A dust concentration monitoring system and method based on multi-sensor data fusion

Abstract

This application proposes a multi-sensor data fusion dust concentration monitoring system and method, relating to the field of dust concentration monitoring technology. The system includes: a laser emitting component, multiple laser receiving components, and a processing component. The laser emitting component comprises a rotation drive mechanism, a pitch drive mechanism, and a laser emitter. The laser emitting component sequentially emits lasers to each laser receiving component. Multiple laser receiving components are distributed at different locations in the space to be measured, with each location having the same number of laser receiving components. The laser receiving components generate measurement data based on the received lasers. The processing component determines a first probability assessment distribution of the safety level for each location based on the measurement data of the current measurement cycle, and performs fusion processing on the first probability assessment distribution using a preset first data fusion algorithm to obtain a fused evaluation of the target dust concentration. This monitoring system can achieve dust concentration monitoring and provide a safety risk assessment result.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of dust concentration monitoring, and particularly relates to a dust concentration monitoring system and method based on multi-sensor data fusion. BACKGROUND

[0002] Artificial board is a board or molded product formed by separating wood or non-wood plants into various unit materials through mechanical processing and then gluing or not gluing with adhesives and other additives. The application of such artificial board can effectively improve the comprehensive utilization rate of wood, can extend products and deep-processed products to hundreds of kinds, and also marks the beginning of the modern era of wood processing. At present, a large amount of wood dust is generated in the production process of artificial board, which not only occupies a large amount of land area, but also pollutes the environment and is easy to cause fire.

[0003] At present, the traditional dust concentration monitoring methods include a weighing method, a beta ray method and an electric charge method. The weighing method sets a filter membrane in a pipeline, and a gas pump is used to pump gas into the pipeline. When the dust-containing gas passes through the filter membrane, the dust is intercepted on the filter membrane, and the dust concentration can be obtained by weighing the mass difference of the filter membrane before and after. The method needs manual replacement of the filter membrane, and the measurement efficiency is low. The beta ray method uses the characteristic that the intensity of the ray is reduced after the dust absorbs the ray, and the dust concentration is calculated by measuring the intensity difference of the ray. The method needs expensive equipment, and the beta ray generated is a radioactive ray, which needs strict management during use. The electric charge method uses the principle that the dust particles generate electricity when passing through the measurement sensor, and estimates the dust concentration by detecting the electric charge of the charged particles. However, the artificial board dust is mainly composed of organic matter, and has weak charging capacity and large changes with the environmental humidity, so it is not suitable for measurement by this method. SUMMARY

[0004] Therefore, the present application provides a dust concentration monitoring system and method based on multi-sensor data fusion.

[0005] In a first aspect, the present application provides a dust concentration monitoring system based on multi-sensor data fusion, comprising: a laser emission assembly, a plurality of laser receiving assemblies and a processing assembly.

[0006] The laser emission assembly comprises a rotating driving mechanism, a pitching driving mechanism and a laser emitter, the laser emitter is arranged on the pitching driving mechanism, the rotating driving mechanism is used to drive the pitching driving mechanism to rotate, so as to synchronously drive the laser emitter to rotate, and the pitching driving mechanism is used to adjust the pitch angle of the laser emitter; wherein the laser emission assembly emits laser to each laser receiving assembly in a predetermined sequence in a measurement cycle.

[0007] A plurality of the laser receiving assemblies are distributed in different directions of the to-be-measured space, each direction of the to-be-measured space has the same number of laser receiving assemblies, and the laser receiving assemblies are configured to generate measurement data according to received laser;

[0008] The processing assembly is configured to acquire the measurement data output by each of the laser receiving assemblies, determine a first probability evaluation distribution of the safety level of each direction according to each of the measurement data of the current measurement period, perform fusion processing on the first probability evaluation distribution by using a preset first data fusion algorithm, obtain a target dust concentration fusion evaluation, and determine the target dust concentration fusion evaluation as the safety level evaluation of the current measurement period.

[0009] In an embodiment, the processing assembly is further configured to, when the number of measurement rounds corresponding to the current measurement period is not less than two, acquire each of the measurement data of the current measurement period and a previous measurement period, and determine the dust concentration change direction of the detection area of each of the laser receiving assemblies according to the acquired each of the measurement data.

[0010] In an embodiment, the processing assembly is further configured to, when the number of measurement rounds corresponding to the current measurement period is not less than three, acquire the measurement data of the current measurement period and the previous two measurement periods, determine a second probability evaluation distribution of the dust concentration change trend of each direction according to the acquired each of the measurement data, perform fusion processing on the second probability evaluation distribution by using a preset second data fusion algorithm, obtain a target fusion evaluation of the dust concentration change trend, and determine the target fusion evaluation of the dust concentration change trend as the dust concentration change trend of the current measurement period.

[0011] In an embodiment, the processing assembly is further configured to determine a control suggestion or a control strategy according to the safety level evaluation and the dust concentration change trend of the current measurement period and a preset control strategy table, and correspondingly output the control suggestion or execute the control strategy.

[0012] In an embodiment, the processing assembly is further configured to, based on a direction processing sequence, take a first sequence direction and a second sequence direction as a first direction and a second direction respectively, perform a first fusion processing operation, and obtain a target dust concentration fusion probability evaluation, the target dust concentration fusion probability evaluation including a probability distribution of different safety levels; and determine a safety level corresponding to a maximum probability in the target dust concentration fusion probability evaluation as the target dust concentration fusion evaluation.

[0013] The first fusion processing operation includes: fusing the probability assessment of the first orientation and the second orientation safety level to obtain a dust concentration fusion probability assessment of the first orientation and the second orientation; taking the dust concentration fusion probability assessment of the first orientation and the second orientation as a new first orientation safety level probability assessment, and taking a next sequence orientation as a new second orientation; repeating the above processing procedure until the probability assessment of the safety level of all orientations is fused.

[0014] In an embodiment, the probability assessment of the safety level of the orientation i is:

[0015]

[0016] wherein O is the number of laser receiving components contained in the orientation i, m i (S), m i (R) and m i (D) are the probability assessments of the relative safety, general safety and relative danger of the safety level corresponding to the orientation i, respectively, the measurement data output by the laser receiving components are used to assess the safety level, s i is the number of laser receiving components corresponding to the relative safety in the orientation i, r i is the number of laser receiving components corresponding to the general safety in the orientation i, and d i is the number of laser receiving components corresponding to the relative danger in the orientation i.

[0017] The calculation formula for fusing the probability assessments of the initial first orientation and the initial second orientation is:

[0018]

[0019] wherein m1(S), m1(R) and m1(D) are the probability assessments of the safety level of the initial first orientation, m2(S), m2(R) and m2(D) are the probability assessments of the safety level of the initial second orientation, m 12 (S), m 12 (R) and m 12 (D) are the dust concentration fusion probability assessments of the first orientation and the second orientation, s1 is the number of laser receiving components corresponding to the relative safety in the first orientation, r1 is the number of laser receiving components corresponding to the general safety in the first orientation, d1 is the number of laser receiving components corresponding to the relative danger in the first orientation, s2 is the number of laser receiving components corresponding to the relative safety in the second orientation, r2 is the number of laser receiving components corresponding to the general safety in the second orientation, d2 is the number of laser receiving components corresponding to the relative danger in the second orientation, and K 12 is the first conflict coefficient, and the calculation formula of the first conflict coefficient is:

[0020]

[0021] After performing the first fusion processing operation, a calculation formula of a target dust concentration fusion probability evaluation is as follows:

[0022]

[0023] wherein n is the number of azimuths, is a relative safety fusion probability evaluation corresponding to the first n-1 azimuths, is a general safety fusion probability evaluation corresponding to the first n-1 azimuths, is a relative danger fusion probability evaluation corresponding to the first n-1 azimuths, m 12…n is a relative safety fusion probability evaluation corresponding to the first n azimuths, m 12…n is a general safety fusion probability evaluation corresponding to the first n azimuths, m 12…n is a relative danger fusion probability evaluation corresponding to the first n azimuths, s n is the number of laser receiving components corresponding to the relative safety in the azimuth n, r n is the number of laser receiving components corresponding to the general safety in the azimuth n, d n is the number of laser receiving components corresponding to the relative danger in the azimuth n; and a calculation formula of the target dust concentration fusion evaluation is as follows:

[0024] Mi=argmax(m 12…n (S),m 12…n (R),m 12…n (D));

[0025] wherein K 12…n is a second conflict coefficient, and a calculation formula of the second conflict coefficient is as follows:

[0026]

[0027] In an embodiment, the processing component is further configured to perform a second fusion processing operation based on the azimuth processing sequence, taking the first sequence azimuth and the second sequence azimuth as the first azimuth and the second azimuth respectively, to obtain a target change trend fusion probability evaluation including a probability distribution corresponding to different trends, and determine a change trend corresponding to a maximum probability in the target change trend fusion probability evaluation as a target fusion evaluation of the dust concentration change trend.

[0028] The second fusion processing operation includes: fusing the probability evaluation of the dust concentration change trend of the first orientation and the second orientation to obtain a change trend fusion probability evaluation of the first orientation and the second orientation; taking the change trend fusion probability evaluation of the first orientation and the second orientation as a new first orientation dust concentration change trend probability evaluation, and taking a next sequential orientation as a new second orientation; and repeating the above processing procedure until the probability evaluation of the dust concentration change trend of all orientations is fused.

[0029] In an embodiment, the probability evaluation of the dust concentration change trend of the orientation i is:

[0030]

[0031] wherein O is the number of laser receiving components contained in the orientation i, m i (B), m i (P) and m i (G) are respectively the probability evaluation of the orientation i corresponding to aggravating rise, relative stability and aggravating decline, the measurement data output by the laser receiving components in at least three measurement periods is used for evaluating the change trend, b i is the number of laser receiving components corresponding to aggravating rise in the orientation i, p i is the number of laser receiving components corresponding to relative stability in the orientation i, g i is the number of laser receiving components corresponding to aggravating decline in the orientation i;

[0032] The calculation formula for fusing the probability evaluation of the initial first orientation and the initial second orientation is:

[0033]

[0034] wherein m1(B), m1(P) and m1(G) are the probability evaluation of the dust concentration change trend of the initial first orientation, m2(B), m2(P) and m2(G) are the probability evaluation of the dust concentration change trend of the initial second orientation, m 12 (B), m 12 (P) and m 12 (G) are the change trend fusion probability evaluation of the first orientation and the second orientation, b1 is the number of laser receiving components corresponding to aggravating rise in the first orientation, p1 is the number of laser receiving components corresponding to relative stability in the first orientation, g1 is the number of laser receiving components corresponding to aggravating decline in the first orientation, b2 is the number of laser receiving components corresponding to aggravating rise in the second orientation, p2 is the number of laser receiving components corresponding to relative stability in the second orientation, g2 is the number of laser receiving components corresponding to aggravating decline in the second orientation, and K' 12 is a third conflict coefficient, and the calculation formula of the third conflict coefficient is:

[0035]

[0036] After performing the second fusion processing operation, the calculation formula of the target dust concentration fusion probability evaluation is:

[0037]

[0038] Wherein, n is the number of azimuths, is the fusion probability evaluation corresponding to the aggravating rise of the previous n-1 azimuths, is the fusion probability evaluation corresponding to the relative stability of the previous n-1 azimuths, is the fusion probability evaluation corresponding to the aggravating decline of the previous n-1 azimuths, m 12…n (B) is the fusion probability evaluation corresponding to the aggravating rise of the previous n azimuths, m 12…n (P) is the fusion probability evaluation corresponding to the relative stability of the previous n azimuths, m 12…n (G) is the fusion probability evaluation corresponding to the aggravating decline of the previous n azimuths, b n is the number of laser receiving components corresponding to the aggravating rise in the azimuth n, p n is the number of laser receiving components corresponding to the relative stability in the azimuth n, g n is the number of laser receiving components corresponding to the aggravating decline in the azimuth n; the calculation formula of the target change trend fusion probability evaluation is:

[0039] MBi=argmax(m 12…n (S),m 12…n (R),m 12…n (D));

[0040] Wherein, K′ 12…n is the fourth conflict coefficient, and the calculation formula of the fourth conflict coefficient is:

[0041]

[0042] In an embodiment, the laser receiving component includes a light trap, a photoelectric sensor, a directional light shield, and a single-chip microcomputer, the light trap is located in the directional light shield, the light receiving surface of the light trap faces the opening of the directional light shield, and the opening of the directional light shield faces the laser emitting component; the photoelectric sensor is connected with the single-chip microcomputer, the photoelectric sensor is used for receiving the light transmitted by the light trap, outputting a measurement electric signal according to the received light, and the single-chip microcomputer is used for generating the measurement data according to the measurement electric signal.

[0043] In a second aspect, the application further provides a dust concentration monitoring method based on multi-sensor data fusion, the dust concentration monitoring method based on multi-sensor data fusion applying the dust concentration monitoring system according to the first aspect, and the dust concentration monitoring method based on multi-sensor data fusion comprising the following steps:

[0044] acquiring the measurement data output by each laser receiving assembly;

[0045] determining a first probability evaluation distribution of the safety level of each orientation according to the measurement data of the current measurement period;

[0046] performing fusion processing on the first probability evaluation distribution by using a preset first data fusion algorithm to obtain a target dust concentration fusion evaluation, and determining the target dust concentration fusion evaluation as the safety level evaluation of the current measurement period.

[0047] The dust concentration monitoring system based on multi-sensor data fusion according to the application has the following beneficial effects relative to the related art:

[0048] 1. The dust concentration monitoring system according to the application can measure the dust concentration of artificial boards by using the light scattering method through the cooperation of the laser emitting assembly and the laser receiving assembly. Since the dust concentration in the space to be measured can change at any time and is not uniformly distributed in the limited working space, it is suitable to use this method to monitor the dust concentration. The method can calculate the dust concentration by using the Mie scattering theory based on the scattering effect generated when the laser interacts with the dust particles, and has the advantages of real-time monitoring and high sensitivity.

[0049] 2. The laser emitting assembly according to the application can adjust the pose of the laser emitter by rotation and pitch adjustment, so that one laser emitting assembly can be used to pair with multiple laser receiving assemblies, and multiple sets of transmitting and receiving systems do not need to be arranged, thereby simplifying the dust concentration monitoring system and reducing the cost of the dust concentration monitoring system. In addition, after the orientations of the laser receiving assemblies are determined, the pose adjustment path of the laser emitting assembly can be set, and the laser emitting assembly can automatically adjust the pose and emit laser, so that automatic and real-time monitoring of the dust concentration can be realized, and the measurement efficiency is high.

[0050] 3. The dust concentration monitoring method based on multi-sensor data fusion according to the application determines a first probability evaluation distribution of the safety level of each orientation according to the measurement data of the current measurement period, performs fusion processing on the first probability evaluation distribution by using a preset first data fusion algorithm to obtain a target dust concentration fusion evaluation, and determines the target dust concentration fusion evaluation as the safety level evaluation of the current measurement period, so that the data of multiple measurement points are fused to obtain a more universal and representative safety risk evaluation result, which provides a reliable reference for subsequent adjustment. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the following will briefly introduce the drawings needed to be used in the embodiments or the related art description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0052] Figure 1 Structure diagram of a dust concentration monitoring system with multi-sensor data fusion in an embodiment of the present application;

[0053] Figure 2 Sectional structure diagram of a laser emitting assembly in an embodiment of the present application;

[0054] Figure 3 Top view of a laser emitting assembly in an embodiment of the present application;

[0055] Figure 4 Flowchart of multi-round evaluation of a dust concentration monitoring system with multi-sensor data fusion in an embodiment of the present application;

[0056] Figure 5 Flowchart of a dust concentration monitoring method with multi-sensor data fusion in an embodiment of the present application. DETAILED DESCRIPTION

[0057] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the embodiments of the present application. Obviously, the described embodiments only constitute some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0058] In some embodiments, as shown in Figure 1 A dust concentration monitoring system with multi-sensor data fusion provided by the present application includes a laser emitting assembly 1, a plurality of laser receiving assemblies 2, and a processing assembly 3.

[0059] The laser emitting assembly 1 includes a rotation driving mechanism, a pitch driving mechanism, and a laser emitter. The laser emitter is arranged on the pitch driving mechanism. The rotation driving mechanism is used to drive the pitch driving mechanism to rotate, so as to synchronously drive the laser emitter to rotate. The pitch driving mechanism is used to adjust the pitch angle of the laser emitter. The laser emitting assembly 1 emits laser to each laser receiving assembly 2 in a predetermined order. Through the cooperation of the rotation driving mechanism and the pitch driving mechanism, the laser emitter can emit laser to any direction, so that the laser emitting assembly 1 can emit laser to the plurality of laser receiving assemblies 2.

[0060] In the application, the laser emitting assembly 1 can irradiate each laser receiving assembly 2 in turn according to the orientation and serial number of the laser receiving assembly 2, and at this time the corresponding laser receiving assembly 2 also synchronously performs data acquisition. If the data acquisition time of a single laser receiving assembly 2 plus the preset time for the laser rotating platform to move to the next laser receiving assembly 2 is t, and the number of laser receiving assemblies 2 is m, then the time required for the entire system to complete a round of measurement (i.e., a round of measurement period) is T = m · t.

[0061] The plurality of laser receiving assemblies 2 are distributed at different orientations of the to-be-measured space, each orientation of the to-be-measured space has the same number of laser receiving assemblies 2, and the laser receiving assembly 2 is used to generate measurement data according to the received laser.

[0062] It should be noted that when the light beam passes through a non-uniform medium, part of the light beam will deviate from the original direction and disperse, and the phenomenon of light can also be seen from the side, which is called light scattering. Light scattering is divided into Rayleigh scattering and Mie scattering. When the particle size of the scattering particles is much smaller than the wavelength of the light, it belongs to Rayleigh scattering, at this time the intensity of the scattered light is uniform in all directions, and it is inversely proportional to the fourth power of the incident wavelength; when the particle size of the scattering particles is equal to or greater than the wavelength of the incident light, it belongs to Mie scattering, at this time the intensity of the scattered light is related to the scattering angle, and has no dependence on the wavelength of the incident light. The wood dust suspended in the air is larger than the wavelength of light, and when the laser emitted by the laser source passes through the dust cloud, Mie scattering will occur.

[0063] When the light beam generated by the laser emitter is an approximately ideal light beam, and the light beam passes through the suspended particulate matter and Mie scattering occurs. According to the principle of Mie scattering, the number N of dust particles in the scattering area and the light intensity IS after scattering satisfy the relationship:

[0064]

[0065] Formula (1) uses IS as the intensity of the scattered light, measured by the laser receiver. K is the complex scattering coefficient of the dust particle group, representing the refraction and absorption characteristics during propagation in wood materials. Its value is related to the type of wood, the particle size and shape of dust generated by different lathes and processes, the ambient humidity, and the wavelength of the incident light. This parameter can be expressed by the formula K = n0 - m0i, where n0 is the real part of the complex scattering coefficient. Since the refraction of light by wood fibers and the main components of wood (such as cellulose and lignin) is relatively weak, its range is usually between 1.4 and 1.6; m0 is the imaginary part of the complex scattering coefficient. Since the absorption capacity of wood dust is limited (especially in the visible light band), its range is usually between 0.01 and 0.1. N is the number of dust particles in the scattering region, which is an unknown quantity to be determined. II is the intensity of the incident light, and λ is the wavelength of the incident light. Both parameters are determined when the laser source is selected. d is the distance from the scattering point to the photoelectric sensor in the laser receiving component 2. This parameter is determined after the laser transmitter and receiver are installed and fixed, for example, it can be 0.05m.

[0066] When the measurement area is located in a dark room and the measurement distance is relatively short, the required incident light intensity is low. For example, a laser emitter with a power of 1mW and a beam diameter of 1mm can be used, with a light intensity of approximately 70W / m². 2 When the measurement area is placed within the entire working range and the measurement distance is long, the required light intensity also needs to be higher. For example, a laser emitter with a power of 10mW and a beam diameter of 1mm can be used, with a light intensity of approximately 700W / m. 2 According to Mie scattering theory, scattering weakens when the wavelength differs significantly from the particle size of the dust, making it unsuitable for measuring scattered light. Since wood dust consists of large particles, a longer wavelength laser emitter, such as an infrared or red laser emitter, is preferable. For example, a 650nm (red) laser emitter can be used.

[0067]

[0068] Here, S1(θ) and S2(θ) are amplitude functions, which are related to the Bessel function and the Hankel function.

[0069] θ is the angle between the scattered light and the z-axis. Let θ be the angle between the scattered light and the x-axis. Since the laser emitter and receiver are located on the same plane, and a method is adopted to measure the scattered light at a 90-degree angle, then θ is 90 degrees. It is 0 degrees.

[0070] As can be seen from the above, when the parameters K, I I ,d,λ,θ, When all parameters are determined, the intensity of the scattered light is directly proportional to the number of dust particles in the area, and consequently, to the dust concentration in the area. By selecting appropriate positions and angles to measure the intensity of the scattered light, the dust concentration in the scattering area can be accurately characterized. Therefore, based on the Mie scattering principle, the dust concentration in a corresponding area can be measured by using laser emitting component 1 and multiple laser receiving components 2 in conjunction.

[0071] The processing component 3 is used to acquire the measurement data output by each laser receiving component 2, determine the first probability assessment distribution of the safety level in each direction based on the measurement data of the current measurement cycle, perform fusion processing on the first probability assessment distribution using a preset first data fusion algorithm, obtain the target dust concentration fusion evaluation, and determine the target dust concentration fusion evaluation as the safety level evaluation of the current measurement cycle.

[0072] It should be noted that the process of calculating the dust concentration in the corresponding area can be completed using either the laser receiving component 2 or the processing component 3.

[0073] It is understood that the dust concentration in the detection space corresponding to each laser receiving component 2 can be determined based on the measurement data of each laser receiving component 2. Based on this, a safety assessment can be conducted according to the dust concentration assessment standard, yielding the corresponding safety assessment result. The dust concentration assessment standard can be specified according to relevant national safety regulations and the safety standards of each manufacturer. For example, the safety standard can be set as shown in Table 1.

[0074] Table 1 shows the safety assessment standards for dust concentration.

[0075]

[0076] Since the number of laser receivers is the same in each direction, the number o of laser receiver components 2 in a single direction is:

[0077]

[0078] In formula (3), m represents the total number of laser receiving components 2, and n represents the number of azimuths. Since each azimuth has o data points, and each data point has already received a safety assessment based on the dust concentration safety assessment standard, the safety assessment for a single azimuth can be calculated based on the number of each assessment. The safety assessment statistics table for azimuth i is shown below.

[0079] Table 2 is a statistical table of safety evaluation for orientation i.

[0080]

[0081] Where: s i +r i +d i =o(4)

[0082] Based on the safety assessment statistics of dust concentration in various locations, the corresponding basic probability functions can be derived. The first probability assessment distribution of the safety level in each location is shown in Table 3.

[0083] Table 3 shows the first probability assessment distribution of security levels in each direction.

[0084]

[0085]

[0086] After obtaining the first probability assessment distribution of the safety level in each direction, a preset first data fusion algorithm is used to fuse the first probability assessment distribution to obtain the target dust concentration fusion evaluation. This target dust concentration fusion evaluation is then determined as the safety level evaluation for the current measurement period, thereby determining the safety level evaluation of the space under test and ultimately determining whether the space under test is safe. It should be noted that the first data fusion algorithm can be a data fusion algorithm based on DS evidence theory.

[0087] This application utilizes the cooperation of a laser emitting component 1 and a laser receiving component 2 to measure the concentration of wood dust in engineered wood products using the light scattering method. Since the concentration of wood dust in the measurement space changes constantly and is not uniformly distributed within a limited working space, this method is suitable for dust concentration monitoring. This method leverages the scattering effect generated when laser light interacts with dust particles, and the dust concentration can be calculated using Mie scattering theory, offering advantages such as real-time monitoring and high sensitivity. Furthermore, the laser emitting component 1 can adjust its position through rotation and pitch adjustment, allowing one laser emitting component 1 to be paired with multiple laser receiving components 2, eliminating the need for multiple sets of transmission and reception systems, thus simplifying the dust concentration monitoring system and reducing its cost. After determining the orientation of each laser receiving component 2, the position adjustment path of the laser emitting component 1 can be set. The laser emitting component 1 can automatically adjust its position and emit laser light, enabling automatic and real-time monitoring of dust concentration with high measurement efficiency. Processing component 3 integrates the target dust concentration evaluation to determine the safety level evaluation for the current measurement cycle, thereby fusing data from multiple measurement points to obtain a more universal and representative safety risk evaluation result, providing a reliable reference for subsequent adjustments.

[0088] In some embodiments, such as Figure 2 and Figure 3As shown, the laser emitting assembly 1 may also include a base 14, and a rotation drive mechanism 11 may be disposed within the base 14. The base 14 may be equipped with the power supply system and control system for the entire laser emitting assembly 1. The control system may control the rotation drive mechanism 11 to drive the pitch drive mechanism 12 to rotate, and the control system may also control the pitch drive mechanism 12 to adjust the pitch angle of the laser emitter 13.

[0089] In applications, the laser emitting assembly 1 may further include a rectangular housing 15, with the pitch drive mechanism 12 disposed within the rectangular housing 15, and the laser emitter 13 may be partially located within the rectangular housing 15. The rectangular housing 15 provides protection for the pitch drive mechanism 12 and the laser emitter 13.

[0090] In one example, the rotation drive mechanism 11 may include a first stepper motor 111 and a main shaft 112. The motor shaft of the first stepper motor 111 may be driveably connected to the main shaft 112. For example, the motor shaft of the first stepper motor 111 may be driveably connected to the main shaft 112 via gears. The main shaft 112 is connected to the pitch drive mechanism 12. The first stepper motor 111 drives the main shaft 112 to rotate, thereby driving the pitch drive mechanism 12 to rotate. The pitch drive mechanism 12 may include a second stepper motor 121 and a transmitter bracket 122. The laser emitter 13 is rotatably connected to the transmitter bracket 122. The second stepper motor 121 may drive the laser emitter 13 to rotate relative to the transmitter bracket 122, thereby achieving pitch angle adjustment.

[0091] An electric slip ring can also be fixed to the top of the main spindle 112. The external part of the electric slip ring is fixed to the pitch drive mechanism 12 and rotates synchronously with the main spindle 112. The internal part of the electric slip ring is fixed to the base support and remains stationary during equipment operation. The external connecting wire of the electric slip ring is connected to the power supply wire of the second stepper motor 121 and the laser emitter 13, thereby enabling the rotating platform to rotate in a single direction without restriction.

[0092] It should be noted that the main connection methods for the components in laser emitting assembly 1 are screw and nut connections and sliding groove connections. Thanks to the fact that the entire laser emitting assembly 1 is completely sealed after assembly, the probability of system failure due to dust entering the device is significantly reduced, thereby reducing maintenance costs by decreasing maintenance frequency.

[0093] For example, the first stepper motor 111 located within the base 14 can be a Type 57 stepper motor, fixed to the inside of the base 14 housing by a stepper motor bracket. A ruler asymptotic gear with 18 teeth and a module of 3 is mounted on the motor shaft of the first stepper motor 111, which meshes with a ruler asymptotic gear with the same module and 50 teeth. The larger gear rotates coaxially with the main shaft 112 and the pitch drive mechanism 12 (or a square housing 15) fixed to the main shaft 112 via a connecting key. The step angle of the Type 57 stepper motor is 1.8 degrees, meaning that for every step the stepper motor rotates clockwise, the main shaft 112 and the fixed pitch drive mechanism 12 rotate counterclockwise by 5 degrees. Therefore, the minimum horizontal measurement angle of the laser emitting assembly 1 is 5 degrees. However, after weighing the efficiency and accuracy of dust concentration measurement, the default horizontal measurement angle is set to 30 degrees. The second stepper motor 121 can be a 42-type stepper motor, which can drive the laser emitter 13 to pitch 90 degrees. The step angle of this stepper motor is 1.8 degrees, that is, the minimum vertical measurement angle is also 1.8 degrees. However, after weighing the efficiency and accuracy of dust concentration measurement, the default vertical measurement angle is set to 18 degrees.

[0094] Since the laser emitting assembly 1 is located in a space filled with wood dust, the airtightness of its housing needs to be ensured to reduce the frequency of maintenance after system operation. Therefore, after the spindle 112 and the stepper motor are mounted on their respective connecting brackets, they are connected to the housing of the emitting platform by screws and nuts, ensuring both system airtightness and installation tightness. The housing of the laser emitting assembly 1 is connected by a sliding groove, which ensures system airtightness while reducing the complexity of disassembly and assembly, and improving the efficiency of single maintenance. The laser emitting assembly 1 is dustproofed by mounting a square housing 15, and an opening is provided on the square housing 15 to allow normal pitch operation of the laser emitter 13. The gaps in the opening can be sealed with a dustproof cloth. The base 14 of the laser emitting assembly 1 can also be provided with four threaded holes, which are connected to the corresponding lifting platform by screws and nuts.

[0095] In some embodiments, the laser receiving component 2 includes a light trap, a photoelectric sensor, a directional light shield, and a microcontroller. The light trap is located inside the directional light shield, with its light-receiving surface facing the opening of the directional light shield, which in turn faces the laser emitting component 1. The photoelectric sensor is connected to the microcontroller and is used to receive the light transmitted from the light trap. Based on the received light, the photoelectric sensor outputs a measurement electrical signal, and the microcontroller generates measurement data based on the measurement electrical signal. The photoelectric sensor can be a photodiode.

[0096] When laser emitting component 1 emits a laser beam towards laser receiving component 2, its aiming position is the light trap of laser receiving component 2. This is to prevent non-target scattered light from being captured by the measuring element, thus avoiding increased error in the measuring instrument. The photoelectric sensor is the core measuring element, possessing the characteristic of changing the current passing through it when illuminated by light. By comparing the current change before and after the laser scattered light illuminates it, the dust concentration is measured. Unlike traditional enclosed light scattering dust concentration measuring instruments, the laser emitting component 1 and laser receiving component 2 of this detection system are exposed to ambient light. To minimize the influence of ambient light and collect laser scattered light from specific areas, a directional light shield is needed to cover the photoelectric sensor. The microcontroller generates measurement data based on the measured electrical signal and transmits the measurement data to the processing component 3. It should be noted that to ensure power supply to the laser receiving component, a battery can also be installed on laser receiving component 2 to improve the flexibility of its placement and the stability of its power supply.

[0097] In some embodiments, the processing component 3 is further configured to acquire measurement data for the current measurement cycle and the previous measurement cycle, provided that the number of measurement rounds corresponding to the current measurement cycle is not less than two, and determine the direction of dust concentration change in the detection area of ​​each laser receiving component 2 based on the acquired measurement data. Wherein, if the measurement data measured by each laser receiving component 2 in the first measurement cycle is set as... Then the measurement data measured by each laser receiving component 2 in the subsequent j-th round of measurement can be set as By comparing the measurement data of the i-th laser receiving component 2 in the j-th round with that in the (j-1)-th round, the change in dust concentration of the i-th laser receiving component 2 can be determined, and the corresponding formula is as follows:

[0098]

[0099] Then, in the j-th measurement cycle, the difference between each laser receiving component 2 and its value in the previous cycle is... The direction of dust concentration change can then be determined based on the differences, as shown in Table 4.

[0100] Table 4 is a table for assessing the direction of dust concentration change.

[0101]

[0102]

[0103] Based on the evaluation method in Table 4, and according to the measurement data from the current measurement cycle and the previous measurement cycle, the direction of dust concentration change in the detection area of ​​each laser receiving component 2 can be determined. After determining the direction of dust concentration change in each detection area, a control strategy can be determined for each detection area to avoid excessively high dust concentrations. Alternatively, the overall dust concentration change direction of the space under test can be determined based on the direction of dust concentration change in each detection area, thereby determining a control strategy for the space under test.

[0104] In some embodiments, the processing component 3 is further configured to acquire measurement data of the current measurement cycle and the previous two measurement cycles when the number of measurement rounds corresponding to the current measurement cycle is not less than three, determine a second probability evaluation distribution of the dust concentration change trend in each direction based on the acquired measurement data, perform fusion processing on the second probability evaluation distribution using a preset second data fusion algorithm to obtain a target fusion evaluation of the dust concentration change trend, and determine the target fusion evaluation of the dust concentration change trend as the dust concentration change trend of the current measurement cycle.

[0105] It is understandable that, when j≥3, the dust concentrations measured by each laser receiving component 2 in the j-th round of measurement are respectively The trend of dust concentration change at the i-th laser receiving component 2 can be determined based on the current measurement cycle and the measurement data from the previous two measurement cycles. The corresponding formula is as follows:

[0106]

[0107] In formula (6), This represents the index of the rate of change in dust concentration corresponding to laser receiver component 2, numbered i, during the j-th round of measurement. When this occurs, it indicates that the change in dust concentration in this round is in the same direction as the change in the previous round, but the change is greater; when This indicates that the change in dust concentration in this round is smaller than the change in the previous round, or that the direction of change has been directly altered. Table 5 is designed to evaluate the rate of change in dust concentration measured by the i-th receiver in the j-th round.

[0108] Table 5 shows the assessment table for dust concentration change trends.

[0109]

[0110] By combining the evaluation of the dust concentration change direction of each laser receiving component 2, the dust concentration change trend of the i-th receiver in the j-th round can be determined. The dust concentration change trend of the i-th receiver in the j-th round is shown in Table 6.

[0111] Table 6 shows the specific changes in dust concentration.

[0112]

[0113] Since the control recommendations for both gradual upward and downward changes are the same, they can be statistically grouped into a new category of relatively stable conditions. Similarly, the number of data points corresponding to each trend of change at the same location is counted, and these are compiled into a change statistics table similar to Table 2, resulting in the specific change statistics table of dust concentration at a single location shown in Table 7.

[0114] Table 7 shows the specific changes in dust concentration.

[0115]

[0116] In Table 7, the sum of the evaluation numbers for the three trends should equal the total number of laser receiving components 2 in a single orientation. Based on the measurement data, the evaluation numbers corresponding to different trends in a single orientation can be obtained. Then, based on the evaluation numbers in different orientations, the second probability assessment distribution of the dust concentration change trend in each orientation can be determined. The second probability assessment distribution of the dust concentration change trend in each orientation is shown in Table 8.

[0117] Table 1 shows the second probability assessment distribution of dust concentration variation trends in various locations.

[0118]

[0119]

[0120] After obtaining the second probability assessment distribution of dust concentration change trends in various directions, a preset second data fusion algorithm is used to fuse these distributions. This yields a target fusion evaluation of the dust concentration change trend, which is then used to determine the dust concentration change trend for the current measurement period. This helps to identify the dust concentration change trend in the measured space and provide data support for subsequent control strategies. It should be noted that the second data fusion algorithm can also be a data fusion algorithm based on DS evidence theory.

[0121] In some embodiments, processing component 3 is further configured to determine control recommendations or control strategies by consulting a preset control strategy table based on the safety level assessment and dust concentration change trend of the current measurement period, and output the corresponding control recommendations or execute the control strategies. In conjunction with the above embodiments, the process by which processing component 3 performs the safety level assessment and change trend assessment of the current measurement period and obtains control recommendations is as follows: Figure 4 As shown, after at least three rounds of measurement, the safety level assessment and trend assessment for the current measurement period can be determined, and control recommendations for the current measurement period can be made.

[0122] It is understandable that after determining the safety level assessment and dust concentration change trend for the current measurement period, control recommendations or control strategies can be determined by referring to the preset control strategy table based on the safety level assessment and dust concentration change trend for the current measurement period. If it is a control recommendation, it can be output through the corresponding output device; if it is a control strategy, the corresponding control equipment (e.g., a fan) can be controlled to operate according to the control strategy. For example, the preset control strategy table can be shown in Table 9.

[0123] Table 2 shows the preset control strategies.

[0124]

[0125] In Table 9, "Relaxed Control" indicates a high level of expected safety, allowing for relaxed control to maximize production benefits. "Maintain Control" indicates appropriate control levels, which can be maintained throughout the current measurement cycle. "Increased Control" indicates poor expected safety, requiring immediate increase in control levels. "Maximum Control" indicates the current dust concentration is at a dangerous level, requiring all controlled equipment to operate at full power. "Warning" indicates the dust concentration is approaching a dangerous level in this measurement and is likely to reach a dangerous level in the next measurement; "Severe Warning" indicates the dust concentration has reached a dangerous level in this measurement and shows no signs of rapid decline; "Stop Production" indicates the dust concentration has reached a dangerous level in this measurement, and even full power operation of controlled equipment cannot prevent a rapid increase in dust concentration, in which case immediate cessation of production is recommended.

[0126] In some embodiments, the processing component 3 is further configured to take the first sequential orientation and the second sequential orientation as the first orientation and the second orientation respectively based on the orientation processing order, perform a first fusion processing operation to obtain a target dust concentration fusion probability assessment, the target dust concentration fusion probability assessment including the probability distribution of different safety levels; and determine the safety level corresponding to the highest probability in the target dust concentration fusion probability assessment as the target dust concentration fusion evaluation.

[0127] The first fusion processing operation includes: fusing the probability assessments of the safety levels of the first and second azimuths to obtain a fusion probability assessment of the dust concentration of the first and second azimuths; using the fusion probability assessment of the dust concentration of the first and second azimuths as the new probability assessment of the safety level of the first azimuth, and using the next sequential azimuth as the new second azimuth; repeating the above process until the probability assessments of the safety levels of all azimuths have been fused.

[0128] It is understandable that the above processing method can achieve the fusion of two probability assessments sequentially, ultimately enabling the fusion of probability assessments for security levels in all directions. This approach reduces computational complexity by processing the probability assessments of only two directions at a time, avoiding the high-dimensional data computation and complex weight allocation issues that may arise when fusing multiple directions simultaneously. This significantly improves processing efficiency, especially when dealing with a large number of directions. Secondly, it supports sequential incremental processing, allowing information to be integrated step-by-step according to the actual processing order of the directions. Each fusion result serves as a new input for iterative processing of the next direction, adapting to scenarios where data arrives sequentially in dynamic environments and enhancing the flexibility and controllability of the processing flow.

[0129] In one embodiment, corresponding to the first data fusion algorithm, the probability assessment of the security level of orientation i is as follows:

[0130]

[0131] In formula (7), O represents the number of laser receiving components 2 contained in azimuth i, and m i (S), m i (N) and m i (D) represents the probability assessment of relative safety, general safety, and relative danger corresponding to azimuth i, respectively. The measurement data output by the laser receiving component is used to assess the safety level. i r represents the number of relatively safe laser receiving components in azimuth i. i Let d be the number of laser receiver components corresponding to general safety in azimuth i. i This represents the number of laser receiving components corresponding to the relatively dangerous location in azimuth i.

[0132] The calculation formula for fusing the probability assessments of the initial first position and the initial second position is as follows:

[0133]

[0134] In formula (8), m1(S), m1(R), and m1(D) are the probability assessments of the initial first-position security level, m2(S), m2(R), and m2(D) are the probability assessments of the initial second-position security level, and m 12 (S), m 12 (R) and m 12(D) represents the probability assessment of dust concentration fusion between the first and second azimuth directions. s1 represents the number of relatively safe laser receivers in the first azimuth direction, r1 represents the number of generally safe laser receivers in the first azimuth direction, d1 represents the number of relatively dangerous laser receivers in the first azimuth direction, s2 represents the number of relatively safe laser receivers in the second azimuth direction, r2 represents the number of generally safe laser receivers in the second azimuth direction, and d2 represents the number of relatively dangerous laser receivers in the second azimuth direction. K 12 The first conflict coefficient is defined by the following formula:

[0135] After performing the first fusion processing operation, the calculation formula corresponding to the target dust concentration fusion probability assessment is as follows:

[0136]

[0137] Where n is the number of directions. This is an assessment of the relatively safe fusion probability for the first n-1 directions. The fusion probability assessment corresponds to the first n-1 orientations and is generally safe. For the fusion probability assessment of the relative danger corresponding to the first n-1 directions, m 12…n (S) represents the relatively safe fusion probability assessment for the first n directions, m 12…n (R) represents the fusion probability assessment for the first n orientations corresponding to general security, m 12…n (D) represents the fusion probability assessment of the relative danger corresponding to the first n directions, s n r represents the number of relatively safe laser receiving components in azimuth n. n Let d be the number of laser receivers corresponding to general safety in azimuth n. n Let n be the number of laser receiving components corresponding to the relative danger in azimuth n; the calculation formula for the target dust concentration fusion evaluation is:

[0138] Mi = argmax(m 12…n (S),m 12…n (R),m 12…n (D)) (10)

[0139] Among them, K 12…n The second conflict coefficient is calculated using the following formula:

[0140]

[0141] In some embodiments, the processing component 3 is further configured to take the first sequential orientation and the second sequential orientation as the first orientation and the second orientation respectively based on the orientation processing order, perform a second fusion processing operation to obtain a target change trend fusion probability assessment, the target change trend fusion probability assessment including the probability distribution corresponding to different trends; and determine the change trend corresponding to the highest probability in the target change trend fusion probability assessment as the target fusion evaluation of the dust concentration change trend.

[0142] The second fusion processing operation includes: fusing the probability assessments of dust concentration change trends in the first and second directions to obtain a fusion probability assessment of the change trends in the first and second directions; using the fusion probability assessment of the change trends in the first and second directions as a new probability assessment of the dust concentration change trend in the first direction, and using the next sequential direction as a new second direction; repeating the above process until the probability assessments of dust concentration change trends in all directions have been fused.

[0143] Similarly, it can be understood that the above processing method can achieve the fusion of two probability assessments sequentially, ultimately enabling the fusion of probability assessments of dust concentration change trends in all directions. This approach reduces computational complexity by processing the probability assessments of only two directions at a time, avoiding the high-dimensional data computation and complex weight allocation problems that may arise when fusing multiple directions simultaneously. This significantly improves processing efficiency, especially when the number of directions is large. Secondly, it supports sequential incremental processing, allowing information to be integrated step-by-step according to the actual processing order of the directions. Each fusion result serves as a new input for iterative processing of the next direction, adapting to scenarios where data arrives sequentially in dynamic environments and enhancing the flexibility and controllability of the processing flow.

[0144] In one embodiment, corresponding to the second data fusion algorithm, the probability assessment of the dust concentration change trend at location i is as follows:

[0145]

[0146] Where O represents the number of laser receiving components 2 contained in azimuth i, and m i (B), m i (P) and m i (G) represents the probability assessment of accelerated increase, relative stability, and accelerated decrease corresponding to azimuth i, respectively. Measurement data output by the laser receiving component in at least three measurement cycles is used to assess the changing trend. i p represents the number of laser receiving components in azimuth i that increase exponentially. i g represents the number of relatively stable laser receiving components in azimuth i. i The number of laser receiving components corresponding to the increased descent in azimuth i.

[0147] The calculation formula for fusing the probability assessments of the initial first position and the initial second position is as follows:

[0148]

[0149] Wherein, m1(B), m1(P), and m1(G) are the probabilistic assessments of the initial dust concentration change trend in the first direction, and m2(B), m2(P), and m2(G) are the probabilistic assessments of the initial dust concentration change trend in the second direction. 12 (B), m 12 (P) and m 12 (G) represents the probability assessment of the fusion of the changing trends in the first and second azimuth directions. b1 represents the number of laser receivers showing an accelerated increase in the first azimuth direction, p1 represents the number of laser receivers showing a relatively stable trend in the first azimuth direction, g1 represents the number of laser receivers showing an accelerated decrease in the first azimuth direction, b2 represents the number of laser receivers showing an accelerated increase in the second azimuth direction, p2 represents the number of laser receivers showing a relatively stable trend in the second azimuth direction, and g2 represents the number of laser receivers showing an accelerated decrease in the second azimuth direction. K' 12 The third conflict coefficient is calculated using the following formula:

[0150] After performing the second fusion processing operation, the calculation formula corresponding to the target dust concentration fusion probability assessment is as follows:

[0151]

[0152] Where n is the number of directions. The assessment of the fusion probability of the first n-1 directions is based on the increased intensity. This provides a relatively stable fusion probability assessment for the first n-1 directions. For the assessment of the fusion probability of the first n-1 directions, m 12…n (B) represents the fusion probability assessment for the first n directions, where m 12…n (P) represents the relatively stable fusion probability assessment for the first n directions, m 12…n (G) represents the fusion probability assessment for the first n directions, where the decrease is exacerbated. n p represents the number of laser receiving components in azimuth n that increase exponentially. n g represents the number of relatively stable laser receiving components in azimuth n. n Let n be the number of laser receiving components that decrease more rapidly in azimuth n; the formula for calculating the target change trend fusion probability assessment is:

[0153] MBi = argmax(m 12…n (S),m 12…n (R),m12…n (D)) (14)

[0154] Wherein, K′ 12…n The fourth conflict coefficient is calculated using the following formula:

[0155]

[0156] In some embodiments, this application also provides a dust concentration monitoring method based on multi-sensor data fusion, which is applied to a dust concentration monitoring system as described above. Figure 5 As shown, the dust concentration monitoring method based on multi-sensor data fusion includes the following steps S501 to S503.

[0157] S501: Acquire the measurement data output by each laser receiving component.

[0158] S502: Determine the first probability assessment distribution of the security level in each direction based on the measurement data of the current measurement period.

[0159] S503: The first probability assessment distribution is fused using a preset first data fusion algorithm to obtain the target dust concentration fusion evaluation, and the target dust concentration fusion evaluation is determined as the safety level evaluation for the current measurement period.

[0160] In some embodiments, the dust concentration monitoring method based on multi-sensor data fusion further includes: acquiring measurement data for the current measurement cycle and the previous measurement cycle when the number of measurement rounds corresponding to the current measurement cycle is not less than two; and determining the direction of dust concentration change in the detection area of ​​each laser receiving component based on the acquired measurement data.

[0161] In some embodiments, the multi-sensor data fusion dust concentration monitoring method further includes: acquiring measurement data for the current measurement period and the previous two measurement periods, provided that the number of measurement rounds corresponding to the current measurement period is not less than three; determining a second probability evaluation distribution of dust concentration change trends in each direction based on the acquired measurement data; performing fusion processing on the second probability evaluation distribution using a preset second data fusion algorithm to obtain a target fusion evaluation of the dust concentration change trend; and determining the target fusion evaluation of the dust concentration change trend as the dust concentration change trend for the current measurement period.

[0162] In some embodiments, the dust concentration monitoring method based on multi-sensor data fusion further includes: determining control recommendations or control strategies by referring to a preset control strategy table based on the safety level evaluation and dust concentration change trend of the current measurement period, and outputting control recommendations or implementing control strategies accordingly.

[0163] In some embodiments, a preset first data fusion algorithm is used to fuse the first probability assessment distribution to obtain a target dust concentration fusion evaluation, including: taking the first sequential orientation and the second sequential orientation as the first orientation and the second orientation respectively based on the orientation processing order, performing a first fusion processing operation to obtain a target dust concentration fusion probability evaluation, wherein the target dust concentration fusion probability evaluation includes probability distributions of different safety levels; and determining the safety level corresponding to the highest probability in the target dust concentration fusion probability evaluation as the target dust concentration fusion evaluation.

[0164] The first fusion processing operation includes: fusing the probability assessments of the safety levels of the first and second azimuths to obtain a fusion probability assessment of the dust concentration of the first and second azimuths; using the fusion probability assessment of the dust concentration of the first and second azimuths as the new probability assessment of the safety level of the first azimuth, and using the next sequential azimuth as the new second azimuth; repeating the above process until the probability assessments of the safety levels of all azimuths have been fused.

[0165] In some embodiments, a preset second data fusion algorithm is used to fuse the second probability evaluation distribution to obtain a target fusion evaluation of the dust concentration change trend. This includes: taking the first sequential orientation and the second sequential orientation as the first orientation and the second orientation respectively based on the orientation processing order, performing a second fusion processing operation to obtain a target change trend fusion probability evaluation, wherein the target change trend fusion probability evaluation includes probability distributions corresponding to different trends; and determining the change trend corresponding to the highest probability in the target change trend fusion probability evaluation as the target fusion evaluation of the dust concentration change trend.

[0166] The second fusion processing operation includes: fusing the probability assessments of dust concentration change trends in the first and second directions to obtain a fusion probability assessment of the change trends in the first and second directions; using the fusion probability assessment of the change trends in the first and second directions as a new probability assessment of the dust concentration change trend in the first direction, and using the next sequential direction as a new second direction; repeating the above process until the probability assessments of dust concentration change trends in all directions have been fused.

[0167] It should be noted that the multi-sensor data fusion dust concentration monitoring method provided in this application embodiment and the multi-sensor data fusion dust concentration monitoring system provided in this application embodiment are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned multi-sensor data fusion dust concentration monitoring system, and the repeated parts will not be described again.

[0168] In some embodiments, an electronic device provided in this application includes a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements the above-described multi-sensor data fusion method for dust concentration monitoring.

[0169] This application also provides a computer-readable medium storing a computer program thereon, which, when executed by a processor, implements the dust concentration monitoring method of multi-sensor data fusion described above. This computer-readable medium may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into that device / apparatus / system. The aforementioned computer-readable medium carries one or more programs, which, when executed, implement the method as described in the embodiments of this application.

[0170] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application. Therefore, the scope of this application should not be limited to the above embodiments, but should be defined not only by the appended claims, but also by their equivalents. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A dust concentration monitoring system with multi-sensor data fusion, characterized by, The application relates to a laser dust concentration measuring device. The device comprises a laser emission assembly, a plurality of laser receiving assemblies and a processing assembly. The laser emission assembly comprises a rotating driving mechanism, a pitching driving mechanism and a laser emitter, the laser emitter is arranged on the pitching driving mechanism, the rotating driving mechanism is used for driving the pitching driving mechanism to rotate so as to synchronously drive the laser emitter to rotate, and the pitching driving mechanism is used for adjusting the pitching angle of the laser emitter; wherein the laser emission assembly emits laser to each laser receiving assembly in a predetermined sequence in a measurement cycle. The plurality of laser receiving assemblies are distributed in different directions of a to-be-measured space, each direction of the to-be-measured space has the same number of laser receiving assemblies, and the laser receiving assemblies are used for generating measurement data according to received laser. The processing assembly is used for acquiring the measurement data output by each laser receiving assembly, determining a first probability evaluation distribution of the safety level of each direction according to each measurement data in a current measurement cycle, performing fusion processing on the first probability evaluation distribution by using a preset first data fusion algorithm to obtain a target dust concentration fusion evaluation, taking a first sequence direction and a second sequence direction as a first direction and a second direction respectively based on a direction processing sequence, performing a first fusion processing operation to obtain a target dust concentration fusion probability evaluation, the target dust concentration fusion probability evaluation comprises probability distributions of different safety levels, determining the safety level corresponding to the maximum probability in the target dust concentration fusion probability evaluation as the target dust concentration fusion evaluation, and determining the target dust concentration fusion evaluation as a safety level evaluation of the current measurement cycle. The probability evaluation of the safety level of the direction i is as follows: ； wherein is the number of laser receiving components contained in the orientation i, , and are the probability assessments of the relative safety, general safety and relative danger, respectively, of the orientation i, the measured data outputted by the laser receiving components being used to assess the safety level, is the number of laser receiving components corresponding to relative safety in the orientation i, is the number of laser receiving components corresponding to general safety in the orientation i, is the number of laser receiving components corresponding to relative danger in the orientation i; The calculation formula for fusion processing of the probability evaluations of the initial first direction and the initial second direction is as follows: ； wherein, , and are probability assessments of the initial first orientation safety level, , and are probability assessments of the initial second orientation safety level, , and are dust concentration fusion probability assessments of the first orientation and the second orientation, is the number of laser receiving components corresponding to relatively safe in the first orientation, is the number of laser receiving components corresponding to general safety in the first orientation, is the number of laser receiving components corresponding to relatively dangerous in the first orientation, is the number of laser receiving components corresponding to relatively safe in the second orientation, is the number of laser receiving components corresponding to general safety in the second orientation, is the number of laser receiving components corresponding to relatively dangerous in the second orientation, K 12 is the first conflict coefficient, and the calculation formula of the first conflict coefficient is: 。 2. The multi-sensor data fusion-based dust concentration monitoring system as claimed in claim 1, wherein, The processing assembly is further used for acquiring each measurement data of the current measurement cycle and a previous measurement cycle when the measurement round corresponding to the current measurement cycle is not less than two, and determining the dust concentration change direction of the detection area of each laser receiving assembly according to the acquired measurement data.

3. The multi-sensor data fusion-based dust concentration monitoring system as claimed in claim 1, wherein, The processing assembly is further used for acquiring measurement data of the current measurement cycle and two previous measurement cycles when the measurement round corresponding to the current measurement cycle is not less than three, determining a second probability evaluation distribution of the dust concentration change trend of each direction according to the acquired measurement data, performing fusion processing on the second probability evaluation distribution by using a preset second data fusion algorithm to obtain a target fusion evaluation of the dust concentration change trend, and determining the target fusion evaluation of the dust concentration change trend as the dust concentration change trend of the current measurement cycle.

4. The multi-sensor data fusion-based dust concentration monitoring system as claimed in claim 3, wherein, The processing assembly is further used for determining a control suggestion or a control strategy according to the safety level evaluation and the dust concentration change trend of the current measurement cycle and a preset control strategy table, and outputting the control suggestion or executing the control strategy.

5. The multi-sensor data fusion-based dust concentration monitoring system as claimed in claim 1, wherein, The first fusion processing operation includes: fusing the probability evaluation of the first orientation and the second orientation safety level to obtain the dust concentration fusion probability evaluation of the first orientation and the second orientation; taking the dust concentration fusion probability evaluation of the first orientation and the second orientation as the new probability evaluation of the first orientation safety level, and taking the next sequence orientation as the new second orientation; repeating the above processing procedure until the probability evaluation of the safety level of all orientations is fused.

6. The multi-sensor data-fusion based dust concentration monitoring system as claimed in claim 5, wherein, After the first fusion processing operation is performed, the calculation formula corresponding to the target dust concentration fusion probability evaluation is: ； Wherein, n is the number of azimuths, is the fusion probability assessment corresponding to the relatively safe of the first n-1 azimuths, is the fusion probability assessment corresponding to the general safety of the first n-1 azimuths, is the fusion probability assessment corresponding to the relatively dangerous of the first n-1 azimuths, is the fusion probability assessment corresponding to the relatively safe of the first n azimuths, is the fusion probability assessment corresponding to the general safety of the first n azimuths, is the fusion probability assessment corresponding to the relatively dangerous of the first n azimuths, is the number of laser receiving components corresponding to the relatively safe in the azimuth n, is the number of laser receiving components corresponding to the general safety in the azimuth n, is the number of laser receiving components corresponding to the relatively dangerous in the azimuth n; the calculation formula of the target dust concentration fusion evaluation is: ； wherein, is a second conflict coefficient, and a calculation formula of the second conflict coefficient is: 。 7. The multi-sensor data fusion-based dust concentration monitoring system as claimed in claim 3, wherein, The processing component is also used to execute a second fusion processing operation based on the orientation processing sequence, taking the first sequence orientation and the second sequence orientation as the first orientation and the second orientation respectively, to obtain a target change trend fusion probability evaluation, wherein the target change trend fusion probability evaluation includes the probability distribution corresponding to different trends; The change trend corresponding to the maximum probability in the target change trend fusion probability evaluation is determined as the target fusion evaluation of the dust concentration change trend. The second fusion processing operation includes: fusing the probability evaluation of the dust concentration change trend of the first orientation and the second orientation to obtain the change trend fusion probability evaluation of the first orientation and the second orientation; taking the change trend fusion probability evaluation of the first orientation and the second orientation as the new probability evaluation of the dust concentration change trend of the first orientation, and taking the next sequence orientation as the new second orientation; repeating the above processing procedure until the probability evaluation of the dust concentration change trend of all orientations is fused.

8. The multi-sensor data-fusion based dust concentration monitoring system as claimed in claim 7, wherein, The probability evaluation of the dust concentration change trend of orientation i is: ； wherein, is the number of laser receiving components in the azimuth i, , and are the probability assessments of the azimuth i corresponding to the accelerated increase, the relative stability and the accelerated decrease respectively, the measurement data output by the laser receiving components in at least three measurement periods are used to assess the change trend, is the number of laser receiving components in the azimuth i corresponding to the accelerated increase, is the number of laser receiving components in the azimuth i corresponding to the relative stability, is the number of laser receiving components in the azimuth i corresponding to the accelerated decrease; The calculation formula for fusing the probability evaluation of the initial first orientation and the initial second orientation is: ； in, , as well as This is a probability assessment of the initial trend of dust concentration change in the first location. , as well as This is a probability assessment of the initial second-direction dust concentration change trend. , as well as A probability assessment is performed by fusing the changing trends of the first and second azimuth directions. This represents the number of laser receiving components that increase dramatically in the first orientation. This represents the number of relatively stable laser receiving components in the first orientation. This represents the number of laser receiving components that decrease more sharply in the first orientation. This corresponds to a significant increase in the number of laser receiving components in the second orientation. This represents the number of relatively stable laser receiving components in the second orientation. K' represents the number of laser receiving components that decrease more sharply in the second orientation. 12 The third conflict coefficient is calculated using the following formula: ； After the second fusion processing operation is performed, the calculation formula corresponding to the target dust concentration fusion probability evaluation is: ； Wherein, n is the number of azimuths, is the fusion probability evaluation corresponding to the aggravating rise of the previous n-1 azimuths, is the fusion probability evaluation corresponding to the relatively stable of the previous n-1 azimuths, is the fusion probability evaluation corresponding to the aggravating decline of the previous n-1 azimuths, is the fusion probability evaluation corresponding to the aggravating rise of the previous n azimuths, is the fusion probability evaluation corresponding to the relatively stable of the previous n azimuths, is the fusion probability evaluation corresponding to the aggravating decline of the previous n azimuths, is the number of laser receiving components corresponding to the aggravating rise in the azimuth n, is the number of laser receiving components corresponding to the relatively stable in the azimuth n, is the number of laser receiving components corresponding to the aggravating decline in the azimuth n; the calculation formula of the target change trend fusion probability evaluation is: ； wherein, is a fourth conflict coefficient, and a calculation formula of the fourth conflict coefficient is: 。 9. The multi-sensor data fusion-based dust concentration monitoring system as claimed in claim 1, wherein, The laser receiving component includes a light trap, a photoelectric sensor, a directional light shield, and a single-chip microcomputer. The light trap is located in the directional light shield, the light receiving surface of the light trap faces the opening of the directional light shield, and the opening of the directional light shield faces the laser emitting component. The photoelectric sensor is connected with the single-chip microcomputer. The photoelectric sensor is used to receive the light transmitted by the light trap and output a measurement electric signal according to the received light. The single-chip microcomputer is used to generate the measurement data according to the measurement electric signal.

10. A dust concentration monitoring method of multi-sensor data fusion, characterized by, The multi-sensor data fusion dust concentration monitoring method applies the dust concentration monitoring system according to any one of claims 1 to 9. The multi-sensor data fusion dust concentration monitoring method includes: Obtaining the measurement data output by each laser receiving component; Determining the first probability evaluation distribution of the safety level of each orientation according to each measurement data of the current measurement period; The first preset data fusion algorithm is used to perform fusion processing on the first probability evaluation distribution to obtain a target dust concentration fusion evaluation. Based on a direction processing sequence, a first sequence direction and a second sequence direction are taken as a first direction and a second direction respectively, a first fusion processing operation is performed, and a target dust concentration fusion probability evaluation is obtained. The target dust concentration fusion probability evaluation includes probability distributions of different safety levels. A safety level corresponding to a maximum probability in the target dust concentration fusion probability evaluation is determined as the target dust concentration fusion evaluation, and the target dust concentration fusion evaluation is determined as a safety level evaluation of a current measurement period. The probability evaluation of the direction i safety level is as follows: ； wherein is the number of laser receiving components in the orientation i, , and are the probability assessments of the relative safety, general safety and relative danger, respectively, of the orientation i, the measured data of the laser receiving components being used for assessing the safety level, is the number of laser receiving components in the orientation i corresponding to relative safety, is the number of laser receiving components in the orientation i corresponding to general safety, is the number of laser receiving components in the orientation i corresponding to relative danger; The calculation formula for performing fusion processing on the probability evaluations of the initial first direction and the initial second direction is as follows: ； wherein, , and are probability assessments of the initial first-orientation safety level, , and are probability assessments of the initial second-orientation safety level, , and are dust concentration fusion probability assessments of the first orientation and the second orientation, is the number of laser receiving components corresponding to relatively safe in the first orientation, is the number of laser receiving components corresponding to general safety in the first orientation, is the number of laser receiving components corresponding to relatively dangerous in the first orientation, is the number of laser receiving components corresponding to relatively safe in the second orientation, is the number of laser receiving components corresponding to general safety in the second orientation, is the number of laser receiving components corresponding to relatively dangerous in the second orientation, K 12 is the first conflict coefficient, and the calculation formula of the first conflict coefficient is: 。

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