Signal processing method based on laser methane sensor

Abstract

The invention discloses a signal processing method based on a laser methane sensor. The method comprises the following steps: step 1, providing stable current for a laser through a constant current source circuit; step 2, acquiring the environment temperature in real time when the laser generates laser by using a temperature acquisition circuit; 3, processing the data of the temperature acquisition circuit by using a temperature control algorithm, and controlling the environment temperature to be the temperature most suitable for laser generation of the laser according to the preset optimal temperature parameter; step 4, receiving laser which is generated by the laser and passes through the methane gas by using a photodiode; and step 5, the amplified signal is collected through the single-chip microcomputer. In order to ensure that a laser of the sensor can stably emit laser, a PID algorithm is adopted to control and adjust the temperature of a light-emitting environment; and processing the acquired output signal of the amplifying circuit by using an improved Kalman filtering algorithm, removing noise and obtaining effective signal information.

Description

Technical Field

[0001] The invention relates to the field of laser signal processing, and more specifically to a method for processing laser methane monitoring sensor signals. Background Art

[0002] As the world pays more and more attention to clean energy, the monitoring and detection of methane as a major greenhouse gas has become crucial. Methane not only plays an important role in energy production and consumption, but its leakage can have serious impacts on the environment and public safety. Therefore, the development of efficient methane sensors, especially those based on laser detection technology, has become an important research field.

[0003] The working principle of the laser methane sensor is based on optical absorption technology. Specifically, the laser beam is used to irradiate methane gas, and the selective absorption characteristics of methane molecules to lasers of specific wavelengths are used to measure the attenuation of the laser signal to determine the concentration of methane. Since the absorption spectrum of methane is in the near-infrared region, commonly used laser sources include tunable laser diodes (TDL) and quantum cascade lasers (QCL). These lasers can provide high-precision wavelength tuning capabilities, which greatly improves the sensitivity and selectivity of methane gas detection.

[0004] Although laser methane sensors have high sensitivity and selectivity, signal processing is still a challenge in practical applications. The output signal of the sensor is often interfered by various factors such as environmental noise, temperature changes and airflow, resulting in inaccurate measurement results. Therefore, signal processing technology is particularly important in improving sensor performance. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of laser methane sensors that use TDLAS technology to directly perform laser detection of methane gas: when the laser emits light, the change in ambient temperature affects the light-emitting effect; the signal generated by the photodiode contains noise, resulting in unclear information, and use filtering technology to obtain clearer and more useful information.

[0006] The present invention provides a signal processing method based on a laser methane sensor, which is performed according to the following steps:

[0007] Step 1, providing a stable current to the laser through a constant current source circuit;

[0008] Step 2: Using a temperature acquisition circuit, real-time acquisition of the ambient temperature when the laser generates laser light;

[0009] Step 3: Use the temperature control algorithm to process the data of the temperature acquisition circuit, and according to the preset optimal temperature parameters, control the ambient temperature to the most suitable temperature for the laser to generate laser, ensure that the generated laser meets the requirements, and perform temperature control through the temperature control circuit;

[0010] Step 4, using a photodiode to receive the laser light generated by the laser and passing through the methane gas, and using an amplifier circuit to amplify the weak current generated by the laser light;

[0011] Step 5: The amplified signal is collected by the single chip microcomputer, and the collected signal is processed according to the following steps:

[0012] Step (1) setting various parameters in the Kalman filter algorithm;

[0013] Step (2) obtaining an output signal;

[0014] Step (3) prediction: perform Kalman filter processing, starting from the second data point, predict the current data point based on the previous data point and calculate the prediction error covariance;

[0015] Among them, the formula for predicting state estimation is:

[0016] The formula for the prediction error covariance is: P-(k) = P(k-1) + Q, where Q is the process noise covariance;

[0017] Step (4) calculates the Kalman filter gain, updates the state estimate, and then updates the error covariance to ensure that the measurement information is integrated and valid signal information is obtained;

[0018] The calculation method of the filter gain is: R is the measurement noise covariance;

[0019] The formula for updating the state estimate is:

[0020] The error covariance calculation formula is: P(k) = (1-K(k))*P - (k);

[0021] (5) Use adaptive algorithm to adjust the noise covariance matrix.

[0022] The specific steps of using the temperature control algorithm to process the data of the temperature acquisition circuit are as follows:

[0023] (1) Obtain the actual temperature value;

[0024] (2) Parameter initialization: set the values ​​of the proportional coefficient (Kp), integral coefficient (Ki), differential coefficient (Kd) and target temperature;

[0025] (3) Calculation: first, error calculation is performed; then PID parameter calculation is performed; then the output of the PID controller is calculated; at the same time, the temperature parameters are updated; and finally, the error parameters are updated;

[0026] Among them, the PID algorithm formula is as follows:

[0027]

[0028] Where Kp, Ki and Kd are the parameters set in parameter initialization;

[0029] (4) Finally, the appropriate temperature parameters are obtained and the algorithm ends.

[0030] The present invention has the following beneficial effects:

[0031] 1. In order to ensure the stability of the operating environment of the sensor during work, in terms of hardware, a constant current source circuit is used to provide a stable current to support the laser light emission; the temperature of the light emission environment is collected through the temperature acquisition circuit, and the ambient temperature is controlled by the temperature control circuit; finally, the signal amplification circuit is used to amplify the output signal to facilitate collection and analysis.

[0032] 2. In addition, in terms of algorithm design, in order to ensure that the laser of the sensor can emit laser stably, the PID algorithm is used to control and adjust the temperature of the light-emitting environment; the improved Kalman filter algorithm is used to process the collected output signal of the amplifier circuit to remove noise and obtain effective signal information.

[0033] The signal processing method of the laser methane sensor of the present invention combines a variety of advanced technologies, including digital filtering, signal enhancement, etc. The application of these technologies not only improves the detection sensitivity and reliability of the sensor, but also provides important guarantees for environmental monitoring and public safety. With the continuous advancement of technology, laser methane sensors will be widely used in more fields.

[0034] Digital filters can effectively remove high-frequency noise from signals while retaining useful low-frequency signals. Kalman filter is a filtering method based on state space model, which can update system status in real time and dynamically optimize filtering parameters to improve measurement accuracy.

[0035] In addition, signal enhancement technology is also an effective means to improve the performance of laser methane sensors. Through devices such as phase-locked amplifiers, weak methane signals can be extracted from background noise, significantly improving the signal-to-noise ratio. This method is particularly suitable for dynamic environments, allowing the sensor to maintain good detection capabilities under complex conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the process of the present invention;

[0037] Figure 2 It is a schematic diagram of the ambient temperature adjustment process;

[0038] Figure 3 It is a flowchart of the improved Kalman filter algorithm. DETAILED DESCRIPTION

[0039] The present invention will be further described below in conjunction with the accompanying drawings.

[0040] like Figure 1 and Figure 3 As shown, the present invention is carried out according to the following steps:

[0041] Step 1: Provide a stable current to the laser through a constant current source circuit.

[0042] Step 2: Use the temperature acquisition circuit to collect the ambient temperature of the laser when it generates laser in real time.

[0043] Step three, use the temperature control algorithm to process the data of the temperature acquisition circuit, and according to the pre-set optimal temperature parameters, control the ambient temperature at the most suitable temperature for the laser to generate laser, ensure that the generated laser meets the requirements, and perform temperature control through the temperature control circuit.

[0044] (1) Get the actual temperature value.

[0045] (2) Parameter initialization: Set the values ​​of the proportional coefficient (Kp), integral coefficient (Ki), differential coefficient (Kd) and target temperature.

[0046] (3) Perform calculations: first, calculate the error; then calculate the PID parameters; then calculate the output of the PID controller; at the same time, update the temperature parameters; and finally update the error parameters.

[0047] Among them, the PID algorithm formula is as follows:

[0048]

[0049] Where Kp, Ki and Kd are the parameters set in parameter initialization, which are set to 110, 6 and 4 respectively.

[0050] (4) Finally, the appropriate temperature parameters are obtained and the algorithm ends.

[0051] Step 4: Use a photodiode to receive the laser light generated by the laser and passing through the methane gas, and use an amplifier circuit to amplify the weak current generated by the laser light.

[0052] Step 5: The amplified signal is collected by the single chip microcomputer, and then processed by the improved Kalman filter algorithm to reduce the noise interference in the collected signal and retain and highlight its effective information. Figure 2 shown.

[0053] (1) Parameter initialization: Set various parameters in the Kalman filter algorithm: process noise covariance Q is 0.00001; measurement noise covariance R is 0.51; initial error covariance P(1) is 0.9.

[0054] (2) Extract the amplified signal.

[0055] (3) Prediction: Perform Kalman filter processing, starting from the second data point, predict the current data point based on the previous data point and calculate the predicted error covariance.

[0056] Among them, the formula for predicting state estimation is: The formula for prediction error covariance is: P-(k)=P(k-1)+Q, where Q is the process noise covariance.

[0057] (4) Calculate the Kalman filter gain, update the state estimate, and then update the error covariance to ensure that the measurement information is integrated and obtain valid signal information.

[0058] The calculation method of the filter gain is: R is the measurement noise covariance; the formula for state estimation update is: The error covariance calculation formula is: P(k) = (1-K(k))*P - (k).

[0059] (5) Use adaptive algorithm to adjust the noise covariance matrix.

[0060] Step 6: Determine the methane concentration based on the processed signal and decide whether to sound an alarm.

[0061] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A signal processing method based on a laser methane sensor, characterized in that: Signal processing is performed in the following steps: Step 1, providing a stable current to the laser through a constant current source circuit; Step 2: Using a temperature acquisition circuit, real-time acquisition of the ambient temperature when the laser generates laser light; Step 3: Use the temperature control algorithm to process the data of the temperature acquisition circuit, and according to the preset optimal temperature parameters, control the ambient temperature to the most suitable temperature for the laser to generate laser, ensure that the generated laser meets the requirements, and perform temperature control through the temperature control circuit; Step 4, using a photodiode to receive the laser light generated by the laser and passing through the methane gas, and using an amplifier circuit to amplify the weak current generated by the laser light; Step 5: The amplified signal is collected by the single chip microcomputer, and the collected signal is processed according to the following steps: Step (1) setting various parameters in the Kalman filter algorithm; Step (2) obtaining an output signal; Step (3) prediction: perform Kalman filter processing, starting from the second data point, predict the current data point based on the previous data point and calculate the prediction error covariance; Among them, the formula for predicting state estimation is: The formula for prediction error covariance is: P-(k)=P(k-1)+Q, where Q is the process noise covariance. Step (4) calculates the Kalman filter gain, updates the state estimate, and then updates the error covariance to ensure that the measurement information is integrated and valid signal information is obtained; The calculation method of the filter gain is: R is the measurement noise covariance; The formula for updating the state estimate is: The error covariance calculation formula is: P(k) = (1-K(k))*P-(k); (5) Use adaptive algorithm to adjust the noise covariance matrix.

2. The temperature control method of a laser methane sensor according to claim 1, characterized in that: The specific steps of using the temperature control algorithm to process the data of the temperature acquisition circuit are as follows: (1) Obtain the actual temperature value; (2) Parameter initialization: set the values ​​of the proportional coefficient Kp, integral coefficient Ki, differential coefficient Kd and target temperature; (3) Calculation: first, error calculation is performed; then PID parameter calculation is performed; then the output of the PID controller is calculated; at the same time, the temperature parameters are updated; and finally, the error parameters are updated; Among them, the PID algorithm formula is as follows: Where Kp, Ki and Kd are the parameters set in parameter initialization; (4) Finally, the appropriate temperature parameters are obtained and the algorithm ends.

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