An intelligent detection system for shear beam sensors

Abstract

The present invention relates to the field of sensor detection technology, and in particular to an intelligent detection system for a shear beam sensor, the system comprising an information acquisition module for acquiring shear beam sensor information and environmental information; a fluctuation analysis module for analyzing the abnormality of the signal fluctuation of the shear beam sensor; an abnormality analysis module for analyzing the abnormality of the working environment of the shear beam sensor; an early warning module for providing a user with an abnormality warning according to the analysis results of the abnormality of the working environment of the shear beam sensor in each abnormal monitoring cycle, and adjusting the process of providing the user with an abnormality warning; a detection update module for updating each load threshold and temperature threshold of the shear sensor in the next management cycle, and also optimizing the update process of each load threshold of the shear sensor in the next management cycle. The present invention improves the detection efficiency of the shear beam sensor and prolongs the life of the shear beam sensor.

Description

Technical Field

[0001] The present invention relates to the technical field of sensor detection, and in particular to an intelligent detection system for a shear beam sensor. Background Art

[0002] Traditional shear beam sensor detection methods often rely on regular manual inspections or simple threshold alarm systems. These methods cannot achieve real-time monitoring and early warning, and have limited data analysis and processing capabilities, making it difficult to adapt to complex and changeable actual application scenarios.

[0003] Chinese Patent Publication No.: CN116878728B discloses a pressure sensor fault detection, analysis and processing system, which includes: a pressure sensor environment detection module, a pressure sensor environment analysis module, a pressure sensor transmission parameter acquisition module, a pressure sensor transmission quality analysis module, a pressure sensor fault evaluation index analysis module, a pressure sensor fault judgment module, a display terminal and a cloud database. The present invention makes up for the defect of the prior art that the attention paid to the noise of the environment in which the pressure sensor is located is not high, and the analysis is more comprehensive, thereby improving the accuracy of the data transmitted by the pressure sensor during use. The present invention ensures the transmission quality of the pressure sensor and extends the service life of the pressure sensor to a certain extent, thereby providing strong data support for subsequent pressure sensor fault analysis and ensuring the operating performance of the pressure sensor; it can be seen that when the scheme performs fault detection on the pressure sensor, it only analyzes environmental factors, and there are problems of low sensor detection efficiency and short sensor life. Summary of the invention

[0004] To this end, the present invention provides a shear beam sensor intelligent detection system to overcome the problems of low sensor detection efficiency and short sensor life in the prior art.

[0005] To achieve the above object, the present invention provides a shear beam sensor intelligent detection system, the system comprising:

[0006] An information acquisition module, used to obtain shear beam sensor information and environmental information;

[0007] A fluctuation analysis module, used to analyze the abnormality of the signal fluctuation of the shear beam sensor according to the electrical signal of the shear beam sensor obtained during the fluctuation monitoring period;

[0008] An abnormality analysis module is used to analyze the abnormality of the working environment of the shear beam sensor according to the load and ambient temperature of the shear beam sensor obtained during the abnormality monitoring period;

[0009] An early warning module is used to warn users of abnormal working conditions based on the analysis results of abnormal working conditions of the shear beam sensor in each abnormal monitoring period, and to adjust the process of warning users of abnormal working conditions based on the average environmental noise obtained in the abnormal monitoring period, and to adjust the process of warning users of abnormal working conditions based on the average environmental humidity obtained in the abnormal monitoring period;

[0010] The detection and update module is used to update the load thresholds and temperature thresholds of the shear sensor in the next management period according to the abnormal signal fluctuations and abnormal working warning results of the shear beam sensor in the management period, and is also used to optimize the update process of the load thresholds in the next management period according to the obtained usage time of the shear beam sensor.

[0011] Furthermore, the fluctuation analysis module sorts the electrical signals of the shear beam sensor obtained during the fluctuation monitoring period in descending order, and records the maximum value of the electrical signal as a1, and the minimum value of the electrical signal as a2. The fluctuation analysis module calculates the difference between the maximum value and the minimum value of the output signal, and compares the calculation result with the preset difference a0. According to the comparison result, the abnormality of the signal fluctuation of the shear beam sensor during the fluctuation monitoring period is analyzed, wherein:

[0012] When a1-a2≤a0, the fluctuation analysis module determines that the fluctuation of the shear beam sensor signal in the current fluctuation monitoring period is normal;

[0013] When a1-a2>a0, the fluctuation analysis module determines that the shear beam sensor signal fluctuation in the current fluctuation monitoring period is abnormal.

[0014] Furthermore, the abnormality analysis module is provided with a load analysis unit, which is used to compare the acquired load b0 of the shear beam sensor with each preset load threshold, and analyze the abnormality of the load according to the comparison result, wherein:

[0015] When b0≤b1, the load analysis unit determines that the load of the shear beam sensor is normal;

[0016] When b1<b0<b2, the load analysis unit determines that the load of the shear beam sensor is abnormal at the first level;

[0017] When b0≥b2, the load analysis unit determines that the load of the shear beam sensor is secondary abnormal;

[0018] The abnormality analysis module is further provided with a temperature analysis unit, which is used to compare the acquired ambient temperature t0 with each preset temperature threshold, and analyze the abnormality of the ambient temperature according to the comparison result, wherein:

[0019] When t0≤t1, the temperature analysis unit determines that the ambient temperature is normal;

[0020] When t1<t0<t2, the temperature analysis unit determines that the ambient temperature is abnormal at the first level;

[0021] When t0≥t2, the temperature analysis unit determines that the ambient temperature is secondary abnormal;

[0022] Wherein, t1 is a first preset temperature threshold, t2 is a second preset temperature threshold, and t1<t2.

[0023] Furthermore, the abnormality analysis module is provided with an abnormality analysis unit, and the abnormality analysis unit is used to analyze the abnormality of the shear sensor working environment based on the analysis results of the shear beam sensor load abnormality and the ambient temperature abnormality during the abnormality monitoring period, wherein:

[0024] When w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0≤A, the abnormality analysis unit determines that the working environment of the shear beam sensor in the current abnormality monitoring period is normal;

[0025] When w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0>A, the abnormality analysis unit determines that the working environment of the shear beam sensor in the current abnormality monitoring period is abnormal;

[0026] Among them, w1 is the first load weight, w2 is the second load weight, w3 is the first temperature weight, w4 is the second temperature weight, w1+w2+w3+w4=1, w4>w2>w3>w1, i1 is the duration of the first-level load abnormality of the shear beam sensor within the abnormal monitoring period, i2 is the duration of the second-level load abnormality of the shear beam sensor within the abnormal monitoring period, i3 is the duration of the first-level ambient temperature abnormality within the abnormal monitoring period, i4 is the duration of the second-level load abnormality of the shear beam sensor within the abnormal monitoring period, i0 is the duration of the abnormal monitoring period, and A is the preset abnormality coefficient.

[0027] Furthermore, the warning module is provided with a warning unit, which is used to warn the user of abnormal working conditions according to the analysis result of the abnormal working environment of the shear beam sensor during the abnormal monitoring period, wherein:

[0028] When the working environment of the shear beam sensor is normal, the warning unit does not issue a warning of abnormal working state to the user;

[0029] When the working environment of the shear beam sensor is abnormal, if (w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0-A) / A≤D1, the early warning unit does not warn the user of abnormal working conditions; if D1<(w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0-A) / A<D2, the early warning module warns the user of low risk of abnormal working conditions; if (w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0-A) / A≥D2, the early warning module warns the user of high risk of abnormal working conditions;

[0030] Among them, D1 is the preset minimum abnormal proportion, and D2 is the preset maximum abnormal proportion.

[0031] Furthermore, the warning module is provided with a first adjustment unit, which is used to compare the average environmental noise v0 of the abnormal monitoring period obtained with the preset noise v1, and adjust the process of providing the user with a work abnormality warning according to the comparison result, wherein:

[0032] When v0≤v1, the first adjustment unit determines that the ambient noise in the current abnormal monitoring period is normal and does not make any adjustment;

[0033] When v0>v1, the first adjustment unit determines that the environmental noise in the current abnormal monitoring period is abnormal, and adjusts the process of providing work abnormality warning to the user, and sets the adjusted preset minimum abnormality ratio to D1', setting D1'=D1×[1+sin(π / 2)×(v0-v1) / (v0+v1)], and sets the adjusted preset maximum abnormality ratio to D2', setting D2'=D1×[1+sin(π / 2)×(v0-v1) / (v0+v1)].

[0034] Furthermore, the warning module is provided with a second adjustment unit, which is used to compare the average ambient humidity s0 of the abnormal monitoring period obtained with the preset humidity s1, and make a secondary adjustment to the process of providing abnormal work warning to the user according to the comparison result, wherein:

[0035] When s0≤s1, the second adjustment unit determines that the ambient humidity in the current abnormal monitoring period is normal;

[0036] When s0>s1, the second adjustment unit determines that the ambient humidity in the current abnormal monitoring period is abnormal, and makes a secondary adjustment to the process of providing abnormal working warning to the user, and sets the adjusted preset noise to v1', and sets v1'=v1×{1-arctan[(s0-s1) / (s0+s1)×(π / 4)]}.

[0037] Furthermore, the detection update module is provided with a first update unit, which is used to update each load threshold of the shear sensor in the next management period according to the abnormality of the signal fluctuation of the shear beam sensor in the management period and the result of the abnormal working warning to the user, wherein:

[0038] When the shear beam sensor signal fluctuation is normal, if z1×m1 / m0+z2×m2 / m0≤k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 1. Set b B 1 = b B If z1×m1 / m0+z2×m2 / m0>k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 2. Set b B 2 = b B ×[1-α×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)];

[0039] When the shear beam sensor signal fluctuates abnormally, if z1×m1 / m0+z2×m2 / m0≤k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 3. Set b B 3 = b B ×{1-In[1+(a1-a2-a0) / (a1-a2+a0)] / In2}, if z1×m1 / m0+z2×m2 / m0>k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 4. Set b B 4 = b B ×[1-γ×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)];

[0040] Among them, m1 is the number of abnormal monitoring cycles in which low-risk warnings of work abnormalities are issued to users within the management cycle, m2 is the number of abnormal monitoring cycles in which high-risk warnings of work abnormalities are issued to users within the management cycle, m0 is the number of abnormal monitoring cycles in the management cycle, z1 is the low-risk weight, z2 is the high-risk weight, z1+z2=1, z1<z2, B=1,2, k is the preset proportional coefficient, b B is the load threshold of the shear beam sensor, and α is the preset first adjustment coefficient.

[0041] Further, the detection update module is provided with a second update unit, which updates each temperature threshold of the shear sensor in the next management period according to the management result of each load threshold of the shear sensor in the next management period and the result of the abnormal working warning to the user, wherein:

[0042] When b B When x≤B0, if z1×m1 / m0+z2×m2 / m0≤k, the second updating unit sets the load thresholds of the shear sensors in the next management period to t T 1. Set t T 1 = t T If z1×m1 / m0+z2×m2 / m0>k, the second updating unit sets the load thresholds of the shear sensors in the next management period to t T 2. Set t T 2 = t T 2×[1-β×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)];

[0043] When b B When x>B0, if z1×m1 / m0+z2×m2 / m0≤k, the second updating unit sets the load thresholds of the shear sensors in the next management period to t T 3. Set t T 3 = t T If z1×m1 / m0+z2×m2 / m0>k, the second updating unit sets the load thresholds of the shear sensors in the next management period to t T 4. Set t T 4 = t T 4×[1-η×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)];

[0044] Among them, B0 is the preset load extreme value, b B x is the analysis result of the load threshold of the shear beam sensor, x=1, 2, 3, 4; β is the preset first adjustment coefficient, η is the preset second adjustment coefficient, β<η.

[0045] Furthermore, the detection update module is provided with an update optimization unit, which is used to compare the obtained use time u0 of the shear beam sensor with the preset time u1, and optimize the update process of each load threshold of the shear sensor in the next management period according to the comparison result, wherein:

[0046] When u0≤u1, the update optimization unit determines that the service life of the shear beam sensor is normal and does not perform optimization;

[0047] When u0>u1, the update optimization unit determines that the use time of the shear beam sensor is abnormal, and optimizes the update process of each load threshold of the shear beam sensor in the next management period, and sets the optimized preset proportional coefficient to k', setting k'=k×[1-e 3(u0-u1) / (u0+u1)-3 ].

[0048] Compared with the prior art, the beneficial effects of the present invention are that the fluctuation analysis module improves the accuracy of the shear beam sensor signal fluctuation abnormality analysis by setting a preset difference, thereby improving the accuracy of the load threshold and temperature threshold analysis of the shear sensor in the next management period; the abnormality analysis module improves the accuracy of the shear beam sensor load abnormality analysis by setting each preset load threshold, improves the accuracy of the shear temperature abnormality analysis by setting each preset temperature threshold, and improves the accuracy of the shear beam sensor working environment abnormality analysis by setting a preset abnormality coefficient and each weight, thereby improving the accuracy of the shear beam sensor working abnormality warning, and improving the accuracy of the load threshold and temperature threshold analysis of the shear sensor in the next management period; the early warning module improves the accuracy of the shear beam sensor working abnormality warning by setting each preset abnormality proportion, thereby improving the accuracy of the load threshold and temperature threshold analysis of the shear sensor in the next management period, By setting a preset noise to reduce the impact of excessive environmental noise on the signal transmission of the shear beam sensor, the accuracy of the abnormal working warning of the shear beam sensor is improved. By setting a preset humidity to reduce the impact of excessive environmental humidity on the operation of the shear beam sensor, the accuracy of the abnormal working warning of the shear beam sensor is improved. The detection update module sets a preset proportional coefficient, each preset adjustment coefficient and each weight to improve the accuracy of the load threshold management of the shear sensor in the next management period. By setting each preset adjustment coefficient, the accuracy of the temperature threshold management of the shear sensor in the next management period is improved. By setting a preset time to reduce the impact of aging caused by excessive use of the sensor on the management result, the accuracy of the load threshold management of the shear sensor in the next management period is improved, and then the accuracy of the temperature threshold management of the shear sensor in the next management period is improved, thereby improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a structural schematic diagram of a shear beam sensor intelligent detection system according to this embodiment;

[0050] Figure 2 This is a schematic diagram of the structure of the abnormality analysis module of this embodiment;

[0051] Figure 3 This is a schematic diagram of the structure of the early warning module of this embodiment;

[0052] Figure 4 This is a schematic diagram of the structure of the detection and update module in this embodiment. DETAILED DESCRIPTION

[0053] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0054] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0055] It should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] See also Figure 1 As shown, it is a structural schematic diagram of a shear beam sensor intelligent detection system of this embodiment, the system includes:

[0057] An information acquisition module is used to acquire shear beam sensor information and environmental information, wherein the shear beam sensor information includes the load, electrical signal and usage time of the shear beam sensor; the environmental information includes ambient temperature, average ambient humidity and average ambient noise; in this embodiment, no specific limitation is imposed on the acquisition method of the shear beam sensor information and the environmental information, and those skilled in the art can freely set it, as long as the acquisition requirements of the shear beam sensor information and the environmental information are met, wherein the load of the shear beam sensor can be acquired by measuring the strain on the beam by the shear beam sensor, the electrical signal of the shear beam sensor can be acquired by a strain gauge and related circuits, the usage time of the shear beam sensor can be acquired by interaction, the ambient temperature can be acquired by a temperature sensor, the average ambient humidity can be acquired by a humidity sensor, and the average ambient noise can be acquired by a sound sensor;

[0058] A fluctuation analysis module is used to analyze the abnormality of the signal fluctuation of the shear beam sensor according to the electrical signal of the shear beam sensor obtained within the fluctuation monitoring period, and the fluctuation analysis module is connected to the information acquisition module; in this embodiment, no specific limitation is made to the setting of the fluctuation monitoring period, and those skilled in the art can freely set it, as long as the setting requirements of the fluctuation monitoring period are met, wherein the fluctuation monitoring period can be set to 1h, 2h, etc.; it is worth noting that in this embodiment, when obtaining the electrical signal of the shear beam sensor within the fluctuation monitoring period, the shear beam sensor is placed under a known and stable load, and the electrical signal is recorded;

[0059] An abnormality analysis module is used to analyze the abnormality of the working environment of the shear beam sensor according to the load and ambient temperature of the shear beam sensor obtained during the abnormality monitoring period. The abnormality analysis module is connected to the information acquisition module. In this embodiment, the setting of the abnormality monitoring period is not specifically limited. Those skilled in the art can freely set it as long as the setting requirements of the abnormality monitoring period are met. Among them, the abnormality monitoring period can be set to 2h, 3h, etc.;

[0060] An early warning module, used to warn users of abnormal working conditions according to the analysis results of abnormal working conditions of the shear beam sensor in each abnormal monitoring period, and to adjust the process of warning users of abnormal working conditions according to the average environmental noise obtained in the abnormal monitoring period, and to adjust the process of warning users of abnormal working conditions according to the average environmental humidity obtained in the abnormal monitoring period. The early warning module is connected to the abnormal analysis module;

[0061] A detection and update module is used to update the load thresholds and temperature thresholds of the shear sensor in the next management period according to the abnormality of the signal fluctuation of the shear beam sensor in the management period and the result of the abnormal work warning to the user, and is also used to optimize the update process of the load thresholds of the shear sensor in the next management period according to the obtained use time of the shear beam sensor. The detection and update module is connected with the fluctuation analysis module and the warning module. In this embodiment, no specific limitation is made to the setting of the management period, and those skilled in the art can set it freely, and only need to meet the setting requirements of the management period, wherein the fluctuation monitoring period is set as the beginning of the management period, followed by n abnormal monitoring periods, that is, the management period is composed of the fluctuation monitoring period and n abnormal monitoring periods. In this embodiment, no specific limitation is made to the setting of n, and those skilled in the art can set it freely, and only need to meet the setting requirements of n, wherein n can be set to 300, 400, 500, etc.;

[0062] The output module is used to output the management results of the load thresholds and temperature thresholds of the shear sensor in the next management cycle as a management solution to the user. The output module is connected to the detection and update module.

[0063] See also Figure 2 As shown, it is a schematic diagram of the structure of the abnormality analysis module of this embodiment, and the abnormality analysis module includes:

[0064] A load analysis unit, used to analyze the abnormality of the load according to the load of the shear beam sensor obtained;

[0065] A temperature analysis unit, used to analyze the abnormality of the ambient temperature according to the acquired ambient temperature, the temperature analysis unit being connected to the load analysis unit;

[0066] The abnormality analysis unit is used to analyze the abnormality of the working environment of the shear sensor according to the analysis results of the load abnormality of the shear beam sensor and the ambient temperature abnormality within the abnormality monitoring period. The abnormality analysis unit is connected to the temperature analysis unit.

[0067] See also Figure 3 As shown, it is a schematic diagram of the structure of the early warning module of this embodiment, and the early warning module includes:

[0068] An early warning unit is used to warn the user of abnormal working conditions based on the analysis results of the abnormal working environment of the shear beam sensor during the abnormal monitoring period;

[0069] A first adjustment unit, used for adjusting the process of providing a warning of abnormal working state to the user according to the average environmental noise of the abnormal monitoring period obtained, and the first adjustment unit is connected to the warning unit;

[0070] The second adjustment unit is used to make secondary adjustments to the process of providing abnormal work warning to the user according to the average ambient humidity of the abnormal monitoring period obtained, and the second adjustment unit is connected to the first adjustment unit.

[0071] See also Figure 4 As shown, it is a schematic diagram of the structure of the detection and update module of this embodiment, and the detection and update module includes:

[0072] A first updating unit is used to update each load threshold value of the shear sensor in the next management period according to the abnormality of the signal fluctuation of the shear beam sensor in the management period and the result of the abnormal working warning to the user;

[0073] a second updating unit, used for updating each temperature threshold of the shear sensor in the next management period according to the management result of each load threshold of the shear sensor in the next management period and the result of the abnormal working warning to the user, the second updating unit is connected to the first updating unit;

[0074] The updating optimization unit is used to optimize the updating process of each load threshold value of the shear beam sensor in the next management period according to the acquired service life of the shear beam sensor, and the updating optimization unit is connected to the second updating unit.

[0075] Specifically, the fluctuation analysis module sorts the electrical signals of the shear beam sensor obtained during the fluctuation monitoring period in descending order, and records the maximum value of the electrical signal as a1, and the minimum value of the electrical signal as a2. The fluctuation analysis module calculates the difference between the maximum value and the minimum value of the output signal, and compares the calculation result with the preset difference a0. According to the comparison result, the abnormality of the signal fluctuation of the shear beam sensor during the fluctuation monitoring period is analyzed, wherein:

[0076] When a1-a2≤a0, the fluctuation analysis module determines that the fluctuation of the shear beam sensor signal in the current fluctuation monitoring period is normal;

[0077] When a1-a2>a0, the fluctuation analysis module determines that the shear beam sensor signal fluctuation in the current fluctuation monitoring period is abnormal.

[0078] Specifically, the fluctuation analysis module sets a preset difference to improve the accuracy of the shear beam sensor signal fluctuation abnormality analysis, thereby improving the accuracy of the load threshold and temperature threshold analysis of the shear beam sensor in the next management period, ultimately improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor; in this embodiment, no specific limitation is made to the value of the preset difference, and technical personnel in this field can set it freely, as long as the value requirement of the preset difference is met, wherein the optimal value of the preset difference is the average value of the electrical signal obtained during the fluctuation monitoring period × 0.18; in this embodiment, no specific limitation is made to the sorting method of the shear beam sensor electrical signal, and technical personnel in this field can set it freely, as long as the sorting requirements of the shear beam sensor electrical signal are met, wherein the sorting method of the shear beam sensor electrical signal can be a bubble sort method.

[0079] Specifically, the load analysis unit compares the acquired load b0 of the shear beam sensor with each preset load threshold, and analyzes the abnormality of the load according to the comparison result, wherein:

[0080] When b0≤b1, the load analysis unit determines that the load of the shear beam sensor is normal;

[0081] When b1<b0<b2, the load analysis unit determines that the load of the shear beam sensor is abnormal at the first level;

[0082] When b0≥b2, the load analysis unit determines that the load of the shear beam sensor is secondary abnormal;

[0083] Wherein, b1 is the first preset load threshold, b2 is the second preset load threshold, and b1<b2.

[0084] Specifically, the load analysis unit sets preset load thresholds to improve the accuracy of load abnormality analysis of the shear beam sensor, thereby improving the accuracy of working environment abnormality analysis of the shear beam sensor, thereby improving the accuracy of abnormal warning of the shear beam sensor, and improving the accuracy of load threshold and temperature threshold analysis of the shear sensor in the next management cycle, ultimately improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor. In this embodiment, the values ​​of the preset load thresholds are not specifically limited, and those skilled in the art can set them freely as long as the value requirements of the preset load thresholds are met. Among them, the optimal value of b1 is 48kN, and the optimal value of b2 is 50kN.

[0085] Specifically, the temperature analysis unit compares the acquired ambient temperature t0 with each preset temperature threshold, and analyzes the abnormality of the ambient temperature according to the comparison result, wherein:

[0086] When t0≤t1, the temperature analysis unit determines that the ambient temperature is normal;

[0087] When t1<t0<t2, the temperature analysis unit determines that the ambient temperature is abnormal at the first level;

[0088] When t0≥t2, the temperature analysis unit determines that the ambient temperature is secondary abnormal;

[0089] Wherein, t1 is a first preset temperature threshold, t2 is a second preset temperature threshold, and t1<t2.

[0090] Specifically, the load analysis unit improves the accuracy of shear temperature abnormality analysis by setting preset temperature thresholds, thereby improving the accuracy of shear beam sensor working environment abnormality analysis, thereby improving the accuracy of shear beam sensor working abnormality warning, and improving the accuracy of load threshold and temperature threshold analysis of the shear sensor in the next management cycle, ultimately improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor. In this embodiment, the value of each preset temperature threshold is not specifically limited, and technical personnel in this field can set it freely as long as the value requirements of each preset temperature threshold are met. Among them, the optimal value of t1 is 56°C, and the optimal value of t2 is 62°C.

[0091] Specifically, the abnormality analysis unit analyzes the abnormality of the shear sensor working environment based on the analysis results of the shear beam sensor load abnormality and the ambient temperature abnormality during the abnormality monitoring period, wherein:

[0092] When w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0≤A, the abnormality analysis unit determines that the working environment of the shear beam sensor in the current abnormality monitoring period is normal;

[0093] When w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0>A, the abnormality analysis unit determines that the working environment of the shear beam sensor in the current abnormality monitoring period is abnormal;

[0094] Among them, w1 is the first load weight, w2 is the second load weight, w3 is the first temperature weight, w4 is the second temperature weight, w1+w2+w3+w4=1, w4>w2>w3>w1, i1 is the duration of the first-level load abnormality of the shear beam sensor within the abnormal monitoring period, i2 is the duration of the second-level load abnormality of the shear beam sensor within the abnormal monitoring period, i3 is the duration of the first-level ambient temperature abnormality within the abnormal monitoring period, i4 is the duration of the second-level load abnormality of the shear beam sensor within the abnormal monitoring period, i0 is the duration of the abnormal monitoring period, and A is the preset abnormality coefficient.

[0095] Specifically, the abnormality analysis unit improves the accuracy of the abnormality analysis of the working environment of the shear beam sensor by setting preset abnormality coefficients and weights, thereby improving the accuracy of the abnormality warning of the shear beam sensor, and improving the accuracy of the analysis of the load thresholds and temperature thresholds of the shear sensor in the next management cycle, ultimately improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor; in this embodiment, there is no specific limitation on the values ​​of the preset abnormality coefficients and the weights, and those skilled in the art can set them freely as long as the value requirements of the preset abnormality coefficients and the weights are met. Among them, the best value of w1 is 0.18, the best value of w2 is 0.28, the best value of w3 is 0.22, the best value of w4 is 0.32, and the best value of A is 0.15.

[0096] Specifically, the warning unit warns the user of abnormal working conditions based on the analysis results of the abnormal working environment of the shear beam sensor during the abnormal monitoring period, wherein:

[0097] When the working environment of the shear beam sensor is normal, the warning unit does not issue a warning of abnormal working state to the user;

[0098] When the working environment of the shear beam sensor is abnormal, if (w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0-A) / A≤D1, the early warning unit does not warn the user of abnormal working conditions; if D1<(w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0-A) / A<D2, the early warning module warns the user of low risk of abnormal working conditions; if (w1×i1 / i0+w2×i2 / i0+w3×i3 / i0+w4×i4 / i0-A) / A≥D2, the early warning module warns the user of high risk of abnormal working conditions;

[0099] Among them, D1 is the preset minimum abnormal proportion, and D2 is the preset maximum abnormal proportion.

[0100] Specifically, the warning unit improves the accuracy of the abnormal warning of the shear beam sensor by setting preset abnormal proportions, thereby improving the accuracy of the load threshold and temperature threshold analysis of the shear beam sensor in the next management period, and ultimately improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor; in this embodiment, no specific limitation is made to the value of each preset abnormal proportion, and technical personnel in this field can set it freely, as long as the value requirements of each preset abnormal proportion are met, among which the optimal value of D1 is 0.3, and the optimal value of D2 is 0.4; the low risk warning of the working abnormality in this embodiment means that the shear beam sensor is at risk of inaccurate measurement data, and the high risk warning of the working abnormality means that the shear beam sensor is at risk of damage, and users can take corresponding measures according to different warning types.

[0101] Specifically, the first adjustment unit compares the average environmental noise v0 of the abnormal monitoring period obtained with the preset noise v1, and adjusts the process of providing the user with an abnormal work warning according to the comparison result, wherein:

[0102] When v0≤v1, the first adjustment unit determines that the ambient noise in the current abnormal monitoring period is normal and does not make any adjustment;

[0103] When v0>v1, the first adjustment unit determines that the environmental noise in the current abnormal monitoring period is abnormal, and adjusts the process of providing work abnormality warning to the user, and sets the adjusted preset minimum abnormality ratio to D1', setting D1'=D1×[1+sin(π / 2)×(v0-v1) / (v0+v1)], and sets the adjusted preset maximum abnormality ratio to D2', setting D2'=D1×[1+sin(π / 2)×(v0-v1) / (v0+v1)].

[0104] Specifically, the first adjustment unit sets a preset noise to reduce the impact of excessive environmental noise on the signal transmission of the shear beam sensor, thereby improving the accuracy of the abnormal warning of the shear beam sensor, thereby improving the accuracy of the analysis of each load threshold and temperature threshold of the shear beam sensor in the next management cycle, and ultimately improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor. In this embodiment, the value of the preset noise is not specifically limited, and technical personnel in this field can set it freely as long as the value requirement of the preset noise is met. Among them, the optimal value of v1 is 80dB.

[0105] Specifically, the second adjustment unit compares the average ambient humidity s0 of the abnormal monitoring period obtained with the preset humidity s1, and makes a secondary adjustment to the process of providing the user with an abnormal work warning according to the comparison result, wherein:

[0106] When s0≤s1, the second adjustment unit determines that the ambient humidity in the current abnormal monitoring period is normal;

[0107] When s0>s1, the second adjustment unit determines that the ambient humidity in the current abnormal monitoring period is abnormal, and makes a secondary adjustment to the process of providing abnormal working warning to the user, and sets the adjusted preset noise to v1', and sets v1'=v1×{1-arctan[(s0-s1) / (s0+s1)×(π / 4)]}.

[0108] Specifically, the second adjustment unit reduces the impact of excessive ambient humidity on the operation of the shear beam sensor by setting a preset humidity, thereby improving the accuracy of the abnormal warning of the shear beam sensor, thereby improving the accuracy of the analysis of each load threshold and temperature threshold of the shear beam sensor in the next management cycle, and ultimately improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor. In this embodiment, the value of the preset humidity is not specifically limited, and technical personnel in this field can set it freely as long as the value requirement of the preset humidity is met. Among them, the optimal value of v1 is 75% RH.

[0109] Specifically, the first updating unit updates each load threshold of the shear sensor in the next management period according to the abnormality of the signal fluctuation of the shear beam sensor in the management period and the result of the abnormal working warning to the user, wherein:

[0110] When the shear beam sensor signal fluctuation is normal, if z1×m1 / m0+z2×m2 / m0≤k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 1. Set b B 1 = b BIf z1×m1 / m0+z2×m2 / m0>k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 2. Set b B 2 = b B ×[1-α×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)];

[0111] When the shear beam sensor signal fluctuates abnormally, if z1×m1 / m0+z2×m2 / m0≤k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 3. Set b B 3 = b B ×{1-In[1+(a1-a2-a0) / (a1-a2+a0)] / In2}, if z1×m1 / m0+z2×m2 / m0>k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 4. Set b B 4 = b B ×[1-γ×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)];

[0112] Among them, m1 is the number of abnormal monitoring cycles in which low-risk warnings of work abnormalities are issued to users within the management cycle, m2 is the number of abnormal monitoring cycles in which high-risk warnings of work abnormalities are issued to users within the management cycle, m0 is the number of abnormal monitoring cycles in the management cycle, z1 is the low-risk weight, z2 is the high-risk weight, z1+z2=1, z1<z2, B=1,2, k is the preset proportional coefficient, b B is the load threshold of the shear beam sensor, α is the preset first adjustment coefficient, γ is the preset second adjustment coefficient, α<γ.

[0113] Specifically, the first update unit sets a preset proportional coefficient, preset adjustment coefficients and weights to improve the accuracy of load threshold management of the shear sensor in the next management period, thereby improving the accuracy of temperature threshold management of the shear sensor in the next management period, thereby improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor; in this embodiment, no specific limitation is made on the values ​​of the preset proportional coefficient, the preset adjustment coefficients and the weights, and those skilled in the art may set them freely as long as the requirements for the values ​​of the preset proportional coefficient, the preset adjustment coefficients and the weights are met, among which the optimal value of z1 is 0.35, the optimal value of z2 is 0.65, the optimal value of k is 0.2, the optimal value of α is 0.25, and the optimal value of γ is 0.35.

[0114] Specifically, the second updating unit updates each temperature threshold of the shear sensor in the next management period according to the management result of each load threshold of the shear sensor in the next management period and the result of the abnormal working warning to the user, wherein:

[0115] When b B When x≤B0, if z1×m1 / m0+z2×m2 / m0≤k, the second updating unit sets the load thresholds of the shear sensors in the next management period to t T 1. Set t T 1 = t T If z1×m1 / m0+z2×m2 / m0>k, the second updating unit sets the load thresholds of the shear sensors in the next management period to t T 2. Set t T 2 = t T 2×[1-β×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)];

[0116] When b B When x>B0, if z1×m1 / m0+z2×m2 / m0≤k, the second updating unit sets the load thresholds of the shear sensors in the next management period to t T 3. Set t T 3 = t T If z1×m1 / m0+z2×m2 / m0>k, the second updating unit sets the load thresholds of the shear sensors in the next management period to t T 4. Set t T 4 = t T 4×[1-η×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)];

[0117] Among them, B0 is the preset load extreme value, b B x is the analysis result of the load threshold of the shear beam sensor, x=1, 2, 3, 4; β is the preset first adjustment coefficient, η is the preset second adjustment coefficient, β<η.

[0118] Specifically, the second update unit improves the accuracy of the temperature threshold management of the shear sensor in the next management period by setting each preset adjustment coefficient, thereby improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor. In this embodiment, there is no specific limitation on the value of each preset adjustment coefficient, and technical personnel in this field can set it freely as long as the value requirements of each preset adjustment coefficient are met. Among them, the optimal value of β is 0.18, and the optimal value of η is 0.22.

[0119] Specifically, the update optimization unit compares the obtained usage time u0 of the shear beam sensor with the preset time u1, and optimizes the update process of each load threshold of the shear sensor in the next management period according to the comparison result, wherein:

[0120] When u0≤u1, the update optimization unit determines that the service life of the shear beam sensor is normal and does not perform optimization;

[0121] When u0>u1, the update optimization unit determines that the use time of the shear beam sensor is abnormal, and optimizes the update process of each load threshold of the shear beam sensor in the next management period, and sets the optimized preset proportional coefficient to k', setting k'=k×[1-e 3(u0-u1) / (u0+u1)-3 ].

[0122] Specifically, the update optimization unit reduces the impact of aging caused by prolonged use of the sensor on the management results by setting a preset time, thereby improving the accuracy of the management of each load threshold of the shear sensor in the next management cycle, and further improving the accuracy of the management of each temperature threshold of the shear sensor in the next management cycle, thereby improving the detection efficiency of the shear beam sensor and extending the life of the shear beam sensor. In this embodiment, the setting of the preset time is not specifically limited, and technical personnel in this field can set it freely as long as the setting requirements of the preset time are met. The preset time can be set to 3000 days.

[0123] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A shear beam sensor intelligent detection system, characterized in that: include, An information acquisition module, used to obtain shear beam sensor information and environmental information; A fluctuation analysis module, used to analyze the abnormality of the signal fluctuation of the shear beam sensor according to the electrical signal of the shear beam sensor obtained during the fluctuation monitoring period; An abnormality analysis module is used to analyze the abnormality of the working environment of the shear beam sensor according to the load and ambient temperature of the shear beam sensor obtained during the abnormality monitoring period; An early warning module is used to warn users of abnormal working conditions based on the analysis results of abnormal working conditions of the shear beam sensor in each abnormal monitoring period, and to adjust the process of warning users of abnormal working conditions based on the average environmental noise obtained in the abnormal monitoring period, and to adjust the process of warning users of abnormal working conditions based on the average environmental humidity obtained in the abnormal monitoring period; A detection and update module is used to update the load thresholds and temperature thresholds of the shear beam sensor in the next management period according to the results of the abnormal signal fluctuation and abnormal work warning of the shear beam sensor in the management period, and is also used to optimize the update process of the load thresholds in the next management period according to the obtained use time of the shear beam sensor; The fluctuation analysis module sorts the electrical signals of the shear beam sensor obtained during the fluctuation monitoring period in descending order, and records the maximum value of the electrical signal as a1, and the minimum value of the electrical signal as a2. The fluctuation analysis module calculates the difference between the maximum value and the minimum value of the output signal, and compares the calculation result with the preset difference a0, and analyzes the abnormality of the signal fluctuation of the shear beam sensor during the fluctuation monitoring period according to the comparison result; The abnormality analysis module is provided with a load analysis unit, which is used to compare the acquired load b0 of the shear beam sensor with each preset load threshold, and analyze the abnormality of the load according to the comparison result, wherein: When b0≤b1, the load analysis unit determines that the load of the shear beam sensor is normal; When b1<b0<b2, the load analysis unit determines that the load of the shear beam sensor is abnormal at the first level; When b0≥b2, the load analysis unit determines that the load of the shear beam sensor is secondary abnormal; The abnormality analysis module is further provided with a temperature analysis unit, which is used to compare the acquired ambient temperature t0 with each preset temperature threshold, and analyze the abnormality of the ambient temperature according to the comparison result, wherein: When t0≤t1, the temperature analysis unit determines that the ambient temperature is normal; When t1<t0<t2, the temperature analysis unit determines that the ambient temperature is abnormal at the first level; When t0≥t2, the temperature analysis unit determines that the ambient temperature is secondary abnormal; Wherein, t1 is a first preset temperature threshold, t2 is a second preset temperature threshold, and t1<t2; The abnormality analysis module is provided with an abnormality analysis unit, and the abnormality analysis unit is used to analyze the abnormality of the shear sensor working environment based on the analysis results of the shear beam sensor load abnormality and the ambient temperature abnormality during the abnormality monitoring period, wherein: When w1×i1 / i0+ w2×i2 / i0+ w3×i3 / i0 +w4×i4 / i0≤A, the abnormality analysis unit determines that the working environment of the shear beam sensor in the current abnormality monitoring period is normal; When w1×i1 / i0+ w2×i2 / i0+ w3×i3 / i0 +w4×i4 / i0>A, the abnormality analysis unit determines that the working environment of the shear beam sensor in the current abnormality monitoring period is abnormal; Wherein, w1 is the first load weight, w2 is the second load weight, w3 is the first temperature weight, w4 is the second temperature weight, w1+w2+w3+w4=1, w4>w2>w3>w1, i1 is the duration of the first-level abnormality of the load of the shear beam sensor within the abnormal monitoring period, i2 is the duration of the second-level abnormality of the load of the shear beam sensor within the abnormal monitoring period, i3 is the duration of the first-level abnormality of the ambient temperature within the abnormal monitoring period, i4 is the duration of the second-level abnormality of the ambient temperature within the abnormal monitoring period, i0 is the duration of the abnormal monitoring period, and A is the preset abnormality coefficient; The early warning module is provided with an early warning unit, which is used to warn the user of abnormal working conditions according to the analysis result of the abnormal working environment of the shear beam sensor during the abnormal monitoring period, wherein: When the working environment of the shear beam sensor is normal, the warning unit does not issue a warning of abnormal working state to the user; When the working environment of the shear beam sensor is abnormal, if (w1×i1 / i0+ w2×i2 / i0+ w3×i3 / i0 +w4×i4 / i0-A) / A≤D1, the early warning unit does not warn the user of abnormal working conditions; if D1<(w1×i1 / i0+ w2×i2 / i0+ w3×i3 / i0 +w4×i4 / i0-A) / A<D2, the early warning module warns the user of low risk of abnormal working conditions; if (w1×i1 / i0+ w2×i2 / i0+ w3×i3 / i0 +w4×i4 / i0-A) / A≥D2, the early warning module warns the user of high risk of abnormal working conditions; Among them, D1 is the preset minimum abnormal proportion, and D2 is the preset maximum abnormal proportion; The warning module is provided with a first adjustment unit, which is used to compare the average environmental noise v0 obtained during the abnormal monitoring period with the preset noise v1, and adjust the process of providing the user with a warning of abnormal work according to the comparison result, wherein: When v0≤v1, the first adjustment unit determines that the ambient noise in the current abnormal monitoring period is normal and does not make any adjustment; When v0>v1, the first adjustment unit determines that the ambient noise in the current abnormal monitoring period is abnormal, and adjusts the process of providing the user with an abnormal work warning, and sets the adjusted preset minimum abnormal proportion to D1', setting D1'=D1×[1+sin(π / 2)×(v0-v1) / (v0+v1)], and sets the adjusted preset maximum abnormal proportion to D2', setting D2'=D2×[1+sin(π / 2)×(v0-v1) / (v0+v1)]; The warning module is provided with a second adjustment unit, which is used to compare the average ambient humidity s0 of the abnormal monitoring period obtained with the preset humidity s1, and to make a secondary adjustment to the process of providing the user with a warning of abnormal work according to the comparison result, wherein: When s0≤s1, the second adjustment unit determines that the ambient humidity in the current abnormal monitoring period is normal; When s0>s1, the second adjustment unit determines that the ambient humidity in the current abnormal monitoring period is abnormal, and makes a secondary adjustment to the process of providing abnormal working warning to the user, and sets the adjusted preset noise to v1', setting v1'=v1×{1-arctan[(s0-s1) / (s0+s1)×(π / 4)]}.

2. The shear beam sensor intelligent detection system according to claim 1, characterized in that: The analysis process of the shear beam sensor signal fluctuation abnormality within the fluctuation monitoring period of the fluctuation analysis module is as follows: When a1-a2≤a0, the fluctuation analysis module determines that the fluctuation of the shear beam sensor signal in the current fluctuation monitoring period is normal; When a1-a2>a0, the fluctuation analysis module determines that the shear beam sensor signal fluctuation in the current fluctuation monitoring period is abnormal.

3. The shear beam sensor intelligent detection system according to claim 2, characterized in that: The detection update module is provided with a first update unit, which is used to update each load threshold of the shear sensor in the next management period according to the abnormality of the signal fluctuation of the shear beam sensor in the management period and the result of the abnormal working warning to the user, wherein: When the shear beam sensor signal fluctuation is normal, if z1×m1 / m0+z2×m2 / m0≤k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 1. Set b B 1=b B If z1×m1 / m0+z2×m2 / m0>k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 2. Set b B 2=b B ×[1-α×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)]; When the shear beam sensor signal fluctuates abnormally, if z1×m1 / m0+z2×m2 / m0≤k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 3. Set b B 3=b B ×{1-In[1+(a1-a2-a0) / (a1-a2+a0)] / In2}, if z1×m1 / m0+z2×m2 / m0>k, the first updating unit sets the load thresholds of the shear sensors in the next management period to b B 4. Set b B 4=b B ×[1-γ×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)]; Among them, m1 is the number of abnormal monitoring cycles in which low-risk warnings of work abnormalities are issued to users within the management cycle, m2 is the number of abnormal monitoring cycles in which high-risk warnings of work abnormalities are issued to users within the management cycle, m0 is the number of abnormal monitoring cycles in the management cycle, z1 is the low-risk weight, z2 is the high-risk weight, z1+z2=1, z1<z2, B=1,2, k is the preset proportional coefficient, b B is the load threshold of the shear beam sensor, α is the preset first adjustment coefficient, and γ is the preset second adjustment coefficient.

4. The shear beam sensor intelligent detection system according to claim 3, characterized in that: The detection update module is provided with a second update unit, which updates each temperature threshold of the shear sensor in the next management period according to the management result of each load threshold of the shear sensor in the next management period and the result of the abnormal working warning to the user, wherein: When b B When x≤B0, if z1×m1 / m0+z2×m2 / m0≤k, the second updating unit sets the temperature thresholds of the shear sensors in the next management period to t T 1. Set t T 1=t T If z1×m1 / m0+z2×m2 / m0>k, the second updating unit sets the temperature thresholds of the shear sensors in the next management period to t T 2. Set t T 2=t T ×[1-β×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)]; When b B When x>B0, if z1×m1 / m0+z2×m2 / m0≤k, the second updating unit sets the temperature thresholds of the shear sensors in the next management period to t T 3. Set t T 3=t T If z1×m1 / m0+z2×m2 / m0>k, the second updating unit sets the temperature thresholds of the shear sensors in the next management period to t T 4. Set t T 4=t T ×[1-η×(z1×m1 / m0+z2×m2 / m0-k) / (z1×m1 / m0+z2×m2 / m0+k)]; Among them, B0 is the preset load extreme value, b B x is the analysis result of the load threshold of the shear beam sensor, x=1, 2, 3, 4; β is the preset first adjustment coefficient, η is the preset second adjustment coefficient, β<η.

5. The shear beam sensor intelligent detection system according to claim 4, characterized in that: The detection update module is provided with an update optimization unit, which is used to compare the obtained use time u0 of the shear beam sensor with the preset time u1, and optimize the update process of each load threshold of the shear sensor in the next management period according to the comparison result, wherein: When u0≤u1, the update optimization unit determines that the usage time of the shear beam sensor is normal and does not perform optimization; When u0>u1, the update optimization unit determines that the use time of the shear beam sensor is abnormal, and optimizes the update process of each load threshold of the shear beam sensor in the next management period, and sets the optimized preset proportional coefficient to k', setting k'=k×[1-e 3(u0-u1) / (u0+u1)-3 ], k is the preset proportional coefficient.

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