Portable PM and smoke combined detection device and detection method thereof

Abstract

This invention discloses a portable PM and smoke opacity joint detection device and method, relating to the field of engine exhaust gas detection technology. The device includes a PM sampling probe, a micro-current detection module, a filter circuit, an ADC acquisition module, and an MCU control module. The PM sampling probe outputs a weak current signal related to particulate matter concentration. The micro-current detection module includes a transimpedance amplifier circuit that converts the weak current signal into a voltage signal. The MCU control module is configured to perform zero-point calibration, abnormal pulse rejection, and steady-state range determination on the digital signal converted by the ADC acquisition module. When the signal is determined to be in a steady-state range, the current characteristic value of the digital signal is extracted. A pre-calibrated relationship model between the PM sensor current characteristic value and the smoke opacity light absorption coefficient K is invoked, and the corresponding smoke opacity light absorption coefficient K is calculated using the extracted current characteristic value. This enables portable, integrated on-site joint detection under complex working conditions.

Description

Technical Field

[0001] This invention relates to the field of engine exhaust testing technology, and in particular to a portable PM and smoke detection device and its detection method, which is especially suitable for rapid on-site detection of particulate matter and smoke in the exhaust of diesel engines, non-road mobile machinery, construction machinery and engine benches. Background Technology

[0002] Diesel engines and non-road mobile machinery emit large amounts of particulate matter (PM) during operation, posing a serious threat to the atmospheric environment and human health. Therefore, rapid and effective on-site detection of exhaust particulate matter is of great significance for environmental supervision and equipment maintenance.

[0003] Currently, the evaluation methods for exhaust particulate matter are mainly divided into two categories: particulate matter mass concentration detection and exhaust smoke opacity detection. PM mass concentration can directly reflect the level of pollutant emissions, but the relevant detection equipment is generally bulky and expensive, and is mostly limited to laboratory use; smoke opacity detection, on the other hand, uses the light absorption coefficient (K value, m) to measure the light absorption coefficient. - ¹) It characterizes the degree of black smoke in exhaust gas and has the characteristics of fast response and simple operation, but its optical measurement nature determines that it cannot accurately reflect the absolute value of particulate matter mass concentration.

[0004] Ideally, if the electrical response of a PM sensor to particulate matter can be correlated with the smoke opacity K value, which reflects extinction characteristics, it would be possible to obtain both evaluation indicators simultaneously using a single sensor. Existing technologies, such as Chinese invention patent CN104849186B, disclose a calibration system and method for a particulate matter sensor. This system generates stable soot through a burner and simultaneously acquires the output voltage signal of the particulate matter sensor and the soot concentration value from a transient smoke meter. Finally, a calibration curve is plotted between the sensor voltage and particulate matter concentration, providing a basis for the correlation between the two.

[0005] However, the aforementioned existing technologies have clear limitations, making them unsuitable for direct conversion into a joint testing solution applicable in the field.

[0006] First, this scheme is essentially a laboratory calibration system. Its stable soot generation environment and controllable dilution and heating conditions are completely different from the violent flow fluctuations, complex component interferences and transient operating condition changes in the actual exhaust of the engine.

[0007] Secondly, this solution only obtains the calibration relationship and does not reveal how to engineer this calibration relationship into a detection method and processing algorithm that can run in real time on portable devices and autonomously cope with harsh on-site signal conditions. In actual engine exhaust environments, the nA or μA level raw current signal output by the PM sensor is extremely weak and easily submerged in electromagnetic interference, exhaust pulsation, and abnormal spike pulses generated by sampling contact. If the problems of high-fidelity extraction of weak signals, intelligent rejection of abnormal signals, and identification of effective data segments under non-steady-state conditions cannot be effectively solved, then directly applying the laboratory calibration relationship to on-site detection will lead to serious distortion and poor repeatability of the detection results, making it impossible to obtain consistent and comparable PM concentration and smoke opacity K values.

[0008] In summary, while existing technologies provide a theoretical possibility for the correlation between sensor signals and smoke opacity, they have not solved the key technical problem of synchronously, accurately, and reliably realizing PM detection and smoke opacity inversion calculation in complex field environments within portable, integrated devices.

[0009] Therefore, there is an urgent need for a portable, integrated testing device and method that can overcome the above-mentioned shortcomings and successfully transform laboratory calibration models into portable testing devices and methods adapted to harsh field conditions. Summary of the Invention

[0010] The technical problem to be solved by this invention is how to engineer the calibration relationship between the current characteristic value of PM sensor and the smoke opacity K value into a portable device that can cope with harsh conditions such as strong electromagnetic interference, exhaust pulsation and abnormal pulses on site, and achieve synchronous, accurate and reliable correlation output of PM concentration and smoke opacity K value on the same portable device through robust processing of weak signals and specific algorithms.

[0011] In a first aspect, to solve the above-mentioned technical problems, a portable PM and smoke opacity joint detection device is provided, comprising a PM sampling probe, a micro-current detection module, a filter circuit, an ADC acquisition module, and an MCU control module integrated in one unit and electrically connected in sequence. The PM sampling probe is used to collect particulate matter in engine exhaust and output a weak current signal related to the particulate matter concentration. The microcurrent detection module includes a transimpedance amplifier circuit that converts the weak current signal into a voltage signal. The MCU control module is configured as follows: (1) Perform zero-point calibration, abnormal pulse rejection and steady-state range judgment on the digital signal converted by the ADC acquisition module; (2) When it is determined that the signal is in a steady state range, the current characteristic value of the digital signal is extracted; (3) Call the pre-calibrated relationship model between the current characteristic value of the PM sensor and the smoke light absorption coefficient K value, and use the extracted current characteristic value to calculate the corresponding smoke light absorption coefficient K value.

[0012] Furthermore, the MCU control module is also configured to: When performing zero-point calibration on the digital signal, a zero-point reference value is acquired during the device startup phase or in a state with no particulate matter input, and this zero-point reference value is subtracted from the subsequent detection signal.

[0013] Furthermore, the abnormal pulse rejection performed by the MCU control module specifically includes: Calculate the degree of deviation between the current sampling point and the mean or variance of the signal within the sliding window; When the deviation exceeds a preset threshold, the sampling point is identified as an abnormal pulse and is either discarded or replaced with a nearby valid sampling value.

[0014] Furthermore, the steady-state interval determination performed by the MCU control module specifically includes: Within a preset time window, calculate the fluctuation amplitude, rate of change, or variance of the digital signal; When the fluctuation amplitude, rate of change, or variance is less than the corresponding preset steady-state threshold, the current time window is determined to be the steady-state interval.

[0015] Furthermore, the relationship model between the PM sensor current characteristic value and the smoke light absorption coefficient K value satisfies the expression:

[0016] In the formula, The light absorption coefficient of smoke opacity is expressed in m. - ¹; The particulate matter mass concentration is calculated from the current characteristic value, and the unit is mg / m³; , These are the fitting coefficients determined through experimental calibration.

[0017] Furthermore, the current characteristic values ​​include the steady-state average current, peak current, response slope, and integrated charge; the MCU control module extracts the current characteristic values ​​and inputs them into the relational model to calculate the smoke light absorption coefficient K value.

[0018] Furthermore, it also includes: A filtering protection module is provided at least one of the power input terminal and the signal acquisition path to provide at least one of the following functions: overvoltage protection, reverse connection protection, electrostatic discharge protection, power filtering, and electromagnetic interference suppression. The display module, which is connected to the MCU control module, is used to synchronously display detection information including at least PM detection results, smoke light absorption coefficient K value, sensor current value, and equipment status; and when an abnormal signal, unstable sampling, smoke light absorption coefficient K value exceeding a preset threshold, or device malfunction is detected, the display module outputs corresponding alarm prompt information. The communication module is used to output the detection results to a host computer, mobile terminal or detection platform via at least one of the following communication methods: serial port, Bluetooth, WiFi or USB.

[0019] Furthermore, it also includes a housing assembly, wherein the PM sampling probe is connected to the housing assembly via a sensor interface; wherein the housing assembly integrates a display screen, a button module, a communication interface, and a data interface.

[0020] A second aspect of the present invention provides a portable method for joint detection of PM and smoke opacity based on the aforementioned device, comprising the following steps: Place the PM sampling probe at the engine exhaust detection position to collect particulate matter in the exhaust and output a weak current signal. The weak current signal is converted into a voltage signal by the transimpedance amplifier circuit in the microcurrent detection module; The filtering circuit performs filtering processing on the voltage signal; The ADC acquisition module converts the filtered analog voltage signal into a digital signal; The MCU control module performs zero-point calibration, abnormal pulse rejection, and steady-state range determination on the digital signal; When the signal is determined to be in the steady-state range, the MCU control module extracts the current characteristic value; The relationship model between the pre-calibrated PM sensor current characteristic value and the smoke light absorption coefficient K value is invoked, and the smoke light absorption coefficient K value is calculated using the extracted current characteristic value. The PM detection results and the calculated smoke light absorption coefficient K value are output and displayed synchronously.

[0021] Furthermore, the abnormal pulse rejection includes: By comparing the difference between the current sampling point and the mean of the sliding window, or by comparing the variance within the sliding window with a preset variance threshold, abnormal pulses caused by electromagnetic interference, sudden changes in exhaust flow rate, or abnormal sampling contact can be identified and eliminated.

[0022] Furthermore, the determination of the steady-state interval includes: Within a preset time window, monitor the amplitude, rate of change, or variance of the signal fluctuation. When the value is consistently below the preset steady-state threshold, it is determined to be in a steady-state range; otherwise, it indicates that the detection state is unstable and sampling continues.

[0023] Furthermore, the method also includes: Zero-point reference values ​​are collected and stored during device startup or when there is no particulate matter input. The zero-point calibration includes subtracting the zero-point reference value from the digital signal to reduce the effects of zero-point drift.

[0024] Furthermore, the relationship model is established by simultaneously connecting the detection device and the standard smoke meter to the same exhaust source, synchronously collecting the current characteristic value and the smoke light absorption coefficient K value measured by the standard smoke meter under different operating conditions, and then performing linear regression fitting.

[0025] Compared with the prior art, the present invention has at least the following beneficial effects: This invention integrates a PM sampling probe, micro-current detection, filtering circuit, analog-to-digital converter, and MCU control module into a single portable device. The MCU control module incorporates a digital processing flow for zero-point calibration, abnormal pulse rejection, and steady-state range judgment. This effectively overcomes the impact of harsh conditions such as strong electromagnetic interference, large signal fluctuations, and numerous abnormal pulses at the engine exhaust site on the detection of weak current signals, ensuring that current characteristic values ​​are extracted only from stable and effective signal segments. Based on this, by calling a pre-calibrated relationship model between the PM sensor current characteristic values ​​and the smoke opacity light absorption coefficient K, the smoke opacity K value is calculated from the extracted characteristic values. Thus, two key indicators, PM concentration and smoke opacity, are obtained simultaneously under a single sampling path. This completely solves the problem of asynchronous sampling and data mismatch between the two sets of equipment in traditional split-type detection schemes, truly realizing portable, integrated on-site joint detection under complex working conditions, and improving the consistency and reliability of the detection results. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram of the overall structure of the detection device disclosed in this invention.

[0028] Figure 2 This is a schematic diagram of the overall structure of the detection device disclosed in this invention.

[0029] Figure 3 This is a flowchart of the detection method disclosed in this invention.

[0030] Figure 4This is a schematic diagram illustrating the calibration relationship between the current characteristic value of the PM sensor and the smoke light absorption coefficient K value disclosed in this invention.

[0031] Figure 5 This is a flowchart illustrating the calculation of the smoke light absorption coefficient K value based on the relationship model between the current characteristic value of the PM sensor and the smoke light absorption coefficient K value disclosed in this invention. Detailed Implementation

[0032] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] This invention provides a portable PM and smoke opacity combined detection device, which aims to simultaneously obtain particulate matter mass concentration and smoke opacity light absorption coefficient K value through a single sampling probe and a unified data processing path.

[0034] Specifically, this invention integrates a PM sensor current characteristic value-smoke opacity K-value relationship model, established based on laboratory calibration, into a portable on-site detection device. This device not only reliably converts and acquires weak current signals at the nA / μA level into digital voltage signals, but more importantly, its internal MCU control module is configured to execute a series of targeted signal purification and feature extraction steps, including zero-point calibration, abnormal pulse rejection, and steady-state range determination. This ensures the extraction of effective current characteristic values ​​even under harsh environments with strong interference and fluctuations in engine exhaust. Furthermore, by calling the pre-calibrated relationship model, the smoke opacity light absorption coefficient K-value is calculated from the current characteristic values, achieving integrated correlation detection of PM concentration and smoke opacity.

[0035] Please see Figure 1 The device mainly includes a PM sampling probe, a micro-current detection module, a transimpedance amplifier circuit, a filter circuit, an ADC acquisition module, an MCU control module, a PM-smoke fusion algorithm module, a display module, a data storage module, a communication module, a power supply module, and a filter protection module. It should be noted that the PM-smoke fusion algorithm module is not a separate hardware module in its physical implementation; rather, it is embedded in the program memory of the MCU control module as firmware or software code, and is executed by the MCU's processing core. All modules can be integrated and packaged into a single housing component to form a portable handheld detection device. The following is a detailed description of each module: In this embodiment, the PM sampling probe is the front-end sensing component of the portable device. In application, the PM sampling probe is installed at the exhaust pipe detection position of a diesel engine, off-road mobile machinery, or engine bench via a standard sampling conduit or direct insertion. Particulate matter in the exhaust gas enters the detection area inside the probe with the airflow, generating a weak current signal under the action of the sensor's internal detection structure. This weak current signal is related to the exhaust particulate matter concentration or particulate matter emission level.

[0036] In this embodiment, the microcurrent detection module is electrically connected to the PM sampling probe via a shielded cable to receive weak current signals at the nA / μA level from the PM sampling probe.

[0037] As those skilled in the art will know, the output signal of a PM sampling probe is typically a current signal in the nA or μA range, with a small amplitude, making it susceptible to electromagnetic interference, exhaust fluctuations, and contact noise. Therefore, this invention incorporates a transimpedance amplifier circuit in the micro-current detection module. This transimpedance amplifier circuit typically includes a high-input-impedance, ultra-low-bias-current precision operational amplifier and a high-precision feedback resistor. The feedback resistor is connected between the inverting input and output of the operational amplifier. The output current of the PM sampling probe is directly injected into the inverting input of the operational amplifier, while the non-inverting input is connected to ground or a stable bias voltage. Due to the virtual short and virtual open characteristics of the operational amplifier, almost all the input current flows through the feedback resistor, thereby generating a voltage signal proportional to the input current at the operational amplifier output. In other words, the transimpedance amplifier circuit converts an extremely weak current signal into a voltage signal of suitable amplitude, facilitating subsequent acquisition by the ADC acquisition module.

[0038] In this embodiment, the input of the filter circuit is connected to the output of the micro-current detection module to condition the voltage signal after transimpedance amplification. Because the engine exhaust testing site is a complex electromagnetic environment, equipment such as alternators, ignition systems, and high-power motors generate strong radiation and conducted interference. Furthermore, the exhaust itself has pulsations, resulting in a large amount of random noise and periodic interference superimposed on the converted voltage signal. The function of the filter circuit is to suppress these useless signals to the greatest extent possible while retaining the useful signal components reflecting changes in particulate matter concentration.

[0039] In some specific implementations, the filter circuit preferably adopts a multi-stage cascaded structure, including a low-pass filter stage, an anti-aliasing filter stage, and a limiting protection stage, to reduce the impact of electromagnetic interference, mechanical vibration, exhaust pulsation, and abnormal spike signals on the test results during on-site testing.

[0040] In this embodiment, the ADC acquisition module is connected to the filtering circuit and is used to convert the analog voltage signal processed by the filtering circuit into a digital signal. The ADC acquisition module can be an ADC built into the MCU or an external high-precision ADC chip. The converted digital signal is transmitted to the MCU control module in real time via a serial bus such as SPI or I2C.

[0041] In this embodiment, the MCU control module is connected to the ADC acquisition module to acquire digital signals and perform zero-point calibration, abnormal pulse rejection, filtering, steady-state range judgment, and feature value extraction.

[0042] Specifically, the MCU control module is configured to perform the following logic control: (1) Zero-point calibration: After the device is powered on, or before each formal measurement, the MCU control module will first execute the zero-point calibration procedure. At this time, the PM sampling probe should be placed in a clean air or particulate-free environment, or switched to a bypass filtration system via a solenoid valve. The MCU continuously acquires digital signals from hundreds of sampling points, calculates their arithmetic mean, and stores this average value as the zero-point reference value in non-volatile memory. In each subsequent actual measurement, the MCU will subtract this zero-point reference value from the real-time acquired digital signal value, thereby eliminating systematic errors introduced by factors such as sensor bias, circuit temperature drift, and long-term drift, and improving measurement accuracy.

[0043] (2) Abnormal Pulse Removal: Even after zero-point calibration, the digital signal sequence may still contain abnormal pulses caused by transient strong electromagnetic interference, accidental discharge inside the sensor, sudden changes in exhaust flow rate, or poor contact of connectors. These pulses manifest as a rapid jump in signal amplitude within a very short time, deviating far from the normal signal level. If not processed, they will severely distort subsequent statistical analysis and characteristic value calculations.

[0044] In this embodiment, the MCU control module uses a sliding window statistical method to identify and eliminate abnormal pulses in real time. Specifically, for the current sampling point, the previous M valid sampling points (e.g., M=10 to 50) are taken to form a window, and the mean of the signal within this window is calculated. and standard deviation If the current sample value is close to the mean... The absolute value of the deviation exceeds a preset threshold, for example... or If a point is identified as an abnormal pulse, it is discarded and replaced with its nearest preceding valid sample value or the window mean to ensure the continuity and length of the data sequence. This real-time processing ensures that the digital signal entering subsequent stages is a relatively clean data stream that primarily reflects the essential changes in particulate matter concentration.

[0045] (3) Steady-state range determination: As is well known, under actual operating conditions, the concentration of exhaust particulate matter in an engine fluctuates drastically with transient changes in engine speed, load, and combustion state. If signal features are extracted under such non-steady-state transitional conditions, the calculated values ​​will neither represent the emission level under a certain stable operating condition nor match the relationship model calibrated under steady-state conditions, resulting in a large error in the final output smoke opacity K value.

[0046] Therefore, the MCU control module must determine whether the signal has entered a relatively stable state before extracting feature values.

[0047] In this embodiment, the steady-state interval determination is also based on a sliding window. The MCU continuously monitors the signal statistics within a sliding window of a preset time length (e.g., 1-5 seconds). When the peak-to-peak value, root mean square error, or absolute rate of change of the signal fluctuation within the window is consistently lower than its corresponding preset threshold, the current window is considered a steady-state interval. For example, within a 2-second window, if the signal variance is less than a certain constant value, it is determined to have entered a steady state. Once a steady-state interval is determined, the MCU begins to extract the feature values ​​within that interval. If the signal fluctuation exceeds the threshold, it is determined that the detection state is unstable, and the system will continue to collect and judge data, and can display a message indicating that it is waiting for the operating condition to stabilize.

[0048] (4) Current feature extraction: After determining that the signal is in the steady state range, the MCU control module processes the calibrated digital signal within the steady state window and extracts a set of feature values ​​that can characterize the particulate matter emission state in multiple dimensions.

[0049] In this embodiment, the extracted current feature values ​​include, but are not limited to, the following four types: ① Steady-state average current: The arithmetic mean of the actual current values ​​(calculated by back-calculation of the ADC digital quantity through the transimpedance amplification factor) corresponding to all sampling points within the steady-state window is used to characterize the average intensity of particulate matter emissions under this steady-state condition.

[0050] ② Peak current: refers to the maximum value of the signal within the steady-state window, used to capture the instantaneous high emission pulse that may occur under this operating condition.

[0051] ③ Response slope: A linear fit is performed on the rising or falling edge of the signal within the window, and the slope is taken to reflect the sensor's response speed to concentration changes. In actual calculations, the difference ratio between the initial and final segments of the window can be calculated.

[0052] ④ Integrated charge: The current signal within the window is integrated over time, i.e., the area under the current-time curve is calculated, which represents the cumulative total of the sensor response during that time period. The integrated charge is obtained through numerical integration.

[0053] (5) PM-Smoke fusion calculation: The control processing module calls its internally integrated PM-smoke fusion algorithm module, takes the current feature value extracted in the previous step as input, and calculates the smoke light absorption coefficient K value by inverting the relationship model between the current feature value of the PM sensor and the smoke light absorption coefficient K value through the pre-calibrated and established model.

[0054] To further explain, the PM-smoke fusion algorithm module is a program algorithm unit embedded in the MCU. Its core is an empirical model established through data fitting by simultaneously testing with the same detection system of this invention and a standard reference instrument under laboratory conditions. Figure 4 This calibration relationship is visually demonstrated.

[0055] The specific calibration method is as follows: The combined detection system of this invention is simultaneously connected to the same engine exhaust source along with a metrologically calibrated standard filter paper smoke meter or split-flow opacity smoke meter. Under a series of different engine steady-state operating conditions (such as different engine speeds and load points), the PM sensor current characteristic value extracted by the system of this invention, and the light absorption coefficient K value measured by the standard smoke meter are recorded synchronously. For each steady-state operating point, the particulate matter mass concentration PM (in mg / m³) converted from the current characteristic value is plotted on a rectangular coordinate system as the ordinate, and the standard K value is plotted as the abscissa, forming a graph as shown below. Figure 4 The scatter plot shown. Linear regression analysis of these scatter points revealed a highly significant linear correlation between PM concentration and K value, with a correlation coefficient R² close to 1. The fitted linear equation is the relationship model, satisfying the expression:

[0056] In the formula, The light absorption coefficient of smoke opacity is expressed in m. - ¹; The particulate matter mass concentration is calculated from the current characteristic value, and the unit is mg / m³. , These are the fitting coefficients determined through experimental calibration.

[0057] Figure 4 In the diagram, the horizontal axis represents the PM concentration (mg / m³) derived from the current characteristic values ​​extracted in this invention, and the vertical axis represents the smoke opacity light absorption coefficient K value (m²). - ¹). The experimental data points are closely clustered near a straight line. After fitting, the linear model can be expressed as:

[0058] In the formula, the value of the fitting coefficient 152.99485 depends on the specific sensor model, circuit gain and calibration conditions used. In actual products, this coefficient can vary within a certain tolerance range, such as ±1.10092, which are all valid calibration results.

[0059] In actual testing, the MCU control module first calculates the current PM mass concentration value based on the extracted current characteristic value, combined with the sensor sensitivity coefficient and circuit gain. The conversion relationship can be obtained from the sensitivity curve provided by the sensor manufacturer, or determined through secondary calibration using standard mass concentration instruments such as an electrostatic low-voltage impactor during the calibration process. Subsequently, the PM value is substituted into the above relationship model to directly calculate the corresponding smoke opacity K value. If the current characteristic value contains multiple characteristic quantities, the fusion algorithm module can use more complex models such as multiple linear regression or neural networks.

[0060] Therefore, this invention achieves true joint detection by using a single PM sampling probe and a series of signal processing and algorithm conversions to simultaneously obtain two key evaluation indicators, PM mass concentration and smoke opacity K value, in the same portable device.

[0061] In a further embodiment, the device also includes a display module, a data storage module, a communication module, a power supply module, and a filtering and protection module.

[0062] The display module is connected to the MCU control module to present detection information and system status in real time. In some specific implementations, the display screen uses a high-brightness segment LCD or graphic dot matrix LCD, which is clearly readable even in strong outdoor light. The display interface is configured to synchronously refresh and display the following: current PM detection concentration value (unit: mg / m³), current smoke opacity K value (unit: m³ / m³). - ¹) Real-time current value of the PM sampling probe (unit: nA), duration or timestamp of this test, and equipment operating status indication (e.g., "Detecting", "Steady State", "Calibration Mode", "Low Battery Voltage", etc.). When the system diagnoses an abnormality, the display module will immediately flash or change color to display the corresponding alarm information. For example: When the K value calculated from the extracted feature values ​​exceeds the preset alarm threshold of environmental regulations, the interface will highlight "Smoke Exceeds Standard".

[0063] When the MCU detects that the signal is continuously unstable and cannot enter the steady-state range, it displays "Signal is unstable, please check sampling".

[0064] When the power supply voltage is below the normal operating range or communication is interrupted, the corresponding fault code will be displayed.

[0065] The intuitive information feedback provided by the display module greatly facilitates rapid diagnosis and enforcement by on-site operators.

[0066] The data storage module uses a high-capacity Flash memory or a removable Micro SD card for long-term storage of all detection data. Stored content includes, but is not limited to: the sequence number of each detection, start and end times, raw current waveform data for the entire steady-state range, the four extracted feature values, calculated PM concentration and smoke opacity K values, the calibration model version number used at the time, and any abnormal status codes that occurred. Data is stored in standard formats such as CSV or JSON for easy data analysis and report generation via computer. The storage module also saves the calibration parameters and zero-point reference values ​​written at the factory, ensuring no data loss in the event of a power outage.

[0067] The communication module provides multiple channels for data exchange between the testing device and external equipment. It integrates at least two of the following: RS-232 serial port, Bluetooth 4.0 / 5.0, Wi-Fi, and USB Type-C interface. Testing results can be sent in real-time to host computer monitoring software via serial port, or wirelessly transmitted to law enforcement personnel's mobile terminal APP via Bluetooth to generate electronic testing reports. Results can also be directly printed via USB cable connection to a printer. All communication protocols are open standards, ensuring strong compatibility and easy integration into existing environmental monitoring network platforms.

[0068] The power module provides energy to the entire system. Considering portability requirements, this embodiment preferably uses a high-capacity rechargeable lithium battery pack as the main power source, equipped with battery power monitoring and protection circuitry. Simultaneously, to accommodate the needs of long-term continuous testing or bench testing, the device also retains an external DC power input interface, accepting 12V / 24V vehicle power supplies or AC adapters. The power module internally integrates multiple DC-DC converters and low-dropout linear regulators to generate the different voltage levels required by each module, such as ±5V, +3.3V, and +1.8V, and provides an extremely low-noise power rail to the micro-current detection module, avoiding interference from power ripple on weak signal detection.

[0069] The filtering and protection module is not a standalone functional module, but rather distributed across the power input and various signal interfaces. Specifically, a resettable fuse and transient voltage suppressor are installed at the power input to provide overcurrent, overvoltage, and surge protection; a common-mode choke and a π-type filter network are used in the power path to suppress common-mode / differential-mode noise from the vehicle's electrical grid or AC power grid; electrostatic discharge protection diode arrays are installed at each external communication interface and sensor interface to prevent damage to internal sensitive components from static electricity from the human body or cable discharge; in addition, a gas discharge tube is connected in parallel to ground at the sensor input port to discharge high-voltage static electricity that may be coupled to the probe from the exhaust system.

[0070] likeFigure 2 As shown, the entire system is integrated within a housing assembly made of engineering plastic or metal, featuring a dustproof and splashproof design suitable for field operations. The front panel houses the display screen and button module, while the sides or bottom contain sensor interfaces, communication interfaces, and data interfaces. The sensor interface is a coaxial connector with a locking mechanism for reliably connecting the PM sampling probe cable. The button module includes several membrane buttons for power switch, menu selection, and start / stop detection, which are operated in conjunction with the menu interface on the display screen.

[0071] This invention also provides a portable method for joint detection of PM and smoke opacity, such as... Figure 3 As shown, the main steps include: S1. System startup, self-test and zero-point calibration.

[0072] Press the power button to power on the system. The power module begins supplying power to the various circuits, and the MCU control module loads the firmware. It first performs a hardware self-test, including checking the integrity of the internal memory, the normality of ADC communication, and the sufficient battery power. If a fault is detected during the self-test, an error code is output through the display module, and the subsequent process stops; if the self-test passes, it automatically enters the zero-point calibration procedure.

[0073] S2 and PM sampling probe placement and sampling.

[0074] The operator securely installs the PM sampling probe on the exhaust tailpipe of the diesel engine, off-road machinery, or engine bench, ensuring that the probe tip is facing the airflow direction, the sampling pipeline is free of bends and leaks, and the ground wire is properly connected.

[0075] S3 and PM sampling probes acquire weak current signals.

[0076] When the engine is started, particulate matter in the exhaust gas is carried into the PM sampling probe by the airflow. The particulate matter causes physical or chemical changes in the sensor's detection area, resulting in the sensor outputting a weak current signal in the nA or μA range, which is related to the particulate matter concentration. This signal is continuously output to the micro-current detection module in real time.

[0077] S4, Transimpedance Amplification and Voltage Conversion.

[0078] The transimpedance amplifier circuit within the micro-current detection module converts the weak input current signal into a voltage signal with a fixed gain. This conversion is linear, and the converted voltage signal completely preserves all the characteristics of the original current signal.

[0079] S5, Filtering.

[0080] The filter circuit receives the voltage signal from the transimpedance amplifier circuit, performs low-pass filtering to remove high-frequency noise, anti-aliasing filtering to satisfy the sampling theorem, and limiting protection to prevent overload of the subsequent stage, and finally outputs a clean and smooth analog voltage signal.

[0081] S6, ADC acquisition.

[0082] The ADC acquisition module samples and quantizes the filtered analog voltage signal at a preset sampling rate, converting it into a digital signal sequence, which is then transmitted to the MCU control module in real time. At this point, the analog signal has been converted into a digital quantity that the MCU can process and calculate.

[0083] S7, Digital Signal Processing.

[0084] The MCU control module performs the core processing flow on the received digital signal stream, combined with... Figure 5 The PM-smoke fusion algorithm flowchart shown includes the following steps: Starting with AD data acquisition, zero-point correction is first performed, followed by a loop: new data points are read from the cache, and abnormal pulses are removed. If a point is abnormal, it is discarded and replaced with a valid value. Next, the valid data is sent to the steady-state judgment stage. If the steady-state condition is not met, the process returns to read the next data point. Once a steady-state interval is determined, feature value extraction is performed to obtain four feature values. Finally, these feature values ​​are input into the fusion algorithm model to calculate and output the smoke opacity K value.

[0085] Specifically, step S7 is further subdivided into: S7.1 Zero-point correction. The MCU subtracts the zero-point reference value previously saved in step S1 from each digital sample value to obtain the calibrated digital signal.

[0086] S7.2 Abnormal Pulse Removal. The MCU uses a sliding window algorithm to determine in real time whether the current sampling point is an abnormal pulse. Taking a window length of M=20 as an example, the mean of the current point and its 19 previous valid points is calculated. and standard deviation If the current point value falls within Anything outside of this range is considered an abnormal pulse, and the value at that point is used... Replacement.

[0087] S7.3 Steady-state interval determination. The MCU continuously calculates the variance of the signal within a sliding window of 2 seconds. When the variance is below the threshold ε for 1 consecutive second, it is determined that the signal has entered the steady-state interval from the end of the 2-second window, and subsequent data is recorded for feature extraction; otherwise, it returns to S7.2 to continue processing new data points.

[0088] S8. Extraction of current characteristic values.

[0089] After determining that the system has entered the steady-state region, the MCU acquires and records a steady-state data segment of a preset length (e.g., 10 seconds). Based on this data, the MCU calculates and extracts four current characteristic values: steady-state average current, peak current, response slope (the absolute value of the slope changes at the beginning and end of the segment), and integrated charge. These characteristic values ​​constitute a feature vector for smoke opacity calculation.

[0090] S9. Calculation of smoke opacity K value.

[0091] The MCU calls the PM-smoke fusion algorithm module, inputting the feature values ​​extracted in step S8. First, the equivalent PM concentration is calculated based on the calibrated multivariate linear model. Then, the PM concentration is substituted into the core linear model K = (PM - 1.5) / 152.99485 to calculate the smoke light absorption coefficient K, in m³ / sm. - ¹.

[0092] S10. Results are displayed synchronously.

[0093] The MCU sends the calculated PM concentration and smoke opacity K value, along with the real-time sensor current value and the current time, to the display module to refresh the screen display. Thus, a complete PM and smoke opacity joint detection is synchronously completed on a single device.

[0094] S11, Data storage and communication.

[0095] Simultaneously, the MCU writes the complete data packet of this detection (including detection time, steady-state raw waveform, characteristic values, PM concentration, K value, system status, etc.) into the data storage module. If the communication module has already established a connection with the host computer or mobile terminal, the MCU actively pushes the data packet out to achieve remote monitoring and recording.

[0096] S12, Emission Status Assessment.

[0097] On-site operators or the host computer software can quickly and accurately assess the particulate matter emission status of the engine under test by comparing the PM concentration and smoke opacity K value displayed on the screen with relevant emission standards. Since PM and K values ​​are obtained by correlating data from the same sampling path and time period using the same algorithm, they have excellent consistency and correspondence, overcoming the problem of difficulty in verifying data from traditional separate measurement methods.

[0098] This invention truly achieves low-cost integrated detection. By using a relatively low-cost PM sampling probe and a signal processing algorithm, PM concentration and smoke opacity K value can be obtained simultaneously in the same device, eliminating the need to purchase separate PM detectors and smoke opacities, thus significantly reducing hardware investment.

[0099] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A portable PM and smoke opacity combined detection device, characterized in that, It includes an integrated PM sampling probe, a micro-current detection module, a filter circuit, an ADC acquisition module, and an MCU control module that are electrically connected in sequence. The PM sampling probe is used to collect particulate matter in engine exhaust and output a weak current signal related to the particulate matter concentration. The microcurrent detection module includes a transimpedance amplifier circuit that converts the weak current signal into a voltage signal. The MCU control module is configured as follows: (1) Perform zero-point calibration, abnormal pulse rejection and steady-state range judgment on the digital signal converted by the ADC acquisition module; (2) When it is determined that the signal is in a steady state range, the current characteristic value of the digital signal is extracted; (3) Call the pre-calibrated relationship model between the current characteristic value of the PM sensor and the smoke light absorption coefficient K value, and use the extracted current characteristic value to calculate the corresponding smoke light absorption coefficient K value.

2. The portable PM and smoke opacity combined detection device according to claim 1, characterized in that, The MCU control module is also configured to: When performing zero-point calibration on the digital signal, a zero-point reference value is acquired during the device startup phase or in a state with no particulate matter input, and this zero-point reference value is subtracted from the subsequent detection signal.

3. The portable PM and smoke opacity combined detection device according to claim 1, characterized in that, The abnormal pulse rejection performed by the MCU control module specifically includes: Calculate the degree of deviation between the current sampling point and the mean or variance of the signal within the sliding window; When the deviation exceeds a preset threshold, the sampling point is identified as an abnormal pulse and is either discarded or replaced with a nearby valid sampling value.

4. The portable PM and smoke opacity combined detection device according to claim 1, characterized in that, The steady-state range determination performed by the MCU control module specifically includes: Within a preset time window, calculate the fluctuation amplitude, rate of change, or variance of the digital signal; When the fluctuation amplitude, rate of change, or variance is less than the corresponding preset steady-state threshold, the current time window is determined to be the steady-state interval.

5. The portable PM and smoke opacity combined detection device according to claim 1, characterized in that, The relationship model between the current characteristic value of the PM sensor and the smoke light absorption coefficient K value satisfies the expression: In the formula, The light absorption coefficient of smoke opacity is expressed in m. - ¹; The particulate matter mass concentration is calculated from the current characteristic value, and the unit is mg / m³; , These are the fitting coefficients determined through experimental calibration.

6. The portable PM and smoke opacity combined detection device according to claim 1 or 5, characterized in that, The current characteristic values ​​include the steady-state average current, peak current, response slope, and integrated charge. The MCU control module extracts the current characteristic value and inputs it into the relational model to calculate the smoke light absorption coefficient K value.

7. The portable PM and smoke opacity combined detection device according to claim 1, characterized in that, Also includes: A filtering protection module is provided at least one of the power input terminal and the signal acquisition path to provide at least one of the following functions: overvoltage protection, reverse connection protection, electrostatic discharge protection, power filtering, and electromagnetic interference suppression. The display module, which is connected to the MCU control module, is used to synchronously display detection information including at least PM detection results, smoke light absorption coefficient K value, sensor current value, and equipment status; and when an abnormal signal, unstable sampling, smoke light absorption coefficient K value exceeding a preset threshold, or device malfunction is detected, the display module outputs corresponding alarm prompt information. The communication module is used to output the detection results to a host computer, mobile terminal or detection platform via at least one of the following communication methods: serial port, Bluetooth, WiFi or USB.

8. The portable PM and smoke opacity combined detection device according to claim 1, characterized in that, It also includes a housing assembly, and the PM sampling probe is connected to the housing assembly via a sensor interface; wherein, the housing assembly integrates a display screen, a button module, a communication interface and a data interface.

9. A portable method for joint detection of PM and smoke opacity based on the device described in any one of claims 1-8, characterized in that, Includes the following steps: Place the PM sampling probe at the engine exhaust detection position to collect particulate matter in the exhaust and output a weak current signal. The weak current signal is converted into a voltage signal by the transimpedance amplifier circuit in the microcurrent detection module; The filtering circuit performs filtering processing on the voltage signal; The ADC acquisition module converts the filtered analog voltage signal into a digital signal; The MCU control module performs zero-point calibration, abnormal pulse rejection, and steady-state range determination on the digital signal; When the signal is determined to be in the steady-state range, the MCU control module extracts the current characteristic value; The relationship model between the pre-calibrated PM sensor current characteristic value and the smoke light absorption coefficient K value is invoked, and the smoke light absorption coefficient K value is calculated using the extracted current characteristic value. The PM detection results and the calculated smoke light absorption coefficient K value are output and displayed synchronously.

10. The portable PM and smoke opacity joint detection method according to claim 9, characterized in that, The abnormal pulse rejection includes: By comparing the difference between the current sampling point and the mean of the sliding window, or by comparing the variance within the sliding window with a preset variance threshold, abnormal pulses caused by electromagnetic interference, sudden changes in exhaust flow rate, or abnormal sampling contact can be identified and eliminated.

11. The portable PM and smoke opacity joint detection method according to claim 9, characterized in that, The steady-state interval determination includes: Within a preset time window, monitor the amplitude, rate of change, or variance of the signal fluctuation. When the value is consistently below the preset steady-state threshold, it is determined to be in a steady-state range; otherwise, it indicates that the detection state is unstable and sampling continues.

12. The portable PM and smoke opacity joint detection method according to claim 9, characterized in that, The method further includes: Zero-point reference values ​​are collected and stored during device startup or when there is no particulate matter input. The zero-point calibration includes subtracting the zero-point reference value from the digital signal to reduce the effects of zero-point drift.

13. The portable PM and smoke opacity joint detection method according to claim 9, characterized in that, The relationship model is established by simultaneously connecting the detection device and a standard smoke meter to the same exhaust source, synchronously collecting the current characteristic value and the smoke light absorption coefficient K value measured by the standard smoke meter under different operating conditions, and then performing linear regression fitting.

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