Intelligent adaptive optical fiber sensing environment parameter optimization adjustment system

Abstract

The invention belongs to the technical field of environment optimization, and provides an intelligent self-adaptive optical fiber sensing environment parameter optimization and adjustment system, which comprises the following steps: on the basis of processing and analyzing environment parameters, identifying dangerous environment parameters in all the environment parameters, constructing an environment parameter change curve, processing and analyzing to obtain a change rule value, and adjusting the change rule value according to the change rule value; judging the change type of the dangerous environment parameters, determining the residual critical duration corresponding to the dangerous environment parameters based on the change type of the dangerous environment parameters, carrying out processing analysis to obtain a dangerous environment parameter sorting table and the optimization limit duration corresponding to each dangerous environment parameter, and carrying out optimization adjustment on the environment parameters of the target environment. According to the method, the environmental parameters are sequentially optimized through reasonable distribution of optimization time, and the situation that adjustment of the environmental parameters is affected by interaction among the environmental parameters due to the fact that the multiple environmental parameters are optimized and adjusted at the same time is avoided.

Description

Technical Field

[0001] The invention belongs to the technical field of environmental optimization, and in particular is an intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system. Background Art

[0002] In reality, with the development of technology, the requirements for the environment are getting higher and higher. For example, a high-quality environment is needed in technical research and in daily life, but the environment is unpredictable. How to better control the environmental quality according to the use requirements of the environment has far-reaching and important significance.

[0003] A Chinese patent application with publication number CN109916025A discloses a dynamic optimization method for environmental control parameters in subway stations based on the RWI indicator. The method sets the maximum relative thermal index RWI value in the station according to the environmental parameters outside the subway station collected in real time, preliminarily sets the environmental parameters of each area in the station, draws a curve of the RWI value changes of passengers throughout the subway ride, determines the point where the RWI value in the station increases in steps, takes local optimization measures to reduce the RWI value in this area, increases the temperature and humidity set values ​​in the area where the RWI value is reduced, and determines several environmental parameter set values ​​according to the rules for determining the thermal comfort environmental parameters of the human body in the station.

[0004] In the prior art, environmental parameters are monitored by environmental detection equipment, and when the environmental parameters exceed the ideal range, control is performed to achieve optimal adjustment of the environmental parameters. The existing problems are: first, the environmental parameter adjustment is not timely, and advance optimization control is not performed when the environmental parameters are about to exceed the ideal range, and the real-time quality of the environment cannot be guaranteed; second, when adjusting the environmental parameters, the interaction of the environmental parameters is not taken into account, and the accuracy and controllability of the environmental optimization cannot be guaranteed.

[0005] To this end, the present invention provides an intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system. Summary of the invention

[0006] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0007] The technical solution adopted by the present invention to solve the technical problem is: an intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system, comprising:

[0008] Parameter identification module: uses intelligent optical fiber sensors to collect environmental parameters of the target environment in real time, processes and analyzes the environmental parameters, and identifies dangerous environmental parameters among all environmental parameters;

[0009] Hazard type analysis module: obtains all environmental parameters during the hazardous change period, constructs an environmental parameter change curve, obtains a change law value based on the processing and analysis of the environmental parameter change curve, and determines the change type of the hazardous environmental parameters based on the change law value, where the change type includes linear change and nonlinear change;

[0010] Prediction and analysis module: Determine the remaining critical time corresponding to the dangerous environment parameters based on the change type of the dangerous environment parameters;

[0011] Parameter processing module: Based on the processing and analysis of the remaining critical time corresponding to the hazardous environment parameters, a hazardous environment parameter ranking table and the optimized limit time corresponding to each hazardous environment parameter are obtained, and the environmental parameters of the target environment are optimized and adjusted according to the hazardous environment parameter ranking table and the optimized limit time corresponding to each hazardous environment parameter.

[0012] As a further technical solution of the present invention, the identification process of the hazardous environment parameters is as follows:

[0013] If the environmental parameters deviate from the preset optimal environmental parameters and reach the critical environmental parameters, an analysis signal is generated, and the environmental parameters corresponding to the analysis signal are marked as dangerous environmental parameters.

[0014] As a further technical solution of the present invention, the method for obtaining the change regularity value is:

[0015] The same direction ratio TX, the synchronous ratio TB and the slope absolute difference mean XL are processed to obtain the change law performance value BG through the formula: where s1, s2 and s3 are all preset proportional coefficients;

[0016] The judgment process of the change type of the hazardous environment parameter is as follows:

[0017] If the change law performance value BG is greater than or equal to the change law performance threshold, it means that the change type of the hazardous environment parameter is linear change;

[0018] If the change law performance value BG is less than the change law performance threshold, it means that the change type of the hazardous environment parameter is nonlinear change.

[0019] As a further technical solution of the present invention, the method for obtaining the isotropic ratio TX is as follows:

[0020] Obtain all environmental parameters within the dangerous change period, mark them in the XY two-dimensional coordinate system, connect the marked environmental parameter points, and obtain an environmental parameter change curve; wherein the dangerous change period represents the period from the time point when the environmental parameter deviates from the preset optimal environmental parameter to the time point when the environmental parameter reaches the critical environmental parameter;

[0021] The environmental parameter variation curve is divided into a plurality of curve segments, and the slope of the curve segments is measured. At the same time, the two end points of the environmental parameter variation curve are connected to obtain a curve end point connecting line, and the slope of the curve end point connecting line is measured;

[0022] If the slope of a curve segment is of the same sign as the slope of the line connecting the endpoints of the curve, the curve segment is marked as a curve segment of the same direction;

[0023] The number of curve segments in the same direction is counted and the ratio is processed with the number of curve segments to obtain the same direction ratio, which is marked as TX.

[0024] As a further technical solution of the present invention, the slope absolute difference mean XL is obtained as follows:

[0025] The slope of the same-direction curve segment is subtracted from the slope of the line connecting the curve endpoints, and the absolute value of the difference is taken to obtain the absolute difference of the slope of the same-direction curve segment. The absolute differences of the slopes of all the same-direction curve segments are summed and averaged to obtain the mean of the absolute differences of the slopes, which is marked as XL.

[0026] As a further technical solution of the present invention, the synchronization ratio TB is obtained in the following manner:

[0027] The absolute difference of the slopes of the same-direction curve segments is compared with the mean of the absolute difference of the slopes. If the absolute difference of the slopes of the same-direction curve segments is less than or equal to the mean of the absolute difference of the slopes, the same-direction curve segments are marked as synchronous curve segments. The number of synchronous curve segments is counted and the ratio is processed with the number of the same-direction curve segments to obtain the synchronization ratio, which is marked as TB.

[0028] As a further technical solution of the present invention, the process of obtaining the remaining critical time includes:

[0029] If the change type of the hazardous environment parameter is a linear change, then in the coordinate system where the environmental parameter change curve is located, the preset environmental parameter range endpoint value close to the end of the environmental parameter change curve is used as the reference value and marked on its Y axis, and a straight line parallel to the X axis is drawn through the reference value and marked as the range limit line;

[0030] The least square method is used to fit the environmental parameter change curve to obtain a fitting straight line, which is marked as the environmental change trend line;

[0031] Extend the environmental change trend line and intersect it with the range limit line, obtain the time point corresponding to the intersection on the X-axis, and mark it as the critical time point;

[0032] The time point when the environmental parameters deviate from the preset optimal environmental parameters and reach the critical environmental parameters is obtained, and the time point is subtracted from the critical time point to obtain the remaining critical time.

[0033] As a further technical solution of the present invention, the process of obtaining the remaining critical time also includes:

[0034] If the change type of the hazardous environment parameter is nonlinear, the environment parameter change value and the environment parameter change duration corresponding to all synchronous curve segments are obtained, and the environment parameter change value and the environment parameter change duration are processed by ratio to obtain the environment parameter change rate; wherein, the environment parameter change value is obtained by performing difference processing on the environment parameters corresponding to the two end points of the synchronous curve segment, and the environment parameter change duration is obtained by performing difference processing on the time points corresponding to the two end points of the synchronous curve segment;

[0035] Obtain the environmental parameter change rate corresponding to each synchronous curve segment respectively, and select the largest environmental parameter change rate as the target change rate;

[0036] The critical environmental parameter when the analysis signal is generated is processed with the adjacent preset environmental parameter range endpoint value, and the difference is taken as the absolute value to obtain the environmental residual change value. The environmental residual change value is ratioed with the target change rate to obtain the remaining critical time.

[0037] As a further technical solution of the present invention, the process of obtaining the optimized limited time length includes:

[0038] Sort the hazardous environment parameters from small to large according to the remaining critical time to obtain a hazardous environment parameter sorting table;

[0039] If the remaining critical time lengths corresponding to the dangerous environment parameters in the dangerous environment parameter sorting table are all different, the remaining critical time length corresponding to the dangerous environment parameter is differenced with the remaining critical time length corresponding to the previous dangerous environment parameter to obtain the optimized limit time length corresponding to the dangerous environment parameter.

[0040] As a further technical solution of the present invention, the process of obtaining the optimized limited time length further includes:

[0041] If in the hazardous environment parameter sorting table, there are hazardous environment parameters corresponding to the same remaining critical time, then the same remaining critical time corresponding to the hazardous environment parameter is processed by difference with the previous different remaining critical time to obtain the optimized total time limit, and the number of hazardous environment parameters with the same remaining critical time is processed by ratio to obtain the optimized time limit corresponding to the hazardous environment parameter;

[0042] If in the hazardous environment parameter sorting table, the remaining critical time lengths are equal starting from the first adjusted parameter, then the equal remaining critical time lengths are directly ratioed with the number of hazardous parameters with equal remaining critical time lengths to obtain the optimized limit time length corresponding to the hazardous environment parameter.

[0043] The beneficial effects of the present invention are as follows:

[0044] 1. Use intelligent fiber optic sensors to collect environmental parameters of the target environment in real time, identify dangerous environmental parameters among all environmental parameters based on processing and analysis of the environmental parameters, obtain all environmental parameters within a dangerous change period based on the dangerous environmental parameters, construct an environmental parameter change curve, obtain a change law value based on processing and analysis of the environmental parameter change curve, and judge the change type of the dangerous environmental parameters based on the change law value, wherein the change type includes linear change and nonlinear change. The present invention identifies the dangerous environmental parameters based on the change analysis of the environmental parameters collected in real time, and analyzes the change trend of the dangerous environmental parameters. The present invention is conducive to timely discovering abnormal changes in environmental parameters, preventing abnormal changes in environmental parameters from causing abnormalities in the target environment, and analyzing the change trend of the dangerous environmental parameters, so as to facilitate the implementation of subsequent environmental parameter optimization strategies.

[0045] 2. Based on the change type of the dangerous environment parameters, determine the remaining critical time corresponding to the dangerous environment parameters, and based on the processing and analysis of the remaining critical time corresponding to the dangerous environment parameters, obtain a ranking table of dangerous environment parameters and the optimization limit time corresponding to each dangerous environment parameter, and optimize and adjust the environmental parameters of the target environment according to the ranking table of dangerous environment parameters and the optimization limit time corresponding to each dangerous environment parameter. The present invention predicts and determines the remaining time for the dangerous environment parameters to reach the edge of the endpoint of the preset range according to the change type of the dangerous environment parameters, and processes and allocates it with the remaining time to obtain the optimization limit time corresponding to each dangerous environment parameter, and optimizes and adjusts the target environment according to the ranking table of dangerous environment parameters and the optimization limit time corresponding to each dangerous environment parameter. The present invention realizes the sequential optimization of environmental parameters through the reasonable allocation of optimization time, which is conducive to avoiding the optimization and adjustment of multiple environmental parameters at the same time, which causes the adjustment of environmental parameters to be affected by the interaction between environmental parameters, thereby reducing the quality of environmental optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The present invention will be further described below in conjunction with the accompanying drawings.

[0047] Figure 1 It is a flowchart of an intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to an embodiment of the present invention;

[0048] Figure 2 It is an environmental optimization flow chart of an intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system described in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0050] Example 1

[0051] like Figure 1-2 As shown, an intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to an embodiment of the present invention includes:

[0052] Parameter identification module: uses intelligent optical fiber sensors to collect environmental parameters of the target environment in real time, processes and analyzes the environmental parameters, and identifies dangerous environmental parameters among all environmental parameters;

[0053] Among them, environmental parameters include but are not limited to: temperature, humidity, pressure, light intensity and vibration;

[0054] In some embodiments, environmental parameters of the target environment are collected in real time;

[0055] If the environmental parameters deviate from the preset optimal environmental parameters and reach the critical environmental parameters, an analysis signal is generated;

[0056] If the environmental parameters deviate from the preset optimal environmental parameters and do not reach the critical environmental parameters, a normal signal is generated;

[0057] If the environmental parameters do not deviate from the preset optimal environmental parameters, a normal signal is generated;

[0058] Based on normal signals, no processing is performed;

[0059] Based on the analysis signal, the environmental parameter corresponding to the analysis signal is marked as a dangerous environmental parameter;

[0060] It should be noted that the preset optimal environmental parameters represent the optimal environmental parameters set according to the environmental usage requirements;

[0061] Among them, the acquisition method and the meaning of the critical environmental parameter are as follows: a critical environmental parameter is set within a preset environmental parameter range, and the critical environmental parameter includes a first critical environmental parameter and a second critical environmental parameter, wherein the maximum value within the preset environmental parameter range>the first critical environmental parameter>the optimal environmental parameter>the second critical environmental parameter>the minimum value within the preset environmental parameter range. It should be noted that the critical environmental parameter is set by those skilled in the art based on experience, and the critical environmental parameter essentially represents the warning value of the change of the environmental parameter within the allowable range of variation (the preset environmental parameter range). The significance lies in providing an early warning before the environmental parameter changes beyond the allowable range of variation. When the environmental parameter reaches the critical environmental parameter, as the environmental parameter changes, the environmental parameter may exceed the preset environmental parameter range, and it will be marked as a dangerous environmental parameter;

[0062] Hazard type analysis module: obtains all environmental parameters during the hazardous change period, constructs an environmental parameter change curve, obtains a change law value based on the processing and analysis of the environmental parameter change curve, and determines the change type of the hazardous environmental parameters based on the change law value, where the change type includes linear change and nonlinear change;

[0063] The dangerous change period refers to the period from the time when the environmental parameters deviate from the preset optimal environmental parameters to the time when the environmental parameters reach the critical environmental parameters;

[0064] Obtain all environmental parameters during the dangerous change period and mark them in an XY two-dimensional coordinate system, where the X-axis represents time and the Y-axis represents environmental parameters. Connect the marked environmental parameter points to obtain an environmental parameter change curve.

[0065] The environmental parameter variation curve is divided into a plurality of curve segments, and the slope of the curve segments is measured. At the same time, the two end points of the environmental parameter variation curve are connected to obtain a curve end point connecting line, and the slope of the curve end point connecting line is measured;

[0066] If the slope of a curve segment is of the same sign as the slope of the line connecting the endpoints of the curve, the curve segment is marked as a curve segment of the same direction;

[0067] If the slope of the curve segment is not the same as the slope of the line connecting the end points of the curve, the curve segment is marked as a reverse curve segment;

[0068] It should be noted that the same positive and negative means that the slope of the curve segment and the slope of the line connecting the end points of the curve are of the same positive or negative, and different positive and negative means that the slope of the curve segment and the slope of the line connecting the end points of the curve are of different positive or different negative, or one is 0 and the other is not 0;

[0069] Count the number of curve segments in the same direction, and compare it with the number of curve segments to obtain the same direction ratio, which is marked as TX.

[0070] Perform difference processing on the slope of the same-direction curve segment and the slope of the connecting line of the curve endpoints, and take the absolute value of the difference to obtain the absolute difference of the slope of the same-direction curve segment. Sum and average the absolute differences of the slopes of all the same-direction curve segments to obtain the average of the absolute differences of the slopes, and mark it as XL;

[0071] Compare the absolute difference of the slopes of the same-direction curve segments with the mean of the absolute differences of the slopes. The specific comparison process is as follows:

[0072] If the absolute difference of the slopes of the same-direction curve segments is greater than the mean of the absolute difference of the slopes, the same-direction curve segments are marked as asynchronous curve segments;

[0073] If the absolute difference of the slopes of the same-direction curve segments is less than or equal to the mean of the absolute difference of the slopes, the same-direction curve segments are marked as synchronous curve segments;

[0074] The number of synchronous curve segments is counted and the ratio is processed with the number of curve segments in the same direction to obtain the synchronization ratio, which is marked as TB.

[0075] The obtained unidirectional ratio TX, synchronous ratio TB and slope absolute difference mean XL are processed by the formula: Obtain the change law performance value BG, where s1, s2 and s3 are all preset proportional coefficients;

[0076] It should be noted that the change law performance value BG means: by analyzing whether the curve segment change of the environmental parameter change curve is in the same direction and synchronization with the overall change of the environmental parameter, to analyze whether the environmental parameter is a regular and continuous change, wherein the regular and continuous change is a continuous linear change, for example, the environmental parameter change presents a continuous linear increase or decrease, and its regularity is reflected by the same direction ratio TX, the synchronization ratio TB and the average value of the absolute difference of the slope XL, wherein the same direction ratio TX reflects the degree of same direction, and the synchronization ratio TB and the average value of the absolute difference of the slope XL reflect the degree of synchronization, wherein the larger the change law performance value BG is, the closer the change of the environmental parameter is to a continuous linear change, and the smaller the change law performance value BG is, the less close the change of the environmental parameter is to a continuous linear change;

[0077] In some embodiments, the change rule performance value BG is compared with the change rule performance threshold value, specifically:

[0078] If the change law performance value BG is greater than or equal to the change law performance threshold, it means that the change type of the hazardous environment parameter is linear change;

[0079] If the change law performance value BG is less than the change law performance threshold, it means that the change type of the hazardous environment parameter is nonlinear change;

[0080] The technical solution of the embodiment of the present invention is: using intelligent optical fiber sensors to collect environmental parameters of the target environment in real time, based on processing and analyzing the environmental parameters, identifying dangerous environmental parameters among all environmental parameters, based on the dangerous environmental parameters, obtaining all environmental parameters within the dangerous change period, constructing an environmental parameter change curve, based on processing and analyzing the environmental parameter change curve, obtaining a change law value, and judging the change type of the dangerous environmental parameter based on the change law value, wherein the change type includes linear change and nonlinear change. The present invention identifies its dangerous environmental parameters based on the change analysis of the environmental parameters collected in real time, and analyzes the change trend of its dangerous environmental parameters. The present invention is conducive to timely discovering abnormal changes in environmental parameters, preventing abnormal changes in environmental parameters from causing abnormalities in the target environment, and analyzing the change trend of its dangerous environmental parameters, so as to facilitate the implementation of subsequent environmental parameter optimization strategies.

[0081] Example 2

[0082] like Figure 1-2 As shown, based on Example 1, an intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to an embodiment of the present invention includes:

[0083] Prediction and analysis module: Determine the remaining critical time corresponding to the dangerous environment parameters based on the change type of the dangerous environment parameters;

[0084] Specifically, if the change type of the hazardous environment parameter is a linear change, then in the coordinate system where the environmental parameter change curve is located, the preset environmental parameter range endpoint value close to the end of the environmental parameter change curve is used as the reference value and marked on the Y axis, and a straight line parallel to the X axis is drawn through the reference value and marked as the range limit line. For example, the environmental parameter corresponding to the end of the environmental parameter change curve is 40, the optimal environmental parameter is 30, and the preset environmental parameter range is 5-55, then 55 is used as the reference value;

[0085] The least square method is used to fit the environmental parameter change curve to obtain a fitting straight line, which is marked as the environmental change trend line;

[0086] Extend the environmental change trend line and intersect it with the range limit line, obtain the time point corresponding to the intersection on the X-axis, and mark it as the critical time point;

[0087] It should be noted that the critical time point refers to the time point when the environmental parameter change reaches the edge of the end point of the preset environmental parameter range;

[0088] Obtain the time point at which the environmental parameters deviate from the preset optimal environmental parameters and reach the critical environmental parameters, and perform a difference calculation between the time point and the critical time point to obtain the remaining critical time length;

[0089] It should be noted that the remaining critical time in the case of linear change represents the predicted time when the environmental parameter change reaches the edge of the preset environmental parameter range end point;

[0090] If the change type of the hazardous environment parameter is nonlinear, the environment parameter change values ​​and the environment parameter change duration corresponding to all synchronous curve segments are obtained, and the environment parameter change value and the environment parameter change duration are processed by ratio to obtain the environment parameter change rate;

[0091] The environmental parameter change value is obtained by performing difference processing on the environmental parameters corresponding to the two end points of the synchronous curve segment, and the environmental parameter change duration is obtained by performing difference processing on the time points corresponding to the two end points of the synchronous curve segment;

[0092] Obtain the environmental parameter change rate corresponding to each synchronous curve segment respectively, and select the largest environmental parameter change rate as the target change rate;

[0093] The critical environmental parameter when the analysis signal is generated is subjected to difference processing with the nearest preset environmental parameter range endpoint value, and the difference is taken as absolute to obtain the environmental residual change value;

[0094] It should be noted that the residual environmental change value represents the value that can still allow environmental parameters to change when the analysis signal is generated;

[0095] The remaining change value of the environment is processed by ratio with the target change rate to obtain the remaining critical time;

[0096] It should be noted that the remaining critical time under nonlinear change conditions refers to the time when the predicted environmental parameter change reaches the edge of the preset environmental parameter range endpoint, calculated according to the fastest change speed of the environmental parameter during the dangerous change period;

[0097] Parameter processing module: based on the analysis of the remaining critical time corresponding to the dangerous environment parameters, a dangerous environment parameter ranking table and the optimization limit time corresponding to each dangerous environment parameter are obtained, and the environmental parameters of the target environment are optimized and adjusted according to the dangerous environment parameter ranking table and the optimization limit time corresponding to each dangerous environment parameter;

[0098] Specifically, the dangerous environment parameters are sorted from small to large according to the remaining critical time, and a dangerous environment parameter sorting table is obtained;

[0099] If the remaining critical time lengths corresponding to the dangerous environment parameters in the dangerous environment parameter sorting table are all different, the remaining critical time length corresponding to the dangerous environment parameter is subjected to difference processing with the remaining critical time length corresponding to the previous dangerous environment parameter to obtain the optimized limit time length corresponding to the dangerous environment parameter;

[0100] The optimization limit time corresponding to the dangerous environment parameter is sent to the environment adjustment device corresponding to the dangerous environment parameter in sequence according to the dangerous environment parameter sorting table. The environment adjustment device adjusts the value corresponding to the dangerous environment parameter to the value corresponding to the preset optimal environment parameter during the optimization limit time corresponding to the dangerous environment parameter. It should be noted that the optimization limit time corresponding to the next dangerous environment parameter is sent only after the optimization adjustment of the current dangerous environment parameter is completed.

[0101] An exemplary description is given below, for example, a hazardous environment parameter ranking table is:

[0102] (1) Temperature - 1 min;

[0103] (2) Pressure - 3 min;

[0104] (3)Humidity-4min;

[0105] (4) Vibration - 8 min; (min means minutes)

[0106] The optimization limit time corresponding to temperature is 1min, the optimization limit time corresponding to pressure is 3min-1min=2min; the optimization limit time corresponding to humidity is 4min-3min=1min, and the optimization limit time corresponding to vibration is 8min-4min=4min;

[0107] If there are dangerous environment parameters in the ranking table that have the same remaining critical time, the same remaining critical time corresponding to the dangerous environment parameters is processed with the previous different remaining critical time to obtain the optimized total time limit, and the number of dangerous environment parameters with the same remaining critical time is processed by ratio to obtain the optimized time limit corresponding to the dangerous environment parameters. The following is an exemplary description. For example, the ranking table of dangerous environment parameters is:

[0108] (1) Temperature - 1 min;

[0109] (2) Pressure - 3 min;

[0110] (3) Humidity - 3 min;

[0111] (4) Vibration - 8 min; (min means minutes)

[0112] Among them, if the remaining critical time corresponding to pressure and humidity is the same, the remaining critical time corresponding to pressure and humidity is processed with the remaining critical time corresponding to temperature to obtain the optimized total time limit, and the optimized total time limit = 3min-1min = 2min. The number of hazardous environment parameters with the same optimized total time limit and the remaining critical time limit is processed by ratio, specifically: 2min÷2=1min, the optimized time limit corresponding to pressure is 1min, and the optimized time limit corresponding to humidity is 1min;

[0113] It should be noted that the optimization adjustment of the environmental parameters of the target environment is adjusted in sequence according to the ranking table of dangerous environmental parameters. Only one environmental parameter is adjusted at a time. Only after the optimization adjustment of the previous environmental parameter is completed, the corresponding environmental parameter is optimized and adjusted within the optimization limit time. This is conducive to avoiding the optimization adjustment of multiple environmental parameters at the same time, which causes the adjustment of environmental parameters to be affected by the interaction between environmental parameters.

[0114] If the hazardous environment parameter ranking table is:

[0115] (1) Temperature - 3 min;

[0116] (2) Pressure - 3 min;

[0117] (3) Humidity - 3 min;

[0118] (4) Vibration - 8 min; (min means minutes), where the remaining critical time is equal from the first adjusted parameter, then the equal remaining critical time is directly ratioed with the number of dangerous parameters with the same remaining critical time to obtain the optimized limit time corresponding to the dangerous environment parameter, specifically: 3 min ÷ 3 = 1 min, then the optimized limit time corresponding to temperature, pressure and humidity is 1 min;

[0119] The technical solution of the embodiment of the present invention is: based on the change type of the dangerous environment parameter, determine the remaining critical time corresponding to the dangerous environment parameter, based on the processing and analysis of the remaining critical time corresponding to the dangerous environment parameter, obtain a dangerous environment parameter ranking table and the optimization limit time corresponding to each dangerous environment parameter, and optimize and adjust the environmental parameters of its target environment according to the dangerous environment parameter ranking table and the optimization limit time corresponding to each dangerous environment parameter. The present invention predicts and determines the remaining time that the dangerous environment parameter will reach the edge of the endpoint of the preset range according to the change type of the dangerous environment parameter, and processes and allocates it with the remaining time to obtain the optimization limit time corresponding to each dangerous environment parameter, and optimizes and adjusts its target environment according to the dangerous environment parameter ranking table and the optimization limit time corresponding to each dangerous environment parameter. The present invention realizes the sequential optimization of environmental parameters through the reasonable allocation of optimization time, which is conducive to avoiding the optimization and adjustment of multiple environmental parameters at the same time, resulting in the adjustment of environmental parameters being affected by the interaction between environmental parameters, thereby reducing the quality of environmental optimization.

[0120] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system, characterized in that: include: Parameter identification module: uses intelligent optical fiber sensors to collect environmental parameters of the target environment in real time, processes and analyzes the environmental parameters, and identifies dangerous environmental parameters among all environmental parameters; Hazard type analysis module: obtains all environmental parameters during the hazardous change period, constructs an environmental parameter change curve, obtains a change law value based on the processing and analysis of the environmental parameter change curve, and determines the change type of the hazardous environmental parameters based on the change law value, where the change type includes linear change and nonlinear change; Prediction and analysis module: Determine the remaining critical time corresponding to the dangerous environment parameters based on the change type of the dangerous environment parameters; Parameter processing module: Based on the processing and analysis of the remaining critical time corresponding to the hazardous environment parameters, a hazardous environment parameter ranking table and the optimized limit time corresponding to each hazardous environment parameter are obtained, and the environmental parameters of the target environment are optimized and adjusted according to the hazardous environment parameter ranking table and the optimized limit time corresponding to each hazardous environment parameter.

2. The intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to claim 1, characterized in that: The identification process of the hazardous environment parameters is as follows: If the environmental parameters deviate from the preset optimal environmental parameters and reach the critical environmental parameters, an analysis signal is generated, and the environmental parameters corresponding to the analysis signal are marked as dangerous environmental parameters.

3. The intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to claim 1 is characterized in that: The method for obtaining the change rule value is as follows: The same direction ratio TX, the synchronous ratio TB and the slope absolute difference mean XL are processed to obtain the change law performance value BG through the formula: where s1, s2 and s3 are all preset proportional coefficients; The judgment process of the change type of the hazardous environment parameter is as follows: If the change law performance value BG is greater than or equal to the change law performance threshold, it means that the change type of the hazardous environment parameter is linear change; If the change law performance value BG is less than the change law performance threshold, it means that the change type of the hazardous environment parameter is nonlinear change.

4. The intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to claim 3 is characterized in that: The same direction ratio TX is obtained as follows: Obtain all environmental parameters within the dangerous change period, mark them in the XY two-dimensional coordinate system, connect the marked environmental parameter points, and obtain an environmental parameter change curve; wherein the dangerous change period represents the period from the time point when the environmental parameter deviates from the preset optimal environmental parameter to the time point when the environmental parameter reaches the critical environmental parameter; The environmental parameter variation curve is divided into a plurality of curve segments, and the slope of the curve segments is measured. At the same time, the two end points of the environmental parameter variation curve are connected to obtain a curve end point connecting line, and the slope of the curve end point connecting line is measured; If the slope of a curve segment is of the same sign as the slope of the line connecting the endpoints of the curve, the curve segment is marked as a curve segment of the same direction; The number of curve segments in the same direction is counted and the ratio is processed with the number of curve segments to obtain the same direction ratio, which is marked as TX.

5. The intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to claim 3 is characterized in that: The slope absolute difference mean XL is obtained as follows: The slope of the same-direction curve segment is subtracted from the slope of the line connecting the curve endpoints, and the absolute value of the difference is taken to obtain the absolute difference of the slope of the same-direction curve segment. The absolute differences of the slopes of all the same-direction curve segments are summed and averaged to obtain the mean of the absolute differences of the slopes, which is marked as XL.

6. The intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to claim 3 is characterized by: The synchronization ratio TB is obtained as follows: The absolute difference of the slopes of the same-direction curve segments is compared with the mean of the absolute difference of the slopes. If the absolute difference of the slopes of the same-direction curve segments is less than or equal to the mean of the absolute difference of the slopes, the same-direction curve segments are marked as synchronous curve segments. The number of synchronous curve segments is counted and the ratio is processed with the number of the same-direction curve segments to obtain the synchronization ratio, which is marked as TB.

7. The intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to claim 1, characterized in that: The process of obtaining the remaining critical time includes: If the change type of the hazardous environment parameter is a linear change, then in the coordinate system where the environmental parameter change curve is located, the preset environmental parameter range endpoint value close to the end of the environmental parameter change curve is used as the reference value and marked on its Y axis, and a straight line parallel to the X axis is drawn through the reference value and marked as the range limit line; The least square method is used to fit the environmental parameter change curve to obtain a fitting straight line, which is marked as the environmental change trend line; Extend the environmental change trend line and intersect it with the range limit line, obtain the time point corresponding to the intersection on the X-axis, and mark it as the critical time point; The time point when the environmental parameters deviate from the preset optimal environmental parameters and reach the critical environmental parameters is obtained, and the time point is subtracted from the critical time point to obtain the remaining critical time.

8. The intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to claim 7, characterized in that: The process of obtaining the remaining critical time also includes: If the change type of the hazardous environment parameter is nonlinear, the environment parameter change value and the environment parameter change duration corresponding to all synchronous curve segments are obtained, and the environment parameter change value and the environment parameter change duration are processed by ratio to obtain the environment parameter change rate; wherein, the environment parameter change value is obtained by performing difference processing on the environment parameters corresponding to the two end points of the synchronous curve segment, and the environment parameter change duration is obtained by performing difference processing on the time points corresponding to the two end points of the synchronous curve segment; Obtain the environmental parameter change rate corresponding to each synchronous curve segment respectively, and select the largest environmental parameter change rate as the target change rate; The critical environmental parameter when the analysis signal is generated is subjected to difference processing with the nearest preset environmental parameter range endpoint value, and the difference is taken as the absolute value to obtain the residual environmental change value, and the residual environmental change value is subjected to ratio processing with the target change rate to obtain the remaining critical time.

9. The intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to claim 1, characterized in that: The process of obtaining the optimization limit duration includes: Sort the hazardous environment parameters from small to large according to the remaining critical time to obtain a hazardous environment parameter sorting table; If the remaining critical time lengths corresponding to the dangerous environment parameters in the dangerous environment parameter sorting table are all different, the remaining critical time length corresponding to the dangerous environment parameter is subtracted from the remaining critical time length corresponding to the previous dangerous environment parameter to obtain the optimized limit time length corresponding to the dangerous environment parameter.

10. The intelligent adaptive optical fiber sensing environmental parameter optimization and adjustment system according to claim 9, characterized in that: The process of obtaining the optimization limit duration also includes: If in the hazardous environment parameter sorting table, there are hazardous environment parameters corresponding to the same remaining critical time, then the same remaining critical time corresponding to the hazardous environment parameter is processed by difference with the previous different remaining critical time to obtain the optimized total time limit, and the number of hazardous environment parameters with the same remaining critical time is processed by ratio to obtain the optimized time limit corresponding to the hazardous environment parameter; If in the hazardous environment parameter sorting table, the remaining critical time lengths are equal starting from the first adjusted parameter, then the equal remaining critical time lengths are directly ratioed with the number of hazardous parameters with equal remaining critical time lengths to obtain the optimized limit time length corresponding to the hazardous environment parameter.

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