A dust environment concentration monitoring method and system

Abstract

The application provides a dust environment concentration monitoring method and system, and relates to the technical field of dust concentration monitoring, wherein the method comprises the following steps: obtaining the stator current, stator voltage, rotor speed and shell temperature of a motor; determining the electromagnetic interference intensity of each position in the space around the motor according to the stator current and stator voltage; determining the vibration intensity distribution of each position in the space around the motor according to the rotor speed; generating an interference intensity distribution map by means of an interference distribution model according to the electromagnetic interference intensity and the vibration intensity distribution; determining the installation position of a dust sensor according to the interference intensity distribution map, and collecting the output electrical signal thereof; obtaining the local electromagnetic interference intensity and local vibration intensity at the installation position, and performing notch filtering on the electrical signal according to the local electromagnetic interference intensity to obtain a corrected signal; and performing compensation correction on the corrected signal according to the local vibration intensity and the shell temperature to obtain a dust concentration value. The application improves the anti-interference ability and measurement accuracy of dust concentration monitoring.

Description

Technical Field

[0001] This application relates to the field of dust concentration monitoring technology, and in particular to a method and system for monitoring dust environmental concentration. Background Technology

[0002] Dust concentration monitoring has broad application prospects in industrial and mining enterprises, construction sites, and grain processing plants. By acquiring real-time data on the concentration of suspended particulate matter in the air, it can provide crucial information for worker health protection, coordinated control of dust removal equipment, and early warning of safe production. With the increasing automation of industrial production, the scenario of co-deploying dust sensors with motor-driven equipment is becoming more common. How to achieve stable dust concentration monitoring in the complex interference environment generated by equipment operation has become a key focus in related fields.

[0003] In existing technologies, dust concentration monitoring typically employs sensors based on light scattering or charge induction methods, directly installed in the area to be measured. The sensor outputs an electrical signal related to dust concentration, which is then processed by a fixed-frequency filtering circuit or simple software filtering. Some solutions also incorporate ambient temperature or equipment vibration parameters to perform single-factor correction on the sensor's output signal, aiming to reduce the influence of external factors on the measurement results.

[0004] In industrial environments driven by electric motors, electromagnetic radiation and mechanical vibrations generated during equipment operation coexist, both interfering with the signal acquisition of dust sensors. Traditional filtering methods struggle to accurately suppress the specific interference characteristics at the sensor's location, while single-factor compensation based on temperature or vibration cannot completely eliminate measurement deviations caused by the coupling effect of multi-source interference. Consequently, the stability and accuracy of dust concentration monitoring fail to meet practical application requirements. Therefore, existing technologies suffer from insufficient accuracy in dust concentration monitoring under multi-source interference environments. Summary of the Invention

[0005] This application provides a method and system for monitoring dust concentration in the environment, in order to solve the problems of poor anti-interference ability and low measurement accuracy of dust concentration monitoring in the prior art.

[0006] To address the aforementioned technical problems, in a first aspect, this application provides a method for monitoring dust environmental concentration, comprising: The operating parameters of the motor are obtained, including the stator current, stator voltage, rotor speed, and motor housing temperature. Based on the stator current and the stator voltage, the electromagnetic field distribution data of the motor is calculated, and based on the electromagnetic field distribution data, the electromagnetic interference intensity at different locations in the space surrounding the motor is determined. Based on the rotor speed, the vibration intensity distribution at different locations in the space surrounding the motor is determined, and based on the electromagnetic interference intensity and the vibration intensity distribution, an interference intensity distribution map of the space surrounding the motor is generated using a preset interference distribution model. Based on the interference intensity distribution map, the installation location of the dust sensor is determined, and the electrical signal output by the dust sensor is collected. The electrical signal is used to characterize the dust concentration in the environment. The local electromagnetic interference intensity and local vibration intensity of the dust sensor at the installation position are obtained, and the electrical signal is notched and filtered to remove interference signals based on the local electromagnetic interference intensity to obtain a correction signal. Based on the local vibration intensity and the motor housing temperature, the correction signal is compensated and corrected to eliminate sensor measurement deviation and obtain the dust concentration value.

[0007] Optionally, the step of performing notch filtering on the electrical signal to filter out interference signals and obtain a correction signal based on the local electromagnetic interference intensity includes: Based on the local electromagnetic interference intensity, the dominant frequency component that matches the local electromagnetic interference intensity is queried from a preset electromagnetic interference frequency mapping table and used as the interference frequency at the installation location. Based on the interference frequency, calculate the center frequency and bandwidth of the notch filter, and configure the notch filter according to the center frequency and bandwidth to obtain the configured notch filter. The electrical signal is input into the configured notch filter, which attenuates the electrical signal and outputs the attenuated signal as a correction signal.

[0008] Optionally, the step of determining the vibration intensity distribution at different locations in the space surrounding the motor based on the rotor speed, and generating an interference intensity distribution map of the space surrounding the motor based on the electromagnetic interference intensity and the vibration intensity distribution using a preset interference distribution model, includes: Obtain the rotor mass distribution parameters and bearing support stiffness parameters of the motor, and calculate the excitation force amplitude and excitation force frequency at the bearing housing position based on the rotor speed, the rotor mass distribution parameters and the bearing support stiffness parameters; The excitation force amplitude and the excitation force frequency are transmitted to each node on the surface of the motor housing to obtain the vibration displacement amplitude and vibration frequency of each node on the surface of the motor housing. The vibration displacement amplitude and vibration frequency of each node on the surface of the motor housing are propagated to each spatial position in the space surrounding the motor, and the vibration displacement amplitude of each spatial position in the space surrounding the motor is obtained as the vibration intensity distribution of each spatial position. Based on the vibration intensity distribution and electromagnetic interference intensity at each spatial location, the electromagnetic interference intensity and vibration intensity distribution at the same spatial location are weighted and summed using the interference distribution model to obtain the comprehensive interference intensity at each spatial location. Based on the comprehensive interference intensity at each spatial location and the corresponding spatial coordinates, an interference intensity distribution map of the space surrounding the motor is generated.

[0009] Secondly, this application provides a dust environmental concentration monitoring system, comprising: The acquisition module is used to acquire the operating parameters of the motor, including the stator current, stator voltage, rotor speed and motor housing temperature. The calculation module is used to calculate the electromagnetic field distribution data of the motor based on the stator current and the stator voltage, and to determine the electromagnetic interference intensity at different locations in the space surrounding the motor based on the electromagnetic field distribution data. The determination module is used to determine the vibration intensity distribution at different locations in the space surrounding the motor based on the rotor speed, and to generate an interference intensity distribution map of the space surrounding the motor based on the electromagnetic interference intensity and the vibration intensity distribution through a preset interference distribution model. The acquisition module is used to determine the installation location of the dust sensor according to the interference intensity distribution map, and to acquire the electrical signal output by the dust sensor, wherein the electrical signal is used to characterize the dust concentration in the environment; The filtering module is used to obtain the local electromagnetic interference intensity and local vibration intensity of the dust sensor at the installation position, and to perform notch filtering on the electrical signal according to the local electromagnetic interference intensity to obtain a correction signal; The compensation module is used to compensate and correct the correction signal based on the local vibration intensity and the motor housing temperature to eliminate sensor measurement deviation and obtain the dust concentration value.

[0010] Thirdly, this application provides an electronic device, comprising: Memory, used to store computer programs; A processor is configured to execute the computer program to implement the steps of the dust environmental concentration monitoring method as described in the first aspect above.

[0011] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the dust environmental concentration monitoring method described in the first aspect above.

[0012] The technical solution provided in this application has the following beneficial effects: This application first obtains the stator current, stator voltage, rotor speed, and housing temperature of the motor. Then, it calculates the electromagnetic field distribution around the motor based on the stator current and stator voltage, thereby determining the electromagnetic interference intensity at various locations in space. Simultaneously, it determines the vibration intensity distribution at various locations in space based on the rotor speed. The electromagnetic interference intensity and vibration intensity distribution are then fused using a preset model to generate an interference intensity distribution map reflecting the coupling effect of electromagnetic and vibration. Based on this distribution map, the installation location of the dust sensor is selected to avoid areas with strong interference. After collecting the electrical signal output by the sensor, notch filtering is performed on the electrical signal according to the local electromagnetic interference intensity corresponding to the installation location to specifically filter out interference components. Finally, the filtered signal is compensated and corrected according to the local vibration intensity and housing temperature to eliminate sensor measurement deviation. Through the synergistic effect of the above-mentioned spatial interference pre-assessment, optimized location layout, and multi-level signal correction, the anti-interference capability and measurement accuracy of dust concentration monitoring are effectively improved.

[0013] Furthermore, in the notch filtering stage, this application retrieves the dominant frequency component from a preset mapping table based on the local electromagnetic interference intensity at the installation location as the interference frequency. Then, the center frequency and bandwidth of the notch filter are calculated based on the interference frequency, and the filter configuration is completed. Finally, the electrical signal is input into the configured filter for attenuation processing to output a correction signal, thereby achieving accurate filtering of the actual interference frequency at the sensor location.

[0014] Furthermore, this method dynamically matches the filtering parameters with the electromagnetic interference characteristics of the space where the sensor is located, avoiding the problem of incomplete suppression of interference signals or accidental damage to valid signals in traditional fixed-frequency filtering methods. This further ensures the input quality of the signal correction process and improves the reliability of dust concentration monitoring.

[0015] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating a dust environmental concentration monitoring method provided in this application embodiment; Figure 2 This is a schematic diagram illustrating a specific implementation of a dust environmental concentration monitoring method provided in this application embodiment; Figure 3This is a schematic diagram of a dust environment concentration monitoring system provided in an embodiment of this application. Detailed Implementation

[0018] In motor-driven industrial environments, dust sensors are often deployed close to the motor equipment. However, the electromagnetic radiation and mechanical vibration generated by the motor during operation can simultaneously affect the sensor, creating compound interference on the output signal. Traditional dust concentration monitoring methods typically use fixed-frequency filtering circuits to process the sensor signal, or compensate for the measurement results based solely on a single factor such as ambient temperature or equipment vibration. This approach is insufficient to precisely suppress the interference characteristics faced by the actual installation location of the sensor, nor can it eliminate the comprehensive measurement deviation caused by the coupling of electromagnetic and vibration effects. Consequently, the stability and accuracy of the monitoring data fail to meet the requirements of field applications.

[0019] To address the aforementioned issues, this application proposes a method for monitoring dust environmental concentration. The core of this method lies in first calculating the electromagnetic interference intensity distribution and vibration intensity distribution around the motor using its own operating parameters, then fusing these two distributions to generate a spatial distribution map reflecting the overall interference intensity. This allows for the selection of the installation location with the lowest interference intensity for the dust sensor. In the sensor signal processing stage, the electrical signal is first subjected to notch filtering based on the local electromagnetic interference intensity corresponding to the sensor's location, specifically filtering out the dominant frequency interference components at that location. Then, the filtered signal is compensated and corrected based on the local vibration intensity and the motor housing temperature to eliminate measurement deviations caused by vibration and temperature changes.

[0020] This method guides the optimized deployment of sensors through spatial interference pre-assessment and combines a multi-level, multi-factor signal correction mechanism to systematically suppress the effects of electromagnetic interference, mechanical vibration, and temperature changes on dust concentration measurement. It fundamentally solves the problem of insufficient monitoring accuracy of existing technologies in multi-source interference environments and improves the reliability and stability of dust concentration monitoring.

[0021] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are merely some embodiments of the present application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] The core of this application is to provide a method for monitoring dust concentration in the environment, and a flowchart of one specific implementation is shown below. Figure 1 As shown, the method includes: Step 101: Obtain the operating parameters of the motor, including the stator current, stator voltage, rotor speed and motor housing temperature.

[0023] In step 101, an electric motor refers to a rotary power device that converts electrical energy into mechanical energy. It contains a stator winding and a rotor assembly. When the stator winding is energized, it generates a rotating magnetic field that drives the rotor to rotate. In industrial production sites, this motor is both a potential source of dust and a common nearby device for dust sensors. The stator current and stator voltage refer to the actual current flowing through the stator winding and the voltage across the winding during operation. Together, they determine the electromagnetic field distribution state generated after the motor is energized. Rotor speed refers to the actual rotational speed of the motor rotor during rotation. This speed directly determines the frequency and amplitude of mechanical vibration generated by the rotating parts of the motor. Motor housing temperature refers to the measured temperature value of the motor housing surface during operation. This temperature value can reflect the internal heating state of the motor and the temperature changes of the surrounding environment.

[0024] In this embodiment, the stator current and stator voltage are first collected by current transformers and voltage transformers arranged on the motor power supply line, the rotor speed is obtained by a speed sensor installed on the rotor shaft end of the motor, and the motor housing temperature is collected by a temperature sensor attached to the surface of the motor housing. Thus, multi-dimensional parameters of the motor under the operating state are obtained, providing basic data for subsequent analysis of the electromagnetic field distribution and mechanical vibration distribution in the space around the motor.

[0025] Step 102: Calculate the electromagnetic field distribution data of the motor based on the stator current and the stator voltage, and determine the electromagnetic interference intensity at different locations in the space surrounding the motor based on the electromagnetic field distribution data.

[0026] Among them, electromagnetic field distribution data refers to the collection of magnetic field vector data and electric field vector data at various spatial locations inside and around the motor. This data is used to describe the complete distribution of the electromagnetic field in space. The space around the motor refers to the three-dimensional spatial region extending outward from the geometric center of the motor to the detectable range of the electromagnetic field. This region includes all spatial locations within a certain distance outside the motor casing. Different locations refer to points with different spatial coordinates in the space around the motor, and each point corresponds to a set of electromagnetic field distribution data. Electromagnetic interference intensity refers to the quantitative value of the strength of electromagnetic fluctuations generated by the motor in the surrounding space when it is running. This intensity is used to characterize the severity of interference caused by the electromagnetic field at that location to nearby electronic equipment.

[0027] In this embodiment, step 102 includes the following process: Step 1021: Obtain the winding structure parameters of the motor, and based on the stator current, the stator voltage and the winding structure parameters, obtain the current density distribution and voltage gradient distribution of each phase winding of the motor in space.

[0028] In step 1021, the winding structure parameters refer to the arrangement of the stator windings of the motor in space, the number of turns of each phase winding, and the geometric dimensions of the winding conductors. These parameters determine the distribution of the magnetomotive force generated in space when the current passes through the windings. The current density distribution refers to the spatial distribution state formed by the magnitude of the current passing through each phase winding per unit cross-sectional area at each position in space. The voltage gradient distribution refers to the spatial distribution state formed by the voltage change per unit length at each position in space.

[0029] In this embodiment, the winding structure parameters of the motor are first retrieved from the motor design parameter library. These winding structure parameters include the spatial coordinate range of each phase winding, the number of turns, and the cross-sectional area of ​​the winding conductor. Then, the stator current is distributed to the corresponding spatial coordinate points according to the position and number of turns of each phase winding to obtain the current density value at each spatial position, thereby forming a current density distribution. Similarly, the stator voltage is distributed to the corresponding spatial coordinate points according to the position and length of each phase winding to obtain the voltage gradient value at each spatial position, thereby forming a voltage gradient distribution.

[0030] In practical applications, taking a three-phase asynchronous motor with a rated power of 15 kW as an example, the stator winding of this motor adopts a double-layer lap winding arrangement. The winding structure parameters record the coordinates of the 12 slots of the A-phase winding in a spatial rectangular coordinate system, the number of turns of each coil is 32, and the cross-sectional area of ​​the winding conductor is 2.5 square millimeters. The A-phase stator current of this motor is obtained as 18.5 amperes. The 18.5 amperes current is calculated according to the 32 turns of each coil of the A-phase winding and the cross-sectional area of ​​2.5 square millimeters. The current density at each of the 12 slot coordinate points is calculated to be approximately 7.4 × 10⁶ amperes per square meter, thus forming the current density distribution of the A-phase winding in space. Similarly, the A-phase stator voltage is obtained as 380 volts. The 380 volt voltage is distributed to the 12 slot coordinate points according to the conductor length of each coil of the A-phase winding. The voltage gradient at each slot coordinate point is calculated to be approximately 215 volts per meter, thus forming the voltage gradient distribution of the A-phase winding in space.

[0031] Step 1022: Using the geometric model of the motor, map the current density distribution and the voltage gradient distribution to various spatial locations inside and around the motor to obtain the magnetomotive force source strength and electric field source strength at each spatial location.

[0032] In step 1022, the geometric model refers to the digital model of the motor housing outline, the internal structure of the motor, and the surrounding space of the motor constructed using a three-dimensional spatial coordinate system. This model discretizes the space into several volume units, each volume unit corresponding to a spatial location point. The geometric model adopts the solid element model in finite element analysis, specifically a combination of tetrahedral and hexahedral elements. The stator core region of the motor uses hexahedral elements to accurately simulate the magnetic field distribution, while the winding region and surrounding space region use tetrahedral elements to adapt to complex boundary shapes. During the model design, the motor is divided into five substructures: stator core, stator winding, rotor, casing, and surrounding air domain. Continuity constraints are established between the substructures through node coupling.

[0033] This model is not obtained through training, but is directly constructed based on the CAD design drawings and material property parameters of the motor. The specific process is as follows: the 3D CAD model of the motor is imported into the finite element preprocessing software, the stator core and windings are meshed according to the unit size of 1 mm to 5 mm, the surrounding air domain is meshed according to the unit size of 5 mm to 20 mm, and each mesh unit is assigned corresponding material properties, including the relative permeability of silicon steel sheets, the conductivity of copper windings and the relative permittivity of air, and finally a geometric model for solving electromagnetic fields is formed.

[0034] It should be noted that the above structure is exemplary. This application does not impose specific limitations on the internal structure design corresponding to the geometric model, and can make corresponding settings according to the actual situation.

[0035] Mapping refers to the operation of extrapolating the current density and voltage gradient values ​​originally distributed at the location of the winding conductor to each spatial location point in the geometric model according to the physical laws of electromagnetic field propagation; the magnetomotive force source strength refers to the magnitude of the magnetomotive force generated by the current density distribution in space, which is used to describe the strength of the source of the magnetic field; the electric field source strength refers to the magnitude of the electric field generated by the voltage gradient distribution in space, which is used to describe the strength of the source of the electric field.

[0036] In this embodiment, a three-dimensional Cartesian coordinate system with the geometric center of the motor as the origin is first established. A geometric model of the motor is constructed in this coordinate system. The space inside and around the motor with a radius of 2 meters is divided into a cubic grid with a size of 1×1×1 cm. The center point of each grid is taken as a spatial location point. Then, for each spatial location point in the geometric model, the current density distribution of each phase winding is vector-superimposed at the point according to the spatial distance and relative azimuth angle between the point and the conductors of each phase winding to obtain the magnetomotive force source intensity at the point. Similarly, the voltage gradient distribution of each phase winding is vector-superimposed at the point to obtain the electric field source intensity at the point.

[0037] In practical applications, following the example of the aforementioned 15 kW three-phase asynchronous motor, a three-dimensional rectangular coordinate system with the geometric center of the motor as the origin is established. The spherical space with a radius of 2 meters inside and around the motor is divided into a cubic grid with a side length of 1 cm, totaling approximately 3.35 million grid cells. For a spatial location point with coordinates 0.5 meters away from the center of the motor and located directly in front of the motor, the spatial distance and relative azimuth angle between this point and the coordinates of the 12 slots of the A-phase winding are calculated. The current density values ​​of each slot coordinate point of the A-phase winding obtained in step 1021 are vector-superimposed according to the inverse square relationship of the distance, resulting in a magnetomotive force source intensity of 1280 amperes per meter at this spatial location point. Similarly, the voltage gradient values ​​of this point and each slot coordinate point are vector-superimposed, resulting in an electric field source intensity of 37 volts per meter at this spatial location point.

[0038] Step 1023: Based on the magnetomotive force source strength and the electric field source strength at each spatial location, the electromagnetic field distribution data at each spatial location is obtained by solving the electromagnetic field control equation of the motor.

[0039] In step 1023, the electromagnetic field control equations refer to Maxwell's equations, which describe the mathematical relationship between the strength of the magnetomotive force source and the strength of the electric field source and the magnetic flux density and electric field strength at various points in space.

[0040] The electromagnetic field governing equations are expressed in differential form of Maxwell's equations, where the curl equation of the magnetic field intensity is given by: ×H=J+ D / The equation for the curl of the electric field intensity is expressed as t. ×E=- B / The magnetic flux density divergence equation is expressed as t. When B=0, the electric field intensity divergence equation is expressed as: ·D=ρ; In the above system of equations, × denotes the curl operator. • represents the divergence operator, H represents the magnetic field strength vector in amperes per meter, J represents the current density vector in amperes per square meter, D represents the electric displacement vector in coulombs per square meter, t represents time in seconds, E represents the electric field strength vector in volts per meter, B represents the magnetic flux density vector in tesla, and ρ represents the charge density in coulombs per cubic meter.

[0041] In practical applications of solving the electromagnetic field of a motor, since the motor operates in AC power frequency mode and there is no free charge accumulation in the solution region, the equations are usually simplified to a time-harmonic field form, that is, the field quantities are expressed in complex form, and the time partial derivative terms are reduced. / Replace t with jω, where j is the imaginary unit and ω is the angular frequency in radians per second, thus transforming the system of partial differential equations into elliptic partial differential equations in the complex domain for numerical solution.

[0042] In this embodiment, the magnetomotive force source intensity and electric field source intensity at each spatial location point in the geometric model are used as input parameters of Maxwell's equations. The finite element numerical solution method is used to solve Maxwell's equations. Specifically, the cubic mesh in the geometric model is used as the element mesh for finite element analysis. The magnetic flux density and electric field intensity in each mesh element are expressed as a linear combination of shape functions. Maxwell's equations are transformed into a discretized algebraic equation system. The magnetic flux density vector and electric field intensity vector at the center point of each mesh element are obtained by iteratively solving the algebraic equation system. The magnetic flux density vector and electric field intensity vector at each spatial location point are used as the electromagnetic field distribution data at that spatial location point.

[0043] In practical applications, the 3.35 million cubic grid cells used in the aforementioned example are adopted. The magnetomotive force source intensity and electric field source intensity at the center point of each grid cell are input into Maxwell's equations. The Maxwell's equations are solved using finite element analysis software. For a spatial location point with coordinates 0.5 meters away from the center of the motor and located directly in front of the motor, the magnetic flux density vector obtained has components of 0.38 Tesla, 0.25 Tesla, and 0.40 Tesla in the three directions, and the electric field intensity vector obtained has components of 38 volts per meter, 25 volts per meter, and 40 volts per meter in the three directions, respectively. The magnetic flux density vector and electric field intensity vector are used as the electromagnetic field distribution data at this spatial location point. The above example is only one example of this application. In practical applications, it can be set according to the requirements. This application does not limit it.

[0044] Step 1024: Perform spectral decomposition on the electromagnetic field distribution data at each spatial location, extract the root mean square value of the electromagnetic fluctuation amplitude at each spatial location within a preset frequency band, and use the root mean square value as the electromagnetic interference intensity at each spatial location.

[0045] In step 1024, the preset frequency band refers to the frequency range in which the electromagnetic interference signals generated by the motor are concentrated. This frequency band is related to the power supply frequency of the motor and its harmonics. The root mean square value is the value obtained by summing the squares of the electromagnetic fluctuation amplitudes corresponding to each frequency component at a certain spatial location point within the preset frequency band, taking the average value, and then taking the square root.

[0046] In this embodiment, the electromagnetic field distribution data is first obtained as a time-series sequence, which records the change of the electromagnetic field vector at each spatial location point over time. Then, Fourier transform is used to convert the time-series data of each spatial location point to the frequency domain, obtaining the electromagnetic fluctuation amplitude of each spatial location point in each frequency component. Next, the electromagnetic fluctuation amplitude of each frequency component is extracted within a preset frequency band, and the sum of the squares of these amplitudes is divided by the number of frequency points to obtain the average value. Then, the square root of the average value is taken to obtain the root mean square value. Finally, the root mean square value of each spatial location point is used as the electromagnetic interference intensity at that point.

[0047] In practical applications, using the coordinates of the aforementioned example, a spatial location point 0.5 meters from the center of the motor and directly in front of it, is used. 100 sampling data points of the electric field intensity vector at this point are continuously collected within 1 second at a sampling interval of 0.01 seconds, resulting in a time-varying sequence of the electric field intensity vector. A Fast Fourier Transform is then used to convert this time sequence to the frequency domain, obtaining the electromagnetic fluctuation amplitude at each frequency point within the range of 0 Hz to 1000 Hz. The preset frequency bands are set to 45 Hz to 55 Hz and 90 Hz to 110 Hz. The electromagnetic fluctuation amplitude at each frequency point within these bands is extracted, and the root mean square value of these amplitudes is calculated to be 18.6 volts per meter. This root mean square value is used as the electromagnetic interference intensity at this spatial location point.

[0048] This application provides a spatial distribution basis for the optimized layout and targeted filtering of dust sensors by converting the stator current and stator voltage of the motor into electromagnetic interference intensity at various locations in space.

[0049] Step 103: Based on the rotor speed, determine the vibration intensity distribution at different locations in the space surrounding the motor, and based on the electromagnetic interference intensity and the vibration intensity distribution, generate an interference intensity distribution map of the space surrounding the motor using a preset interference distribution model.

[0050] Among them, vibration intensity distribution refers to the spatial distribution of the intensity of vibration at various spatial locations in the space surrounding the motor. This distribution is quantified by the vibration displacement amplitude at each location point. Interference intensity distribution map refers to a three-dimensional spatial distribution map with spatial coordinates as the horizontal, vertical and vertical axes and the comprehensive interference intensity as the numerical value. This map is used to intuitively show the strength of comprehensive interference at various locations in the space surrounding the motor.

[0051] The interference distribution model adopts a linear weighted fusion model structure, specifically a multi-physics coupled weighted summation model. This model consists of four parts: an electromagnetic interference intensity input substructure, a vibration intensity input substructure, a weight coefficient configuration substructure, and a comprehensive interference intensity output substructure. In terms of structural design, the electromagnetic interference intensity input substructure receives the electromagnetic interference intensity values ​​at each spatial location point, the vibration intensity input substructure receives the vibration displacement amplitude at the same spatial location point, the weight coefficient configuration substructure stores preset electromagnetic interference weight coefficients and vibration weight coefficients, and the comprehensive interference intensity output substructure adds the product of the electromagnetic interference intensity and the electromagnetic interference weight coefficient and the product of the vibration intensity and the vibration weight coefficient before outputting the result.

[0052] The model does not require a training process. The weighting coefficients are determined by synchronously measuring the electromagnetic interference and vibration sensors at the actual operating site of the motor. After collecting multiple sets of data, the least squares method is used for fitting. Specifically, several sampling points are selected in the space around the motor, and electromagnetic probes and accelerometers are arranged to collect the electromagnetic interference intensity and vibration intensity at each point. The goal is to maximize the correlation between the comprehensive interference intensity and the interference component in the dust sensor output signal. The electromagnetic interference weighting coefficient and vibration weighting coefficient are obtained by linear regression calculation.

[0053] It should be noted that the above structure is exemplary. This application does not impose specific limitations on the internal structure design corresponding to the interference distribution model, and can make corresponding settings according to the actual situation.

[0054] In this embodiment, step 103 includes the following process: Step 1031: Obtain the rotor mass distribution parameters and bearing support stiffness parameters of the motor. Based on the rotor speed, the rotor mass distribution parameters, and the bearing support stiffness parameters, calculate the excitation force amplitude and excitation force frequency at the bearing housing location.

[0055] In step 1031, the rotor mass distribution parameter refers to the mass value of each component on the motor rotor and its distribution position information in the direction of the rotating shaft. This parameter includes the mass of the rotor core, the mass of the rotor winding, and the mass distribution of the rotating shaft itself. The bearing support stiffness parameter refers to the value of the motor bearing's ability to resist deformation in the radial and axial directions. This parameter reflects the degree of constraint of the bearing on the rotor vibration. The excitation force amplitude refers to the magnitude of the periodic force generated at the bearing housing position due to mass imbalance during rotor rotation. The excitation force frequency refers to the frequency of this periodic force changing with time.

[0056] In this embodiment, the rotor mass distribution parameters are first obtained from the motor design parameters. These parameters record the mass value of each segment after the rotor is divided into several segments along the axial direction, as well as the distance from the center of mass of each segment to the shaft support point. Then, the bearing support stiffness parameters are obtained, which include the bearing stiffness coefficient in the radial direction. Next, the rotor rotational angular frequency is calculated based on the rotor speed. The unbalanced mass in the rotor mass distribution parameters is multiplied by the square of the rotational angular frequency, and then multiplied by the distance from the unbalanced mass to the bearing support point to obtain the excitation force amplitude. At the same time, the rotor speed is divided by 60 to obtain the rotational frequency, which is used as the excitation force frequency.

[0057] In practical applications, using the aforementioned 15 kW three-phase asynchronous motor example, the rotor mass distribution parameters of this motor are recorded as follows: rotor core mass is 12.5 kg, rotor winding mass is 3.8 kg, and shaft mass is 5.2 kg. The distances of the center of mass of each component from the left bearing support point are 0.15 m, 0.18 m, and 0.12 m, respectively. The radial stiffness coefficient in the bearing support stiffness parameters is 2.5 × 10⁸ Newtons per meter. The current rotor speed is 1470 revolutions per minute, and the calculated rotational angular frequency is... ,in, Indicates the rotational angular frequency. This indicates the rotor speed; multiplying the total rotor mass of 21.5 kg by the assumed unbalanced eccentricity of 0.01 mm yields an unbalanced mass of 0.000215 kg, i.e. The formula for calculating the excitation force amplitude is: ,in For unbalanced mass, The eccentricity is substituted into the calculation to obtain... The excitation frequency is The above example is only one example of this application. In practical applications, it can be set according to the requirements. This application does not limit it.

[0058] Step 1032: Transmit the excitation force amplitude and the excitation force frequency to each node on the surface of the motor housing to obtain the vibration displacement amplitude and vibration frequency of each node on the surface of the motor housing.

[0059] In step 1032, each node on the motor housing surface refers to each mesh node formed after the motor housing surface is discretized in the structural finite element model, and each node corresponds to a specific spatial position on the housing surface; the vibration displacement amplitude refers to the maximum distance that each node on the motor housing surface deviates from the equilibrium position under the action of the excitation force; the vibration frequency refers to the frequency of particle vibration at each spatial position when each node on the motor housing surface acts as a vibration source to propagate vibration to the surrounding space, and this frequency is consistent with the excitation force frequency.

[0060] In this embodiment, a finite element model of the motor structure is first constructed, which divides the motor housing into several elements, and the connection points between the elements are nodes. Then, the excitation force amplitude calculated in step 1031 is applied to the node corresponding to the bearing housing position, and the excitation force frequency is used as the excitation frequency. Next, the modal superposition method is used to solve the structural dynamic equations, and the vibration displacement response of each node on the surface of the motor housing under the action of the excitation force is calculated. Finally, the amplitude of the vibration displacement response of each node is extracted as the vibration displacement amplitude, and the response frequency is extracted as the vibration frequency.

[0061] In practical applications, following the previous example, a finite element model of the motor structure is constructed, dividing the motor housing into 5000 tetrahedral elements, totaling 8500 nodes, with the bearing housing position corresponding to node number 1240. An excitation force amplitude of 0.00051 Newtons is applied radially to node number 1240, and the excitation frequency is set to 24.5 Hz. The modal superposition method is used to solve the structural dynamic equations, and the vibration displacement amplitude of each node on the housing surface is extracted. The vibration displacement amplitude of the node located at the center of the top of the motor is 0.0032 mm, and the vibration frequency of this node is 24.5 Hz.

[0062] Step 1033: Propagate the vibration displacement amplitude and vibration frequency of each node on the surface of the motor housing to each spatial position in the space surrounding the motor, and obtain the vibration displacement amplitude of each spatial position in the space surrounding the motor as the vibration intensity distribution of each spatial position.

[0063] In this embodiment, an acoustic propagation model of the space surrounding the motor is first established. This model uses each node on the surface of the motor housing as a vibration source, and the vibration displacement amplitude and vibration frequency of each node are used as sound source parameters. Then, the boundary element method is used to calculate the sound pressure amplitude generated by each vibration source at each spatial location in the surrounding space. Then, according to the conversion relationship between the sound pressure amplitude and the particle vibration displacement amplitude, the sound pressure amplitude at each spatial location is converted into the vibration displacement amplitude. Finally, the vibration displacement amplitude at each spatial location is used as the vibration intensity distribution at that point.

[0064] In practical applications, following the previous example, a spatial acoustic model of the space surrounding the motor is established with the motor's geometric center as the origin. The vibration displacement amplitude and vibration frequency of 8500 nodes on the motor casing surface are used as the sound source input. The acoustic boundary element method is used to calculate the sound pressure amplitude at a point 0.5 meters away from the motor center and directly in front of the motor, which is 0.015 Pascals. Based on the relationship between sound pressure and particle vibration displacement in air, the particle vibration displacement amplitude is equal to the sound pressure amplitude divided by the product of air density, sound velocity, and angular frequency. The air density is taken as 1.2 kg / m³, the sound velocity as 340 m / s, and the angular frequency as 2 × 3.14 × 24.5 ≈ 154 radians / s. The vibration displacement amplitude at this point is calculated to be... The amplitude of the vibration displacement is taken as the vibration intensity distribution at that spatial location point.

[0065] Step 1034: Based on the vibration intensity distribution and electromagnetic interference intensity at each spatial location, the electromagnetic interference intensity and vibration intensity distribution at the same spatial location are weighted and summed using the interference distribution model to obtain the comprehensive interference intensity at each spatial location. Based on the comprehensive interference intensity at each spatial location and the corresponding spatial coordinates, an interference intensity distribution map of the space surrounding the motor is generated.

[0066] In step 1034, the comprehensive interference intensity refers to the total interference level under the coupling effect of electromagnetic interference and mechanical vibration at the same spatial location. This intensity is calculated by weighted summation of electromagnetic interference intensity and vibration intensity distribution, and is used to quantify the comprehensive influence of this location on the dust sensor signal acquisition.

[0067] In this embodiment, the electromagnetic interference intensity of each spatial location point calculated in step 102 and the vibration intensity distribution of the same spatial location point calculated in step 1033 are first obtained; then, preset electromagnetic interference weighting coefficients and vibration weighting coefficients are obtained, the electromagnetic interference intensity of the same spatial location point is multiplied by the electromagnetic interference weighting coefficient, the vibration intensity is multiplied by the vibration weighting coefficient, and the two products are added together to obtain the comprehensive interference intensity of the spatial location point; finally, all spatial location points around the motor are traversed, and the spatial coordinates of each point are associated with the comprehensive interference intensity of that point to generate an interference intensity distribution map.

[0068] In practical applications, using the coordinates from the previous example, the point is located 0.5 meters from the center of the motor and directly in front of it. The electromagnetic interference intensity at this point is 18.6 volts per meter, and the vibration intensity is... Assuming an electromagnetic interference weighting coefficient of 0.7 and a vibration weighting coefficient of 0.3, the calculated comprehensive interference intensity is 0.7 × 18.6 + 0.3 × ≈13.02 volts per meter; Traverse 3.35 million spatial location points in the space around the motor, store the three-dimensional spatial coordinates of each point and the comprehensive interference intensity value calculated for that point, and generate a three-dimensional distribution map with spatial coordinates as the horizontal, vertical and vertical coordinate axes and comprehensive interference intensity as the numerical value. The above example is only one example of this application. In actual applications, it can be set according to the requirements. This application does not limit it.

[0069] This application converts rotor speed into spatial vibration intensity distribution, and then weights and fuses electromagnetic interference intensity with vibration intensity distribution to generate a comprehensive interference intensity distribution map that reflects the coupling effect of electromagnetic and vibration, providing a comprehensive spatial interference assessment basis for the optimized deployment of dust sensors.

[0070] Step 104: Determine the installation location of the dust sensor according to the interference intensity distribution map, and collect the electrical signal output by the dust sensor. The electrical signal is used to characterize the dust concentration in the environment.

[0071] Among them, the electrical signal refers to the electrical quantity output by the dust sensor when it is working in the measured environment. The amplitude or frequency of the electrical signal is related to the concentration of dust particles in the environment.

[0072] In this embodiment, step 104 includes the following process: Step 1041: Locate the spatial region in the interference intensity distribution map where the overall interference intensity is less than the preset intensity threshold.

[0073] In step 1041, the preset intensity threshold refers to a pre-set comprehensive interference intensity value, which is used to distinguish between areas suitable for installing dust sensors and areas unsuitable for installing dust sensors. It is assumed that the preset intensity threshold is set to 10 volts per meter. The spatial region refers to a connected region composed of several adjacent spatial location points, where the comprehensive interference intensity of all points in the region is less than the preset intensity threshold.

[0074] In this embodiment, the interference intensity distribution map generated in step 103 is first read from the storage device. The distribution map records the three-dimensional coordinates of each spatial location point in the space around the motor and its corresponding comprehensive interference intensity value. Then, the comprehensive interference intensity of each spatial location point is compared with a preset intensity threshold, and all spatial location points with comprehensive interference intensity less than the preset intensity threshold are selected. Next, the selected spatial location points are clustered according to spatial adjacency, and adjacent points are grouped into the same spatial region, finally obtaining one or more spatial regions.

[0075] Step 1042: Select a spatial location from the spatial region as the installation location of the dust sensor.

[0076] In step 1042, the selection criterion is to prioritize the spatial location that is farthest from the motor and convenient for installation and maintenance as the installation location of the dust sensor.

[0077] In this embodiment of the application, when there is only one spatial area located in step 1041, a spatial location that is easy to install and operate is directly selected within the spatial area as the installation location of the dust sensor; when there are multiple spatial areas located, the spatial area that is farthest from the motor or closest to the dust source to be measured is selected first, and a spatial location within the spatial area is selected as the installation location.

[0078] Step 1043: Fix the dust sensor at the installation position and collect the electrical signal generated by the dust particles in the environment hitting the dust sensor.

[0079] In this embodiment, the dust sensor is first fixed at the installation position determined in step 1042 using a bracket or mounting base, ensuring that the sensing surface of the sensor faces the direction of the dust source to be measured. Then, the dust sensor is activated, and an electrostatic field or optical path is generated inside the sensor. When suspended dust particles in the environment enter the sensing area of ​​the sensor and collide with the sensor's sensitive element, the sensor converts the collision event of the dust particles into a pulse electrical signal or a continuously changing current signal output. Finally, the electrical signal output by the sensor is continuously recorded by a data acquisition device for subsequent signal processing and concentration calculation.

[0080] This application uses an interference intensity distribution map to select the spatial area with the least overall interference as the installation location for the dust sensor, thereby reducing the impact of electromagnetic interference and mechanical vibration on sensor signal acquisition from the source.

[0081] Step 105: Obtain the local electromagnetic interference intensity and local vibration intensity of the dust sensor at the installation position, and perform notch filtering on the electrical signal according to the local electromagnetic interference intensity to filter out the interference signal and obtain the correction signal.

[0082] Among them, the local electromagnetic interference intensity refers to the electromagnetic interference intensity value at the dust sensor installation location, which is extracted from the electromagnetic interference intensity obtained in step 102; the local vibration intensity refers to the vibration intensity value at the dust sensor installation location, which is extracted from the vibration intensity distribution obtained in step 103; notch filtering is a filtering method that attenuates the signal near a specific frequency point, which is used to filter out interference of specific frequency components in the signal; the correction signal refers to the signal obtained after notch filtering the original electrical signal, in which the electromagnetic interference components of specific frequencies have been attenuated.

[0083] In this embodiment, step 105 includes the following process, such as... Figure 2 As shown: Step 1051: Based on the local electromagnetic interference intensity, look up the dominant frequency component that matches the local electromagnetic interference intensity from a preset electromagnetic interference frequency mapping table, and use it as the interference frequency at the installation location.

[0084] In step 1051, the preset electromagnetic interference frequency mapping table refers to a pre-established data table used to record the correspondence between electromagnetic interference intensity values ​​and dominant interference frequencies. This table is obtained through experimental calibration or electromagnetic field simulation, as shown in Table 1:

[0085] In this mapping table, the electromagnetic interference intensity range is divided according to the power supply frequency and its harmonics when the motor is running. The dominant frequency component corresponds to the motor's rotation frequency, power supply frequency or its harmonics. The values ​​in the table are only one example of this application. In actual applications, they can also be set according to the actual parameters of the motor and the field test data. This application does not limit this.

[0086] The dominant frequency component refers to the frequency value in the electromagnetic interference signal where the energy is most concentrated; the interference frequency refers to the main frequency component of the electromagnetic interference signal at the installation location, and this frequency is used to set the filtering parameters of the notch filter.

[0087] In this embodiment of the application, the local electromagnetic interference intensity at the dust sensor installation location determined in step 104 is first obtained; then, a preset electromagnetic interference frequency mapping table is read, which stores multiple sets of electromagnetic interference intensity values ​​and interference frequencies; next, the record closest to the local electromagnetic interference intensity value is found in the mapping table, and the interference frequency corresponding to the record is taken as the interference frequency at the installation location.

[0088] In practical applications, using the example above, the local electromagnetic interference intensity at the installation location is 18.6 volts per meter. The preset electromagnetic interference frequency mapping table records that when the electromagnetic interference intensity is in the range of 15 volts per meter to 20 volts per meter, the corresponding interference frequency is 24.5 Hz. Therefore, the interference frequency at this installation location is found to be 24.5 Hz.

[0089] Step 1052: Calculate the center frequency and bandwidth of the notch filter based on the interference frequency, and configure the notch filter according to the center frequency and bandwidth to obtain the configured notch filter.

[0090] Among them, a notch filter is a filter with an extremely narrow stopband at a specific frequency point. This filter is used to attenuate the energy of specific frequency components in a signal; the center frequency refers to the frequency value at the center of the notch filter's stopband; the bandwidth refers to the width range of the notch filter's stopband; and the configured notch filter refers to a notch filter that has completed parameter settings and is ready for use.

[0091] Step 1052 may specifically include the following steps: A1: The interference frequency is taken as the center frequency of the notch filter.

[0092] In this embodiment of the application, the interference frequency obtained in step 1051 is directly assigned to the center frequency parameter of the notch filter, so that the stopband center of the notch filter is aligned with the interference frequency.

[0093] In practical applications, following the example above, the interference frequency of 24.5 Hz is used as the center frequency of the notch filter.

[0094] A2: Multiply the center frequency by the preset bandwidth coefficient to obtain the bandwidth of the notch filter.

[0095] In step A2, the preset bandwidth coefficient refers to the coefficient set in advance for calculating the bandwidth of the notch filter, which determines the width range of the stopband.

[0096] In practical applications, following the previous example, if the preset bandwidth coefficient is 0.05, then the bandwidth is the center frequency of 24.5 Hz multiplied by 0.05, which calculates to a bandwidth of 1.225 Hz.

[0097] A3: Determine the zero-point frequency and pole-point frequency in the transfer function of the notch filter based on the center frequency and the bandwidth.

[0098] In step A3, the transfer function refers to the input-output relationship expression of the notch filter in the frequency domain, which describes the attenuation characteristics of the filter for signals of different frequencies; the zero frequency refers to the frequency value corresponding to the numerator of the transfer function being zero, at which the filter attenuates the signal the most; the pole frequency refers to the frequency value corresponding to the denominator of the transfer function being zero, which affects the shape and width of the filter's stopband.

[0099] In this embodiment, the zero-point frequency and pole frequency of the notch filter are calculated based on the center frequency and bandwidth, wherein the zero-point frequency is set as the center frequency, and the pole frequency is calculated based on the center frequency and bandwidth using a preset filter design formula.

[0100] In practical applications, following the previous example, the center frequency is 24.5 Hz, the bandwidth is 1.225 Hz, the zero frequency is set to 24.5 Hz, and the pole frequency is determined by the formula... Calculation, where The pole frequency, For the center frequency, Given the bandwidth, the frequencies of the two poles are calculated as follows: and .

[0101] A4: Load the zero frequency and the pole frequency into the parameter register of the notch filter to complete the configuration of the notch filter.

[0102] In step A4, the parameter register refers to the storage unit in the notch filter used to store configuration parameters.

[0103] The configuration method of notch filters varies depending on the implementation: when the notch filter is implemented in hardware, the configuration process is as follows: the calculated center frequency and bandwidth are converted into digital control words, and the control words are written into the configuration register of the hardware filter chip through the microcontroller's general-purpose input / output interface or serial peripheral interface bus. The hardware filter chip then adjusts the equivalent parameters of the internal resistor and capacitor network or the coefficients of the digital filter according to the values ​​in the register, thereby completing the hardware parameter configuration of the notch filter. When a notch filter is implemented in software, the configuration process involves calculating the transfer function coefficients of the digital notch filter based on the calculated center frequency and bandwidth using the filter design formula. These coefficients are then loaded into the digital filter algorithm module of the digital signal processor or microcontroller to update the filter's coefficient array, thereby completing the parameter configuration of the software notch filter.

[0104] In this embodiment of the application, the zero-point frequency and pole frequency determined in step A3 are written into the parameter register of the notch filter, so that the notch filter attenuates the input signal according to the set center frequency and bandwidth.

[0105] In practical applications, following the previous example, the zero frequency of 24.5 Hz and the pole frequencies of 23.8875 Hz and 25.1125 Hz are written into the parameter register of the notch filter to complete the configuration of the notch filter.

[0106] Step 1053: Input the electrical signal into the configured notch filter, and the configured notch filter attenuates the electrical signal and outputs the attenuated signal as a correction signal.

[0107] In this embodiment, the electrical signal output by the dust sensor is sent as an input signal to the notch filter configured in step 1052. The notch filter processes the input signal according to its transfer function, attenuates the signal near the center frequency, filters out signal components that match the interference frequency, and outputs the attenuated signal as a correction signal.

[0108] In practical applications, following the previous example, the electrical signal output by the dust sensor is input into a notch filter with a center frequency of 24.5 Hz and a bandwidth of 1.225 Hz. The filter attenuates the frequency components near 24.5 Hz in the electrical signal and outputs the attenuated signal as a correction signal.

[0109] This application obtains the interference frequency at the installation location by querying the local electromagnetic interference intensity, and configures a notch filter accordingly to filter the electrical signal, thereby achieving precise suppression of the actual electromagnetic interference at the sensor's location.

[0110] Step 106: Based on the local vibration intensity and the motor housing temperature, compensate and correct the correction signal to eliminate sensor measurement deviation and obtain the dust concentration value.

[0111] Among them, compensation correction refers to the operation of adjusting the correction signal by introducing vibration and temperature compensation, which is used to eliminate sensor measurement deviations caused by vibration and temperature changes; the dust concentration value refers to the final measurement result obtained after compensation correction, which is used to characterize the dust particle content in the environment.

[0112] In this embodiment, step 106 includes the following process: Step 1061: Obtain the sensitivity change coefficient of the dust sensor at the installation location due to vibration.

[0113] In step 1061, the sensitivity change coefficient refers to the degree to which the conversion relationship between the output signal and the dust concentration changes when the dust sensor is subjected to vibration. This coefficient is used to quantify the impact of vibration on the sensor's measurement sensitivity.

[0114] In this embodiment of the application, the sensitivity variation coefficient of the dust sensor is obtained through a pre-conducted vibration calibration experiment. The specific process is as follows: the dust sensor is fixed on a vibration table, vibrations of different amplitudes are applied in a dust-free environment, the change in the sensor output signal is recorded, the ratio of the change in the output signal to the vibration amplitude is calculated, and this ratio is used as the sensitivity variation coefficient and stored in the sensor's parameter table; when needed, the coefficient is read from the parameter table.

[0115] In practical applications, following the example above, the vibration calibration experiment shows that the sensitivity change coefficient of this type of dust sensor at the installation location due to vibration is 0.02 per meter per millivolt. That is, for every 1 micrometer increase in local vibration intensity, the sensor output signal increases by 0.02 millivolts per milligram per cubic meter.

[0116] Step 1062: Obtain the zero-point drift of the dust sensor due to temperature at the motor housing temperature.

[0117] In step 1062, the zero-point drift refers to the offset of the output signal of the dust sensor as the temperature changes in a dust-free environment. This offset is used to quantify the effect of temperature on the zero point of the sensor.

[0118] In this embodiment, the relationship curve between the zero-point drift of the dust sensor and temperature is obtained through a pre-conducted temperature calibration experiment. The specific process is as follows: the dust sensor is placed in a temperature control chamber, and the temperature is gradually increased from the lowest operating temperature to the highest operating temperature in a dust-free environment. The output value of the sensor at each temperature point is recorded. With the output value at a preset reference temperature as a reference, the output offset at each temperature point is calculated to obtain the relationship curve between the zero-point drift and temperature. When needed, the corresponding zero-point drift is retrieved from the relationship curve based on the current motor housing temperature.

[0119] In practical applications, following the previous example, the relationship between the zero-point drift of this dust sensor and temperature was obtained through a temperature calibration experiment. The preset reference temperature was 20 degrees Celsius, and the zero-point drift was 0.15 millivolts when the motor housing temperature was 45 degrees Celsius.

[0120] Step 1063: Multiply the local vibration intensity by the sensitivity change coefficient to obtain the vibration compensation amount of the correction signal.

[0121] In practical applications, following the previous example, the local vibration intensity is: The sensitivity variation coefficient is 0.02 per meter per millivolt, and the vibration compensation is... .

[0122] Step 1064: Based on the difference between the motor housing temperature and the preset reference temperature, multiply the difference by the zero-point drift to obtain the temperature compensation amount of the correction signal.

[0123] In this embodiment of the application, a preset reference temperature is first obtained, which is usually set as the ambient temperature during sensor calibration; then the difference between the current motor housing temperature and the preset reference temperature is calculated; finally, the difference is multiplied by the zero-point drift amount obtained in step 1062 to calculate the temperature compensation amount, which is used to offset the sensor zero-point offset caused by temperature changes.

[0124] In practical applications, following the previous example, the preset reference temperature is 20 degrees Celsius, and the current motor housing temperature is 45 degrees Celsius, with a difference of 25 degrees Celsius; the zero-point drift is 0.006 millivolts per degree Celsius, and the calculated temperature compensation is 25 × 0.006 = 0.15 millivolts.

[0125] Step 1065: Based on the vibration compensation amount and the temperature compensation amount, correct the amplitude of the correction signal to obtain the dust concentration value.

[0126] In this embodiment of the application, the amplitude of the correction signal obtained in step 105 is subtracted by the vibration compensation amount and then by the temperature compensation amount to obtain the corrected signal amplitude; then the corrected signal amplitude is substituted into the concentration conversion relationship pre-calibrated by the sensor to calculate the dust concentration value.

[0127] In practical applications, following the previous example, the amplitude of the correction signal is 1.5 millivolts, and the vibration compensation is... The temperature compensation is 0.15 mV, and the corrected signal amplitude is 1.5 - 0.15 = 1.35 mV. According to the sensor calibration curve, when the output signal is 1.35 mV, the corresponding dust concentration is 2.7 mg / m³. This value is taken as the final dust concentration value.

[0128] This application corrects the calibration signal by using vibration compensation and temperature compensation, eliminating measurement deviations caused by sensor vibration and temperature changes, and improving the accuracy of dust concentration monitoring.

[0129] Figure 3 This is a schematic diagram of the structure of a dust environment concentration monitoring system provided in an embodiment of this application, as shown below. Figure 3 As shown, the system includes: The acquisition module 31 is used to acquire the operating parameters of the motor, including the stator current, stator voltage, rotor speed and motor housing temperature.

[0130] The calculation module 32 is used to calculate the electromagnetic field distribution data of the motor based on the stator current and the stator voltage, and to determine the electromagnetic interference intensity at different locations in the space surrounding the motor based on the electromagnetic field distribution data.

[0131] The determination module 33 is used to determine the vibration intensity distribution at different locations in the space surrounding the motor based on the rotor speed, and to generate an interference intensity distribution map of the space surrounding the motor based on the electromagnetic interference intensity and the vibration intensity distribution and through a preset interference distribution model.

[0132] The acquisition module 34 is used to determine the installation position of the dust sensor according to the interference intensity distribution map, and to acquire the electrical signal output by the dust sensor, wherein the electrical signal is used to characterize the dust concentration in the environment.

[0133] The filtering module 35 is used to obtain the local electromagnetic interference intensity and local vibration intensity of the dust sensor at the installation position, and to perform notch filtering on the electrical signal according to the local electromagnetic interference intensity to obtain a correction signal.

[0134] The compensation module 36 is used to compensate and correct the correction signal based on the local vibration intensity and the motor housing temperature to eliminate sensor measurement deviation and obtain the dust concentration value.

[0135] The dust environment concentration monitoring system of this application embodiment is used to implement the aforementioned dust environment concentration monitoring method. Therefore, the specific implementation of the dust environment concentration monitoring system can be found in the embodiment section of the dust environment concentration monitoring method above. The specific implementation can be referred to the description of the corresponding embodiments, which will not be repeated here.

[0136] This application also provides an electronic device, comprising: a memory for storing a computer program; and a processor for executing the computer program to implement the steps of any of the dust environmental concentration monitoring methods described above.

[0137] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of any of the dust environmental concentration monitoring methods described above.

[0138] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory, random access memory, portable hard drives, magnetic disks, or optical disks.

[0139] The embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the dust environment concentration monitoring method embodiments described above.

[0140] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0141] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of related data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0142] The above provides a detailed description of a dust environmental concentration monitoring method and system provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of this application.

Claims

1. A method for monitoring dust environmental concentration, characterized in that, include: The operating parameters of the motor are obtained, including the stator current, stator voltage, rotor speed, and motor housing temperature. Based on the stator current and the stator voltage, the electromagnetic field distribution data of the motor is calculated, and based on the electromagnetic field distribution data, the electromagnetic interference intensity at different locations in the space surrounding the motor is determined. Based on the rotor speed, the vibration intensity distribution at different locations in the space surrounding the motor is determined, and based on the electromagnetic interference intensity and the vibration intensity distribution, an interference intensity distribution map of the space surrounding the motor is generated using a preset interference distribution model. Based on the interference intensity distribution map, the installation location of the dust sensor is determined, and the electrical signal output by the dust sensor is collected. The electrical signal is used to characterize the dust concentration in the environment. The local electromagnetic interference intensity and local vibration intensity of the dust sensor at the installation position are obtained, and the electrical signal is notched and filtered according to the local electromagnetic interference intensity to obtain a correction signal. Based on the local vibration intensity and the motor housing temperature, the correction signal is compensated and corrected to eliminate sensor measurement deviation and obtain the dust concentration value.

2. The method according to claim 1, characterized in that, The step of performing notch filtering on the electrical signal to remove interference signals based on the local electromagnetic interference intensity to obtain a correction signal includes: Based on the local electromagnetic interference intensity, the dominant frequency component that matches the local electromagnetic interference intensity is queried from a preset electromagnetic interference frequency mapping table and used as the interference frequency at the installation location. Based on the interference frequency, calculate the center frequency and bandwidth of the notch filter, and configure the notch filter according to the center frequency and bandwidth to obtain the configured notch filter. The electrical signal is input into the configured notch filter, which attenuates the electrical signal and outputs the attenuated signal as a correction signal.

3. The method according to claim 1, characterized in that, The step involves determining the vibration intensity distribution at different locations in the space surrounding the motor based on the rotor speed, and generating an interference intensity distribution map of the space surrounding the motor based on the electromagnetic interference intensity and the vibration intensity distribution, using a preset interference distribution model. This includes: Obtain the rotor mass distribution parameters and bearing support stiffness parameters of the motor, and calculate the excitation force amplitude and excitation force frequency at the bearing housing position based on the rotor speed, the rotor mass distribution parameters and the bearing support stiffness parameters; The excitation force amplitude and the excitation force frequency are transmitted to each node on the surface of the motor housing to obtain the vibration displacement amplitude and vibration frequency of each node on the surface of the motor housing. The vibration displacement amplitude and vibration frequency of each node on the surface of the motor housing are propagated to each spatial position in the space surrounding the motor, and the vibration displacement amplitude of each spatial position in the space surrounding the motor is obtained as the vibration intensity distribution of each spatial position. Based on the vibration intensity distribution and electromagnetic interference intensity at each spatial location, the electromagnetic interference intensity and vibration intensity distribution at the same spatial location are weighted and summed using the interference distribution model to obtain the comprehensive interference intensity at each spatial location. Based on the comprehensive interference intensity at each spatial location and the corresponding spatial coordinates, an interference intensity distribution map of the space surrounding the motor is generated.

4. The method according to claim 1, characterized in that, The step of compensating and correcting the correction signal based on the local vibration intensity and the motor housing temperature to eliminate sensor measurement deviation and obtain the dust concentration value includes: Obtain the sensitivity change coefficient of the dust sensor at the installation position due to vibration; The amount of zero-point drift of the dust sensor due to temperature at the motor housing temperature is obtained; Multiplying the local vibration intensity by the sensitivity variation coefficient yields the vibration compensation amount of the correction signal; Based on the difference between the motor housing temperature and the preset reference temperature, the difference is multiplied by the zero-point drift to obtain the temperature compensation amount of the correction signal; The amplitude of the correction signal is corrected based on the vibration compensation amount and the temperature compensation amount to obtain the dust concentration value.

5. The method according to claim 1, characterized in that, The step of calculating the electromagnetic field distribution data of the motor based on the stator current and the stator voltage, and determining the electromagnetic interference intensity at different locations in the space surrounding the motor based on the electromagnetic field distribution data, includes: Obtain the winding structure parameters of the motor, and based on the stator current, the stator voltage, and the winding structure parameters, obtain the current density distribution and voltage gradient distribution of each phase winding of the motor in space; Using the geometric model of the motor, the current density distribution and the voltage gradient distribution are mapped to various spatial locations inside and around the motor to obtain the magnetomotive force source strength and electric field source strength at each spatial location. Based on the magnetomotive force source strength and the electric field source strength at each spatial location, the electromagnetic field distribution data at each spatial location is obtained by solving the electromagnetic field control equation of the motor. The electromagnetic field distribution data at each spatial location is subjected to spectral decomposition to extract the root mean square value of the electromagnetic fluctuation amplitude at each spatial location within a preset frequency band, and the root mean square value is used as the electromagnetic interference intensity at each spatial location.

6. The method according to claim 2, characterized in that, The step of calculating the center frequency and bandwidth of the notch filter based on the interference frequency, and configuring the notch filter according to the center frequency and bandwidth to obtain the configured notch filter includes: The interference frequency is used as the center frequency of the notch filter; The bandwidth of the notch filter is obtained by multiplying the center frequency by a preset bandwidth coefficient. Based on the center frequency and the bandwidth, determine the zero frequency and pole frequency in the transfer function of the notch filter; The zero-point frequency and the pole frequency are loaded into the parameter register of the notch filter to complete the configuration of the notch filter.

7. The method according to claim 1, characterized in that, The step of determining the installation location of the dust sensor based on the interference intensity distribution map and collecting the electrical signal output by the dust sensor includes: Locate the spatial region in the interference intensity distribution map where the overall interference intensity is less than a preset intensity threshold. Select a spatial location from the spatial region as the installation location for the dust sensor; The dust sensor is fixed at the installation position, and the electrical signal generated by the collision of dust particles in the environment with the dust sensor is collected.

8. A dust environmental concentration monitoring system, characterized in that, include: The acquisition module is used to acquire the operating parameters of the motor, including the stator current, stator voltage, rotor speed and motor housing temperature. The calculation module is used to calculate the electromagnetic field distribution data of the motor based on the stator current and the stator voltage, and to determine the electromagnetic interference intensity at different locations in the space surrounding the motor based on the electromagnetic field distribution data. The determination module is used to determine the vibration intensity distribution at different locations in the space surrounding the motor based on the rotor speed, and to generate an interference intensity distribution map of the space surrounding the motor based on the electromagnetic interference intensity and the vibration intensity distribution through a preset interference distribution model. The acquisition module is used to determine the installation location of the dust sensor according to the interference intensity distribution map, and to acquire the electrical signal output by the dust sensor, wherein the electrical signal is used to characterize the dust concentration in the environment; The filtering module is used to obtain the local electromagnetic interference intensity and local vibration intensity of the dust sensor at the installation position, and to perform notch filtering on the electrical signal according to the local electromagnetic interference intensity to obtain a correction signal; The compensation module is used to compensate and correct the correction signal based on the local vibration intensity and the motor housing temperature to eliminate sensor measurement deviation and obtain the dust concentration value.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the steps of the dust environmental concentration monitoring method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, enables the dust environmental concentration monitoring method as described in any one of claims 1 to 7.

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