CN107907899B - Vehicle-mounted terminal with tail gas detection function and detection method thereof - Google Patents
Vehicle-mounted terminal with tail gas detection function and detection method thereof Download PDFInfo
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- CN107907899B CN107907899B CN201711353304.6A CN201711353304A CN107907899B CN 107907899 B CN107907899 B CN 107907899B CN 201711353304 A CN201711353304 A CN 201711353304A CN 107907899 B CN107907899 B CN 107907899B
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
- G01N33/0036—Specially adapted to detect a particular component
- G01N33/004—Specially adapted to detect a particular component for CO, CO2
Abstract
The invention relates to a vehicle-mounted terminal with a tail gas detection function and a detection method thereof, wherein the vehicle-mounted terminal comprises a host microprocessor, a combined positioning module, a wireless communication module, a data storage module, a power module, a tail gas detection module and a camera module, and the tail gas detection module is arranged on an automobile exhaust pipe; the camera shooting module comprises a camera shooting microprocessor, an LCD main control board, a camera shooting storage module and two cameras, wherein the camera shooting microprocessor is connected with the host microprocessor through a USB data line, the cameras acquire images around the vehicle, and the camera shooting microprocessor performs image compression processing and stores the images in the camera shooting storage module. The vehicle-mounted terminal has the functions of video monitoring, data acquisition, space-time and motion attitude reporting, tail gas detection and the like, improves the safety of a vehicle, provides a large amount of real and effective data for a government, and provides tail gas distribution data of the whole city for the government through tail gas detection of the vehicle.
Description
Technical Field
The invention relates to the technical field of vehicle safety, in particular to a vehicle-mounted terminal with a tail gas detection function and a detection method thereof.
Background
With the development of society, in order to meet the requirements of scientific dispatching and management, traffic and safety, vehicle use and maintenance, energy conservation and environmental protection, requirements of insurance claims and the like, and data support for government decisions and corresponding services of related units and individuals, the monitoring requirements for vehicles are more and more intense, but the current monitoring systems cannot meet the increasing requirements.
Disclosure of Invention
The invention aims to provide a vehicle-mounted terminal with a tail gas detection function and a detection method thereof, which are used for solving the problems that the existing vehicle monitoring system is single in function and cannot meet the increasing demands.
In order to achieve the above purpose, the vehicle-mounted terminal with the tail gas detection function comprises a host microprocessor, a combined positioning module, a wireless communication module, a data storage module, a power module, a tail gas detection module and a camera module, wherein the combined positioning module, the wireless communication module, the data storage module, the power module, the tail gas detection module and the camera module are all connected with the host microprocessor;
the tail gas detection module is arranged on an automobile exhaust pipe;
the camera shooting module comprises a camera shooting microprocessor, an LCD main control board, a camera shooting storage module and two cameras, wherein the camera shooting microprocessor is connected with the host microprocessor through a USB data line, the LCD main control board, the camera shooting storage module and the two cameras are all connected with the camera shooting microprocessor, the camera shooting microprocessor obtains images around a vehicle, and the camera shooting microprocessor compresses the images and stores the compressed images in the camera shooting storage module.
The camera is an ultra-wide angle camera.
The vehicle-mounted terminal further comprises an alarm, an external storage module and an OBD interface, wherein the alarm, the external storage module and the OBD interface are connected with the host microprocessor;
the external storage module is used for storing data of the tail gas detection module;
and the host microprocessor is connected with an automobile circuit through an OBD interface, and reads data through the OBD interface.
The wireless communication module is a cellular-based narrowband internet of things (Narrow Band Internet of Things, NB-IoT).
The combined positioning module comprises a satellite positioning navigation module and an inertial navigation module.
The satellite positioning navigation module is a BD/GPS compatible module.
The camera shooting storage module is a TF card.
The host microprocessor is connected to a central monitoring platform through an NB-IoT module.
The combined positioning module comprises a satellite positioning navigation module and an inertial navigation module;
the detection method comprises the following steps:
the host microprocessor transmits the data detected by the tail gas detection module and the camera shooting module to the central monitoring platform through the NB-IoT module, and simultaneously the combined positioning module positions the vehicle-mounted terminal and transmits the data to the central monitoring platform through the NB-IoT module;
the combined positioning module is used for positioning the position of the vehicle-mounted terminal and specifically comprises the following steps of:
s1, a carrier phase tracking loop based on bandwidth self-adaption of a fuzzy reasoning system is adopted, when the signal-to-noise ratio of satellite signals is reduced, the bandwidth of the carrier phase tracking loop is reduced, and the anti-noise interference capability of a receiver is improved;
s2, describing the change of the measured noise by adopting a Kalman filtering integrated navigation algorithm based on the self-adaption of the measured noise model of the fuzzy reasoning system, adjusting the measured noise variance matrix in real time, and improving the anti-noise interference capability of the integrated navigation algorithm.
The specific steps of the step S1 are as follows:
s101, calculating a signal to noise ratio C/N0 according to the GPS digital signal after down-conversion and digital-to-analog conversion, wherein the formula is as follows:
wherein:
in the above two formulas, A is GPS signal amplitude, M E Is the integral count value delta iq Is the standard deviation of signal noise, T Int Is the integration time.
S102, establishing a fuzzy control system, taking C/N0 as input, taking the bandwidth of a GPS tracking loop as output, and adopting the following fuzzy reasoning rule:
(1) If the signal-to-noise ratio is less than 30dB, the phase-locked loop bandwidth is narrow;
(2) If the signal-to-noise ratio is 30-40 dB, the phase-locked loop bandwidth is moderate;
(3) If the signal-to-noise ratio is higher than 40dB, the phase-locked loop bandwidth is wide;
and taking the current output of the fuzzy control system as the next carrier phase tracking loop bandwidth value, realizing the self-adaptive adjustment of the carrier loop bandwidth, and improving the noise anti-interference capability of the GPS or Beidou navigation system.
The specific step of S2 is as follows:
s201, calculating the innovation of the Kalman filter, as shown in the formula (4)
Wherein z is k For actual measurement of quantity H k In order to measure the matrix of the device,is an estimate of the state of the system.
S202, calculating an innovation theory variance, wherein the innovation theory variance can be calculated by a formula (5):
wherein F is k/k-1 For the system state transition matrix, P k-1 To estimate the state variance matrix, Q k-1 R is a system noise array k-1 To measure noise arrays.
S203, calculating the actual variance of the innovation, which can be calculated by the latest N innovation vectors and is represented by a formula (6):
s204, calculating the ratio of the actual variance to the theoretical variance of the innovation. Due toAnd->Are arranged as a diagonal array, so the ratio is also a diagonal array:
s205, designing a fuzzy inference system, wherein the ratio of the actual variance to the theoretical variance of the innovation is used as the input of the fuzzy inference system, the correction coefficient of the measured noise model is used as the output of the fuzzy inference system, and the fuzzy inference rule comprises the following three steps:
(1) If the ratio of the actual variance to the theoretical variance of the innovation becomes lower, the correction coefficient of the measurement noise model becomes smaller;
(2) If the ratio of the actual variance to the theoretical variance of the innovation is unchanged (1), the correction coefficient of the measurement noise model is unchanged (1);
(3) If the ratio of the actual variance to the theoretical variance of the innovation becomes high, the correction coefficient of the measurement noise model becomes large.
The self-adaptive Kalman filtering algorithm based on the fuzzy inference system can ensure that the measurement noise model of the integrated navigation system is accurate under the condition of large measurement noise change, and the system state estimation value is optimal.
Further, the tail gas detection module detects through the sensor installed on the automobile exhaust pipe, and the detected harmful gases such as CO and the like transmit data to the host microprocessor through the CAN2.0, and the host microprocessor performs data storage backup and transmits the data to the central monitoring platform through the wireless communication module.
The invention has the following advantages:
1. the vehicle-mounted terminal has the tail gas detection function, provides a full market tail gas distribution for the government through tail gas detection of the vehicle, and provides a large amount of real and effective data for the government, so that each user can be subjected to behavior analysis through historical data of the vehicle and operation data of vast users, accidents are reduced, misinformation and cheating behaviors are reduced, and reliable data is provided for governmental management of traffic and road planning.
2. The system and the vehicle can automatically alarm when the accident occurs, and provide a large amount of real and effective data for the government through accurate positioning of the vehicle, so that the traffic energy can be utilized uniformly; the accident scene is restored by shooting and monitoring the accident scene, and an identification basis is provided for insurance companies.
3. The invention also has the functions of video monitoring, data acquisition, motion gesture reporting and the like, and improves the safety of vehicles.
4. The satellite navigation system and the inertial navigation system are integrated completely and autonomously, so that combined positioning is realized, the combined positioning and the inertial navigation system are mutually complemented, and the positioning reliability is greatly improved.
5. The detection method of the invention utilizes the combined positioning module to accurately position, thereby providing more accurate tail gas distribution data.
Drawings
Fig. 1 is a schematic structural diagram of embodiment 1 of the present invention.
Fig. 2 is a schematic diagram of a method for positioning a vehicle-mounted terminal by using a combined positioning module according to the present invention.
Fig. 3 is a receiver noise ratio versus bandwidth.
FIG. 4 is a comparison result of the noise model of the conventional method and the novel method.
FIG. 5 is a comparison of navigation accuracy between the conventional method and the novel method.
Fig. 6 is a schematic structural diagram of embodiment 2 of the present invention.
Detailed Description
The following examples are illustrative of the invention and are not intended to limit the scope of the invention.
Example 1
Referring to fig. 1, the vehicle-mounted terminal with the tail gas detection function comprises a host microprocessor, a combined positioning module, a wireless communication module, a data storage module, a power module, a tail gas detection module and a camera module, wherein the combined positioning module, the wireless communication module, the data storage module, the power module, the tail gas detection module and the camera module are all connected with the host microprocessor; the tail gas detection module is arranged on an automobile exhaust pipe.
The camera shooting microprocessor is connected with the host microprocessor through a USB data line, the camera shooting module comprises a camera shooting microprocessor, an LCD main control board, a camera shooting storage module and two ultra-wide-angle cameras, the LCD main control board, the camera shooting storage module and the two ultra-wide-angle cameras are all connected with the camera shooting microprocessor, the ultra-wide-angle cameras obtain images around the vehicle, and the camera shooting microprocessor compresses, processes and stores the images.
The wireless communication module in this embodiment may be, but not limited to, a digital network such as 2G, 3G, 4G, etc., and more preferably, the wireless communication module is a cellular-based narrowband internet of things (Narrow Band Internet of Things, NB-IoT).
The combined positioning module is a satellite positioning module and an inertial navigation module. The satellite navigation system and the inertial navigation system are integrated completely and autonomously, so that combined positioning is realized, the combined positioning and the inertial navigation system are mutually complemented, and the positioning reliability is greatly improved. The satellite positioning module is preferably a BD/GPS compatible module.
The vehicle-mounted terminal uploads data to the central monitoring platform through the wireless communication module, and the central monitoring platform displays the position and tail gas distribution condition of the vehicle in real time after receiving information such as terminal positioning, speed, gesture and tail gas, and stores the running track of the vehicle and plays back the history track. For important vehicles, such as dangerous vehicles or alarming vehicles, the vehicle tracking system can be arranged in the center for real-time tracking.
Further, the tail gas detection module detects through the sensor installed on the automobile exhaust pipe, and the detected harmful gases such as CO and the like transmit data to the host microprocessor through the CAN2.0, and the host microprocessor performs data storage backup and transmits the data to the central monitoring platform through the mobile communication network.
The detection method of the vehicle owner terminal comprises the following steps:
the host microprocessor transmits the data detected by the tail gas detection module and the camera shooting module to the central monitoring platform through the NB-IoT module, and simultaneously the combined positioning module positions the vehicle-mounted terminal and transmits the data to the central monitoring platform through the NB-IoT module;
referring to fig. 2, the method for positioning the position of the vehicle-mounted terminal by using the combined positioning module specifically includes the following steps:
s1, a carrier phase tracking loop based on bandwidth self-adaption of a fuzzy reasoning system is adopted, when the signal-to-noise ratio of satellite signals is reduced, the bandwidth of the carrier phase tracking loop is reduced, and the anti-noise interference capability of a receiver is improved; the bandwidth adaptation of the satellite signal receiver is achieved by a fuzzy inference system with the signal-to-noise ratio (i.e. C/N0) of the satellite signal as input. If the signal-to-noise ratio is reduced, the noise is increased, and the bandwidth of the phase-locked loop of the satellite receiver is reduced to obtain a better filtering effect, namely stronger anti-noise interference capability; if the signal-to-noise ratio increases, the noise becomes smaller, and the phase-locked loop bandwidth of the satellite receiver should be correspondingly increased to obtain better dynamic performance. Because there is no definite mathematical relation between the signal-to-noise ratio and the bandwidth, and the phase-locked loop bandwidth has no unique optimal value under different noise and different dynamic conditions, the method is suitable for adjusting the phase-locked loop bandwidth of the receiver by adopting a fuzzy reasoning system from the aspects of simplifying the adjustment principle and improving the robustness. The method comprises the following specific steps:
s201, calculating a signal to noise ratio C/N0 according to the GPS digital signal after down-conversion and digital-to-analog conversion, wherein the formula is as follows:
wherein:
in the above two formulas, A is GPS signal amplitude, M E Is the integral count value delta iq Is the standard deviation of signal noise, T Int Is the integration time.
S202, establishing a fuzzy control system, taking C/N0 as input, taking the bandwidth of a GPS tracking loop as output, and adopting the following fuzzy reasoning rule:
(1) If the signal-to-noise ratio is less than 30dB, the phase-locked loop bandwidth is narrow;
(2) If the signal-to-noise ratio is 30-40 dB, the phase-locked loop bandwidth is moderate;
(3) If the signal-to-noise ratio is higher than 40dB, the phase-locked loop bandwidth is wide;
and taking the current output of the fuzzy control system as the next carrier phase tracking loop bandwidth value, realizing the self-adaptive adjustment of the carrier loop bandwidth, and improving the noise anti-interference capability of the GPS or Beidou navigation system.
The input C/N0 of the fuzzy inference system is calculated by using a variance summation algorithm (VSM) according to tracking results (in-phase signals and quadrature signals) generated by an integral-zero clearing process of a receiver.
S2, describing the change of the measured noise by adopting a Kalman filtering integrated navigation algorithm based on the self-adaption of the measured noise model of the fuzzy reasoning system, adjusting the measured noise variance matrix in real time, and improving the anti-noise interference capability of the integrated navigation algorithm. The basic principle of the measurement noise model adjustment is to make the theoretical innovation variance of the Kalman filter consistent with the actual innovation variance. The method comprises the following specific steps:
s201, calculating the innovation of the Kalman filter, wherein the innovation refers to the difference between the predicted measurement and the actual measurement in the Kalman filter, as shown in the formula (4)
Wherein z is k For actual measurement of quantity H k In order to measure the matrix of the device,is an estimate of the state of the system.
S202, innovation shows the state of a Kalman filtering algorithm: if the system state modeling and measurement matrix is correct, and the system noise and measurement noise model is accurate, and the Kalman filtering is normal, the innovation should be white noise with zero mean value, and the innovation theoretical variance is calculated, which can be calculated by the formula (5):
wherein F is k/k-1 For the system state transition matrix, P k-1 To estimate the state variance matrix, Q k-1 R is a system noise array k-1 To measure noise arrays.
S203, calculating the actual variance of the innovation, which can be calculated by the latest N innovation vectors and is represented by a formula (6):
s204, calculating the ratio of the actual variance to the theoretical variance of the innovation. Due toAnd->Are arranged as a diagonal array, so the ratio is also a diagonal array:
s205, designing a fuzzy inference system, wherein the ratio of the actual variance to the theoretical variance of the innovation is used as the input of the fuzzy inference system, the correction coefficient of the measured noise model is used as the output of the fuzzy inference system, and the fuzzy inference rule comprises the following three steps:
(1) If the ratio of the actual variance to the theoretical variance of the innovation becomes lower, the correction coefficient of the measurement noise model becomes smaller;
(2) If the ratio of the actual variance to the theoretical variance of the innovation is unchanged (1), the correction coefficient of the measurement noise model is unchanged (1);
(3) If the ratio of the actual variance to the theoretical variance of the innovation becomes high, the correction coefficient of the measurement noise model becomes large.
If the Kalman filter is working properly, then the innovation and actual and theoretical variances should be consistent. If the theoretical variance deviates from the actual variance, it is indicated that the theoretical variance is calculated with errors, and the reasons may be that the system model is wrong or the noise model is inaccurate.
In general, F k/k-1 、P k-1 And Q k-1 Are easily obtained or measured with high accuracy, and the noise array R is measured k-1 Then it changes with the measurement noise and may change more drastically in different situations. For a satellite and inertial integrated navigation system, the measurement can be the pseudo-range and pseudo-range rate of all visible satellites, wherein the pseudo-range rate is obtained by a phase-locked loop, if the satellite signal noise changes greatly, the pseudo-range rate noise also changes, and the measurement noise array R is corrected k-1 。
When the pseudo-range rate noise changes, the actual variance of the innovation changes correspondingly, so that the measurement noise model R can be corrected according to the difference between the theoretical variance and the actual variance k-1 Thus, the self-adaptive Kalman filtering algorithm is realized, namely, the measuring noise model is corrected on line in real time.
The self-adaptive Kalman filtering algorithm based on the fuzzy inference system can ensure that the measurement noise model of the integrated navigation system is accurate under the condition of large measurement noise change, and the system state estimation value is optimal.
Referring to FIG. 3, to verify the validity of the scheme, noise was artificially added at 20 seconds, such that the signal-to-noise ratio was changed from 45dB-Hz to 25dB-Hz, and slowly ramped back up at 30 seconds to 45dB-Hz. As can be seen from fig. 1, the bandwidth of the phase-locked loop decreases rapidly as the signal-to-noise ratio decreases, thereby enhancing the noise immunity of the receiver.
Referring to fig. 4, the upper graph is the standard deviation comparison of measured noise, and the lower graph is the comparison result of the ratio of theoretical innovation variance to actual innovation variance. As can be seen from the figure, the system proposal provided by the invention can carry out online adjustment on the measurement noise model, so that the ratio of the theoretical innovation variance to the actual innovation variance is always 1 (namely 0 dB), but the traditional system can not adjust the measurement noise model, and the ratio of the innovation variance to the actual innovation variance can be changed by 20dB when the noise changes.
Referring to fig. 5, it is obvious from the figure that the navigation accuracy of the integrated navigation module is obviously better than that of the conventional integrated navigation system when the signal-to-noise ratio of the satellite signal is low and the noise variation is obvious (20 s-35 s).
The invention combines the fuzzy self-adaptive phase-locked loop bandwidth with the fuzzy self-adaptive Kalman filtering algorithm, so that the noise immunity of the integrated navigation system is obviously enhanced, the navigation output with higher precision can be still maintained under the conditions of lower signal-to-noise ratio of satellite signals and larger noise variation, and the comparison result diagram can be seen from the attached figures 3 to 5 of the specification.
Example 2
Referring to fig. 6, in order to schematically illustrate the structure of embodiment 2 of the vehicle-mounted terminal with tail gas detection function of the present invention, the vehicle-mounted terminal with tail gas detection function of the present invention may further include an alarm, an external storage module, and an OBD interface on the basis of fig. 1. The alarm, the external storage module and the OBD interface are all connected with the host microprocessor.
The external storage module is used for storing data of the tail gas detection module.
The vehicle-mounted terminal is provided with an OBD (On-Board Diagnostic "vehicle-mounted Diagnostic system") interface, and the host microprocessor is connected with a vehicle circuit through the OBD interface and reads data through the OBD.
While the invention has been described in detail in the foregoing general description and specific examples, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
Claims (9)
1. Vehicle-mounted terminal with tail gas detection function, its characterized in that: the vehicle-mounted terminal comprises a host microprocessor, a combined positioning module, a wireless communication module, a data storage module, a power module, a tail gas detection module and a camera shooting module, wherein the combined positioning module, the wireless communication module, the data storage module, the power module, the tail gas detection module and the camera shooting module are all connected with the host microprocessor;
the tail gas detection module is arranged on an automobile exhaust pipe;
the camera shooting module comprises a camera shooting microprocessor, an LCD main control board, a camera shooting storage module and two cameras, wherein the camera shooting microprocessor is connected with the host microprocessor through a USB data line, the LCD main control board, the camera shooting storage module and the two cameras are all connected with the camera shooting microprocessor, the camera shooting microprocessor obtains images around a vehicle, and the camera shooting microprocessor compresses the images and stores the images in the camera shooting storage module;
the combined positioning module comprises a satellite positioning navigation module and an inertial navigation module;
the host microprocessor is used for sending the data detected by the tail gas detection module and the camera shooting module to the central monitoring platform through the NB-IoT module, and simultaneously, the combined positioning module is used for positioning the position of the vehicle-mounted terminal and sending the position of the vehicle-mounted terminal to the central monitoring platform through the NB-IoT module;
the combined positioning module is used for positioning the position of the vehicle-mounted terminal and specifically comprises the following steps of:
s1, a carrier phase tracking loop based on bandwidth self-adaption of a fuzzy reasoning system is adopted, when the signal-to-noise ratio of satellite signals is reduced, the bandwidth of the carrier phase tracking loop is reduced, and the anti-noise interference capability of a receiver is improved;
s2, describing the change of the measured noise by adopting a Kalman filtering integrated navigation algorithm based on the self-adaption of the measured noise model of the fuzzy reasoning system, adjusting the measured noise variance matrix in real time, and improving the anti-noise interference capability of the integrated navigation algorithm.
2. The vehicle-mounted terminal with an exhaust gas detection function according to claim 1, wherein: the camera is an ultra-wide angle camera.
3. The vehicle-mounted terminal with an exhaust gas detection function according to claim 1, wherein: the vehicle-mounted terminal further comprises an alarm, an external storage module and an OBD interface, wherein the alarm, the external storage module and the OBD interface are connected with the host microprocessor;
the external storage module is used for storing data of the tail gas detection module;
and the host microprocessor is connected with an automobile circuit through an OBD interface, and reads data through the OBD interface.
4. The vehicle-mounted terminal with an exhaust gas detection function according to claim 1, wherein: the wireless communication module is a cellular-based narrowband internet of things.
5. The vehicle-mounted terminal with an exhaust gas detection function according to claim 1, wherein: the combined positioning module comprises a satellite positioning navigation module and an inertial navigation module.
6. The vehicle-mounted terminal with an exhaust gas detection function according to claim 5, wherein: the satellite positioning navigation module is a BD/GPS compatible module.
7. The vehicle-mounted terminal with an exhaust gas detection function according to claim 1, wherein: the camera shooting storage module is a TF card.
8. The vehicle-mounted terminal with an exhaust gas detection function according to claim 1, wherein: the host microprocessor is connected to a central monitoring platform through an NB-IoT module.
9. The vehicle-mounted terminal with an exhaust gas detection function according to claim 1, wherein: the specific steps of the S1 are as follows:
s101, calculating a signal to noise ratio C/N0 according to the GPS digital signal after down-conversion and digital-to-analog conversion, wherein the formula is as follows:
wherein:
in the above two formulas, A is GPS signal amplitude, M E Is the integral count value delta iq Is the standard deviation of signal noise, T Int Is the integration time;
s102, establishing a fuzzy control system, taking C/N0 as input, taking the bandwidth of a GPS tracking loop as output, and adopting the following fuzzy reasoning rule:
(1) If the signal-to-noise ratio is less than 30dB, the phase-locked loop bandwidth is narrow;
(2) If the signal-to-noise ratio is 30-40 dB, the phase-locked loop bandwidth is moderate;
(3) If the signal-to-noise ratio is higher than 40dB, the phase-locked loop bandwidth is wide;
the current output of the fuzzy control system is used as the bandwidth value of the next carrier phase tracking loop, so that the self-adaptive adjustment of the carrier loop bandwidth is realized, and the noise anti-interference capability of the GPS or Beidou navigation system is improved;
the specific steps of the S2 are as follows:
s201, calculating the innovation of the Kalman filter, as shown in the formula (4)
Wherein z is k For actual measurement of quantity H k In order to measure the matrix of the device,is one estimate of the system state;
s202, calculating an innovation theory variance, wherein the innovation theory variance can be calculated by a formula (5):
wherein F is k/k-1 For the system state transition matrix, P k-1 To estimate the state variance matrix, Q k-1 R is a system noise array k-1 Measuring a noise array;
s203, calculating the actual variance of the innovation, which can be calculated by the latest N innovation vectors and is represented by a formula (6):
s204, calculating the ratio of the actual variance to the theoretical variance of the innovation; due toAnd->Are arranged as a diagonal array, so the ratio is also a diagonal array:
s205, designing a fuzzy inference system, wherein the ratio of the actual variance to the theoretical variance of the innovation is used as the input of the fuzzy inference system, the correction coefficient of the measured noise model is used as the output of the fuzzy inference system, and the fuzzy inference rule comprises the following three steps:
(1) If the ratio of the actual variance to the theoretical variance of the innovation becomes lower, the correction coefficient of the measurement noise model becomes smaller;
(2) If the ratio of the actual variance to the theoretical variance of the innovation is unchanged, the correction coefficient of the measurement noise model is unchanged;
(3) If the ratio of the actual variance to the theoretical variance of the innovation becomes high, the correction coefficient of the measurement noise model becomes large.
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| CN201711353304.6A CN107907899B (en) | 2017-12-15 | 2017-12-15 | Vehicle-mounted terminal with tail gas detection function and detection method thereof |
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| CN109633083A (en) * | 2018-11-21 | 2019-04-16 | 上海柏鼎环保科技有限公司 | Enviromental monitoring equipment, monitoring integration method and computer readable storage medium |
| CN111693566B (en) * | 2020-05-12 | 2023-04-28 | 江苏理工学院 | Automobile exhaust detection device and detection method based on infrared thermal imaging technology |
| CN112287750A (en) * | 2020-09-02 | 2021-01-29 | 厦门理工学院 | Engineering vehicle tail gas emission monitoring and tracking system based on Beidou |
| CN112523849A (en) * | 2020-11-23 | 2021-03-19 | 无锡腾跃汽车部件有限公司 | Automobile exhaust emission monitoring system and monitoring method based on Internet of things technology |
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