CN116342014A - Anesthetic transportation management system based on data analysis - Google Patents
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Abstract
The invention belongs to the field of anesthetic transportation, relates to a data analysis technology, and is used for solving the problem that the existing anesthetic transportation management system cannot perform associated analysis on external interference received by a storage bin in the operation process, in particular to an anesthetic transportation management system based on data analysis, which comprises an early warning analysis module, wherein the early warning analysis module is in communication connection with an operation monitoring module and an inner ring monitoring module; the operation monitoring module is used for monitoring and analyzing the operation state of the anesthetic agent transport vehicle: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, and marking a storage bin of the anesthetic agent transport vehicle as a monitoring object; according to the invention, the running state of the anesthetic transportation vehicle can be monitored and analyzed, the storage parameters of the storage bin in each monitoring period are obtained in a time-division monitoring mode, the stability of the storage bin in the monitoring period is fed back through the running coefficient, and early warning is timely carried out when the stability is abnormal.
Description
Technical Field
The invention belongs to the field of anesthetic transportation, relates to a data analysis technology, and particularly relates to an anesthetic transportation management system based on data analysis.
Background
The anesthetic is a medicament for temporarily and reversibly losing consciousness and pain of a body or a local part of the body by using a medicament or a non-medicament method, is mostly used for surgery or treatment of certain diseases, and is rarely used by people in order to reduce toxicity and side effects of the anesthetic to the greatest extent and expand the safety and application range of the anesthetic, and is generally used by combining animal compound anesthetics or inhalation anesthetics, intravenous anesthetics, physical anesthetics and the like.
The anesthetic agent is required to monitor parameters such as storage temperature, storage stability of a medicament container and the like during transportation, and for the storage bin of the anesthetic agent, the anesthetic agent transportation is a continuous moving process, and the existing anesthetic agent transportation management system can only monitor and analyze storage parameters in the static storage bin, but cannot perform associated analysis on external interference received by the storage bin in the operation process, so that internal structural abnormality and external interference cannot be checked when the storage parameter is abnormal, and further the processing efficiency of the abnormal storage parameter is low.
Aiming at the technical problems, the application provides a solution.
Disclosure of Invention
The invention aims to provide an anesthetic transportation management system based on data analysis, which is used for solving the problem that the existing anesthetic transportation management system cannot perform correlation analysis on external interference received by a storage bin in the running process;
the technical problems to be solved by the invention are as follows: how to provide an anesthetic agent transportation management system based on data analysis, which can perform correlation analysis on external interference suffered by a storage bin in the operation process.
The aim of the invention can be achieved by the following technical scheme:
the anesthetic transportation management system based on data analysis comprises an early warning analysis module, wherein the early warning analysis module is in communication connection with an operation monitoring module and an inner ring monitoring module;
the operation monitoring module is used for monitoring and analyzing the operation state of the anesthetic agent transport vehicle: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, and allocating numbers i, i=1, 2, …, n and n for the monitoring periods in time sequence, wherein n is a positive integer, marking a storage bin of an anesthetic agent transport vehicle as a monitoring object, acquiring an operation coefficient YX of the monitoring object in the monitoring period, and marking the monitoring period as a positive transportation period or a abnormal transportation period through the value of the operation coefficient YX; transmitting an operation analysis signal to the early warning analysis module when the number of the operation different time periods in the monitoring period is not smaller than a preset operation different threshold value;
the inner ring monitoring module is used for monitoring and analyzing the internal storage environment of the anesthetic agent transport vehicle: acquiring a temperature representation value WB and a temperature change value BH in the monitored object at the end time of the monitoring period, judging whether the internal storage environment of the monitored object in the monitoring period meets the requirement or not according to the values of the temperature representation value WB and the temperature change value BH, and sending an inner ring analysis signal to an early warning analysis module when the internal storage environment does not meet the requirement;
the early warning analysis module receives the operation analysis signal, performs a pause analysis on the monitored object and judges whether the operation abnormality and the driving state are associated or not in the abnormal operation period;
and after receiving the inner ring analysis signal, the early warning analysis module carries out heat-linked analysis on the monitored object and judges whether the internal storage environment abnormality in the monitoring period is associated with the driving state or not.
As a preferred embodiment of the present invention, the process of acquiring the operation coefficient YX of the monitoring object in the monitoring period includes: obtaining vibration data ZD and noise data ZS of a monitoring object in a monitoring period, and performing numerical value calculation to obtain an operation coefficient YX, wherein the obtaining process of the vibration data ZD comprises the following steps: and acquiring an average value of vibration frequency values of the bottom wall and the inner side wall in the monitored object, marking the average value as a vibration average value, marking the maximum value of the vibration average value in a monitoring period as vibration data ZD, and obtaining noise data ZS as the maximum value of noise decibels detected by the monitored object in the monitoring period.
As a preferred embodiment of the present invention, the specific process of marking the operation period as the fortune positive period or the fortune abnormal period includes: comparing the operation coefficient YX of the monitoring object in the monitoring period with a preset operation threshold YXmax: if the operation coefficient YX is smaller than the operation threshold YXmax, judging that the operation state of the monitoring object in the monitoring period meets the requirement, and marking the corresponding monitoring period as a positive operation period; if the operation coefficient YX is greater than or equal to the operation threshold value YXmin, judging that the operation state of the monitoring object in the monitoring period does not meet the requirement, and marking the corresponding monitoring period as a abnormal operation period; and sending an operation analysis signal to the early warning analysis module when the number of the operation different time periods in the monitoring period is not smaller than a preset operation different threshold value.
As a preferred embodiment of the present invention, the process of obtaining the temperature representative value WB and the temperature change value BH includes: and summing and averaging the maximum values of the bottom wall temperature value, the inner side wall temperature value and the air temperature value in the monitoring period to obtain a temperature representation value WB, and performing variance calculation on the temperature representation values WB in all the monitoring periods to obtain a temperature variation value BH.
As a preferred embodiment of the present invention, the specific process of determining that the internal storage environment of the monitored object in the monitoring period meets the requirement includes: comparing the temperature representation value WB and the temperature change value BH of the monitoring period with a preset temperature representation threshold value WBmax and a preset temperature change threshold value BHmax respectively: if the temperature representation value WB is smaller than the temperature representation threshold value WBmax and the temperature variation value BH is smaller than the temperature representation threshold value BHmax, judging that the internal storage environment of the monitored object in the monitoring period meets the requirement; otherwise, judging that the internal storage environment of the monitored object in the monitoring period does not meet the requirement, and sending an inner ring analysis signal to the early warning analysis module by the inner ring monitoring module.
As a preferred implementation mode of the invention, the specific process of the early warning analysis module for carrying out the pause analysis on the monitored object comprises the following steps: the method comprises the steps of obtaining a maximum speed value and a minimum speed value of a transport vehicle running in a monitoring period, marking a difference value between the maximum speed value and the minimum speed value as a setback value of the monitoring period, and comparing the setback value with a preset setback threshold value: if the setback value is smaller than the setback threshold, marking the corresponding monitoring period as a stable period; if the setback value is greater than or equal to the setback threshold, marking the corresponding monitoring period as a fluctuation period; marking the number of the different transport time period as a different transport value, marking the number of the fluctuation time period as a fluctuation value, and distributing an associated value for each different transport time period: marking the absolute value of the difference value between the fortune abnormal value and each fluctuation value as a marking value of the fluctuation time period, and marking the marking value with the smallest value as an association value of the fortune abnormal time period; summing and averaging the association values of all different operation periods to obtain an association coefficient, and comparing the association coefficient with a preset association threshold value: if the association coefficient is smaller than the association threshold, judging that the abnormal operation in the abnormal operation period is associated with the driving state, and sending a driving constraint signal to a mobile phone terminal of a manager by the early warning analysis module; if the association coefficient is greater than or equal to the association threshold, judging that the abnormal operation in the abnormal operation period is not associated with the driving state, and sending a storage bin overhaul signal to a mobile phone terminal of a manager by the early warning analysis module.
As a preferred implementation mode of the invention, the specific process of carrying out the heat-linked analysis on the monitored object by the early warning analysis module comprises the following steps: establishing a rectangular coordinate system by taking the execution time of a monitoring period as an X axis and the temperature representation value WB of the monitoring period as a Y axis, marking a plurality of thermometer points in the rectangular coordinate system by taking the end time of the monitoring period as an abscissa and the temperature representation value WB of the monitoring period as an ordinate, marking a plurality of thermometer points in the rectangular coordinate system by taking the end time of the monitoring period as an abscissa and the maximum speed value of the transportation vehicle running in the monitoring period as an ordinate, connecting the thermometer points with the adjacent thermometer points on the right side to obtain speed Wen Xianduan, summing absolute values of all the thermometer segment slope values to obtain a heat-coupling coefficient, and comparing the heat-coupling coefficient with a preset heat-coupling threshold value: if the heat coupling coefficient is smaller than the heat coupling threshold value, judging that the abnormality of the internal storage environment in the monitoring period is not associated with the driving state, and sending a refrigeration maintenance signal to a mobile phone terminal of a manager by the early warning analysis module; if the heat coupling coefficient is greater than or equal to the heat coupling threshold, judging that the abnormality of the internal storage environment in the monitoring period is related to the driving state, and sending a driving constraint signal to a mobile phone terminal of a manager by the early warning analysis module.
The invention has the following beneficial effects:
1. the operation monitoring module can monitor and analyze the operation state of the anesthetic transport vehicle, and the storage bin storage parameters of each monitoring period are obtained in a time-division monitoring mode, so that the storage bin storage parameters are comprehensively calculated and analyzed to obtain operation coefficients, the stability of the storage bin in the monitoring period is fed back through the operation coefficients, and early warning is timely carried out when the stability is abnormal;
2. the internal storage environment of the anesthetic agent transport vehicle can be monitored and analyzed through the inner ring monitoring module, the suitability of the internal storage environment of the monitored object in the monitoring period is fed back through the temperature representation value and the temperature change value in the monitored object, and early warning is carried out when the temperature is too high or the trend is too high, so that the anesthetic agent is prevented from being stored at unsuitable environmental temperature;
3. the early warning analysis module can carry out pause analysis on the monitored object and obtain a correlation coefficient, and the correlation degree of the running speed fluctuation and the running stability is reflected by the correlation coefficient, so that the reason of the running stability abnormality is judged and fed back, data support is provided for the treatment measure selection of the running stability abnormality, and the treatment efficiency of the running stability abnormality is improved;
4. the early warning analysis module can carry out heat coupling analysis on the monitored object and obtain a heat coupling coefficient, and the association degree of the storage environment abnormality and the driving state is fed back through the numerical value of the heat coupling coefficient, so that the reason of the storage environment abnormality is judged, data support is provided for the selection of the treatment measures of the storage environment abnormality, and the treatment efficiency of the storage environment abnormality is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a system block diagram of a first embodiment of the present invention;
FIG. 2 is a flow chart of a bump analysis process in a second embodiment of the present invention;
FIG. 3 is a flow chart of a thermal link analysis process according to a second embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
1-3, an anesthetic transportation management system based on data analysis comprises an early warning analysis module, wherein the early warning analysis module is in communication connection with an operation monitoring module and an inner ring monitoring module.
The operation monitoring module is used for monitoring and analyzing the operation state of the anesthetic agent transport vehicle and sending an operation analysis signal to the early warning analysis module when the operation state does not meet the requirement.
The inner ring monitoring module is used for monitoring and analyzing the internal storage environment of the anesthetic agent transport vehicle and sending an inner ring analysis signal to the early warning analysis module when the internal storage environment does not meet the requirement.
The early warning analysis module is used for carrying out early warning analysis on abnormal states in the anesthetic agent transportation process and sending a storage bin overhaul signal, a heat dissipation overhaul signal or a driving constraint signal to a mobile phone terminal of a manager.
Example 1
As shown in fig. 1, the operation monitoring module monitors and analyzes the operation state of the anesthetic agent transport vehicle: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, and distributing numbers i, i=1, 2, …, n and n for the monitoring periods in a time sequence, wherein the time length of each monitoring period is equal, the time length of the monitoring period is preferably taken for 30s, a storage bin of the anesthetic agent transportation vehicle is marked as a monitoring object, vibration frequency values of the inner bottom wall and the inner side wall of the monitoring object are obtained through vibration sensors arranged on the bottom wall and the inner side wall in the storage bin, the vibration sensors are one of key components in a testing technology, the vibration sensors mainly receive mechanical quantities and convert the mechanical quantities into electric quantities proportional to the mechanical quantities, the average value of the vibration frequency values of the inner bottom wall and the inner side wall is marked as a vibration average value of the monitoring period, the maximum value of the vibration average value in the monitoring period is marked as vibration data ZD, the maximum value of noise decibel detected by the monitoring object in the monitoring period is marked as noise data ZS through a noise sensor, and the noise sensor is internally provided with a capacitance microphone sensitive to sound, the electret film in the microphone vibrates, the vibration sensor causes capacitance change, and the electric signal is generated, and the voltage corresponding to the change is tiny electric signal, and thus the light signal is converted.
By the formula yx=α1
ZD+α2
ZS obtains an operation coefficient YX of the monitored object in a monitoring period, wherein alpha 1 and alpha 2 are proportionality coefficients, and alpha 1 is more than alpha 2 is more than 1; comparing the operation coefficient YX of the monitoring object in the monitoring period with a preset operation threshold YXmax: if the operation coefficient YX is smaller than the operation threshold YXmax, judging that the operation state of the monitoring object in the monitoring period meets the requirement, and marking the corresponding monitoring period as a positive operation period; if the operation coefficient YX is greater than or equal to the operation threshold value YXmin, judging that the operation state of the monitoring object in the monitoring period does not meet the requirement, and marking the corresponding monitoring period as a abnormal operation period; and sending an operation analysis signal to the early warning analysis module when the number of the operation different time periods in the monitoring period is not smaller than a preset operation different threshold value.
It should be noted that, the running coefficient YX is a value reflecting the running stability of the monitoring object in the monitoring period, the smaller the value of the running coefficient YX is, the higher the running stability of the monitoring object in the monitoring period is, the lower the possibility of collision and leakage of the anesthetic in the monitoring period is, and the running threshold YXmax is a value for measuring whether the stability of the monitoring object in the monitoring period meets the requirement or not, and the specific value is set by a manager; the method comprises the steps of monitoring and analyzing the running state of an anesthetic transportation vehicle, acquiring storage bin storage parameters of each monitoring period in a time-division monitoring mode, comprehensively calculating and analyzing the storage bin storage parameters to obtain running coefficients, feeding back the stability of the storage bin in the monitoring period through the running coefficients, and timely early warning when the stability is abnormal.
The inner ring monitoring module monitors and analyzes the internal storage environment of the anesthetic agent transport vehicle: acquiring a temperature representation value WB and a temperature change value BH of the interior of a monitored object at the end time of a monitoring period: summing the maximum values of the bottom wall temperature value, the inner wall temperature value and the air temperature value in the monitoring period of the monitored object to obtain a temperature representation value WB, performing variance calculation on the temperature representation values WB of all the monitoring periods to obtain a temperature variation value BH, and comparing the temperature representation values WB and the temperature variation value BH of the monitoring periods with a preset temperature representation threshold WBmax and a preset temperature variation threshold BHmax respectively: if the temperature representation value WB is smaller than the temperature representation threshold value WBmax and the temperature variation value BH is smaller than the temperature representation threshold value BHmax, judging that the internal storage environment of the monitored object in the monitoring period meets the requirement; otherwise, judging that the internal storage environment of the monitored object in the monitoring period does not meet the requirement, and sending an inner ring analysis signal to the early warning analysis module by the inner ring monitoring module; the method comprises the steps of monitoring and analyzing the internal storage environment of the anesthetic agent transportation vehicle, feeding back the suitability of the internal storage environment of a monitoring object in a monitoring period through the temperature representation value and the temperature change value in the monitoring object, and carrying out early warning when the temperature is too high or the trend is too high, so that the anesthetic agent is prevented from being stored at unsuitable environmental temperature.
It should be noted that the storage temperature ranges of different anesthetic agents are different, the storage temperature of most anesthetic agents should be between 2 ℃ and 8 ℃, and the storage bins of a general anesthetic agent transport vehicle are all provided with a refrigerator, so that the inner ring monitoring and analyzing process of the application only monitors the high temperature in the storage environment.
Example two
As shown in fig. 2, the early warning analysis module performs a pause analysis on the monitored object after receiving the operation analysis signal:
step S1: the method comprises the steps that the maximum value and the minimum value of the speed of a transport vehicle in a monitoring period are obtained, and the difference value between the maximum value and the minimum value of the speed is marked as a setback value of the monitoring period;
step S2: comparing the setback value with a preset setback threshold value: if the setback value is smaller than the setback threshold value, marking the corresponding monitoring time period as a stable time period, wherein the running speed of the monitored object in the monitoring time period is stable, and the stable time period does not have the necessity of setback analysis; if the bump value is greater than or equal to the bump threshold value, marking the corresponding monitoring period as a fluctuation period, which means that the running speed of the monitored object in the monitoring period has larger fluctuation, and the bump analysis needs to be carried out on the fluctuation period;
step S3: marking the number of the different transport time period as a different transport value, marking the number of the fluctuation time period as a fluctuation value, and distributing an associated value for each different transport time period: marking the absolute value of the difference value between the fortune abnormal value and each fluctuation value as a marking value of a fluctuation period, marking the marking value with the smallest value as a correlation value of the fortune abnormal period, summing the correlation values of all the fortune abnormal periods to obtain a correlation coefficient, and taking the average value, wherein the fortune abnormal value is 3, 5 and 7, and when the fluctuation value is 4,8 and 10, the three marking values of the fortune abnormal value 3 are respectively 1,5 and 7, then the correlation value of the running period with the number of 3 is 1, and the correlation values of the running periods with the numbers of 5 and 7 are 1 and 3, and then the correlation coefficient of 5/3 can be obtained by summing and averaging the 1, 1 and 3;
step S4: comparing the association coefficient with a preset association threshold value: if the association coefficient is smaller than the association threshold, judging that the abnormal operation in the abnormal operation period is associated with the driving state, and sending a driving constraint signal to a mobile phone terminal of a manager by the early warning analysis module; if the association coefficient is greater than or equal to the association threshold, judging that the abnormal operation in the abnormal operation period is not associated with the driving state, and sending a storage bin overhaul signal to a mobile phone terminal of a manager by the early warning analysis module.
And carrying out a pause analysis on the monitored object and obtaining a correlation coefficient, and reflecting the correlation degree of the running speed fluctuation and the running stability through the correlation coefficient, so as to judge and feed back the reason of the running stability abnormality, provide data support for the treatment measure selection of the running stability abnormality, and improve the treatment efficiency of the running stability abnormality.
As shown in fig. 2, the early warning analysis module receives the inner ring analysis signal and performs a heat-linked analysis on the monitored object:
step P1: establishing a rectangular coordinate system by taking the execution time of the monitoring period as an X axis and the temperature representation value WB of the monitoring period as a Y axis;
step P2: marking a plurality of thermometer points in a rectangular coordinate system by taking the end time of the monitoring period as an abscissa and the temperature representation value WB of the monitoring period as an ordinate, marking a plurality of thermometer points in the rectangular coordinate system by taking the end time of the monitoring period as an abscissa and the maximum speed value of the transportation vehicle running in the monitoring period as an ordinate, and connecting the thermometer points adjacent to the right side to obtain a speed Wen Xianduan;
step P3: summing absolute values of all the slope values of the quick temperature line segments, taking an average value to obtain a heat coupling coefficient, and comparing the heat coupling coefficient with a preset heat coupling threshold value: if the heat coupling coefficient is smaller than the heat coupling threshold value, judging that the abnormality of the internal storage environment in the monitoring period is not associated with the driving state, and sending a refrigeration maintenance signal to a mobile phone terminal of a manager by the early warning analysis module; if the heat coupling coefficient is greater than or equal to the heat coupling threshold, judging that the abnormality of the internal storage environment in the monitoring period is related to the driving state, and sending a driving constraint signal to a mobile phone terminal of a manager by the early warning analysis module.
And carrying out heat coupling analysis on the monitored object, obtaining a heat coupling coefficient, and feeding back the association degree of the storage environment abnormality and the driving state through the numerical value of the heat coupling coefficient, so as to judge the reason of the storage environment abnormality, provide data support for the selection of the treatment measure of the storage environment abnormality, and improve the treatment efficiency of the storage environment abnormality.
The anesthetic transportation management system based on data analysis generates a monitoring period during operation, divides the monitoring period into a plurality of monitoring periods, marks a storage bin of an anesthetic transportation vehicle as a monitoring object, judges whether the running stability and the storage environment in the monitoring period meet requirements or not through an operating coefficient YX, a temperature representation value WB and a temperature variation value BH of the monitoring period, performs pause and pause analysis on the monitoring object through an early warning analysis module when the running stability does not meet the requirements, and performs heat-linked analysis on the monitoring object through the early warning analysis module when the storage environment does not meet the requirements.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: formula yx=α1
ZD+α2 
ZS；
Collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding operation coefficient for each group of sample data; substituting the set operation coefficient and the acquired sample data into a formula, forming a ternary one-time equation set by any three formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1 and alpha 2 which are respectively 3.25 and 2.14;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding operation coefficient is preliminarily set for each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the operation coefficient is proportional to the value of the vibration data.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (7)
1. The anesthetic transportation management system based on data analysis is characterized by comprising an early warning analysis module, wherein the early warning analysis module is in communication connection with an operation monitoring module and an inner ring monitoring module;
the operation monitoring module is used for monitoring and analyzing the operation state of the anesthetic agent transport vehicle: generating a monitoring period, dividing the monitoring period into a plurality of monitoring periods, and allocating numbers i, i=1, 2, …, n and n for the monitoring periods in time sequence, wherein n is a positive integer, marking a storage bin of an anesthetic agent transport vehicle as a monitoring object, acquiring an operation coefficient YX of the monitoring object in the monitoring period, and marking the monitoring period as a positive transportation period or a abnormal transportation period through the value of the operation coefficient YX; transmitting an operation analysis signal to the early warning analysis module when the number of the operation different time periods in the monitoring period is not smaller than a preset operation different threshold value;
the inner ring monitoring module is used for monitoring and analyzing the internal storage environment of the anesthetic agent transport vehicle: acquiring a temperature representation value WB and a temperature change value BH in the monitored object at the end time of the monitoring period, judging whether the internal storage environment of the monitored object in the monitoring period meets the requirement or not according to the values of the temperature representation value WB and the temperature change value BH, and sending an inner ring analysis signal to an early warning analysis module when the internal storage environment does not meet the requirement;
the early warning analysis module receives the operation analysis signal, performs a pause analysis on the monitored object and judges whether the operation abnormality and the driving state are associated or not in the abnormal operation period;
and after receiving the inner ring analysis signal, the early warning analysis module carries out heat-linked analysis on the monitored object and judges whether the internal storage environment abnormality in the monitoring period is associated with the driving state or not.
2. The anesthetic agent transport management system based on the data analysis according to claim 1, wherein the process of acquiring the operation coefficient YX of the monitoring subject during the monitoring period comprises: obtaining vibration data ZD and noise data ZS of a monitoring object in a monitoring period, and performing numerical value calculation to obtain an operation coefficient YX, wherein the obtaining process of the vibration data ZD comprises the following steps: and acquiring an average value of vibration frequency values of the bottom wall and the inner side wall in the monitored object, marking the average value as a vibration average value, marking the maximum value of the vibration average value in a monitoring period as vibration data ZD, and obtaining noise data ZS as the maximum value of noise decibels detected by the monitored object in the monitoring period.
3. The system of claim 2, wherein the specific process of marking the operational period as a positive period or a abnormal period comprises: comparing the operation coefficient YX of the monitoring object in the monitoring period with a preset operation threshold YXmax: if the operation coefficient YX is smaller than the operation threshold YXmax, judging that the operation state of the monitoring object in the monitoring period meets the requirement, and marking the corresponding monitoring period as a positive operation period; if the operation coefficient YX is greater than or equal to the operation threshold value YXmin, judging that the operation state of the monitoring object in the monitoring period does not meet the requirement, and marking the corresponding monitoring period as a abnormal operation period; and sending an operation analysis signal to the early warning analysis module when the number of the operation different time periods in the monitoring period is not smaller than a preset operation different threshold value.
4. The anesthetic transport management system according to claim 1, wherein the acquiring of the temperature appearance value WB and the temperature change value BH includes: and summing and averaging the maximum values of the bottom wall temperature value, the inner side wall temperature value and the air temperature value in the monitoring period to obtain a temperature representation value WB, and performing variance calculation on the temperature representation values WB in all the monitoring periods to obtain a temperature variation value BH.
5. The system for managing transportation of anesthetic agents based on data analysis according to claim 4, wherein the specific process of determining that the internal storage environment of the monitoring object satisfies the requirement during the monitoring period comprises: comparing the temperature representation value WB and the temperature change value BH of the monitoring period with a preset temperature representation threshold value WBmax and a preset temperature change threshold value BHmax respectively: if the temperature representation value WB is smaller than the temperature representation threshold value WBmax and the temperature variation value BH is smaller than the temperature representation threshold value BHmax, judging that the internal storage environment of the monitored object in the monitoring period meets the requirement; otherwise, judging that the internal storage environment of the monitored object in the monitoring period does not meet the requirement, and sending an inner ring analysis signal to the early warning analysis module by the inner ring monitoring module.
6. The anesthetic transportation management system based on data analysis according to claim 3, wherein the specific process of the early warning analysis module performing the pause analysis on the monitored object comprises: the method comprises the steps of obtaining a maximum speed value and a minimum speed value of a transport vehicle running in a monitoring period, marking a difference value between the maximum speed value and the minimum speed value as a setback value of the monitoring period, and comparing the setback value with a preset setback threshold value: if the setback value is smaller than the setback threshold, marking the corresponding monitoring period as a stable period; if the setback value is greater than or equal to the setback threshold, marking the corresponding monitoring period as a fluctuation period; marking the number of the different transport time period as a different transport value, marking the number of the fluctuation time period as a fluctuation value, and distributing an associated value for each different transport time period: marking the absolute value of the difference value between the fortune abnormal value and each fluctuation value as a marking value of the fluctuation time period, and marking the marking value with the smallest value as an association value of the fortune abnormal time period; summing and averaging the association values of all different operation periods to obtain an association coefficient, and comparing the association coefficient with a preset association threshold value: if the association coefficient is smaller than the association threshold, judging that the abnormal operation in the abnormal operation period is associated with the driving state, and sending a driving constraint signal to a mobile phone terminal of a manager by the early warning analysis module; if the association coefficient is greater than or equal to the association threshold, judging that the abnormal operation in the abnormal operation period is not associated with the driving state, and sending a storage bin overhaul signal to a mobile phone terminal of a manager by the early warning analysis module.
7. The anesthetic transportation management system based on data analysis according to claim 5, wherein the specific process of performing the thermal-link analysis on the monitored object by the early warning analysis module comprises: establishing a rectangular coordinate system by taking the execution time of a monitoring period as an X axis and the temperature representation value WB of the monitoring period as a Y axis, marking a plurality of thermometer points in the rectangular coordinate system by taking the end time of the monitoring period as an abscissa and the temperature representation value WB of the monitoring period as an ordinate, marking a plurality of thermometer points in the rectangular coordinate system by taking the end time of the monitoring period as an abscissa and the maximum speed value of the transportation vehicle running in the monitoring period as an ordinate, connecting the thermometer points with the adjacent thermometer points on the right side to obtain speed Wen Xianduan, summing absolute values of all the thermometer segment slope values to obtain a heat-coupling coefficient, and comparing the heat-coupling coefficient with a preset heat-coupling threshold value: if the heat coupling coefficient is smaller than the heat coupling threshold value, judging that the abnormality of the internal storage environment in the monitoring period is not associated with the driving state, and sending a refrigeration maintenance signal to a mobile phone terminal of a manager by the early warning analysis module; if the heat coupling coefficient is greater than or equal to the heat coupling threshold, judging that the abnormality of the internal storage environment in the monitoring period is related to the driving state, and sending a driving constraint signal to a mobile phone terminal of a manager by the early warning analysis module.
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