CN117969969A - Power frequency magnetic field visual detection method based on array type multi-probe combined detection - Google Patents
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Abstract
The invention relates to a power frequency magnetic field visual detection method based on array type multi-probe combination detection, which solves the technical problem that multi-point collaborative space sensing cannot be completed. Collecting topological structure and electrical equipment parameters of a region to be detected, establishing a scene self-adaptive magnetic field model, calculating power frequency magnetic field distribution according to parameters such as current, voltage, conductor geometric shape and the like, using magnetic field distribution data calculated in the scene self-adaptive magnetic field model, and carrying out data fusion and calibration by combining actual data measured by a probe. Based on the obtained magnetic field distribution data, a three-dimensional image of the magnetic field is drawn, the technical scheme of visualization of the power frequency magnetic field is realized, the problem is well solved, and the method can be used in the fields of electric power, electronics, medicine, engineering design, navigation and the like.
Description
Technical Field
The invention relates to the field, in particular to a power frequency magnetic field visual detection method based on array type multi-probe combined detection.
Background
Electromagnetic information sensing and application are one of the key and difficult directions of long-term research of the power grid. The electromagnetic environment influence of the electric power facilities is gradually known and accepted by masses, various contradictions are alleviated, the severe prevention and control attitude of the power frequency electromagnetic environment of the electric power enterprises is gradually changed, and the electromagnetic environment information is gradually changed from passive support complaint visit to active auxiliary state perception and health assessment of the electric power facilities.
Meanwhile, by summarizing the modern intelligent sensing technology, the work of sensing the state of the power equipment based on a plurality of technical means such as infrared waves, ultraviolet waves, sound waves and ultrasonic waves is greatly developed in the prior art, and the work of defect early warning and positioning of the equipment under different operation characteristics is assisted. However, magnetic field data is used as key and most direct information in electric facilities, the perception capability of the magnetic field data is obviously insufficient, the obtained information still stays at a single point or a plurality of single points in space, the display technology is in a single number (string) form, and the difference is obvious compared with the perception capability of other wave frequency bands.
Currently, the visual research of the power frequency magnetic field is in a primary stage, and only the basis of supporting a single-point or multiple single-point power frequency magnetic field measuring probe, an analysis model and the like exists. There is a technical problem in that the multi-point collaborative spatial perception cannot be completed.
Disclosure of Invention
The invention aims to solve the technical problem that the multipoint collaborative space sensing cannot be completed in the prior art. The novel power frequency magnetic field visual detection method based on the array type multi-probe combination detection has the characteristic of being capable of completing multipoint collaborative space sensing.
In order to solve the technical problems, the technical scheme adopted is as follows:
A power frequency magnetic field visual detection method based on array type multi-probe combined detection comprises the following steps:
Selecting a plurality of magnetic field probes capable of independently measuring magnetic field information to form a probe array, and collecting actual measurement data of power frequency magnetic fields at different positions;
Collecting topological structures and electrical equipment parameters of an area to be detected, establishing a scene self-adaptive magnetic field model based on the positions and the parameters of the electrical equipment, and calculating power frequency magnetic field distribution;
Thirdly, the measured magnetic field data are subjected to data fusion and calibration by using the magnetic field distribution data obtained by calculation in the scene self-adaptive magnetic field model and combining with actual data measured by a sensor, so that the accurate optimization of the power frequency magnetic field distribution is completed;
And step four, using the power frequency magnetic field distribution which is completed to be accurately optimized, correlating the power frequency magnetic field data with the scene model, and drawing a three-dimensional image showing the magnetic field according to the distribution of the power frequency magnetic field data in the scene model.
The working principle of the invention is as follows: the invention can provide more comprehensive and high-resolution spatial magnetic field distribution information by arranging a plurality of probes in a target area, wherein each probe can independently measure magnetic field information. Compared with the traditional single-probe method, more information can be acquired in the same time, and three-dimensional and multi-dimensional observation of the magnetic field is realized. According to the invention, the data fusion and calibration are carried out by using the magnetic field distribution data obtained by calculation in the scene self-adaptive magnetic field model and combining the actual data measured by the sensor, so that more accurate power frequency magnetic field distribution is obtained.
In order to optimize the present invention, in a first step, the magnetic field probes in the probe array are calibrated in sequence, including:
step 1, defining a magnetic field probe distortion calibration model:
;
;
;
Wherein, Is the coordinate value of the predefined ideal magnetic field map point,/>Is the coordinates of the corresponding distorted magnetic field map points,/>Is a distortion center coordinate, and k is a distortion calibration coefficient of the magnetic field probe;
Step 2, presetting n parallel lines which are parallel to each other, and defining a linear equation on an ideal magnetic field diagram as:
；
Wherein, And/>The method meets the following conditions: rank function Rank (/ >))=2；
Step 3, collecting an ith curve on the distorted magnetic field diagram, and selecting m mark points on the curve; the j (j.ltoreq.m) th point coordinate value is defined as; Calculating the coordinate value/>, corresponding to the j-th point coordinate, on the ideal imaging surface according to the distortion calibration model in the step 1；
Calculating a fitting function of the ith curve through a fitting algorithm:
；
Wherein, ，/>；For/>Transposed matrix of/>For/>Is a transposed matrix of (a);
And (3) bringing the fitting function into a linear equation on the ideal image in the step (1), and solving the distortion parameter k simultaneously.
By predicting and correcting the distortion pattern of the magnetic field probe, the complete magnetic field probe is calibrated, and the scanning precision is improved.
Further, in the first step,
The probe array is deployed in a geometric figure, and the geometric figure comprises a spherical surface, a cylindrical surface and a plane.
Further, in the second step, the first step,
The topological structure comprises the position, the connection mode and the circuit arrangement of the equipment;
The electrical device parameters include current, voltage, frequency.
Further, the scene self-adaptive magnetic field model modeling method comprises finite element analysis, a boundary element method and a finite difference method.
The electrical device is defined as a source or load in a magnetic field when modeled.
Further, the second step further comprises parameter estimation and verification of the scene self-adaptive magnetic field model, which is completed through nodes and branches in the self-adaptive magnetic field model;
Distributing defined current values and voltage values for the electrical equipment in the scene self-adaptive magnetic field model by using the electrical equipment parameters, and estimating the parameters based on the measurement data by using a topology analysis method;
And comparing the scene self-adaptive magnetic field model with the measured data to finish verification of the scene self-adaptive magnetic field model.
In the third step, the data fusion and calibration are performed by using the magnetic field distribution data calculated in the scene adaptive magnetic field model and combining the measured actual data, and the method comprises the following steps:
Realizing data fusion by adopting a fusion method comprising data interpolation and a data fusion algorithm;
data calibration is achieved by taking calibration methods including zero calibration, gain calibration, and nonlinear calibration.
Further, in the fourth step, the industrial frequency magnetic field data and the scene model are associated with each other, so that the magnetic field data can be accurately mapped to corresponding positions, and a three-dimensional image showing the magnetic field is drawn according to the distribution of the engineering magnetic field data in the scene model.
Further, the magnetic field probe is a low-frequency electromagnetic field probe, can measure a magnetic field in a frequency range of 1 Hz-4000 Hz, and has a field intensity measuring range of 1 nT-10 mT.
The invention has the beneficial effects that: the three-dimensional visualization technology of the power frequency magnetic field can provide visual and vivid magnetic field information data, and has application prospect and popularization value in the fields of electric power, electronics, medicine, engineering design, navigation and the like. In the power industry, the magnetic field data directly support the work of equipment state research, judgment and early warning, electromagnetic environment evaluation and management, operation, maintenance and guarantee of a power sensor and the like. In the aspects of earth science and environmental protection, the magnetic field visualization technology can assist in geological exploration, mineral resource detection and environmental monitoring, and improves resource development efficiency and environmental protection level. In addition, in the virtual reality, augmented reality and entertainment industries, magnetic field visualization technology can provide users with an immersive visual experience, energize power grid science popularization, and contribute power grid wisdom to people's knowledge of scientific knowledge and fun learning.
Drawings
The invention will be further described with reference to the drawings and examples.
FIG. 1 is a flow chart of the method of example 1;
FIG. 2 is a system model of the array layout process of example 1;
FIG. 3 is a schematic diagram of an array-type multi-probe deployment of example 1;
FIG. 4 is a flow chart of the visualization of the power frequency magnetic field of example 1.
Description of the embodiments
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Examples
The embodiment provides a power frequency magnetic field visual detection method based on array type multi-probe combined detection, which comprises the following steps:
Selecting a plurality of magnetic field probes capable of independently measuring magnetic field information to form a probe array, and collecting actual measurement data of power frequency magnetic fields at different positions;
Collecting topological structures and electrical equipment parameters of an area to be detected, establishing a scene self-adaptive magnetic field model based on the positions and the parameters of the electrical equipment, and calculating power frequency magnetic field distribution;
Thirdly, the measured magnetic field data are subjected to data fusion and calibration by using the magnetic field distribution data obtained by calculation in the scene self-adaptive magnetic field model and combining with actual data measured by a sensor, so that the accurate optimization of the power frequency magnetic field distribution is completed;
And step four, using the power frequency magnetic field distribution which is completed to be accurately optimized, correlating the power frequency magnetic field data with the scene model, and drawing a three-dimensional image showing the magnetic field according to the distribution of the power frequency magnetic field data in the scene model.
The working principle of the invention is as follows: the invention can provide more comprehensive and high-resolution spatial magnetic field distribution information by arranging a plurality of probes in a target area, wherein each probe can independently measure magnetic field information. Compared with the traditional single-probe method, more information can be acquired in the same time, and three-dimensional and multi-dimensional observation of the magnetic field is realized. According to the invention, the data fusion and calibration are carried out by using the magnetic field distribution data obtained by calculation in the scene self-adaptive magnetic field model and combining the actual data measured by the sensor, so that more accurate power frequency magnetic field distribution is obtained.
Specifically, in the first step, the magnetic field probes in the probe array are calibrated sequentially, including:
step 1, defining a magnetic field probe distortion calibration model:
;
;
;
Wherein, Is the coordinate value of the predefined ideal magnetic field map point,/>Is the coordinates of the corresponding distorted magnetic field map points,/>Is a distortion center coordinate, and k is a distortion calibration coefficient of the magnetic field probe;
Step 2, presetting n parallel lines which are parallel to each other, and defining a linear equation on an ideal magnetic field diagram as:
；
Wherein, And/>The method meets the following conditions: rank function Rank (/ >))=2；
Step 3, collecting an ith curve on the distorted magnetic field diagram, and selecting m mark points on the curve; the j (j.ltoreq.m) th point coordinate value is defined as; Calculating the coordinate value/>, corresponding to the j-th point coordinate, on the ideal imaging surface according to the distortion calibration model in the step 1；
Calculating a fitting function of the ith curve through a fitting algorithm:
；
Wherein, ，/>；For/>Transposed matrix of/>For/>Is a transposed matrix of (a);
And (3) bringing the fitting function into a linear equation on the ideal image in the step (1), and solving the distortion parameter k simultaneously.
By predicting and correcting the distortion pattern of the magnetic field probe, the complete magnetic field probe is calibrated, and the scanning precision is improved.
Specifically, in the first step,
The probe array is deployed in a geometric figure, and the geometric figure comprises a spherical surface, a cylindrical surface and a plane.
Specifically, in the second step,
The topological structure comprises the position, the connection mode and the circuit arrangement of the equipment;
The electrical device parameters include current, voltage, frequency.
Specifically, the scene self-adaptive magnetic field model modeling method comprises a finite element analysis, a boundary element method and a finite difference method.
The electrical device is defined as a source or load in a magnetic field when modeled.
The second step further comprises parameter estimation and verification of the scene self-adaptive magnetic field model, wherein the parameter estimation and verification are completed through nodes and branches in the self-adaptive magnetic field model;
Distributing defined current values and voltage values for the electrical equipment in the scene self-adaptive magnetic field model by using the electrical equipment parameters, and estimating the parameters based on the measurement data by using a topology analysis method;
And comparing the scene self-adaptive magnetic field model with the measured data to finish verification of the scene self-adaptive magnetic field model.
Specifically, in the third step, the data fusion and calibration are performed by using the magnetic field distribution data obtained by calculation in the scene adaptive magnetic field model and combining the measured actual data, and the method includes:
Realizing data fusion by adopting a fusion method comprising data interpolation and a data fusion algorithm;
data calibration is achieved by taking calibration methods including zero calibration, gain calibration, and nonlinear calibration.
Specifically, in the fourth step, the industrial frequency magnetic field data and the scene model are associated with each other, so that the magnetic field data can be accurately mapped to corresponding positions, and a three-dimensional image showing a magnetic field is drawn according to the distribution of the engineering magnetic field data in the scene model.
Specifically, the magnetic field probe is a low-frequency electromagnetic field probe, can measure a magnetic field in a frequency range of 1 Hz-4000 Hz, and has a field intensity range of 1 nT-10 mT. Can meet the measurement requirement of a power frequency magnetic field
In the embodiment, visual and vivid magnetic field information data can be provided, and the magnetic field information data has application prospects and popularization values in the fields of electric power, electronics, medicine, engineering design, navigation and the like. In the power industry, the magnetic field data directly support the work of equipment state research, judgment and early warning, electromagnetic environment evaluation and management, operation, maintenance and guarantee of a power sensor and the like. In the aspects of earth science and environmental protection, the magnetic field visualization technology can assist in geological exploration, mineral resource detection and environmental monitoring, and improves resource development efficiency and environmental protection level. In addition, in the virtual reality, augmented reality and entertainment industries, magnetic field visualization technology can provide users with an immersive visual experience, energize power grid science popularization, and contribute power grid wisdom to people's knowledge of scientific knowledge and fun learning.
As shown in FIG. 1, the method comprises the steps of selecting a layout mode of a magnetic field probe and an array, establishing a scene self-adaptive magnetic field model, fusing and calibrating magnetic field calculation data and probe actual measurement data, realizing power frequency magnetic field visualization and the like. The specific implementation method comprises the following steps:
(1) From the aspects of positioning accuracy, coverage, safety, flexibility and the like, a proper magnetic field probe is selected. Common magnetic field probes include hall sensors, inductively coupled sensors, and the like. The probe should be selected to meet the needs of the study. The array layout of the magnetic field probe is designed according to the objectives and needs of the study, which involves determining the position, orientation and spacing of the probes. What the array layout is to handle is the signals collected by the array sensors in some environment of interest.
The relationship between such an environment, sensor array and processor can be described with reference to fig. 2, and a common array layout is shown in fig. 3.
The design of the array should be capable of capturing the magnetic field information of interest and the selected magnetic field probe is installed in the investigation region in accordance with the designed array layout.
These probes are calibrated to ensure that they can accurately measure the magnetic field strength. Calibration involves applying a known magnetic field, adjusting the output of the probe to match the actual magnetic field value. Data acquisition is performed using the installed magnetic field probe.
This requires a special set of data acquisition equipment for recording the measurements of each probe. The frequency and duration of data acquisition depends on the requirements of the study. The acquired magnetic field data needs to be processed to remove noise, correct and combine data from different probes.
(2) And collecting topological structure and electrical equipment parameters, and establishing a scene self-adaptive magnetic field model. The power frequency magnetic field distribution is calculated according to parameters such as current, voltage, conductor geometry and the like by using a numerical calculation method (finite element method) or an analytic calculation method.
(2.1) Topology and device parameter collection: and collecting topological structure information of the electrical equipment in the scene. This includes the location of the device, the manner of connection, the wiring arrangement, etc. CAD design drawings, building plans, or other related documents may be used to obtain this information. A laser rangefinder or GPS device may also be used to measure the precise location of the device. In addition to the topology, it is also necessary to collect parameters of each electrical device, such as current, voltage, frequency, etc. These parameters may typically be obtained from the specifications of the equipment, equipment labels, or electrical engineering documents.
(2.2) Establishment of a magnetic field model: based on the collected data and the targets of the study, an appropriate magnetic field modeling method is selected. Common modeling methods include finite element analysis, boundary element methods, finite difference methods, and the like. Each electrical device is modeled as a source or load in a magnetic field. This requires combining parameters of the device (e.g., current, voltage) with the modeling method chosen to calculate the magnetic field produced by the device. Topology information is used to build a magnetic field model of the entire scene. This includes the location of the device, the manner of connection, the wire arrangement, etc.
(2.3) Model parameter estimation and verification: the electrical device parameters are used to assign corresponding current and voltage values to the devices in the model. This can be achieved by nodes and branches in the model. Parameter estimation may be performed using topology analysis methods or based on measurement data. And verifying whether the established magnetic field model can accurately predict the magnetic field distribution in the actual scene. This can be achieved by comparing with measured data. If the model does not match the actual situation, it may be necessary to adjust the model parameters or reconsider the accuracy of the model.
(2.4) Scene adaptive modeling: if the electrical device layout or parameters in the scene change, the model needs to be able to adapt to these changes. This can be achieved by real-time data acquisition and model updating. For example, if a device is added or moved, the model needs to be updated accordingly.
(3) And deploying a magnetic field probe, and collecting and transmitting the measured magnetic field data to a computer or a data processing unit. And (3) carrying out data fusion and calibration by using the magnetic field distribution data obtained by calculation in the scene self-adaptive magnetic field model and combining with actual data measured by the sensor to obtain more accurate power frequency magnetic field distribution.
(3.1) Fusion data: and fusing the magnetic field data generated by the calculation model with the measured data. This can be achieved by the following method:
a. interpolation of data: the data of the calculation model is matched with the measured data using interpolation techniques. The interpolation method may be linear interpolation, two-dimensional interpolation, or more complex interpolation techniques to fill in gaps between data.
B. Data fusion algorithm: the calculated data and the measured data are combined using a fusion algorithm (e.g., weighted average or Kalman filtering, etc.) to obtain more accurate results. These algorithms may take into account the reliability and weight of the different data sources.
(3.2) Calibration data: data calibration is performed to eliminate any systematic errors between the measured device and the computational model. The method of calibration may comprise the steps of:
a. Zero point calibration: the constant error is eliminated by correcting the zero point deviation of the measured data and the calculated data to zero.
B. gain calibration: the amplitude of the data is calibrated by a scaling factor to match the amplitude of the measured data. This may require adjustment based on the characteristics of the probe.
C. Nonlinear calibration: if there is a nonlinear error, a nonlinear calibration is required to better match the response characteristics of the measured data.
(4) A computer graphic image technology development environment is installed and configured, and a three-dimensional scene model is built according to magnetic field data, wherein the three-dimensional scene model comprises a geometric model representing the electric equipment and the position of the electric equipment. And correlating the power frequency magnetic field data with a scene model, and drawing a three-dimensional image of the magnetic field according to the distribution of the data in the scene. The flow chart of the power frequency magnetic field visualization is shown in fig. 4.
(4.1) Association of scene models: the model-generated magnetic field data is correlated with the scene model. This may include matching the model-generated data with the physical structure of the scene (e.g., building, cable, device, etc.) to determine the location of the data in the scene.
(4.2) Magnetic field distribution visualization image rendering: a suitable three-dimensional visualization tool or software is selected to render a three-dimensional image of the magnetic field. Common tools include Matplotlib, paraView in MATLAB, python, and the like. The fused and calibrated magnetic field data is presented in the form of a three-dimensional image using a mapping tool. This includes generating a perspective view, an isosurface view, a vector field view, etc. The readability of the image is optimized by adjusting visualization parameters such as color mapping, transparency, viewing angle, etc. An interactive visual environment is created, if possible, allowing the user to freely navigate and explore the magnetic field data in a three-dimensional scene. This may be accomplished through the use of specialized visualization libraries or software.
While the foregoing describes the illustrative embodiments of the present invention so that those skilled in the art may understand the present invention, the present invention is not limited to the specific embodiments, and all inventive innovations utilizing the inventive concepts are herein within the scope of the present invention as defined and defined by the appended claims, as long as the various changes are within the spirit and scope of the present invention.
Claims (9)
1. A power frequency magnetic field visual detection method based on array type multi-probe combined detection is characterized in that: the power frequency magnetic field visual detection method based on array type multi-probe combined detection comprises the following steps:
Selecting a plurality of magnetic field probes capable of independently measuring magnetic field information to form a probe array, and collecting actual measurement data of power frequency magnetic fields at different positions;
Collecting topological structures and electrical equipment parameters of an area to be detected, establishing a scene self-adaptive magnetic field model based on the positions and the parameters of the electrical equipment, and calculating power frequency magnetic field distribution;
Thirdly, the measured magnetic field data are subjected to data fusion and calibration by using the magnetic field distribution data obtained by calculation in the scene self-adaptive magnetic field model and combining with actual data measured by a sensor, so that the accurate optimization of the power frequency magnetic field distribution is completed;
And step four, using the power frequency magnetic field distribution which is completed to be accurately optimized, correlating the power frequency magnetic field data with the scene model, and drawing a three-dimensional image showing the magnetic field according to the distribution of the power frequency magnetic field data in the scene model.
2. The method for visualizing a magnetic field based on combined detection of multiple array probes according to claim 1, wherein the method is characterized by: in the first step, calibrating magnetic field probes in the probe array sequentially comprises the following steps:
step 1, defining a magnetic field probe distortion calibration model:
;
;
;
Wherein, Is the coordinate value of the predefined ideal magnetic field map point,/>Is the coordinates of the corresponding distorted magnetic field map points,/>Is a distortion center coordinate, and k is a distortion calibration coefficient of the magnetic field probe;
Step 2, presetting n parallel lines which are parallel to each other, and defining a linear equation on an ideal magnetic field diagram as:
；
Wherein, And/>The method meets the following conditions: rank function Rank (/ >))=2；
Step 3, collecting an ith curve on the distorted magnetic field diagram, and selecting m mark points on the curve; the j (j.ltoreq.m) th point coordinate value is defined as; Calculating the coordinate value/>, corresponding to the j-th point coordinate, on the ideal imaging surface according to the distortion calibration model in the step 1；
Calculating a fitting function of the ith curve through a fitting algorithm:
；
Wherein, ，/>；/>Is thatTransposed matrix of/>For/>Is a transposed matrix of (a);
And (3) bringing the fitting function into a linear equation on the ideal image in the step (1), and solving the distortion parameter k simultaneously.
3. The method for visualizing a magnetic field based on combined detection of multiple array probes according to claim 1, wherein the method is characterized by: in the first step, the first step is to perform,
The probe array is deployed in a geometric figure, and the geometric figure comprises a spherical surface, a cylindrical surface and a plane.
4. The method for visualizing a magnetic field based on combined detection of multiple array probes according to claim 1, wherein the method is characterized by: in the second step, the second step is to carry out the process,
The topological structure comprises the position, the connection mode and the circuit arrangement of the equipment;
The electrical device parameters include current, voltage, frequency.
5. The method for visualizing a magnetic field based on combined detection of multiple array probes according to claim 1, wherein the method is characterized by: in the second step, the second step is to carry out the process,
The scene self-adaptive magnetic field model modeling method comprises a finite element analysis, a boundary element method and a finite difference method;
the electrical device is defined as a source or load in a magnetic field when modeled.
6. The method for visualizing a magnetic field based on combined detection of multiple array probes according to claim 1, wherein the method is characterized by:
The second step also comprises parameter estimation and verification of the scene self-adaptive magnetic field model, which is completed through nodes and branches in the self-adaptive magnetic field model;
Distributing defined current values and voltage values for the electrical equipment in the scene self-adaptive magnetic field model by using the electrical equipment parameters, and estimating the parameters based on the measurement data by using a topology analysis method;
And comparing the scene self-adaptive magnetic field model with the measured data to finish verification of the scene self-adaptive magnetic field model.
7. The method for visualizing a magnetic field based on combined detection of multiple array probes according to claim 1, wherein the method is characterized by:
in the third step, the data fusion and calibration are performed by using the magnetic field distribution data obtained by calculation in the scene self-adaptive magnetic field model and combining the measured actual data, and the method comprises the following steps:
Realizing data fusion by adopting a fusion method comprising data interpolation and a data fusion algorithm;
data calibration is achieved by taking calibration methods including zero calibration, gain calibration, and nonlinear calibration.
8. The method for visualizing a magnetic field based on combined detection of multiple array probes according to claim 1, wherein the method is characterized by:
and step four, the power frequency magnetic field data and the scene model are correlated, so that the magnetic field data can be accurately mapped to corresponding positions, and a three-dimensional image showing a magnetic field is drawn according to the distribution of the engineering magnetic field data in the scene model.
9. The method for visualizing a magnetic field based on combined detection of multiple array probes according to claim 1, wherein the method is characterized by: the magnetic field probe is a low-frequency electromagnetic field probe, can measure a magnetic field in a frequency range of 1 Hz-4000 Hz, and has a field intensity range of 1 nT-10 mT.
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