Integral window adaptive waveform area online measurement method

Abstract

This invention discloses an online waveform area measurement method with an adaptive integral window, comprising: measuring the amplitude of the detector output signal against a set threshold V. TH By comparing and controlling the width of the integration window in real time, this method adapts to the characteristic that the effective integration window width varies with amplitude. The integration window includes a leading-edge compensation window, a main integration window, and a trailing-edge compensation window. Based on amplitude-time walk and signal-to-noise ratio information extracted from similar signals, the leading-edge compensation window and the trailing-edge compensation window are configured to compensate for the amplitude-time walk effect. This method balances the accuracy of the waveform area integration system under different input amplitudes over a large dynamic range and significantly improves the accuracy of waveform area measurement.

Description

An adaptive integral window method for online measurement of waveform area Technical Field

[0001] This invention relates to the field of high-precision charge measurement technology, and in particular to an online method for measuring waveform area with adaptive integration window. Background Technology

[0002] In the field of nuclear detection readout electronics, efficient sampling, accurate quantization, and information extraction of the weak current signal output by the detector are crucial for achieving core functions such as particle energy measurement and particle identification. Among these, extracting the charge information carried by the waveform is particularly critical. When an incident particle is ionized or excited in the detector's sensitive area, its energy loss is converted into a current signal, and the total charge of this current signal is proportional to the event deposition energy. After amplification, filtering, and analog-to-digital conversion by front-end electronics, the total charge of the digital waveform output still maintains a linear relationship with the original signal charge. Therefore, by measuring the waveform area, the charge information output by the detector can be obtained, and the energy of the incident particle can be deduced. This method is collectively known as the "waveform area method." Furthermore, online monitoring, trigger selection, particle identification, and data simplification in nuclear detection systems all require online processing of waveform area measurements.

[0003] Currently, there are two main methods for online waveform area measurement: one is the full waveform integration method, which integrates the entire sampling interval of the digital waveform to directly obtain the total area over the entire time range; the other is the fixed window integration method, which pre-sets a fixed integration window, usually corresponding to the main peak region of the signal, and only performs integration calculations on the waveform within this window. However, both of these methods have significant limitations in practical applications. For the full waveform integration method, since the leading and trailing edges of nuclear detection signals usually have significant noise disturbances, and the output waveforms of some detectors have long, noisy tails, if the integration window is extended to the entire waveform range, the higher proportion of signal components at the tail of the waveform will exacerbate the statistical fluctuations in the integration results, especially when measuring low-energy events with low signal-to-noise ratios. This phenomenon is more pronounced and seriously affects the accuracy of charge extraction.

[0004] The core assumption of the fixed-window integration method is that the location of the signal's main peak region, i.e., the effective integration window where energy information is concentrated, remains stable across signals of different amplitudes. However, in actual nuclear detection, the noise power of the signal is essentially the same, while the incident particle energy is random, resulting in a dynamic range of waveform amplitude that can be tens of times or higher. High-energy events produce signals with higher amplitudes and slower decay, while low-energy events produce signals with lower amplitudes and faster decay. This leads to a significant positive correlation between the effective integration window width (with a sufficiently high signal-to-noise ratio) and the amplitude. A fixed integration window width cannot accommodate this characteristic, causing high-amplitude signals to lose tail charge due to premature window cutoff, and low-amplitude signals to include more tail noise due to late window cutoff, exacerbating statistical fluctuations in the integration results. Furthermore, the different rise rates and amplitudes of signals generated by different energy events cause a "walk" in the time relationship between the effective integration window and the threshold moment, i.e., the "amplitude-time walk effect." A fixed integration window position cannot accommodate this characteristic, leading to a misalignment between the actual integration window and the effective integration window, resulting in systematic bias in energy measurement.

[0005] Therefore, in order to adapt to changes in the width and position of the effective integration window of the signal and improve the measurement accuracy of the online waveform area, this invention is proposed. Summary of the Invention

[0006] The purpose of this invention is to provide an adaptive integral window method for online waveform area measurement, thereby addressing the aforementioned technical problems in the prior art. The method described in this invention maintains the accuracy of the waveform area integration system under different input amplitudes over a large dynamic range and significantly improves the accuracy of waveform area measurement.

[0007] The objective of this invention is achieved through the following technical solution:

[0008] An online waveform area measurement method with adaptive integration window, the method comprising:

[0009] Step 1: By comparing the amplitude of the detector output signal with the set threshold V TH The width of the integration window is controlled in real time to adapt to the characteristic that the width of the effective integration window of the signal changes with the amplitude; the integration window includes the leading edge compensation integration window, the main integration window, and the trailing edge compensation integration window.

[0010] Step 2: Based on the amplitude-time walk information and signal-to-noise ratio information extracted from similar signals, configure the leading edge compensation integration window and the trailing edge compensation integration window to compensate for the influence of the amplitude-time walk effect.

[0011] Compared with existing technologies, the method provided by this invention takes into account the accuracy of the waveform area integration system under different input amplitudes in a large dynamic range, significantly improving the accuracy of waveform area measurement. This method has high versatility and can be applied not only to cosmic ray observation experiments but also to high-precision charge measurement in accelerator experiments, especially to charge measurement systems with a large dynamic range in high-energy physics experiments. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the 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.

[0013] Figure 1 is a flowchart illustrating the online waveform area measurement method with adaptive integration window provided by an embodiment of the present invention;

[0014] Figure 2 is a schematic diagram of the time-domain waveform of the signal described in an embodiment of the present invention;

[0015] Figure 3 shows the simulation optimization process of traversing N at an 85MHz sampling rate provided in the embodiment of the present invention. front N end A schematic diagram showing the area accuracy;

[0016] Figure 4 is a schematic diagram comparing the dynamic control effect of the integral window under different input amplitudes and different sampling rates of the method described in the embodiment of the present invention.

[0017] Figure 5 is a schematic diagram comparing the area accuracy obtained by the method described in the embodiment of the present invention under different input amplitudes and different sampling rates with the full waveform integration method and the fixed window integration method. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them, and do not constitute a limitation on the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0019] The technical solution provided by this invention will be described in detail below. Contents not described in detail in the embodiments of this invention are prior art known to those skilled in the art. Where specific conditions are not specified in the embodiments of this invention, they shall be performed according to conventional conditions in the art or conditions recommended by the manufacturer. Reagents or instruments used in the embodiments of this invention whose manufacturers are not specified are all conventional products that can be purchased commercially.

[0020] Figure 1 shows a flowchart of an online waveform area measurement method with adaptive integration window provided by an embodiment of the present invention. The method includes:

[0021] Step 1: By comparing the amplitude of the detector output signal with the set threshold V TH The comparison is performed, and the width of the integration window is controlled in real time to adapt to the characteristic that the width of the effective integration window of the signal changes with the amplitude.

[0022] The integration window includes the leading edge compensation integration window, the main integration window, and the trailing edge compensation integration window.

[0023] In this step, when the signal arrives, the signal is above the threshold V. TH The previous N front Each sampling point is called the front-end compensation integral window;

[0024] The signal is higher than the threshold V TH The interval defined by the integral is called the main integration window;

[0025] The signal is below the threshold V TH The following N end Each sampling point is called the trailing edge compensation integral window.

[0026] In specific implementation, the threshold V TH Adjustments are made based on the noise power of the input signal and the system's false trigger rate requirements.

[0027] In practice, the adjustment process of the front-end compensation integral window is as follows:

[0028] Using a depth of N front The circular buffer, by processing the last N data streams arriving in the data stream... front Each amplitude value is cyclically buffered and locked after the signal is triggered, wherein:

[0029] First, the signal output from the detector is processed by an analog front-end circuit and an analog-to-digital converter to obtain a continuous amplitude data stream. Then, the last N values ​​arriving in the data stream are processed... front Each amplitude value is buffered cyclically;

[0030] When the system is in a state of waiting to be triggered, the continuously arriving amplitude information is sent to the threshold comparator and compared with the threshold V. TH When the amplitude information is greater than the threshold V, a comparison is made. TH When the threshold comparator outputs 1, it triggers the system to enter the integration state; wherein, the system is a case readout system for processing the digitized waveform data stream into a single case information, the single case information containing charge information;

[0031] When the system transitions from the pending trigger state to the integration state, it will cyclically cache N front Amplitude is locked.

[0032] The adjustment process for the main integral window is as follows:

[0033] A reset accumulator and a threshold comparator are used. The threshold comparator controls the reset accumulator. When the threshold comparator determines that the amplitude of the input signal is greater than the threshold V, the reset accumulator is activated. TH At that time, the control reset accumulator accumulates the incoming amplitude until the threshold comparator determines that the amplitude of the input signal is less than the threshold V. TH ,in:

[0034] Once the system enters the integration state, the reset accumulator continuously accumulates the amplitude of subsequent sample points until the threshold comparator detects a falling edge crossing the threshold V. TH The threshold comparator outputs 0.

[0035] The adjustment process for the trailing edge compensation integral window is as follows:

[0036] Use a reset accumulator and a counting range greater than N. end The counter controls the reset accumulator; when the amplitude of the input signal is lower than the threshold V... TH At this time, the reset accumulator continues to accumulate the incoming amplitude value, while the counter counts synchronously until the counter count reaches N. end The control resets the accumulator to stop accumulating, where:

[0037] After the threshold comparator outputs 0, the reset accumulator continues to accumulate N. end After one amplitude point, the accumulation stops;

[0038] Then lock N in the circular buffer. front Each amplitude value is accumulated into the reset accumulator. After the accumulation is completed, the loop buffer is restored and the integral area obtained by the reset accumulator at this time is sent to the next level system.

[0039] Step 2: Based on the amplitude-time walk information and signal-to-noise ratio information extracted from similar signals, configure the leading edge compensation integration window and the trailing edge compensation integration window to compensate for the influence of the amplitude-time walk effect.

[0040] In this step, the sampling point parameter N of the leading edge compensation integral window front The sampling point parameters N of the trailing edge compensation integral window end The initial N is obtained by calculating the amplitude-time walk information of the input signal. front N end Satisfy the following formula:

[0041] N front ·Ts = V TH ·(1 / V min – 1 / V max )·T r ;

[0042] N end ·T s = V TH ·(1 / V min – 1 / V max )·T f ;

[0043] Among them, T s V is the sampling period of the analog-to-digital converter; TH The trigger threshold set for the system; (V min V max T represents the amplitude range of the input signal of interest. r T is the average rise time of the input signal; f The average fall time of the input signal;

[0044] N front N end The configuration is obtained using initial values ​​or based on simulation tuning.

[0045] For example, Figure 2 shows a schematic diagram of the time-domain waveform of the signal described in an embodiment of the present invention, T s The range is 6.25 ns to 25 ns; V TH Take 5 times the noise standard deviation of the signal, which is 40mV; (V min V max The voltage range is (0.1V, 1.6V); T r Approximately 40 ns; T f Approximately 120ns, taking an 85MHz sampling rate as an example, N front N end The initial values ​​are 1.275 and 3.825, which are rounded down to 1 and 3.

[0046] In practice, the simulation optimization process is as follows:

[0047] Waveforms under different charge values ​​are obtained using a high-speed sampling device, and a waveform area integration device is constructed in a simulation environment.

[0048] The waveform under the same charge is input into the waveform area integrator, and the standard deviation of the output area is calculated.

[0049] For the configuration parameter N that needs to be tuned front N end The process involves iterating through the data, with the range determined by the initial values, to obtain the area standard deviation and the configuration parameter N. frontN end The selected relationship;

[0050] Then select the configuration parameter combination that yields the most accurate area result or that you need.

[0051] For example, as shown in Figure 3, during the simulation optimization process provided by an embodiment of the present invention, N is traversed at a sampling rate of 85MHz. front N end The diagram illustrates the area accuracy. For a simulated analog-to-digital converter with a sampling rate of 85MHz, N is taken as... front N end The tuning traversal ranges are 0~5 and 0~5, respectively. The ratio of the root mean square of the integral area and the average value of the integral area under each parameter combination with an input amplitude of 0.1V is called the relative accuracy (%). The parameter combination with the best relative accuracy (N) is selected. front , N end )=(1, 3) is the configuration after simulation optimization.

[0052] Figure 4 shows a comparison of the dynamic control effect of the integral window under different input amplitudes and different sampling rates according to the embodiment of the present invention. The test results show that the present invention achieves the effect of adaptively adjusting the width of the integral window according to the waveform amplitude with less resource consumption.

[0053] Figure 5 shows a comparison of the area accuracy obtained by the method described in this embodiment of the invention under different input amplitudes and sampling rates with the full waveform integration method and the fixed window integration method. The horizontal axis represents the sampling rate; generally, a lower sampling rate saves more resources. The vertical axis represents the accuracy, i.e., the standard deviation of the obtained area; a smaller standard deviation indicates better area accuracy. The upper part of Figure 5 shows the results under large signal input conditions, and the lower part shows the results under small signal input conditions. Simulation results show that the method described in this invention achieves better results than the existing full waveform integration method and fixed window integration method with less resource consumption. Furthermore, compared to existing algorithms, it better balances area accuracy under different amplitudes, making it particularly suitable for scenarios with large dynamic range inputs.

[0054] This invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the method.

[0055] This invention also provides a computer storage medium storing a plurality of instructions adapted for loading and executing the method by a processor.

[0056] In summary, the method described in this embodiment of the invention takes into account the accuracy of the waveform area integral system under different input amplitudes over a large dynamic range, compensates for the influence of amplitude-time walk effect, and thus improves the overall accuracy of the system. It uses a small amount of hardware resources, including a buffer unit, accumulator, comparator and control logic, without the need for complex hardware circuits, reducing resource consumption and demonstrating good effectiveness and practicality. This method is applicable to high-precision charge measurement in various physics experiments, especially to charge measurement systems with a large dynamic range in high-energy physics experiments, and has high versatility.

[0057] Furthermore, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware, and the corresponding program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0058] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims. The information disclosed in the background section is intended only to enhance the understanding of the overall background technology of the present invention and should not be construed as an admission or implication in any way that such information constitutes prior art known to those skilled in the art.

Claims

1. A method for online measurement of waveform area using an adaptive integral window, characterized in that, The method includes: Step 1, comparing the amplitude of the detector output signal with a set threshold V. TH The comparison is performed, and the width of the integration window is controlled in real time to adapt to the characteristic that the effective integration window width varies with the amplitude. The integration window includes a leading-edge compensation integration window, a main integration window, and a trailing-edge compensation integration window. Step 2: Based on the amplitude-time walk information and signal-to-noise ratio information extracted from similar signals, the leading-edge compensation integration window and the trailing-edge compensation integration window are configured to compensate for the influence of the amplitude-time walk effect. In step 2, the sampling point parameter N of the leading-edge compensation integration window... front The sampling point parameters N of the trailing edge compensation integral window end The initial N is obtained by calculating the amplitude-time walk information of the input signal. front N end Satisfy the following formula: N front ·T s = V TH ·(1 / V min – 1 / V max )·T r N end ·T s = V TH ·(1 / V min – 1 / V max )·T f Among them, T s V is the sampling period of the analog-to-digital converter; TH The trigger threshold set for the system; (V min V max T represents the amplitude range of the input signal of interest. r T is the average rise time of the input signal; f N is the average fall time of the input signal; front N end The configuration is obtained using initial values ​​or based on simulation tuning.

2. The adaptive waveform area online measurement method according to claim 1, characterized in that, In step 1, when the signal arrives, the signal is above the threshold V. TH The previous N front Each sampling point is called the front-edge compensation integral window; the signal is above the threshold V. TH The interval between these intervals is called the main integration window; the signal is below the threshold V. TH The following N end Each sampling point is called the trailing edge compensation integral window.

3. The adaptive waveform area online measurement method with an integral window according to claim 1, characterized in that, In step 1, the threshold V TH Adjustments are made based on the noise power of the input signal and the system's false trigger rate requirements.

4. The adaptive waveform area online measurement method with an integral window according to claim 2, characterized in that, The adjustment process of the leading edge compensation integral window is as follows: using a depth of N front The circular buffer, by processing the last N data streams arriving in the data stream... front Each amplitude value is cyclically buffered and locked after signal triggering. Specifically: first, the signal output from the detector is processed by an analog front-end circuit and an analog-to-digital converter to obtain a data stream of continuous amplitude values. Then, the last N values ​​arriving in the data stream are... front Each amplitude value is buffered cyclically; when the system is in a pending trigger state, the continuously arriving amplitude information is sent to the threshold comparator and compared with the threshold V. TH When the amplitude information is greater than the threshold V, a comparison is made. TH When the threshold comparator outputs 1, it triggers the system to enter the integration state; wherein, the system is a case readout system used to process the digitized waveform data stream into individual case information, each case information containing charge information; when the system enters the integration state from the waiting-to-be-triggered state, it will cyclically buffer N front Amplitude is locked.

5. The adaptive waveform area online measurement method with an integral window according to claim 4, characterized in that, The adjustment process of the main integration window is as follows: A reset accumulator and a threshold comparator are used. The threshold comparator controls the reset accumulator. When the threshold comparator determines that the amplitude of the input signal is greater than the threshold V... TH At that time, the control reset accumulator accumulates the incoming amplitude until the threshold comparator determines that the amplitude of the input signal is less than the threshold V. TH Wherein: after the system enters the integration state, the reset accumulator continues to accumulate the amplitude of subsequent sampling points until the threshold comparator detects a falling edge crossing the threshold V. TH The threshold comparator outputs 0.

6. The adaptive waveform area online measurement method with an integral window according to claim 5, characterized in that, The adjustment process for the trailing edge compensation integral window is as follows: using a reset accumulator and a counting range greater than N... end The counter controls the reset accumulator; when the amplitude of the input signal is lower than the threshold V... TH At this time, the reset accumulator continues to accumulate the incoming amplitude value, while the counter counts synchronously until the counter count reaches N. end The reset accumulator is controlled to stop accumulating, wherein: after the threshold comparator outputs 0, the reset accumulator continues to accumulate N. end After calculating several amplitude points, the accumulation stops; then the N values ​​locked in the loop buffer are... front Each amplitude value is accumulated into the reset accumulator. After the accumulation is completed, the loop buffer is restored and the integral area obtained by the reset accumulator at this time is sent to the next level system.

7. The adaptive waveform area online measurement method with an integral window according to claim 1, characterized in that, The simulation optimization process is as follows: Waveforms under different charge levels are obtained using a high-speed sampling device; a waveform area integrator is constructed in the simulation environment; waveforms under the same charge level are input into the waveform area integrator, and the standard deviation of the output area is calculated; the configuration parameter N to be optimized is then... front N end The process involves iterating through the data, with the range determined by the initial values, to obtain the area standard deviation and the configuration parameter N. front N end Select the relationship; then select the configuration parameter combination that yields the most accurate area result or is the desired result.

8. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 7.

9. A computer storage medium, characterized in that, The computer storage medium stores a plurality of instructions adapted for loading by a processor and executing the method of any one of claims 1 to 7.

Images