CN111912755B - Mining dust concentration sensor, sensor system and method - Google Patents
Mining dust concentration sensor, sensor system and method Download PDFInfo
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Abstract
The invention belongs to the technical field of sensors, and particularly relates to a mining dust concentration sensor, a sensor system and a method. The sensor includes: the dust concentration sensor comprises a sensor shell, a dust concentration sensor unit and an energy supply unit; the dust concentration sensor unit and the energy supply unit are both arranged in the sensor shell; the energy supply unit is used for supplying energy to the dust concentration sensor unit; characterized in that the dust concentration sensor unit includes: a transmitting unit, a receiving unit and an analyzing unit; the transmitting unit comprises a first transmitting unit and a second transmitting unit, the first transmitting unit and the second transmitting unit both transmit light waves, and the receiving unit receives the reflected light waves and the direct light waves. The problem of reduced induction accuracy caused by interference of the emitted light wave on the reflected light wave is solved by processing the emitted light wave and the reflected light wave of the sensor; meanwhile, a unique sensor system is constructed for the mine cavity environment, the mine cavity environment is better adapted, and the monitoring accuracy is improved.
Description
Technical Field
The invention belongs to the technical field of sensors, and particularly relates to a mining dust concentration sensor, a sensor system and a method.
Background
The dust sensor is a mode for counting or measuring mass concentration of suspended particles in air by using an MIE scattering theory. Generally, a dust sensor has an air duct, a light emitting tube, a lens, and a light sensing element. The air flow flows in the air duct, when the air flow flows above the photosensitive element, the air flow is irradiated by laser to generate scattered light, the photosensitive element receives the scattered light, and the condition of dust in the air flow is obtained through analysis of the scattered light.
In the prior art, dust sensors monitor dust in the air mainly through a photosensitive element. The photosensitive element is located below the detection point, and the detection point is usually located above the detection point through which the gas freely flows. Resulting in a reduction in the sensing accuracy of the dust.
Patent No. CN201720660428.8U: a high accuracy laser dust sensor discloses a high accuracy laser dust sensor, includes: a laser emission module; the optical signal receiving module is matched with the laser emitting module; the electrical signal generating module is electrically connected with the optical signal receiving module; the signal amplification module is electrically connected with the electric signal generation module; the distinguishing module is electrically connected with the signal amplifying module and is used for distinguishing electric signals fed back by dust with different particle sizes; the resolution module comprises a plurality of stages of resolution components, and adjacent two stages of resolution components are electrically connected; the filtering module is electrically connected with the distinguishing module and used for filtering interference signals in the electric signals; and the data storage and correction module is electrically connected with the filtering module and is used for storing calibration deviation data of the sensor and correcting the output electric signal.
The sensor can identify weak signals by amplifying signals and correcting data, has strong anti-interference capability, can highly accurately measure the dust content in the environment, but has no influence on the interference of the sensor, and cannot adapt to complex scenes in mine holes.
The patent numbers are: CN201410072979.3A patent: a dust sensor for on-line monitoring dust concentration comprises a box body which is internally provided with an air inlet channel and an air outlet channel which can form a sealed detection area and are positioned at two opposite sides of the detection area, an air inlet pipe and an air outlet pipe which are respectively positioned in the air inlet channel and the air outlet channel, a laser transmitter communicated with the detection area from one end part of the box body, wherein the air inlet pipe and the air outlet pipe are positioned on the same straight line, laser emitted by the laser transmitter is intersected with connecting lines of the air inlet pipe and the air outlet pipe, the dust sensor also comprises a light receiver component positioned above the detection area and a light reflecting component which can be detachably arranged at the bottom of the detection area, wherein the light receiver component is used for receiving information of refracted light generated by irradiating gas particles in the detection area with laser light emitted by the laser transmitter, and meanwhile, the information is received and converted into a signal which is transmitted to a signal processing system of the measuring instrument.
The dust monitoring precision is improved by arranging the air inlet pipe and the air outlet pipe, but the dust monitoring precision is difficult to implement in some complex environments. And still not to reject interference of the emitted light with the received light.
Disclosure of Invention
In view of the above, the main object of the present invention is to provide a dust concentration sensor, a sensor system and a method for mining, which avoid the problem of decreased sensing accuracy caused by interference of reflected light waves caused by emitted light waves by processing the emitted light waves and the reflected light waves of the sensor; meanwhile, a unique sensor system is constructed for the mine cavity environment, the mine cavity environment is better adapted, and the monitoring accuracy is improved.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a mining dust concentration sensor, the sensor comprising: the dust concentration sensor comprises a sensor shell, a dust concentration sensor unit and an energy supply unit; the dust concentration sensor unit and the energy supply unit are both arranged in the sensor shell; the energy supply unit is used for supplying energy to the dust concentration sensor unit; characterized in that the dust concentration sensor unit includes: a transmitting unit, a receiving unit and an analyzing unit; the transmitting unit comprises a first transmitting unit and a second transmitting unit, and after the first transmitting unit and the second transmitting unit both transmit light waves, the receiving unit receives the reflected light waves and the direct light waves; and the analysis unit sequentially performs the steps of direct light wave filtering, reflected light wave conversion and frequency spectrum drawing according to the received reflected light wave and the received direct light wave.
Further, the direct light wave filtering performs the following steps: calculating the direct light wave of the first transmitting unit and the direct light wave of the second transmitting unit received by the receiving unit through Laplace transform by using the following formulaTime delay:
wherein S is1(t) is the direct light wave of the first emission unit, PS1(t)]For its corresponding laplace transform; s2(t) is the direct light wave of the second emission unit, P*[S2(t)]A conjugate transform that is its corresponding laplace transform; f is P [ S ]1(t) and P*[S2(t)]Corresponding frequency, x is the unknown quantity of the laplace transform; and then, calculating the cross-correlation coefficient between the direct light wave of the first emission unit and the direct light wave of the second emission unit:
wherein the content of the first and second substances,
denotes S2(t) inverse laplacian transform; will be provided with
Amplifying by c times to obtain a reflected light wave after filtering the direct light wave:
further, the method of reflected light wave conversion performs the following steps: the reflected light wave is represented by the following formula:
wherein α is an amplitude constant, fcIs a carrier frequency, MsIs a period, tau (t) is a time delay parameterB is the bandwidth, N1Is a rate constant, set to 1.5; the reflected light waves are converted to baseband signals by the following equation:
performing laplace transform on the baseband signal to obtain a frequency spectrum, wherein according to the frequency spectrum, the phase of the baseband signal is obtained as follows: phi (t) ═ 0.8 pi fcτ(t)。
Furthermore, the sensor shell consists of two layers of same electromagnetic shielding structures; the electromagnetic shielding structure includes: a substrate, and a metal foil wrapped around the substrate, wherein the substrate comprises a top surface, a bottom surface, and a plurality of sidewalls, wherein the metal foil covers only the top surface and the plurality of sidewalls of the substrate; the metal foil has opposing first and second surfaces, wherein the first surface is located over the substrate.
A sensor system, the system comprising: a plurality of sensor tuples and analysis processors which are uniformly distributed in the mine hole; the sensor tuple includes: 5 sensors uniformly distributed on the circumference with the same circle center; the circle center position is provided with a tuple processor; the tuple processor is respectively in signal connection with all the sensors; a shielding pool is arranged outside the tuple processor in a surrounding manner; the circumference is a shielding shell; the tuple processor is in signal connection with the analysis processor, and is configured to perform analog-to-digital conversion on data sensed by the sensor and send the data to the analysis processor.
Furthermore, the shielding shell has the same structure as the sensor shell; the shielding pool is formed by a plurality of same structures which are stacked and surrounded by the same circle center.
Further, the analysis processor performs the following processing on the received data in sequence: performing data preprocessing, including: removing the unique attribute, processing missing values and abnormal value detection and processing; and carrying out data specification processing, including: removing an average value, calculating a covariance matrix, calculating an eigenvalue and an eigenvector of the covariance matrix, sorting the eigenvalues from large to small, reserving the largest eigenvector, and converting data into a new space constructed by the eigenvector; finally, new processed data are obtained, and the data are irrelevant pairwise, but the original information is kept; carrying out data standardization processing, and scaling the data in proportion to enable the data to fall into a specific interval; and carrying out data analysis on the data subjected to the data standardization processing to obtain a dust monitoring result.
A method, the method performing the steps of:
step 1: the method comprises the following steps of (1) enabling 5 sensors to form a group together with a tuple processor to form sensor tuples, and uniformly distributing the sensor tuples inside a mine hole;
step 2: and the analysis processor receives the data sensed by the sensor, and performs data analysis on the received data to complete dust monitoring in the mine hole.
Furthermore, 5 sensors are in a group and are uniformly distributed on the circumference with the same circle center; the tuple processor is arranged at the position of the circle center; a shielding pool is arranged outside the tuple processor in a surrounding manner; the circumference is a shielding shell; and the tuple processor is in signal connection with the analysis processor, and sends the data sensed by the sensor to the analysis processor after performing analog-to-digital conversion on the data.
Further, the step 2: the analysis processor receives data sensed by the sensor, performs data analysis on the received data, and completes the dust monitoring method in the mine hole to execute the following steps: obtaining training sensory data for modeling as input variables using xiRepresenting, wherein i represents the ith variable in the data; setting a weight function of wiExpressing, performing convolution operation on each input variable and the corresponding weight function to obtain a first intermediate result; setting an excitation function, wherein the excitation function is as follows:
setting the neuron threshold of the neural network as follows: theta; calculating the first intermediate result, the excitation function and the neuron threshold to obtain a forward directionThe result of the neural network is:
calculating a training error of the forward neural network; the output variable E of the training is 'mine hole dust index', but a predicted value generated after model training is O, so that the obtained error function is as follows:
wherein m represents the number of the input modeling samples at this time, and i represents the ith variable; the update weight w is propagated backwards; reversely transmitting data from the output layer to the input layer, readjusting the value of the weight w until the model error reaches the minimum, and stopping training to complete model creation; data analysis was performed using the generative model.
The mining dust concentration sensor, the sensor system and the method have the following beneficial effects: the problem of reduced induction accuracy caused by interference of the emitted light wave on the reflected light wave is solved by processing the emitted light wave and the reflected light wave of the sensor; meanwhile, a unique sensor system is constructed for the mine cavity environment, the mine cavity environment is better adapted, and the monitoring accuracy is improved. The method is mainly realized by the following steps: 1. direct light wave filtering and reflected light wave conversion are adopted, so that the inaccuracy of dust monitoring caused by interference of reflected light by direct light is avoided; 2. electromagnetic shielding shell: the electromagnetic shielding shell is used for the sensor shell, so that the problem of inaccurate dust monitoring caused by electromagnetic interference is effectively avoided; meanwhile, aiming at the sensor system, the shielding shells with the same structure are used for removing electromagnetic interference; 3. sensor system without dead angle: according to the invention, the sensors are arranged in a complicated manner, the dust monitoring is carried out by using sensor tuples, 5 sensors which work in cooperation with each other are arranged in the sensor tuples, and the sensors monitor the same monitoring area pairwise, so that the monitoring accuracy is ensured; 4. and (3) carrying out data analysis on the sensed data: the invention corrects the data error and analyzes the data aiming at the sensed data, so that the final sensing result is more accurate.
Drawings
Fig. 1 is a schematic structural diagram of a dust concentration sensor unit according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a sensing method according to an embodiment of the present invention.
FIG. 3 is a schematic structural diagram of a sensor cell provided in an embodiment of the present invention;
fig. 4 is a schematic diagram of an experiment curve of dust monitoring accuracy rate varying with experiment times of the mine dust concentration sensor, the sensor system and the method provided by the embodiment of the invention, and a schematic diagram of a comparison experiment effect in the prior art.
The method comprises the following steps of 1-sensor, 2-monitoring area, 3-shielding pool, 4-tuple processor, 5-sensor shell I, 6-sensor shell II, 7-first shielding shell electromagnetic shielding structure and 8-second shielding shell electromagnetic shielding structure.
Detailed Description
The method of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments of the invention.
Example 1
As shown in fig. 1, a mining dust concentration sensor, the sensor comprises: the dust concentration sensor comprises a sensor shell, a dust concentration sensor unit and an energy supply unit; the dust concentration sensor unit and the energy supply unit are both arranged in the sensor shell; the energy supply unit is used for supplying energy to the dust concentration sensor unit; characterized in that the dust concentration sensor unit includes: a transmitting unit, a receiving unit and an analyzing unit; the transmitting unit comprises a first transmitting unit and a second transmitting unit, and after the first transmitting unit and the second transmitting unit both transmit light waves, the receiving unit receives the reflected light waves and the direct light waves; and the analysis unit sequentially performs the steps of direct light wave filtering, reflected light wave conversion and frequency spectrum drawing according to the received reflected light wave and the received direct light wave.
By adopting the technical scheme, the sensor processes the transmitting light wave and the reflected light wave, so that the problem of reduced sensing accuracy caused by interference of the transmitting light wave on the reflected light wave is solved; meanwhile, a unique sensor system is constructed for the mine cavity environment, the mine cavity environment is better adapted, and the monitoring accuracy is improved. The method is mainly realized by the following steps: 1. direct light wave filtering and reflected light wave conversion are adopted, so that the inaccuracy of dust monitoring caused by interference of reflected light by direct light is avoided; 2. electromagnetic shielding shell: the electromagnetic shielding shell is used for the sensor shell, so that the problem of inaccurate dust monitoring caused by electromagnetic interference is effectively avoided; meanwhile, aiming at the sensor system, the shielding shells with the same structure are used for removing electromagnetic interference; 3. sensor system without dead angle: according to the invention, the sensors are arranged in a complicated manner, the dust monitoring is carried out by using sensor tuples, 5 sensors which work in cooperation with each other are arranged in the sensor tuples, and the sensors monitor the same monitoring area pairwise, so that the monitoring accuracy is ensured; 4. and (3) carrying out data analysis on the sensed data: the invention corrects the data error and analyzes the data aiming at the sensed data, so that the final sensing result is more accurate.
Example 2
On the basis of the above embodiment, the direct optical wave filtering performs the following steps: calculating the time delay between the direct light wave of the first transmitting unit and the direct light wave of the second transmitting unit received by the receiving unit through Laplace transform by using the following formula:
wherein S is1(t) is the direct light wave of the first emission unit, PS1(t)]For its corresponding laplace transform; s2(t) is the direct light wave of the second emission unit, P*[S2(t)]A conjugate transform that is its corresponding laplace transform; f is P [ S ]1(t) and P*[S2(t)]Corresponding frequency, x is the unknown quantity of the laplace transform; and then, calculating the cross-correlation coefficient between the direct light wave of the first emission unit and the direct light wave of the second emission unit:
wherein the content of the first and second substances,
denotes S2(t) inverse laplacian transform; will be provided with
Amplifying by c times to obtain a reflected light wave after filtering the direct light wave:
example 3
On the basis of the above embodiment, the method for converting reflected light waves performs the following steps: the reflected light wave is represented by the following formula:
wherein α is an amplitude constant, fcIs a carrier frequency, MsIs a period, tau (t) is a time delay parameter, B is a bandwidth, N1Is a rate constant, set to 1.5; the reflected light waves are converted to baseband signals by the following equation:
performing laplace transform on the baseband signal to obtain a frequency spectrum, wherein according to the frequency spectrum, the phase of the baseband signal is obtained as follows: phi (t) ═ 0.8 pi fcτ(t)。
In particular, spectral analysis is a technique for decomposing a complex signal into simpler signals. Many physical signals can be represented as the sum of many simple signals of different frequencies. The spectral analysis is performed to find information (e.g., amplitude, power, strength, or phase) of a signal at different frequencies.
The light source is composed of different colors, the light of each color has different frequency, and the occupied proportion may also be different. The triple prism refracts light of different frequencies to different positions by means of refraction, so that light of different colors can be seen. Similarly, a common light source may be treated with a prism to project a continuous or discontinuous band of colored light. The color of a band of light indicates its frequency, while the light and dark can indicate how much of its proportion is, which is the spectrum of light, commonly referred to as the spectrum. If the color contents of all frequencies are a sample, the resultant color will be white, and the spectrum whose amplitude corresponds to the frequency will be a horizontal line. Signals with a horizontal line of the spectrum will therefore be generally referred to as "white".
Example 4
On the basis of the previous embodiment, the sensor shell consists of two layers of same electromagnetic shielding structures; the electromagnetic shielding structure includes: a substrate, and a metal foil wrapped around the substrate, wherein the substrate comprises a top surface, a bottom surface, and a plurality of sidewalls, wherein the metal foil covers only the top surface and the plurality of sidewalls of the substrate; the metal foil has opposing first and second surfaces, wherein the first surface is located over the substrate.
Specifically, in the sensor shell, the substrate and the metal foil jointly form an electromagnetic shielding structure; the two layers of electromagnetic shielding structures are respectively a first electromagnetic shielding structure 5 and a second electromagnetic shielding structure 6.
Example 5
A sensor system, the system comprising: a plurality of sensor tuples and analysis processors which are uniformly distributed in the mine hole; the sensor tuple includes: 5 sensors 1 uniformly distributed on the circumference with the same center; the circle center position is provided with a tuple processor 4; the tuple processor 4 is respectively in signal connection with all the sensors 1; a shielding pool 3 is arranged outside the tuple processor 4 in a surrounding manner; the circumference is a shielding shell; the tuple processor 4 is in signal connection with the analysis processor, and is configured to perform analog-to-digital conversion on the data sensed by the sensor and send the data to the analysis processor.
Specifically, every two adjacent sensors monitor one monitoring area 2 together, and the dust concentration condition in the monitoring area 2 is monitored by the two sensors together.
Example 6
On the basis of the previous embodiment, the shielding shell has the same structure as the sensor shell; the shielding pool 3 is formed by a plurality of same structures which are stacked and surrounded by the same circle center.
Specifically, the sensor housing, like the sensor housing, includes a sensor housing I5 and a sensor housing II6, and the shielding housing is also composed of two layers of electromagnetic shielding structures. The substrate and the metal foil jointly form an electromagnetic shielding structure; the two layers of electromagnetic shielding structures are a first shielding shell electromagnetic shielding structure 7 and a second shielding shell electromagnetic shielding structure 8 respectively.
Example 7
On the basis of the previous embodiment, the analysis processor performs the following processing on the received data in sequence: performing data preprocessing, including: removing the unique attribute, processing missing values and abnormal value detection and processing; and carrying out data specification processing, including: removing an average value, calculating a covariance matrix, calculating an eigenvalue and an eigenvector of the covariance matrix, sorting the eigenvalues from large to small, reserving the largest eigenvector, and converting data into a new space constructed by the eigenvector; finally, new processed data are obtained, and the data are irrelevant pairwise, but the original information is kept; carrying out data standardization processing, and scaling the data in proportion to enable the data to fall into a specific interval; and carrying out data analysis on the data subjected to the data standardization processing to obtain a dust monitoring result.
In particular, the original data should be audited mainly from the aspects of completeness and accuracy. The integrity check mainly checks whether units or individuals to be checked have omission or not and whether all the check items or indexes are complete or not. The accuracy audit mainly comprises two aspects: firstly, whether the data material truly reflects the objective actual condition and whether the content accords with the reality is checked; and secondly, checking whether the data has errors or not, calculating whether the data is correct or not, and the like. The method for checking the data accuracy mainly comprises logic check and calculation check. The logical check mainly checks whether the data is in accordance with the logic, whether the content is reasonable and whether the items or the numbers have the phenomenon of mutual contradiction. The calculation check is to check whether each item of data in the questionnaire has errors in calculation results and calculation methods, and is mainly used for checking quantitative (numerical type) data.
For the second-hand data obtained through other channels, besides checking the integrity and accuracy of the second-hand data, the applicability and timeliness of the data should be emphasized. Second-hand data can come from a variety of sources, some of which may have been obtained through special investigation for a particular purpose or have been processed as required for a particular purpose. For the user, it should be clear first of all the source of the data, the aperture of the data and the related background data, so as to determine whether these data meet the needs of self-analysis and research, whether rework and so on are needed, and the hard cover can not be handled blindly. In addition, the timeliness of the data is also checked, and for some problems with strong timeliness, if the acquired data is too late, the significance of research may be lost. In general, the most up-to-date statistics should be used as much as possible. After the data is audited, the data is confirmed to be suitable for actual needs, and further processing and arrangement are necessary.
Example 8
A method, the method performing the steps of:
step 1: the sensors are grouped into a group by 5, the sensors and a tuple processor 4 jointly form a sensor tuple, and the sensor tuple is uniformly distributed in the mine hole;
step 2: and the analysis processor receives the data sensed by the sensor, and performs data analysis on the received data to complete dust monitoring in the mine hole.
Example 9
On the basis of the previous embodiment, 5 sensors are in a group and are uniformly distributed on the circumference with the same circle center; the tuple processor 4 is arranged at the position of the circle center; the tuple processor 4 is surrounded by 3; the circumference is a shielding shell; and the tuple processor 4 is in signal connection with the analysis processor, and sends the data sensed by the sensor to the analysis processor after performing analog-to-digital conversion on the data.
Example 10
On the basis of the above embodiment, the step 2: the analysis processor receives data sensed by the sensor, performs data analysis on the received data, and completes the dust monitoring method in the mine hole to execute the following steps: obtaining training sensory data for modeling as input variables using xiRepresenting, wherein i represents the ith variable in the data; setting a weight function of wiExpressing, performing convolution operation on each input variable and the corresponding weight function to obtain a first intermediate result; setting an excitation function, wherein the excitation function is as follows:
setting the neuron threshold of the neural network as follows: theta; and operating the first intermediate result, the excitation function and the neuron threshold value to obtain a result of the forward neural network, wherein the result is as follows:
calculating a training error of the forward neural network; the output variable E of the training is 'mine hole dust index', but a predicted value generated after model training is O, so that the obtained error function is as follows:
wherein m represents the number of the input modeling samples at this time, and i represents the ith variable; the update weight w is propagated backwards; reversely transmitting data from the output layer to the input layer, readjusting the value of the weight w until the model error reaches the minimum, and stopping training to complete model creation; data analysis was performed using the generative model.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process and related description of the system described above may refer to the corresponding process in the foregoing method embodiments, and will not be described herein again.
It should be noted that, the system provided in the foregoing embodiment is only illustrated by dividing the functional modules, and in practical applications, the functions may be distributed by different functional modules according to needs, that is, the modules or steps in the embodiment of the present invention are further decomposed or combined, for example, the modules in the foregoing embodiment may be combined into one module, or may be further split into multiple sub-modules, so as to complete all or unit functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not to be construed as unduly limiting the present invention.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes and related descriptions of the storage device and the processing device described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Those of skill in the art would appreciate that the various illustrative modules, method steps, and modules described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that programs corresponding to the software modules, method steps may be located in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. To clearly illustrate this interchangeability of electronic hardware and software, various illustrative components and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as electronic hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The terms "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing or implying a particular order or sequence.
The terms "comprises," "comprising," or any other similar term are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.
Claims (8)
1. A mining dust concentration sensor, characterized in that the sensor comprises: the dust concentration sensor comprises a sensor shell, a dust concentration sensor unit and an energy supply unit; the dust concentration sensor unit and the energy supply unit are both arranged in the sensor shell; the energy supply unit is used for supplying energy to the dust concentration sensor unit; characterized in that the dust concentration sensor unit includes: a transmitting unit, a receiving unit and an analyzing unit; the transmitting unit comprises a first transmitting unit and a second transmitting unit, and after the first transmitting unit and the second transmitting unit both transmit light waves, the receiving unit receives the reflected light waves and the direct light waves; the analysis unit sequentially performs steps of direct light wave filtering, reflected light wave conversion and frequency spectrum drawing according to the received reflected light wave and the received direct light wave;
the direct light wave filtering performs the following steps: calculating the time delay between the direct light wave of the first transmitting unit and the direct light wave of the second transmitting unit received by the receiving unit through Laplace transform by using the following formula:
wherein S is1(t) is the direct light wave of the first emission unit, PS1(t)]For its corresponding laplace transform; s2(t) is the direct light wave of the second emission unit, P*[S2(t)]A conjugate transform that is its corresponding laplace transform; f is P [ S ]1(t) and P*[S2(t)]Corresponding frequency, x is the unknown quantity of the laplace transform; and then, calculating the cross-correlation coefficient between the direct light wave of the first emission unit and the direct light wave of the second emission unit:
wherein the content of the first and second substances,
denotes S2(t) inverse laplacian transform; will be provided with
Amplifying by c times to obtain a reflected light wave after filtering the direct light wave:
the method for reflected light wave conversion performs the following steps: the reflected light wave is represented by the following formula:
wherein α is an amplitude constant, fcIs a carrier frequency, MsIs a period, tau (t) is a time delay parameter, B is a bandwidth, N1Is a rate constant, set to 1.5; by such asThe reflected light waves are converted to baseband signals according to the following formula:
performing laplace transform on the baseband signal to obtain a frequency spectrum, wherein according to the frequency spectrum, the phase of the baseband signal is obtained as follows: phi (t) ═ 0.8 pi fcτ(t)。
2. The sensor of claim 1, wherein the sensor housing is comprised of two layers of identical electromagnetic shielding structures; the electromagnetic shielding structure includes: a substrate, and a metal foil wrapped around the substrate, wherein the substrate comprises a top surface, a bottom surface, and a plurality of sidewalls, wherein the metal foil covers only the top surface and the plurality of sidewalls of the substrate; the metal foil has opposing first and second surfaces, wherein the first surface is located over the substrate.
3. A sensor system based on a sensor according to any one of claims 1 to 2, characterized in that the system comprises: a plurality of sensor tuples and analysis processors which are uniformly distributed in the mine hole; the sensor tuple includes: 5 sensors uniformly distributed on the circumference with the same circle center; the circle center position is provided with a tuple processor; the tuple processor is respectively in signal connection with all the sensors; a shielding pool is arranged outside the tuple processor in a surrounding manner; the circumference is a shielding shell; the tuple processor is in signal connection with the analysis processor, and is configured to perform analog-to-digital conversion on data sensed by the sensor and send the data to the analysis processor.
4. The system of claim 3, wherein the shield housing is of the same construction as the sensor housing; the shielding pool is formed by a plurality of same structures which are stacked and surrounded by the same circle center.
5. The system of claim 3, wherein the analysis processor performs the following on the received data in sequence: performing data preprocessing, including: removing the unique attribute, processing missing values and abnormal value detection and processing; and carrying out data specification processing, including: removing an average value, calculating a covariance matrix, calculating an eigenvalue and an eigenvector of the covariance matrix, sorting the eigenvalues from large to small, reserving the largest eigenvector, and converting data into a new space constructed by the eigenvector; finally, new processed data are obtained, and the data are irrelevant pairwise, but the original information is kept; carrying out data standardization processing, and scaling the data in proportion to enable the data to fall into a specific interval; and carrying out data analysis on the data subjected to the data standardization processing to obtain a dust monitoring result.
6. A sensor method based on the system of claim 3, wherein the method performs the steps of:
step 1: the method comprises the following steps of (1) enabling 5 sensors to form a group together with a tuple processor to form sensor tuples, and uniformly distributing the sensor tuples inside a mine hole;
step 2: the analysis processor receives data sensed by the sensor, performs data analysis on the received data, and completes the dust monitoring method in the mine hole to execute the following steps: obtaining training sensory data for modeling as input variables using xiRepresenting, wherein i represents the ith variable in the data; setting a weight function of wiExpressing, performing convolution operation on each input variable and the corresponding weight function to obtain a first intermediate result; setting an excitation function, wherein the excitation function is as follows:
setting the neuron threshold of the neural network as follows: theta; and operating the first intermediate result, the excitation function and the neuron threshold value to obtain a result of the forward neural network, wherein the result is as follows:
calculating a training error of the forward neural network; the output variable E of the training is 'mine hole dust index', but a predicted value generated after model training is O, so that the obtained error function is as follows:
wherein m represents the number of the input modeling samples at this time, and i represents the ith variable; the update weight w is propagated backwards; reversely transmitting data from the output layer to the input layer, readjusting the value of the weight w until the model error reaches the minimum, and stopping training to complete model creation; data analysis was performed using the generative model.
7. The method of claim 6, wherein the sensors are grouped into 5 groups, evenly distributed on the circumference with the same center; the tuple processor is arranged at the position of the circle center; a shielding pool is arranged outside the tuple processor in a surrounding manner; the circumference is a shielding shell; and the tuple processor is in signal connection with the analysis processor, and sends the data sensed by the sensor to the analysis processor after performing analog-to-digital conversion on the data.
8. The method of claim 6, wherein the step 2: the analysis processor receives data sensed by the sensor, performs data analysis on the received data, and completes the dust monitoring method in the mine hole to execute the following steps: obtaining training sensory data for modeling as input variables using xiRepresenting, wherein i represents the ith variable in the data; setting a weight function of wiExpressing, performing convolution operation on each input variable and the corresponding weight function to obtain a first intermediate result; setting an excitation function, wherein the excitation function is as follows:
setting the neuron threshold of the neural network as follows: theta; and operating the first intermediate result, the excitation function and the neuron threshold value to obtain a result of the forward neural network, wherein the result is as follows:
calculating a training error of the forward neural network; the output variable E of the training is 'mine hole dust index', but a predicted value generated after model training is O, so that the obtained error function is as follows:
wherein m represents the number of the input modeling samples at this time, and i represents the ith variable; the update weight w is propagated backwards; reversely transmitting data from the output layer to the input layer, readjusting the value of the weight w until the model error reaches the minimum, and stopping training to complete model creation; data analysis was performed using the generative model.
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