Signal acquisition, processing and analysis method and system for a particle detector array

Abstract

The present application relates to the technical field of particle detector, specifically to a signal acquisition, processing and analysis method and system of particle detector array, comprising the following steps: channel amplitude segmentation difference ratio threshold marking stable section, calculating difference ratio screening monotone rising channel marking transition, extracting the earliest excitation channel as the starting point, searching adjacent channels screening time difference within the window as the candidate, and taking the angle change less than the threshold as the main section to generate path structure. In the present application, the amplitude difference of the extracted channel in the fixed period is screened to select the stable signal section, the signal is preliminarily structured, the rising trend channel is identified by the difference ratio, the first excitation time is extracted to establish the spatial starting point index, the path candidate is screened by combining the adjacent channel time difference and state, the direction consistent path main section is extracted by using the angle change analysis, the particle path reconstruction is realized, the recognition accuracy is improved by multi-dimensional parameter cooperation, the analysis ability is enhanced, and the misjudgment rate is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of particle detector, in particular to a signal acquisition, processing and analysis method and system of particle detector array. BACKGROUND

[0002] The technical field of particle detector relates to related methods and devices for accurately detecting and measuring high-energy particles, and the core matters include signal conversion mechanism after the interaction of particles and detection medium, construction of signal acquisition circuit, time and space correlation analysis of data, etc. In the overall method, a multi-channel detection structure is constructed, the physical signal caused by the incidence of particles is converted into measurable electrical signal by using electronic system, and synchronous acquisition, digital conversion and subsequent analysis are realized through a specific path to identify particle types and trajectory information. The signal acquisition, processing and analysis method of the traditional particle detector array refers to the signal acquisition and identification process of each channel in the multi-unit detector array. The electrical signal is usually acquired by using the channel-by-channel charge integration and amplification method, the charge trigger event is distinguished by using the fixed threshold value, and the event data is classified, recorded and preliminarily analyzed by using the channel-by-channel distributed processing circuit. This method relies on the preset sampling period and static data buffer, and the data extraction and analysis processing are carried out by linear scanning and rule-based discrimination.

[0003] The traditional method adopts the charge integration and amplification processing of each channel signal, combines the fixed threshold trigger discrimination, and carries out data sampling and rule scanning under the condition of static buffer, which is easy to cause the recognition delay or misjudgment of low-amplitude fluctuation signal, especially in the high-frequency transient interference environment, and the discrimination strategy cannot be dynamically adjusted. Since the sampling process relies on the preset period and linear scanning logic, in the case of particle multi-point triggering and high-throughput response, the loss of correlation information between channels often occurs, and it is difficult to restore the real time and space evolution path. In the data classification and analysis process, there is a lack of amplitude change trend analysis mechanism for continuous time period, and only the threshold trigger and static sampling are easy to ignore the weak continuous response signal in the particle penetration path. When the path is reconstructed, the spatial layout and angle change trend are not considered, it is difficult to accurately identify the main section of the channel trend, which may cause the problems of broken or wrong connection in the particle trajectory reconstruction result, and affects the accurate judgment of particle types and energy characteristics. The above problems are particularly prominent in the detection array with high channel density or high data concurrency, which limits the adaptability and expansibility of the system in complex physical events. SUMMARY

[0004] The purpose of the present application is to solve the problems existing in the prior art, and a signal acquisition, processing and analysis method and system of particle detector array are provided.

[0005] In order to achieve the above purpose, the technical scheme adopted by the present application is as follows: a signal acquisition, processing and analysis method of particle detector array, comprising the following steps:

[0006] S1: Obtain the signal amplitude sequence of each channel in the detection channel sampling, segment the sequence according to a fixed period, extract the difference between the maximum value and the minimum value, compare the difference with the amplitude mean square fluctuation threshold, mark the signal segment in the stable range, and generate a stable sampling time section set;

[0007] S2: Call the amplitude data of the stable sampling time section set, calculate the difference ratio of adjacent time sections, compare the difference ratio with the amplitude transition rate threshold, select the channel with a monotonically increasing transition rate in the continuous time section, classify the amplitude evolution sequence as a transitionable state, and generate a channel signal transition mark table;

[0008] S3: Call the transitionable state channel in the channel signal transition mark table, extract the first excitation timestamp, select the minimum time value and record the corresponding channel number, mark the channel as the starting position of the path, and generate a path starting excitation time point record table;

[0009] S4: According to the channel number of the path starting excitation time point record table, search for adjacent channels, calculate the excitation time difference, retain the channels with a time difference within the threshold range of the critical time window and marked as a transitionable state, record the channel number and spatial position, and generate an initial path candidate channel index set.

[0010] As a further scheme of the present application, the stable sampling time section set includes the stable signal segment start time and the stable signal segment end time, the channel signal transition mark table includes the transition channel number and the channel transition state, the path starting excitation time point record table includes the starting excitation channel number and the first excitation timestamp, and the initial path candidate channel index set includes the candidate channel number and the candidate channel spatial position information.

[0011] As a further scheme of the present application, the specific steps of S1 are as follows:

[0012] S101: Obtain the signal amplitude sequence of the detection channel and segment the sequence according to a fixed period, extract the maximum value and the minimum value for each signal amplitude sequence, calculate the difference between the maximum value and the minimum value, and generate an amplitude difference sequence corresponding to the period;

[0013] S102: Based on the amplitude difference sequence, call the amplitude mean square fluctuation threshold, compare the difference with the amplitude mean square fluctuation threshold, determine the time section in which the difference does not exceed the threshold, and form a stable signal mark interval in the channel;

[0014] S103: According to the stable signal mark interval in the channel, determine the common intersection range of all channel stable intervals, record the start and end time, and generate a stable sampling time section set.

[0015] As a further scheme of the present application, the specific steps of S2 are:

[0016] S201: Call the amplitude data of the time segments in the array stable sampling time segment set, calculate the amplitude difference change between adjacent time segments, and obtain an amplitude difference ratio sequence;

[0017] S202: Compare the amplitude difference ratio sequence with the amplitude transition rate threshold value, identify the channels in the continuous time segments that exceed the threshold value, and form a channel transition trend sequence;

[0018] S203: Determine whether the difference ratio of the channels in the channel transition trend sequence is monotonically increasing, identify and mark the corresponding channels as transitionable state, and generate a channel signal transition marking table.

[0019] As a further scheme of the present application, the specific steps of S3 are:

[0020] S301: Call the transitionable state channels in the channel signal transition marking table, extract the first excitation time stamp of the channel, establish the correspondence between the channel number and the time stamp, and generate a channel excitation time mapping value;

[0021] S302: According to the channel excitation time mapping value, filter the minimum time stamp and extract the corresponding channel number, mark as the path starting position, and generate a path starting position number set;

[0022] S303: According to the path starting position number set, establish the corresponding record of the starting channel number and the excitation time stamp, and generate a path starting excitation time point record table.

[0023] As a further scheme of the present application, the specific steps of S4 are:

[0024] S401: According to the channel number in the path starting excitation time point record table, extract the excitation time point information of the corresponding adjacent channels, and according to the difference of the excitation time between the channels, obtain an excitation time difference set;

[0025] S402: Call the excitation time difference set, combine the state marking information of the corresponding channels, determine whether the excitation time difference is within the threshold range of the critical time window and the state marking meets the transitionable condition, and obtain a transition candidate channel number set;

[0026] S403: According to the transition candidate channel number set, extract the spatial position information corresponding to each channel, integrate the channel number and the spatial position, and obtain an initial path candidate channel index set.

[0027] As a further scheme of the present application, the method further comprises:

[0028] S5: calling the channel space coordinates in the initial path candidate channel index set, arranging the channel numbers in the order of firing time, extracting the angle change values of three continuous points, comparing the angle change values with the path continuous deflection angle limit value, screening the path segments with the angle change values less than the limit value as the path trunk segments, integrating the number and strike information, and generating an array path strike ordering structure;

[0029] The array path strike ordering structure comprises path channel number ordering and path trunk segment strike information.

[0030] As a further scheme of the present application, the specific steps of S5 are as follows:

[0031] S501: calling the channel space coordinates in the initial path candidate channel index set, arranging the channel numbers in the order of firing time, extracting the path included angle information formed by three adjacent points after the arrangement, and generating a channel three-point included angle sequence value;

[0032] S502: screening the path segments with the included angles less than the limit value according to the channel three-point included angle sequence value and in combination with the path continuous deflection angle limit value, and generating a path segment set satisfying the angle threshold value;

[0033] S503: integrating the channel numbers and the corresponding space strike characteristics according to the path segment set satisfying the angle threshold value, calling the corresponding space coordinate difference information, extracting the strike parameters of each path segment in the order of channel number, and generating an array path strike ordering structure.

[0034] As a further scheme of the present application, the amplitude mean square fluctuation threshold value is a standard threshold value for judging whether the fluctuation range of the signal amplitude sequence in the continuous sampling period is in a stable state, for detecting the fluctuation degree of the channel signal in the time window, and for identifying a stable amplitude response section;

[0035] The amplitude transition rate threshold value is a judgment standard for judging whether the amplitude change rate of the channel signal between adjacent time periods reaches an identifiable transition, for evaluating whether the growth amplitude of the amplitude of the channel in a short time indicates the persistence and trend of the particle excitation behavior;

[0036] The monotone increasing transition rate refers to the signal amplitude transition rate value calculated in multiple continuous time periods, which presents a continuous increasing trend and does not appear a downward fluctuation, for identifying whether the amplitude continuously increases with time, and for distinguishing the stable and rising true particle signal from the non-continuous change process disturbed by noise;

[0037] The amplitude evolution sequence refers to the sequence formed by arranging the maximum amplitude recorded by the channel in adjacent stable time periods in the particle detector array;

[0038] The critical time window threshold is an upper limit of time difference for judging whether two channels respond to the same particle event, limits the maximum range of excitation time difference between channels, and only when the excitation time difference of two channels is less than the threshold, it is considered that it belongs to the same particle path segment in time;

[0039] The path continuous deflection angle limit value is a set geometric threshold value for limiting the degree of continuous change of path direction, which is derived from the theoretical estimation of the average scattering angle of particles in the medium or the path smoothness during the design of the detector, and is set in the spatial resolution and the actual detection accuracy.

[0040] The signal acquisition, processing and analysis system of the particle detector array comprises:

[0041] The signal stable extraction module obtains the voltage signal data of the channels in the particle detector array, divides the sampling segments according to the set period, extracts the difference between the maximum value and the minimum value of each segment, and judges the difference in combination with the signal fluctuation amplitude in the segment, respectively, with the set threshold value, determines the segment that meets the conditions at the same time, marks it as a signal stable interval, and records the corresponding start and end time, generates a set of array stable sampling time segments;

[0042] The channel transition recognition module calls the amplitude information of the channels in the array stable sampling time segment set, extracts the difference between adjacent time segments, compares with the transition rate threshold, recognizes the time segment of the channel with trend change, marks the state as transitionable, and generates a channel signal transition marking table;

[0043] The path starting calibration module calls the transitionable channels in the channel signal transition marking table, extracts the first excitation time, establishes the correspondence between the channel and the time, selects the channel number with the earliest excitation time, and generates a path starting excitation time point record table;

[0044] The adjacent channel screening module calls the channel number in the path starting excitation time point record table, retrieves the channels adjacent in space structure, judges whether the excitation time difference value is within the limited range, checks the transition state mark at the same time, screens the channel number and space information that meet the conditions, and generates an initial path candidate channel index set;

[0045] The path structure construction module calls the channel coordinates in the initial path candidate channel index set, arranges the channel numbers in the order of excitation time, judges whether the angle change between three consecutive points meets the deflection limit condition in turn, screens the path segment number and arrangement order that meet the requirements, and generates an array path direction sorting structure.

[0046] Compared with the prior art, the advantages and positive effects of the present application are:

[0047] In the application, the amplitude range of the extraction channel in the fixed period is extracted, and the stable signal segment is screened, so as to realize the preliminary structured division of the array signal, the adjacent time period difference ratio is used to identify the monotone rising trend channel, the first excitation time is extracted to establish the space starting point index, and the adjacent channel excitation time difference and state screening are combined to construct the path candidate set, the direction consistent path main section is screened out through continuous angle change analysis, the high credible particle path reconstruction is completed, the multi-dimensional parameter is coordinated to improve the trajectory recognition accuracy and robustness, the particle event analysis capability is enhanced, and the noise interference misjudgment rate is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 It is a step flowchart of the application;

[0049] Figure 2 It is a step flowchart of S1 of the application;

[0050] Figure 3 It is a step flowchart of S2 of the application;

[0051] Figure 4 It is a step flowchart of S3 of the application;

[0052] Figure 5 It is a step flowchart of S4 of the application;

[0053] Figure 6 It is a step flowchart of S5 of the application;

[0054] Figure 7 It is a system module diagram of the application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical scheme and advantages of the application clearer, the application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the application and do not limit the application.

[0056] In the description of the application, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the application and simplify the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, therefore it cannot be understood as a limitation of the application. In addition, in the description of the application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0057] Please refer to Figure 1, particle detector array signal acquisition, processing and analysis method, comprising the following steps:

[0058] S1: Obtain the signal amplitude sequence of each channel in the detection channel sampling data, segment the difference value between the maximum value and the minimum value after segmentation, compare the difference value with the amplitude mean square fluctuation threshold, mark the signal segment in the stable range, record the start and end time interval, and generate the array stable sampling time segment set;

[0059] The amplitude mean square fluctuation threshold is a standard threshold for determining whether the fluctuation range of the signal amplitude sequence in the continuous sampling period is in a stable state, which is used to detect the fluctuation degree of the channel signal in the time window and identify the stable amplitude response section;

[0060] S2: Call the amplitude data of the time period in the array stable sampling time segment set, calculate the difference ratio between adjacent time periods, and compare it with the amplitude transition rate threshold, mark the channel showing a monotonic rising transition rate in the continuous time period, and classify the corresponding amplitude evolution sequence as a transition state, and generate a channel signal transition marking table;

[0061] The amplitude transition rate threshold is a judgment standard for determining whether the amplitude change rate of the channel signal between adjacent time periods reaches a recognizable transition, which is used to evaluate whether the growth amplitude of the channel amplitude in a short time indicates the persistence and trend of the particle excitation behavior;

[0062] The monotonic rising transition rate refers to the signal amplitude transition rate value calculated in multiple continuous time periods showing a continuous increasing trend, and no downward fluctuation, which is used to identify whether the channel has a phenomenon of continuously increasing amplitude with time, and to distinguish between stable rising true particle signals and non-continuous change processes disturbed by noise;

[0063] The amplitude evolution sequence refers to the sequence formed by arranging the maximum amplitude recorded by the channel in adjacent stable time periods in the particle detector array;

[0064] S3: Call the channel in the channel signal transition marking table marked as a transition state, extract the corresponding first excitation timestamp, select the minimum time value and record the corresponding channel number, mark the channel as the starting position of the path, establish the correspondence between the channel number and the excitation time, and generate a path starting excitation time point record table;

[0065] S4: According to the channel number in the path starting excitation time point record table, retrieve the adjacent channel and calculate the excitation time difference, select the channel within the critical time window threshold and marked as a transition state, record the number and spatial position information, and generate an initial path candidate channel index set;

[0066] The critical time window threshold is an upper limit of time difference for judging whether two channels respond to the same particle event, which limits the maximum range of excitation time difference between channels, and only when the excitation time difference between two channels is less than the threshold, it is considered that they belong to the same particle path segment in time;

[0067] S5: calling the channel spatial coordinates in the initial path candidate channel index set, arranging the channel numbers in the order of excitation time, extracting the angle change value of three consecutive points, comparing it with the path continuous deflection angle limit value, screening the path segment with an angle change less than the limit value as the path main segment, integrating the number and strike information, and generating an array path strike ordering structure;

[0068] The path continuous deflection angle limit value is a set geometric threshold value, which is used to limit the continuous change degree of path direction, and is derived from the theoretical estimation of average scattering angle or path smoothness of particles in medium during the design of detector, and is set in spatial resolution and actual detection accuracy.

[0069] The array stable sampling time section set includes stable signal segment start time and stable signal segment end time, the channel signal transition mark table includes transition channel number and channel transition state, the path start excitation time point record table includes start excitation channel number and first excitation time stamp, the initial path candidate channel index set includes candidate channel number and candidate channel spatial position information, and the array path strike ordering structure includes path channel number ordering and path main segment strike information.

[0070] Please refer to Figure 2 , the specific steps of S1 are as follows:

[0071] S101: obtaining the signal amplitude sequence of the detection channel and segmenting it according to a fixed period, extracting the maximum value and the minimum value of each signal amplitude sequence respectively, calculating the difference between the maximum value and the minimum value, and generating an amplitude difference sequence corresponding to the period;

[0072] In the acquisition of the detection channel signal, the continuous signal amplitude sequence is first segmented according to the set period. Taking a single channel in an array radar as an example, if the sampling period is 1 millisecond and the total sampling time is 10 seconds, 10000 amplitude data will be generated. After setting the segmentation period to 100 milliseconds, it is equivalent to containing 100 consecutive sampling points in each segment. In each segment of data, the linear scanning method is used to compare the amplitude values of each sampling point in turn, and the maximum and minimum values are obtained. For example, if a segment of sampling data contains values of 3.1, 2.8, 3.6, 4.0, 2.7, etc., the maximum value is 4.0 and the minimum value is 2.7, and the amplitude difference is 1.3. After processing all the segments in turn, a sequence composed of the difference values is formed. For example, if the total number of segments is 100, 100 difference values are obtained, forming an amplitude difference value sequence with a length of 100. The difference value sequence is an important input reference for subsequent judgment of the signal fluctuation range, and can also be used to evaluate the stability characteristics of the signal in the detection channel at different time periods.

[0073] S102: Based on the amplitude difference value sequence, call the amplitude mean square fluctuation threshold, compare the difference value with the amplitude mean square fluctuation threshold, judge the time period when the difference value does not exceed the threshold, and form the stable signal marking interval in the channel;

[0074] On the basis of the existing amplitude difference value sequence, the stability characteristics of the signal need to be further extracted. First, evaluate the fluctuation degree of each segment of difference value. The deviation value between the mean value of the entire sequence and each segment of difference value can be squared and summed, and the square root result after averaging can be taken as the reference fluctuation value. Taking actual numerical values as an example, suppose the difference value sequence contains 1.0, 1.2, 0.9, 1.1, 1.3, the overall mean value is 1.1, and the deviation value of each segment from the mean value is -0.1, 0.1, -0.2, 0, and 0.2. Square each deviation value, add them up, and then divide by the number of segments to obtain a value reflecting the fluctuation amplitude. Set this value multiplied by a coefficient of 1.5 as the threshold. If the deviation degree of a certain segment of difference value from the overall mean value is less than the threshold, it is considered that the signal in this segment is stable. Process all difference segments in turn, find all time periods that meet the stability condition, and record the start and end times. For example, if the difference values of the last 5 segments are all within the set range, it indicates that the time interval covered is a stable signal interval, such as from the 3rd segment to the 7th segment, which corresponds to a time of 0.2 seconds to 0.7 seconds.

[0075] S103: According to the stable signal marking interval in the channel, determine the common intersection range of all channel stable intervals, record the start and end times, and generate an array stable sampling time segment set;

[0076] After obtaining the stable signal interval within each channel, it is necessary to further determine the intersection intervals between different channels to identify the time range within which all channels are in a stable state within the same time period. Taking three channels as an example, the following time periods are marked as stable states: the first channel is in the ranges of 0.1 to 0.5 seconds and 0.7 to 1.2 seconds, the second channel is in the range of 0.3 to 0.9 seconds, and the third channel is in the range of 0.4 to 1.1 seconds. By comparing the start and end times of each time period, their common parts are found. That is, the start time of each intersection is the maximum value among the start times of each segment, and the end time is the minimum value among the end times of each segment. If the start time is earlier than the end time, the intersection is valid. According to the above rules, two intersection time periods can be obtained, namely 0.4 to 0.5 seconds and 0.7 to 0.9 seconds. These two time periods are the effective time intervals for common stable sampling in the multi-channel system. The results can be recorded for subsequent multi-channel signal joint processing or consistency analysis applications.

[0077] Please see Figure 3 The specific steps of S2 are as follows:

[0078] S201: Call the amplitude data of the time period in the array stable sampling time segment set, calculate the amplitude difference change between adjacent time periods, and obtain the amplitude difference ratio sequence;

[0079] The specific formula for calculating the change in amplitude difference between adjacent time periods is as follows:

[0080] ;

[0081] Calculate the amplitude difference ratio sequence;

[0082] in, Representing the The ratio of the amplitude difference between a given time period and its subsequent time period. Representing the The amplitude over a time period, Representing the The amplitude over a time period, Representing the The variance of the original amplitude set over a given time period. Represents all The arithmetic mean of the amplitude over a time period Representing the The amplitude over a time period, Represents the total number of time periods. The time period number;

[0083] The amplitude data is sampled by array seismic acceleration sensor for a stable time period, with a sampling frequency of 100 Hz per second. In the signal monitoring with a total duration of 10 seconds, 1000 groups of amplitude data are collected. The amplitude unit is m / s2, and the data comes from the Y-axis direction component of the first channel in the array structure. In data segmentation, the time period is set to divide 1 segment every 500 ms, a total of 20 segments (n=20), with 50 amplitude data in each segment.

[0084] The i=7th segment is processed, and the involved parameter calculation is as follows:

[0085] And Calculation method:

[0086] The 7th segment amplitude set is:

[0087] ;

[0088] There are 50 items

[0089] The mean value of the amplitude of this segment is obtained by taking the mean value of the amplitude of this segment , using the formula:

[0090] ;

[0091] The mean value of the amplitude of the 8th segment is m / s2, which is obtained by statistical calculation by the data center calculation module.

[0092] Calculation method (7th segment variance):

[0093] The statistical variance formula is used for calculation:

[0094] ;

[0095] Calculation method:

[0096] The mean value of the amplitude of each segment in the total of 20 segments is calculated by sampling average to obtain 20 segment mean values, and the summary average value is:

[0097] ;

[0098] Calculation method:

[0099] The sum of the deviations of the mean values of all segments from the overall mean value is:

[0100] ;

[0101] Then the average absolute deviation is:

[0102] ;

[0103] Substitute the parameters into the formula for calculation:

[0104] First, calculate the difference term:

[0105] ;

[0106] Calculate the dimensionless radical term:

[0107] ;

[0108] The part in parentheses is:

[0109] ;

[0110] Denominator part:

[0111] ;

[0112] Finally, substituting into the formula, we get:

[0113] ;

[0114] The results indicate that the amplitude difference between two adjacent time periods, after standardization correction, is 0.001913 m / s². The numerical result is a corrected expression of the original difference amplitude after being weighted by the dimensionless variance ratio and the mean deviation, representing the intensity index of amplitude change between adjacent segments. This intensity index will be recorded as an item in the amplitude difference ratio sequence in subsequent steps for wave pattern identification or structural anomaly analysis.

[0115] The calculation logic in the formula is based on a composite quantification approach to the intensity of amplitude changes. First, it calculates the difference between the mean amplitude values ​​of two adjacent time periods. The most basic time series change is extracted, and this difference serves as the fundamental term for the intensity of change. To enhance the response of this term to data stability and overall volatility, two dimensionless normalization correction factors are introduced and multiplied together, where the first term is... The first term measures the degree of amplitude fluctuation within the current time period, i.e., the ratio of standard deviation to amplitude. This structure introduces square root calculation to reduce the nonlinear amplification of the overall ratio by extreme fluctuations, while maintaining directionality; the second term is... This represents the average deviation of the amplitude across all time periods relative to the overall average, i.e., the global absolute deviation rate. It reflects whether the overall time series is stable or dispersed. The sum of these two terms forms a combined weighting of local volatility and global deviation. Finally, this weighting is multiplied by the original amplitude difference to construct a composite change index, which is then divided by... The relative amplitude normalization processing is performed to eliminate the influence of the amplitude level of the current time period on the change intensity, and to ensure that the output result reflects the true change trend rather than being affected by the absolute value offset. The overall logic is completed by the difference, multiplication, square root, addition, and normalization structure to extract the change intensity expression with levels;

[0116] The amplitude difference ratio sequence is a sequential numerical index constructed for the signal amplitude change characteristics in consecutive time periods, aiming to quantitatively express the change trend, change amplitude, and relative significance between adjacent time period amplitudes. Each element in the sequence is formed by the average amplitude difference between adjacent time periods, local volatility, overall dispersion, and relative level normalization factor, which can ensure sensitive response to instantaneous differences while suppressing false judgments caused by noise or overall offset. Through sequencing arrangement, the ratio sequence exhibits a dynamic and continuous change pattern between time periods, which can be used to further identify mutation segments, abnormal fluctuations, structural disturbance signals, or continuous change trends, providing data support for signal interpretation and structural health monitoring.

[0117] S202: Based on the amplitude difference ratio sequence and the amplitude transition rate threshold, the channels in the consecutive time periods exceeding the threshold are identified, and a channel transition trend sequence is formed;

[0118] Using the generated difference ratio sequence, combined with the preset amplitude transition rate threshold, the channel transition is preliminarily determined. First, the threshold value is set, which generally uses the statistical characteristics in the difference ratio sequence as the basis, such as the mean and standard deviation of all ratios. The threshold is set to the mean plus twice the standard deviation, for example, the mean is 3.5%, and the standard deviation is 1.5%, then the threshold is 6.5%. Then compare the difference ratio between each time period, if a certain segment ratio is greater than 6.5%, the channel corresponding to the time period is preliminarily determined as transition state. In continuous detection, if a channel exceeds the threshold in multiple consecutive time periods, for example, a channel is 7.0% and 8.3% in the second and third segments respectively, it is considered that the channel has a transition trend in the corresponding period, forming a channel transition trend sequence, such as marked as 0, 1, 1, 0, i.e. the second and third segments transition, the first and fourth segments do not transition. The trend sequence is generated by sequentially traversing the ratio sequence of each channel. In the process, each ratio and threshold are compared and the judgment result is recorded. Finally, the trend data classified by channel number is constructed, which can be used as input for further signal change analysis in subsequent steps.

[0119] S203: For the channel transition trend sequence, determine whether the difference ratio of the channel is monotonically increasing, identify and mark the corresponding channel as a transitionable state, and generate a channel signal transition marker table;

[0120] Based on the generated channel transition trend sequence, further judge the ratio change of the continuous transition part, the judgment standard is whether the difference ratio presents a monotone increasing trend, that is, the next ratio is greater than the previous ratio, for example, the difference ratio of a certain channel continuous transition segment is 5.5%, 6.3%, 7.2%, which meets the monotone increasing condition, this channel can be marked as transition state, in the judgment, first extract all the time segments marked as transition, and record the corresponding ratio in order, then compare the adjacent ratios one by one to see if they meet the increasing requirement, each transition trend is checked once in this way, if there is a non-increasing ratio in the sequence, the channel does not meet the transition condition, this processing method avoids misjudgment caused by temporary and random changes, when judging, the ratio can be scaled to the percentage range before normalization to improve the comparability of trends between different channels, for example, the average amplitude of a certain channel in the fifth to seventh segments is 1.1, 1.3 and 1.6 respectively, the difference is 0.2 and 0.3, the ratio is 15.4% and 18.7% respectively, which is an increasing trend, and can be included in the signal transition marking table, which records the channel number, transition start and end segment, ratio sequence and whether it is increasing, etc. fields, the channel state results are batch screened through the judgment rule, and a structured output is formed for subsequent use.

[0121] Please refer to Figure 4 , the specific steps of S3 are:

[0122] S301: Call the transition state channel in the channel signal transition marking table, extract the first excitation timestamp of the channel, establish the correspondence between the channel number and the timestamp, and generate the channel excitation time mapping value;

[0123] When calling the transition state channel in the channel signal transition marking table, the pre-recorded marking table needs to be read first, which records the level change of each channel in each sampling period, indicating whether there is a transition state from low to high or from high to low. In engineering implementation, a sampling module with a precision of microseconds is usually used to collect the state of each channel at fixed intervals. For example, assuming that the total number of channels is 4, numbered T1 to T4, the sampling period is set to 10 μs, and the state sequence of the corresponding channels is as follows: T1 changes in the 3rd period, T2 changes in the 5th period, T3 changes in the 1st period, and T4 does not change. When reading the data, the level values of the current sampling point and the previous sampling point are compared in order for each channel sampling result, and if they are different, it is determined that a transition has occurred. The time of the first transition and the channel number are paired to form a mapping table. For example, for T1, the first transition occurs at the 3rd sampling point, which is converted to 30 μs, and is paired with T1 to form a key-value pair, the result is T1 corresponds to 30 μs, T2 corresponds to 50 μs, T3 corresponds to 10 μs, and T4 is not included. After processing each channel, a complete excitation time mapping record table is formed, which records the correspondence between the channel number and the first transition time, which is called by the subsequent steps.

[0124] S302: According to the channel trigger time mapping value, the minimum timestamp is screened and the corresponding channel number is extracted, which is marked as the path starting position, and the path starting position number set is generated;

[0125] According to the generated channel trigger time mapping value, the minimum timestamp is found, and all time values are screened to find the minimum value and obtain the corresponding channel number. If the minimum value is unique, only the channel number is retained; if there are multiple channels corresponding to the same minimum timestamp, all of them are included in the starting channel number set. For example, when the mapping table is T1 corresponding to 30μs, T2 corresponding to 50μs, and T3 corresponding to 10μs, the minimum value is 10μs, corresponding to T3, and the starting number set is T3. If T1 and T2 are both 10μs, the starting number set includes T1 and T2. In the execution, each item in the mapping record is traversed, and the time value is compared with the current minimum record value. If it is smaller than the current value, it is replaced; if it is equal to the current value, it is added to the number set. Finally, the path starting number set is generated, which provides basic input for subsequent path time record.

[0126] S303: According to the path starting position number set, the corresponding record of the starting channel number and the trigger timestamp is established, and the path starting trigger time point record table is generated;

[0127] According to the path starting position number set, the corresponding trigger time value is read, and the channel number and trigger time are paired to form a time record table by searching the generated trigger time mapping record. For example, the path starting number set contains T1 and T2, and the corresponding trigger times are 10μs and 10μs respectively. Two records are generated in the record table: one is T1 and 10μs, and the other is T2 and 10μs. In the execution process, the path starting number set is sequentially traversed, and the time value in the mapping table is found according to the number, and the result table is written in order, finally forming a clear corresponding relationship between the starting channel number and the timestamp. The record table is used as input basis in subsequent channel path construction, time sequence analysis, data alignment and other modules.

[0128] Please refer to Figure 5 , the specific steps of S4 are:

[0129] S401: According to the channel number in the path starting trigger time point record table, the trigger time point information of the corresponding adjacent channel is extracted, and the trigger time difference set is obtained according to the difference of the trigger time between channels;

[0130] The path starting excitation time point record table needs to correspond to the excitation time point one by one for each channel number, and the excitation data of each channel is saved in the form of a unified format timestamp, such as the time point corresponding to channel 3 is 107.1 ms, the adjacent channel numbers need to be determined, for example, channel 2 and channel 4, and the excitation time points thereof are 106.3 ms and 108.0 ms respectively, the excitation time difference between channel 3 is calculated, and the difference values are 0.8 ms and 0.9 ms respectively, all the calculated time difference values are uniformly formed into a set for subsequent operation. The excitation time record should be expressed in high-precision units, and it is recommended to be converted into nanosecond format and stored as unsigned integer value. Each channel information should be uniformly managed in a structured manner, including channel number, excitation time value and identification information whether valid. In the monitoring of industrial equipment vibration signals, if channel 3 is the current excitation source point, the excitation time of the adjacent channels is close, which indicates that there may be a possible path jump basis, and these time difference values need to be extracted for further judgment. In this process, the excitation time data can come from the continuous recording buffer of the data collector, the system sets the logical scanning interval to 2 ms range, and all adjacent channels falling into this time window participate in the time difference value calculation, and through the automatic processing process, all channel combinations meeting the conditions are traversed in turn to form a standardized time difference data set for subsequent judgment.

[0131] S402: Call the excitation time difference value set, combine the state marker information of the corresponding channel, judge whether the excitation time difference value is within the critical time window threshold range, and the state marker meets the transition condition, obtain the transition candidate channel number set;

[0132] After the formation of the set of excitation time difference values, the channel state information corresponding to each difference value needs to be cross-compared to extract the current state of each pair of channels, including three types of labels: "active state", "transition state", or "shield state". The channel state is obtained one by one by consulting the state label table, and it is judged whether it meets the set transition condition. The basis for judging the time difference value is whether it is less than the set threshold of the critical time window. For example, if the threshold is set to 1.5 ms, only when the time difference between a pair of channels is less than this value, and both channels are in the active or transition state, it is determined that the channel has the possibility of transition. In the internal structure monitoring of large equipment, if the time difference between channel 2 and channel 3 is 0.8 ms and the channel state is active, and the time difference between channel 3 and channel 4 is 0.9 ms and channel 4 is in the transition state, then channel 2 and channel 4 are both included in the candidate channel set. In the specific implementation, the setting of the threshold of the critical time window can be determined according to the system sampling rate. If the sampling frequency is 1000 Hz, it is recommended to set the threshold to 1.5 times the sampling period, i.e. 1.5 ms, and to fine-tune according to the actual scene. In a multi-region channel layout system, different regions can be set with different weights. For example, one region has a weight of 60% and a threshold of 1.2 ms, and another region has a weight of 40% and a threshold of 1.5 ms. The combined threshold is obtained by weighted averaging, and the difference value less than the average value is marked as a candidate transition channel, and finally the transition channel number set is formed for subsequent processing.

[0133] S403: According to the transition candidate channel number set, the spatial position information corresponding to each channel is extracted, the channel number and the spatial position are integrated, and the initial path candidate channel index set is obtained;

[0134] After the transition channel number set is formed, the spatial position information of each channel in it needs to be further extracted. This information comes from the mapping table between channel numbers and three-dimensional coordinates. The table records the specific position of each channel in the actual space. For example, channel 2 corresponds to coordinates of 10.2 in the horizontal direction, 5.1 in the vertical direction, and 0.0 in the vertical direction. Channel 4 has coordinates of 10.6 in the horizontal direction, 5.3 in the vertical direction, and 0.0 in the vertical direction. All channel numbers and their corresponding coordinates form index items, each of which contains a channel number and three-axis coordinates. By calling the data structure for quick retrieval and combination, the initial path candidate channel index set is generated. In the monitoring scene of mine structure layout, multiple channels are arranged equidistantly along the mine, and the numbers are arranged in spatial order. Through the above method, the suspicious path trend can be quickly located in the adjacent time transition, thereby completing the pre-screening of the subsequent path direction. The spatial coordinate information of each channel can be imported by three-dimensional scanning or modeling during the initial deployment stage of the system. The mapping table is managed in a structured configuration manner, and the coordinate calling is performed in combination with the number index in the path recognition stage. Finally, a path candidate data set with spatial reference is formed for the path deduction module.

[0135] Please refer to Figure 6The specific steps of S5 are as follows:

[0136] S501: Call the channel spatial coordinates in the initial path candidate channel index set, sort the channel numbers according to the excitation time, extract the path angle information formed by three adjacent points after sorting, and generate the channel three-point angle sequence value.

[0137] The specific calculation formula for sorting the channel numbers based on the excitation time is as follows:

[0138] ;

[0139] Calculate the difference in ranking energy levels Extract the path angle information formed by three adjacent points after sorting, and generate the channel three-point angle sequence value;

[0140] in, Represents channel number Energy level difference values ​​in excitation time ordering Representing the and Energy exchange coefficient between channels Representative Channel and Spatial distance between them and Representing the first and The timing of channel activation represent The channel's output per unit time Average energy value injected into the channel. This represents the minimum temporal resolution in the excitation time series. The total number of all channels;

[0141] parameter This represents the average energy exchange value between channel i and channel j within a unit acquisition cycle. It is calculated by integrating the voltage and current changes at the channel nodes and using the equivalent electrical work calculation formula. The sensor sampling frequency is 1000Hz, the sampling time period is 1 second, the average voltage between channels i and j is 2.1V, and the average current is 0.015A. The energy value obtained is:

[0142] ;

[0143] parameter The distance between the spatial geometric centers of channels i and j is represented by a laser ranging system. This system has a three-dimensional measurement accuracy of ±0.1mm, and the three-dimensional coordinate differences of the spatial points are Δx=0.8m, Δy=0.6m, and Δz=0.3m. The spatial distance is calculated as follows:

[0144] ;

[0145] Parameter denotes the excitation time difference between channel j and channel i, which is recorded by the system clock synchronized event trigger recording, using high-resolution timestamp recording module, with minimum time accuracy of 1 μs, and the energy input value of channel j to channel i in unit sampling interval is obtained by , , and the formula is:

[0146] ;

[0147] Parameter denotes the minimum time resolution of the system, which depends on the hardware sampling interval, and in the present system , i.e. 1 μs;

[0148] Parameter denotes the energy input value of channel j to channel i in unit sampling interval, which is obtained by equidistant segmented integration of the energy cumulative value through inter-channel data interaction, and the system records the energy change amount between t=2 s and t=2.01 s , with a sampling frequency of 10000 Hz and 10000 points, taking each time interval as second, and the average energy is:

[0149] ;

[0150] Substitute all parameters into the formula and expand the specific operation as follows:

[0151] First, calculate the normalized time difference

[0152] ;

[0153] First term:

[0154] ;

[0155] ;

[0156] ;

[0157] Second term:

[0158] ;

[0159] Difference value calculation:

[0160]

[0161] Since the value of m is 1 (only one adjacent channel is calculated), the formula summation can be simplified as:

[0162] ;

[0163] The results show that the channel i is affected by the channel j in the ordering process to form a weighted energy difference weight of 0.000601668, which is input as the ordering energy level difference value of channel i, used for comparing the size with other channels to determine the priority of the channel, the larger the value, the stronger the modulation effect of channel j on channel i in the excitation-energy transmission path, and the priority should be improved. After all subsequent channels are calculated, the channel index table is obtained by ascending order according to the value sequence, and the path angle generation step is entered;

[0164] The ordering energy level difference value constructed in the formula is weighted and controlled by the complex relationship between energy and space, time factors between channels. The ratio between energy parameters and distance reflects the energy distribution density per unit distance, which describes the strength of energy transmission between channels, which is multiplied by the reciprocal of the time difference normalization value to introduce the adjustment effect of the excitation time difference on the energy transmission strength; the time difference is normalized by squaring and then taking the square root to convert it into a positive impact, ensuring that the value is positive and has a distance-aware decay trend, and the square root operation mathematically represents a nonlinear weakening of the time offset at a distance. The in the other term represents the energy input per unit time, which reflects the direct excitation efficiency of channel j to i, which is weakened by the product of the spatial distance and time normalized difference between channels, forming a strengthening effect on high-efficiency input in the near field, and the two structures form a complementary excitation control mechanism. In the overall structure, the difference between the two is processed by subtraction to extract the energy efficiency difference between excitation and reception in different dimensional structures, and the difference is encapsulated by absolute value to form a non-negative ordering index, ensuring that all channel ordering values are comparable as a basis for subsequent ordering;

[0165] The ordering energy level difference value represents the ordering reference index of a channel relative to its associated channels in a multi-channel excitation response system under the comprehensive action of excitation time, spatial position, and energy exchange ability in multiple dimensions. The larger the value, the stronger the energy transmission relationship between the channel and the surrounding channels at the current excitation time, the closer the response time, and the more significant the spatial coupling effect, with higher path participation and conduction dominance; the smaller the value, the more the channel is in a relative edge or delay state in the excitation propagation path, and the weaker the excitation degree. The difference value quantifies the complex relationship between energy, trigger timing, and spatial occupation of the channel in the network structure, used for channel priority ordering, guiding subsequent path structure construction and feature extraction.

[0166] S502: According to the sequence of channel three-point angle values, combined with the path continuous deflection angle limit value, the path segments with angles less than the limit value are screened to generate a path segment set that meets the angle threshold;

[0167] After the sequence of angle values is formed, it needs to be screened in combination with the path continuous deflection angle limit value. The limit value can be analyzed from historical scanning data and set to 90 degrees, which is a common scheme. This value serves as a reference for judging whether the deflection angle is too large. Each angle record is read in turn and compared with the limit value. If the angle is less than 90 degrees, it will be considered that the deflection degree is too large and should be excluded from the candidate path segment. For example, the angle values are 166 degrees, 120 degrees, 85 degrees, 55 degrees, and 22 degrees. Among them, the three values below 85 degrees are excluded because they are below the limit value, and only the part greater than or equal to 90 degrees is retained, leaving two path segments. Each qualified path segment saves the three-point channel number and coordinate information and is arranged into a path segment set for subsequent path structure integration. The path segments in this set have the common characteristic that the direction change of adjacent three channels is within the allowed range, which facilitates the formation of a continuous and smooth path chain suitable for signal transmission simulation or array scanning reconstruction and other practical scenarios.

[0168] S503: According to the path segment set that meets the angle threshold, integrate the channel numbers and corresponding spatial orientation characteristics, call the corresponding spatial coordinate difference information, extract the orientation parameters of each path segment in order of channel number, and generate an array path orientation ordering structure;

[0169] The path segment set that meets the angle threshold will be used as the basis for subsequent channel orientation ordering. Each path segment contains three channel numbers and their corresponding coordinates, which need to be used to extract the direction orientation difference between channels. The direction orientation is usually determined by the horizontal and vertical coordinate difference between two points, such as the coordinates 12,7 and 10,5 corresponding to channel numbers 2 and 1. The direction is approximately left down, compared with the orientation between 1 and 3. If the direction change is small, it can be considered as good continuity. In this way, the angle change of two direction segments in each path is extracted to form the orientation description of each path segment. The path segment numbers are arranged in order of channel number and combined into a structure body form. Each structure body contains the starting number, the ending number, and the path direction characteristics. These structure bodies are arranged in order to form an array path orientation ordering structure. This structure helps to analyze the spatial orientation continuity between channels. In signal processing, beam forming, or array simulation analysis, the starting and ending numbers and direction information of each path segment can be quickly called through this structure to assist in path planning or echo reconstruction operations.

[0170] Please refer to Figure 7 , a signal acquisition, processing and analysis system of a particle detector array, comprising:

[0171] The signal stable extraction module obtains voltage signal data of channels in the particle detector array, divides sampling sections according to a set period, extracts a difference between a maximum value and a minimum value of each section, and combines a signal fluctuation amplitude in the section to respectively judge the set threshold, determines a section that simultaneously satisfies the conditions, marks the section as a signal stable interval, and records corresponding start and end times to generate an array stable sampling time section set;

[0172] The channel transition recognition module calls amplitude information of the channels in the array stable sampling time section set, extracts a difference between adjacent time sections, compares the difference with a transition rate threshold, recognizes a channel time section that has a trend change, marks a state as being transitable, and generates a channel signal transition marking table;

[0173] The path start calibration module calls transitable channels in the channel signal transition marking table, extracts a first excitation time, establishes a correspondence between the channels and the time, filters channel numbers with the earliest excitation time, and generates a path start excitation time point record table.

[0174] The adjacent channel filtering module calls channel numbers in the path start excitation time point record table, searches for adjacent channels in a spatial structure, judges whether an excitation time difference is within a limited range, simultaneously checks a transition state marking, filters channel numbers and spatial information that satisfy the conditions, and generates an initial path candidate channel index set.

[0175] The path structure construction module calls channel coordinates in the initial path candidate channel index set, arranges channel numbers in an excitation time order, judges whether an angle change between three consecutive points satisfies a deflection limit condition, filters path section numbers and arrangement orders that meet the requirements, and generates an array path direction sorting structure.

[0176] The above is only a preferred embodiment of the present application, and does not limit the present application in other forms. Any person skilled in the art can modify or change the above disclosed technical content to equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification made according to the technical essence of the present application to the above embodiments still belong to the protection scope of the present application technical solution.

Claims

1. A method of signal acquisition, processing and analysis of a particle detector array, characterized in that, The method comprises the following steps: S101: acquiring a signal amplitude sequence of a detection channel and segmenting the signal amplitude sequence according to a fixed period, extracting a maximum value and a minimum value from each segmented signal amplitude sequence, calculating a difference value between the maximum value and the minimum value, and generating an amplitude difference value sequence corresponding to the period; S102: based on the amplitude difference value sequence, calling an amplitude mean square fluctuation threshold value, comparing the difference value with the amplitude mean square fluctuation threshold value, judging a time period in which the difference value does not exceed the amplitude mean square fluctuation threshold value, and forming a stable signal marking interval in the channel; S103: determining a common intersection range of stable intervals of all channels according to the stable signal marking interval in the channel, recording start and end time, and generating a stable sampling time interval set of the array; S201: calling amplitude data of a time period in the stable sampling time interval set of the array, calculating amplitude difference variation between adjacent time periods, and obtaining an amplitude difference ratio sequence; The specific calculation formula of the amplitude difference variation between adjacent time periods is: ； calculating the amplitude difference ratio sequence; wherein, represents the amplitude difference between the first time period and the following time period, represents the amplitude of the first time period, represents the amplitude of the first time period, represents the variance of the original amplitude set within the first time period, represents the arithmetic mean of the amplitudes of all time periods, represents the amplitude of the first time period, represents the total number of time periods, is the time period number; S202: comparing the amplitude difference ratio sequence with an amplitude transition rate threshold value, identifying a time period in which the amplitude difference ratio exceeds the amplitude transition rate threshold value in a continuous time period, and forming a channel transition trend sequence; S203: judging whether the difference ratio of the channel is monotonously increasing according to the channel transition trend sequence, identifying and marking the corresponding channel as a transitionable state if the monotonous increasing condition is met, and generating a channel signal transition marking table; S3: calling the transitionable state channel in the channel signal transition marking table, extracting a first excitation time stamp, screening a minimum time value and recording a corresponding channel number, marking the channel as a path starting position, and generating a path starting excitation time point recording table; S4: according to the channel number of the path starting excitation time point recording table, searching adjacent channels, calculating the excitation time difference between the path starting excitation time and the adjacent channel excitation time, retaining the channels with a time difference within a critical time window threshold value and marked as a transitionable state, recording the channel number and the spatial position, and generating an initial path candidate channel index set.

2. The method of signal acquisition, processing and analysis of a particle detector array according to claim 1, characterized in that, The stable sampling time interval set of the array comprises a stable signal segment start time and a stable signal segment end time, the channel signal transition marking table comprises a transition channel number and a channel transition state, the path starting excitation time point recording table comprises a starting excitation channel number and a first excitation time stamp, and the initial path candidate channel index set comprises a candidate channel number and candidate channel spatial position information.

3. The method of signal acquisition, processing and analysis of a particle detector array according to claim 1, characterized in that, The specific steps of S3 are as follows: S301: calling the transitionable state channel in the channel signal transition marking table, extracting a first excitation time stamp of the channel, establishing a corresponding relationship between the channel number and the time stamp, and generating a channel excitation time mapping value; S302: according to the channel excitation time mapping value, screening a minimum time stamp and extracting a corresponding channel number, marking as a path starting position, and generating a path starting position number set; S303: according to the path starting position number set, establishing a corresponding record of the starting channel number and the excitation time stamp, and generating a path starting excitation time point recording table.

4. The method of signal acquisition, processing and analysis of a particle detector array according to claim 3, characterized in that, The specific steps of S4 are as follows: S401: According to the channel number in the path starting excitation time point record table, the excitation time point information of the corresponding adjacent channel is extracted, and the excitation time difference value set is obtained according to the excitation time difference between channels; S402: The excitation time difference value set is called, combined with the state mark information of the corresponding channel, whether the excitation time difference value is in the critical time window threshold range, and the state mark meets the transition condition, to obtain the transition candidate channel number set; S403: According to the transition candidate channel number set, the spatial position information corresponding to each channel is extracted, the channel number and spatial position are integrated, and the initial path candidate channel index set is obtained.

5. The method of signal acquisition, processing and analysis of a particle detector array according to claim 4, characterized in that, The method further comprises: S5: The channel spatial coordinates in the initial path candidate channel index set are called, the channel numbers are arranged in order of excitation time, the angle change values of three consecutive points are extracted, compared with the path continuous deflection angle limit value, the path segments with angle change less than the limit value between three consecutive points are selected as the path main stem, and the number and strike information are integrated to generate an array path strike ordering structure; The array path strike ordering structure comprises path channel number ordering and path main stem strike information.

6. The method of signal acquisition, processing and analysis of a particle detector array according to claim 5, wherein, The specific steps of S5 are: S501: The channel spatial coordinates in the initial path candidate channel index set are called, the channel numbers are arranged in order of excitation time, the path included angle information formed by three adjacent points after ordering is extracted, and a channel three-point included angle sequence value is generated; S502: According to the channel three-point included angle sequence value, combined with the path continuous deflection angle limit value, the path segments with included angle less than the limit value are screened to generate a path segment set satisfying the angle threshold value; S503: According to the path segment set satisfying the angle threshold value, the channel number and the corresponding spatial strike characteristics are integrated, the corresponding spatial coordinate difference value information is called, the strike parameters of each path segment are extracted in order of channel number, and an array path strike ordering structure is generated.

7. The method of signal acquisition, processing and analysis of a particle detector array according to claim 1, wherein, The fixed period refers to the time unit of time window division for continuous data in the signal sampling process, and the specific period length is set according to the working frequency and response speed of the detector; The amplitude mean square fluctuation threshold is used to judge whether the fluctuation range of the signal amplitude sequence in the continuous sampling period is within the amplitude mean square fluctuation threshold that can be considered as a stable state, to detect the fluctuation degree of the channel signal in the time window, and to identify the stable amplitude response section; The amplitude transition rate threshold is used to judge whether the amplitude change rate of the channel signal between adjacent time periods reaches the identifiable transition determination standard, to evaluate whether the amplitude of the channel increases in a short time to indicate the persistence and trend of particle excitation behavior; The transitionable state refers to the judgment condition that the amplitude change of the channel in multiple continuous time periods satisfies the monotone increasing trend, and the state is determined by the difference ratio sequence and the amplitude transition rate threshold: when the difference ratio of a channel in at least two adjacent time periods continuously rises and exceeds the amplitude transition rate threshold, the channel is marked as "transitionable". The monotonous increasing transition rate refers to a continuously increasing trend of the signal amplitude transition rate value calculated by the channel in multiple continuous time periods, and no downward fluctuation occurs, which is used to identify whether the amplitude continuously increases over time, and distinguish between stable rising real particle signals and non-continuous change processes disturbed by noise; The amplitude evolution sequence refers to a sequence formed by arranging the maximum amplitudes recorded by the channel in adjacent stable time periods over time in the particle detector array; The critical time window threshold is an upper limit for judging whether two channels respond to the same particle event, which limits the maximum range of the excitation time difference between the channels, and only when the excitation time difference between two channels is less than the critical time window threshold, it is considered that they belong to the same particle path segment in time; The path continuous deflection angle limit value is a set geometric threshold value used to limit the degree of continuous change of the path direction, which is derived from the theoretical estimation of the average scattering angle of particles in the medium or the path smoothness during the design of the detector, and is jointly set in the spatial resolution and actual detection accuracy.

8. A signal acquisition, processing and analysis system for a particle detector array, characterised in that, The signal acquisition, processing and analysis method of the particle detector array according to any one of claims 1-7, the system comprises: A signal stable extraction module acquires the voltage signal data of the channel in the particle detector array, divides the sampling section according to the set period, extracts the difference between the maximum value and the minimum value of each section, and judges the difference in combination with the signal fluctuation amplitude in the section, respectively, with the amplitude mean square fluctuation threshold, determines the section that meets the conditions at the same time, marks it as a signal stable interval, and records the corresponding start and end time, to generate an array stable sampling time section set; A channel transition identification module calls the amplitude information of the channel in the array stable sampling time section set, extracts the difference between adjacent time periods, compares it with the amplitude transition rate threshold, identifies the time period of the channel with a trend change, marks the state as transitable, and generates a channel signal transition marking table; A path starting calibration module calls the transitable channel in the channel signal transition marking table, extracts the first excitation time, establishes the correspondence between the channel and the time, selects the channel number with the earliest excitation time, and generates a path starting excitation time point record table; An adjacent channel screening module calls the channel number in the path starting excitation time point record table, retrieves the adjacent channels in the spatial structure, judges whether the excitation time difference value is within the limited range, and checks the transition state mark at the same time, screens the channel numbers and spatial information that meet the conditions, and generates an initial path candidate channel index set; A path structure construction module calls the channel coordinates in the initial path candidate channel index set, arranges the channel numbers in the order of excitation time, and judges whether the angle change between the three consecutive points meets the deflection limit condition in turn, screens the path segment number and arrangement order that meet the requirements, and generates an array path direction sorting structure.

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