulation materials with the spectral data of the uncovered algae insulation material for the same class of insulation material to determine peaks in the spectral data of the covered algae insulation material;
matching the peaks in the spectral data with the elemental spectral line information in the NIST database to determine characteristic elemental spectral line data corresponding to each of the coated algae insulation.
5. The method of claim 3, wherein the predetermined fitting model includes but is not limited to a univariate fitting model, a multivariate fitting model, and a random forest fitting model.
6. The method according to claim 1, wherein the step of collecting the spectral data of the measured insulation material by applying the laser pulse with the predetermined power density to the measured insulation material comprises:
acquiring a region with a preset shape and a preset size on the surface of the actually measured insulating material as an action region of laser pulse;
bombarding a plurality of uniformly distributed action points in the action area by using the laser pulse with the preset power density to obtain original spectrum data of the actually measured insulating material;
and preprocessing the original spectrum data, and removing the interference of background spectrum data to obtain the spectrum data of the actually measured insulating material.
7. The device for detecting the algae on the surface of the insulating material is characterized by comprising an acquisition module, an analysis module and an output module;
the acquisition module is used for acting on the actually measured insulating material by using a laser pulse with preset power density to acquire spectral data of the actually measured insulating material;
the judging module is used for comparing the spectral data of the actually measured insulating material through a preset standard spectral database and judging whether the surface of the actually measured insulating material is covered with algae or not;
the analysis module is used for analyzing the species and the density of algae on the surface of the actually measured insulating material when the covered algae of the actually measured insulating material.
8. An apparatus for detecting algae on the surface of an insulating material, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the method for detecting algae on the surface of an insulating material according to any one of claims 1 to 6.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911052804.5A CN110823863A (en) | 2019-10-31 | 2019-10-31 | Method, device and equipment for detecting algae on surface of insulating material |
| PCT/CN2020/107545 WO2021082594A1 (en) | 2019-10-31 | 2020-08-06 | Method, apparatus and device for testing algae on surface of insulating material |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911052804.5A CN110823863A (en) | 2019-10-31 | 2019-10-31 | Method, device and equipment for detecting algae on surface of insulating material |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110823863A true CN110823863A (en) | 2020-02-21 |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111986201A (en) * | 2020-09-28 | 2020-11-24 | 南方电网科学研究院有限责任公司 | Method and device for measuring and calculating density of surface algae of insulator |
| WO2021082594A1 (en) * | 2019-10-31 | 2021-05-06 | 南方电网科学研究院有限责任公司 | Method, apparatus and device for testing algae on surface of insulating material |
| CN113610768A (en) * | 2021-07-14 | 2021-11-05 | 南方电网科学研究院有限责任公司 | Method and device for measuring and calculating coverage rate of algae on surface of insulator and storage medium |
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| CN117517335B (en) * | 2023-12-27 | 2024-03-29 | 国网辽宁省电力有限公司电力科学研究院 | System and method for monitoring pollution of insulator of power transformation equipment |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1668913A (en) * | 2002-05-14 | 2005-09-14 | 阿默森生物科学英国有限公司 | Method for assessing biofilms |
| CN105738364A (en) * | 2015-12-28 | 2016-07-06 | 清华大学深圳研究生院 | Measuring method and measuring apparatus of growth degree of algae on silicone rubber surface on the basis of image processing |
| CN106053432A (en) * | 2016-06-01 | 2016-10-26 | 清华大学深圳研究生院 | Microspheres for coding and decoding and coding and decoding method and decoding system thereof |
| JP2017051162A (en) * | 2015-09-11 | 2017-03-16 | 国立研究開発法人農業・食品産業技術総合研究機構 | Method and device for estimating viable cell count on sample surface, and program incorporated into the device |
| CN106770070A (en) * | 2016-11-11 | 2017-05-31 | 清华大学深圳研究生院 | A kind of insulator surface equivalent salt density measuring method and device |
| WO2018055544A1 (en) * | 2016-09-21 | 2018-03-29 | Presens Precision Sensing Gmbh | Method, arrangement, computer program product and sensor foil for detecting microorganisms on a surface |
| CN109030488A (en) * | 2018-06-25 | 2018-12-18 | 中国海洋大学 | Algae bio quantity measuring method and device |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100510714C (en) * | 2006-12-05 | 2009-07-08 | 中国科学院安徽光学精密机械研究所 | Laser breakdown spectrographic detection method and system for metal pollutants in water body |
| ITMI20120411A1 (en) * | 2012-03-16 | 2013-09-17 | Ricerca Sul Sist Energetico Rs E S P A | APPARATUS FOR MONITORING THE INSULATORS OF AN AIR ELECTRICAL LINE |
| FR3002635B1 (en) * | 2013-02-27 | 2015-04-10 | Areva Nc | SYSTEM FOR THE ANALYSIS, BY LASER-INDUCED PLASMA SPECTROMETRY, OF THE COMPOSITION OF THE SURFACE LAYER OF A MATERIAL AND FOR THE SAMPLING OF SAMPLES FOR COMPLEMENTARY ANALYZES OR CONTROLS OF THIS SURFACE LAYER, AND METHOD RELATING THERETO |
| US9958395B2 (en) * | 2016-02-12 | 2018-05-01 | Bwt Property, Inc. | Laser induced breakdown spectroscopy (LIBS) apparatus for the detection of mineral and metal contamination in liquid samples |
| CN109406541A (en) * | 2018-11-22 | 2019-03-01 | 深圳供电局有限公司 | A kind of device and method detecting the filth of external insulation equipment surface metal |
| CN110823863A (en) * | 2019-10-31 | 2020-02-21 | 中国南方电网有限责任公司电网技术研究中心 | Method, device and equipment for detecting algae on surface of insulating material |
-
2019
- 2019-10-31 CN CN201911052804.5A patent/CN110823863A/en active Pending
-
2020
- 2020-08-06 WO PCT/CN2020/107545 patent/WO2021082594A1/en active Application Filing
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1668913A (en) * | 2002-05-14 | 2005-09-14 | 阿默森生物科学英国有限公司 | Method for assessing biofilms |
| JP2017051162A (en) * | 2015-09-11 | 2017-03-16 | 国立研究開発法人農業・食品産業技術総合研究機構 | Method and device for estimating viable cell count on sample surface, and program incorporated into the device |
| CN105738364A (en) * | 2015-12-28 | 2016-07-06 | 清华大学深圳研究生院 | Measuring method and measuring apparatus of growth degree of algae on silicone rubber surface on the basis of image processing |
| CN106053432A (en) * | 2016-06-01 | 2016-10-26 | 清华大学深圳研究生院 | Microspheres for coding and decoding and coding and decoding method and decoding system thereof |
| WO2018055544A1 (en) * | 2016-09-21 | 2018-03-29 | Presens Precision Sensing Gmbh | Method, arrangement, computer program product and sensor foil for detecting microorganisms on a surface |
| CN106770070A (en) * | 2016-11-11 | 2017-05-31 | 清华大学深圳研究生院 | A kind of insulator surface equivalent salt density measuring method and device |
| CN109030488A (en) * | 2018-06-25 | 2018-12-18 | 中国海洋大学 | Algae bio quantity measuring method and device |
Non-Patent Citations (1)
| Title |
|---|
| 刘木华: "《农产品质量安全光学无损检测技术及应用》", 30 June 2011 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021082594A1 (en) * | 2019-10-31 | 2021-05-06 | 南方电网科学研究院有限责任公司 | Method, apparatus and device for testing algae on surface of insulating material |
| CN111986201A (en) * | 2020-09-28 | 2020-11-24 | 南方电网科学研究院有限责任公司 | Method and device for measuring and calculating density of surface algae of insulator |
| CN111986201B (en) * | 2020-09-28 | 2023-12-22 | 南方电网科学研究院有限责任公司 | Method and device for measuring and calculating density of surface algae of insulator |
| CN113610768A (en) * | 2021-07-14 | 2021-11-05 | 南方电网科学研究院有限责任公司 | Method and device for measuring and calculating coverage rate of algae on surface of insulator and storage medium |
| WO2023284104A1 (en) * | 2021-07-14 | 2023-01-19 | 南方电网科学研究院有限责任公司 | Method and apparatus for calculating algae coverage of insulator surface, and storage medium |
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