CN116704716B

CN116704716B - Laboratory constant temperature and humidity abnormality alarm method and device and computer equipment

Info

Publication number: CN116704716B
Application number: CN202310759757.8A
Authority: CN
Inventors: 姜天宇; 郭铭凯; 王一飞
Original assignee: Wuhan Keyi Future Medical Laboratory Co ltd
Current assignee: Wuhan Keyi Future Medical Laboratory Co ltd
Priority date: 2023-06-26
Filing date: 2023-06-26
Publication date: 2023-12-29
Anticipated expiration: 2043-06-26
Also published as: CN116704716A

Abstract

The invention discloses a laboratory constant temperature and humidity abnormality alarm method, a laboratory constant temperature and humidity abnormality alarm device and computer equipment, and relates to the technical field of environment monitoring. According to the method, the position and the temperature and humidity are related according to the temperature and humidity acquired by a temperature and humidity sensor in real time, the temperature and humidity measured values of a plurality of real measurement points are obtained, the temperature and humidity three-dimensional distribution situation in a laboratory is obtained through inversion according to the temperature and humidity measured values, and finally, if the current temperature and humidity of the corresponding measurement point is not in a preset constant temperature and humidity interval according to the temperature and humidity three-dimensional distribution situation, the abnormality of the constant temperature and humidity environment in the laboratory is judged, and an alarm action is triggered, so that sudden high temperature, low temperature, high humidity and/or low humidity are not required to be transmitted to the sensor installation position, the constant temperature and humidity abnormality situation can be found in time, the treatment time of the abnormality situation can be guaranteed not to be delayed, the maintenance of the constant temperature and humidity environment in the laboratory is facilitated, and practical application and popularization are facilitated.

Description

Laboratory constant temperature and humidity abnormality alarm method and device and computer equipment

Technical Field

The invention belongs to the technical field of environmental monitoring, and particularly relates to a laboratory constant temperature and humidity abnormality alarming method, device and computer equipment.

Background

The Laboratory (Laboratory/Lab) is the site where the experiment is specifically conducted. The laboratory is a scientific cradle, is a base for scientific research, is a source of scientific development, and plays a very important role in the scientific development. The laboratory is required to maintain constant temperature and humidity basically, namely, the following reasons are considered: (1) In order to prevent the precision instrument from being influenced by non-constant temperature and humidity environment, the service life is shortened; (2) The change of temperature and humidity can affect the accuracy of test data and increase errors, so that the maintenance of constant temperature and humidity in a laboratory is very important.

The conventional laboratory constant temperature and humidity environment monitoring system collects temperature and humidity data through a temperature and humidity sensor installed at a specific position in a laboratory, and directly characterizes the temperature and humidity change condition of the whole laboratory global space with the data, but takes certain delay in the air heat transfer and humidity transfer process into consideration, so that when the constant temperature and humidity abnormal condition occurs suddenly at a certain position, if the certain position is far away from the installation position of the sensor, the temperature and humidity environment monitoring system can delay a period of time to be monitored by the system, so that the processing time of the abnormal condition can be delayed, and the maintenance of the laboratory constant temperature and humidity environment is not facilitated.

Disclosure of Invention

The invention aims to provide a laboratory constant temperature and humidity abnormality alarming method, a laboratory constant temperature and humidity abnormality alarming device, computer equipment and a computer readable storage medium, which are used for solving the problems that the existing laboratory constant temperature and humidity environment monitoring system has perception lag and delays processing time when the abnormal conditions of constant temperature and humidity occur suddenly.

In order to achieve the above purpose, the present invention adopts the following technical scheme:

in a first aspect, a laboratory constant temperature and humidity abnormality alarm method is provided, including:

receiving temperature detection signals and humidity detection signals acquired in real time by a plurality of temperature and humidity sensors, wherein each of the temperature and humidity sensors is arranged at different positions in a laboratory;

acquiring temperature actual measurement values at a plurality of actual measurement points in real time according to the temperature detection signals, and acquiring humidity actual measurement values at the plurality of actual measurement points in real time according to the humidity detection signals, wherein the plurality of actual measurement points are the positions of the plurality of temperature and humidity sensors;

according to the temperature actual measurement values of the plurality of actual measurement points, obtaining the temperature three-dimensional distribution condition in the laboratory through real-time inversion, and according to the humidity actual measurement values of the plurality of actual measurement points, obtaining the humidity three-dimensional distribution condition in the laboratory through real-time inversion;

And aiming at any measuring point in the laboratory, if the current temperature at the corresponding measuring point is not in a preset constant temperature interval according to the three-dimensional temperature distribution condition and/or the current humidity at the corresponding measuring point is not in the preset constant humidity interval according to the three-dimensional humidity distribution condition, judging that the laboratory is abnormal in the constant temperature and humidity environment, and triggering an alarm action.

Based on the above-mentioned summary of the invention, an alarm scheme for carrying out temperature and humidity space inversion and judging the abnormal conditions of any measuring point in a laboratory based on a limited temperature and humidity sensor is provided, namely, the relation between the position and the temperature and humidity is firstly carried out according to the temperature and humidity acquired by the temperature and humidity sensor in real time, the measured values of the temperature and humidity in a plurality of real measuring points are obtained, then the three-dimensional distribution conditions of the temperature and humidity in the laboratory are obtained through inversion according to the measured values, and finally, if any measuring point in the laboratory is found according to the three-dimensional distribution conditions of the temperature and humidity that the current temperature and humidity of the corresponding measuring point is not in a preset constant temperature and humidity interval, the abnormal conditions of the constant temperature and humidity environment in the laboratory are judged, and an alarm action is triggered, so that the abnormal conditions of the constant temperature and humidity can be found in time without sudden high temperature, low temperature and high humidity and/or low humidity are transmitted to the sensor installation position, the abnormal conditions of the constant temperature and humidity can be ensured not to delay the processing time of the abnormal conditions, the maintenance of the constant temperature and humidity environment in the laboratory is facilitated, and practical application and popularization are facilitated.

In one possible design, the plurality of temperature and humidity sensors includes temperature and humidity sensors disposed in a center of a ceiling, a center of a floor, and a center of each sidewall, respectively, of the laboratory.

In one possible design, the real-time inversion obtains a three-dimensional distribution of the temperature in the laboratory according to the measured values of the temperature at the plurality of real-time points, and obtains a three-dimensional distribution of the humidity in the laboratory according to the measured values of the humidity at the plurality of real-time points, including:

and according to the temperature and humidity measured values at the plurality of real measurement points, obtaining the three-dimensional distribution condition of the temperature and humidity in the laboratory based on real-time inversion of a Kriging interpolation method, wherein the temperature and humidity refers to temperature or humidity.

In one possible design, according to the measured values of the temperature and the humidity at the plurality of actual measurement points, the three-dimensional distribution situation of the temperature and the humidity in the laboratory is obtained based on real-time inversion of a kriging interpolation method, which comprises the following steps:

respectively calculating the temperature and humidity half variance of each pair of real measurement points in the plurality of real measurement points according to the temperature and humidity actual measurement values of the plurality of real measurement points to obtain temperature and humidity half variance values of the plurality of pairs of real measurement points, and calculating the distance values of the plurality of pairs of real measurement points according to the known coordinates of the plurality of real measurement points, wherein the temperature and humidity refer to temperature or humidity;

Determining hysteresis distance h ₁ And a longest distance value H among the distance values of the plurality of pairs of real measurement points _max Wherein h is ₁ Represents a positive number, H _max Representing greater than h ₁ Positive numbers of (a);

according to the hysteresis distance h ₁ The first interval (0, H _max ]Divided into a plurality of first subintervals as follows: (0, h) ₁ ],(h ₁ ,2*h ₁ ],…,((k-1)*h ₁ ,k*h ₁ ],…,((K-1)*h ₁ ,H _max ]Wherein k=celing (H _max /h ₁ ) Ceiling () represents an upward rounding function, K represents a positive integer less than K;

dividing the pairs of real measurement points into a plurality of first groups corresponding to the first subintervals one by one according to the attribution relation between the distance values of the pairs of real measurement points and the first subintervals;

according to the temperature and humidity half variance values and the distance values of the real measuring points, calculating to obtain a temperature and humidity half variance average value and a distance average value of each first group in the first groups;

fitting to obtain model coefficients of a plurality of experimental variation function models according to the temperature and humidity half variance average values and the distance average values of the first groups, wherein the temperature and humidity half variance average values are used as experimental variation function values in the fitting process, and the distance average values are used as regional variables to the distances from the points to be estimated in the fitting process;

according to the temperature and humidity measured values of the real measurement points, performing error analysis by using model coefficients of the experimental variation function models to obtain model quality evaluation index values of each experimental variation function model in the experimental variation function models;

According to the model quality evaluation index values of the experimental variation function models, determining an optimal experimental variation function model which can best meet the model optimal preset condition from the experimental variation function models;

determining m real measurement points around the target measurement point from the plurality of real measurement points according to the known coordinates of the plurality of real measurement points and the known coordinates of the target measurement point in the laboratory, wherein m represents a positive integer greater than 2;

according to the known coordinates of the target measuring point and the known coordinates of the m real measuring points, calculating to obtain distance values from the target measuring point to each of the m real measuring points, substituting the distance values as regional variables to the measuring point to be estimated into the optimal experimental variation function model, and then applying model coefficients of the optimal experimental variation function model to calculate to obtain experimental variation function values of the target measuring point and each of the m real measuring points;

according to the half variance value of the temperature and humidity of each pair of the m actual measurement points and the experimental variation function value of the target measurement point and each of the m actual measurement points, the following ordinary kriging equation set is established:

Wherein i and j each represent a positive integer, lambda _i Representing the weight coefficient corresponding to the ith real point in the m real points and to be solved, and gamma (x) _i ,x _j ) The temperature and humidity half-variance value corresponding to the ith real measurement point and the jth real measurement point in the m real measurement points is represented, u represents the Lagrange multiplier factor to be solved, and gamma (x) _i ,x ₀ ) The experimental variation function values of the target measuring point and the ith real measuring point are represented;

solving the common kriging equation set to obtain m weight coefficients corresponding to the m real measuring points one by one;

according to the measured temperature and humidity values of the m real measuring points,the temperature and humidity estimated value Z (x) of the target measuring point is calculated according to the following formula ₀ )：

Wherein Z (x) _i ) The temperature and humidity measured value of the ith real measurement point is represented;

and taking the temperature and humidity estimated values of all the target measuring points in the whole domain in the laboratory as the three-dimensional distribution condition of the temperature and humidity in the laboratory.

In one possible design, the hysteresis h is determined ₁ The method comprises the following steps S3031 to S3034:

s3031, in the interval (0, H) _max ]A value is selected as the hysteresis distance h ₁ Then step S3032 is performed, wherein H _max Representing the longest distance value among the distance values of the plurality of pairs of real measurement points;

S3032, aiming at each experimental variogram model in a plurality of experimental variogram models, according to the hysteresis distance h ₁ The current values of the temperature and the humidity measured values of the plurality of actual measurement points are adopted to acquire corresponding temperature and humidity estimated values of the plurality of actual measurement points in a cross verification mode, and then step S3033 is executed;

s3033, calculating corresponding model quality evaluation index values according to the temperature and humidity actual measurement values at the plurality of actual measurement points and the corresponding temperature and humidity estimation values at the plurality of actual measurement points aiming at each experimental variation function model, and executing step S3034;

s3034, judging whether model quality evaluation index values of the experimental variation function models meet preset iteration stop conditions or not, and if yes, setting the hysteresis distance h ₁ The current value is determined to be the final value, otherwise in the interval (0, H _max ]Re-selecting a value as the hysteresis h ₁ Then step S3032 is performed.

In one possible design, when the current temperature of a certain measuring point in the laboratory is found not to be within the preset constant temperature interval according to the three-dimensional temperature distribution condition, the method further includes:

if the current temperature of a certain measuring point is lower than the preset constant temperature interval, starting heating equipment closest to the certain measuring point to heat until the temperature of the certain measuring point is found to return to the preset constant temperature interval, wherein the heating equipment is arranged in the laboratory;

If the current temperature of a certain measuring point is higher than the preset constant temperature interval, starting the refrigerating equipment closest to the certain measuring point to cool until the temperature of the certain measuring point is found to return to the preset constant temperature interval, wherein the refrigerating equipment is arranged in the laboratory.

In one possible design, when the current humidity of a certain measuring point in the laboratory is found not to be in the preset constant humidity interval according to the three-dimensional distribution situation of the humidity, the method further includes:

if the current humidity of the certain measuring point is lower than the preset constant humidity interval, starting an air humidifier nearest to the certain measuring point to humidify until the humidity of the certain measuring point is found to return to the preset constant humidity interval, wherein the air humidifier is arranged in the laboratory;

and if the current humidity of the certain measuring point is higher than the preset constant humidity interval, starting heating equipment closest to the certain measuring point to dry until the humidity of the certain measuring point is found to return to the preset constant humidity interval, wherein the heating equipment is arranged in the laboratory.

The second aspect provides a laboratory constant temperature and humidity abnormality alarm device, which comprises a detection signal receiving module, a temperature and humidity correlation module, a temperature and humidity distribution inversion module and an abnormality alarm triggering module which are sequentially connected in a communication way;

the detection signal receiving module is used for receiving temperature detection signals and humidity detection signals acquired in real time by a plurality of temperature and humidity sensors, wherein each temperature and humidity sensor in the plurality of temperature and humidity sensors is respectively arranged at different positions in a laboratory;

the temperature and humidity correlation module is used for acquiring temperature actual measurement values at a plurality of actual measurement points in real time according to the temperature detection signals and acquiring humidity actual measurement values at the plurality of actual measurement points in real time according to the humidity detection signals, wherein the plurality of actual measurement points are the positions of the plurality of temperature and humidity sensors;

the temperature and humidity distribution inversion module is used for obtaining the three-dimensional distribution condition of the temperature in the laboratory through real-time inversion according to the actual measurement values of the temperature at the plurality of actual measurement points, and obtaining the three-dimensional distribution condition of the humidity in the laboratory through real-time inversion according to the actual measurement values of the humidity at the plurality of actual measurement points;

The abnormal alarm triggering module is used for judging that the laboratory constant temperature and humidity environment is abnormal and triggering an alarm action if the current temperature of the corresponding measuring point is not in a preset constant temperature interval according to the three-dimensional temperature distribution condition and/or the current humidity of the corresponding measuring point is not in a preset constant humidity interval according to the three-dimensional humidity distribution condition aiming at any measuring point in the laboratory.

In a third aspect, the present invention provides a computer device comprising a memory, a processor and a transceiver in communication connection in sequence, wherein the memory is configured to store a computer program, the transceiver is configured to send and receive a message, and the processor is configured to read the computer program and execute the laboratory constant temperature and humidity abnormality alarm method according to the first aspect or any of the possible designs of the first aspect.

In a fourth aspect, the present invention provides a computer readable storage medium having instructions stored thereon which, when executed on a computer, perform the laboratory constant temperature and humidity anomaly alarm method as described in the first aspect or any of the possible designs of the first aspect.

In a fifth aspect, the present invention provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the laboratory constant temperature and humidity anomaly alarm method as described in the first aspect or any of the possible designs of the first aspect.

The beneficial effect of above-mentioned scheme:

(1) The invention creatively provides an alarm scheme for carrying out temperature and humidity space inversion and judging the abnormal conditions of temperature and humidity of any measuring point in a laboratory based on a limited temperature and humidity sensor, namely, carrying out position and temperature and humidity correlation according to the temperature and humidity acquired by the temperature and humidity sensor in real time to obtain the temperature and humidity measured values of a plurality of real measuring points, then carrying out inversion according to the temperature and humidity measured values to obtain the three-dimensional distribution conditions of the temperature and humidity in the laboratory, finally judging that the constant temperature and humidity environment of the laboratory is abnormal and triggering an alarm action if the current temperature and humidity of the corresponding measuring point is not in a preset constant temperature and humidity interval according to the three-dimensional distribution conditions of the temperature and humidity, so that the sudden high temperature, low temperature, high humidity and/or low humidity are not required to be transmitted to the sensor installation position, the abnormal conditions of the constant temperature and the constant humidity can be found in time, further, the processing time for the abnormal conditions can not be delayed, the maintenance of the constant temperature and the constant humidity environment of the laboratory is facilitated, and practical application and popularization are facilitated;

(2) The three-dimensional temperature and humidity distribution result meeting the use requirement and the precision requirement can be quickly and efficiently obtained by only depending on the actual measurement data of a small number of actual measurement points, the required time is greatly shortened, and the three-dimensional temperature and humidity distribution method has certain theoretical significance and higher engineering practical value;

(3) The proper hysteresis distance h capable of obtaining a more ideal model can be automatically determined by a cross-validation and iteration mode ₁ So as to further facilitate the rapid and efficient acquisition of the final three-dimensional temperature and humidity distribution result.

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 schematic flow chart of a laboratory constant temperature and humidity abnormality alarm method according to an embodiment of the present application.

Fig. 2 is a schematic structural diagram of a laboratory constant temperature and humidity abnormality alarm device according to an embodiment of the present application.

Fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present application.

Detailed Description

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be briefly described below with reference to the accompanying drawings and the description of the embodiments or the prior art, and it is obvious that the following description of the structure of the drawings is only some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art. It should be noted that the description of these examples is for aiding in understanding the present invention, but is not intended to limit the present invention.

It should be understood that although the terms first and second, etc. may be used herein to describe various objects, these objects should not be limited by these terms. These terms are only used to distinguish one object from another. For example, a first object may be referred to as a second object, and similarly a second object may be referred to as a first object, without departing from the scope of example embodiments of the invention.

It should be understood that for the term "and/or" that may appear herein, it is merely one association relationship that describes an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: three cases of A alone, B alone or both A and B exist; as another example, A, B and/or C, can represent the presence of any one of A, B and C or any combination thereof; for the term "/and" that may appear herein, which is descriptive of another associative object relationship, it means that there may be two relationships, e.g., a/and B, it may be expressed that: the two cases of A and B exist independently or simultaneously; in addition, for the character "/" that may appear herein, it is generally indicated that the context associated object is an "or" relationship.

Examples:

as shown in fig. 1, the laboratory constant temperature and humidity abnormality alarm method provided in the first aspect of the present embodiment may be performed by, but not limited to, a computer device having a certain computing resource and respectively connected to a temperature and humidity sensor, an alarm reminding device, a heating device, a cooling device and an air humidifier in a communication manner, for example, a laboratory server, a personal computer (Personal Computer, PC, a multipurpose computer with a size, price and performance suitable for personal use, a desktop computer, a notebook computer, a small notebook computer, a tablet computer, an ultra-notebook computer, etc. all belong to a personal computer), a smart phone, a personal digital assistant (Personal Digital Assistant, PDA) or an electronic device such as a portable device. As shown in FIG. 1, the laboratory constant temperature and humidity abnormality alarm method may include, but is not limited to, the following steps S1 to S4.

S1, receiving temperature detection signals and humidity detection signals acquired in real time by a plurality of temperature and humidity sensors, wherein each of the temperature and humidity sensors is arranged at different positions in a laboratory.

In the step S1, the temperature and humidity sensor is used for collecting the temperature and humidity of the location, and may be implemented by using existing products. In order to be able to collect as comprehensive temperature and humidity data as possible with a small number of sensors, it is preferred that the plurality of temperature and humidity sensors include, but are not limited to, temperature and humidity sensors respectively arranged in the center of the top surface, the center of the ground and the center of each side wall of the laboratory, for example, when the laboratory is a square room, only six temperature and humidity sensors need to be arranged. In addition, the transmission mode of the temperature detection signal and the humidity detection signal can be realized based on a wired communication mode in particular but not limited to.

S2, acquiring temperature actual measurement values of a plurality of actual measurement points in real time according to the temperature detection signals, and acquiring humidity actual measurement values of the plurality of actual measurement points in real time according to the humidity detection signals, wherein the plurality of actual measurement points are positions of the plurality of temperature and humidity sensors.

In the step S2, specific obtaining manners of the measured temperature value and the measured humidity value include, but are not limited to, a conventional analog-to-digital conversion processing manner.

S3, according to the temperature actual measurement values of the plurality of actual measurement points, obtaining the temperature three-dimensional distribution situation in the laboratory through real-time inversion, and according to the humidity actual measurement values of the plurality of actual measurement points, obtaining the humidity three-dimensional distribution situation in the laboratory through real-time inversion.

In the step S3, because the air heat transfer process is a molecular thermal motion process and the moisture transfer process is a free diffusion process of water vapor molecules, they have corresponding spatial characteristics respectively, and based on the spatial characteristics, the temperature and humidity measured values of the local space (i.e. the temperature measured values/humidity measured values at the plurality of real measurement points) can be utilized to invert to obtain the temperature and humidity measured values of the global space, so as to obtain the three-dimensional temperature distribution condition and the three-dimensional humidity distribution condition in the laboratory. Because the temperature and humidity of a certain point are related to the temperature and humidity of the points around the point and can be derived from the temperature and humidity of the points around the point, specifically, the three-dimensional distribution situation of the temperature and humidity in the laboratory can be obtained by real-time inversion based on the measured temperature and humidity values of the plurality of real points (also called the kriging method, which is a spatial interpolation method proposed by the south african engineer kriging DG, the basic assumption is that the attribute value of a point is related to the attribute value of the points around the point and can be derived from the attribute value of the points around the point, and the three-dimensional distribution situation of the temperature and humidity in the laboratory is obtained by taking a variation function/variation function as a calculation tool and combining an optimal and unbiased estimation method with strong spatial correlation of structural analysis. In addition, the temperature three-dimensional distribution condition and the humidity three-dimensional distribution condition can be output and displayed in an isosurface mode, and inversion updating can be carried out along with updating results of the temperature and humidity measured values.

S4, aiming at any measuring point in the laboratory, if the current temperature of the corresponding measuring point is found not to be in a preset constant temperature interval in real time according to the three-dimensional temperature distribution condition and/or the current humidity of the corresponding measuring point is found not to be in a preset constant humidity interval in real time according to the three-dimensional humidity distribution condition, judging that the constant temperature and humidity environment of the laboratory is abnormal, and triggering an alarm action.

In the step S4, the preset constant temperature interval and the preset constant humidity interval may be specifically determined in advance based on the actual requirement of the laboratory, for example, the preset constant temperature interval is specifically 21.4 ℃ to 21.6 ℃, and the preset constant humidity interval is specifically 50.0% to 54.0%. Further, the triggering alarm action may include, but is not limited to, specifically: an alarm prompt message is sent to a laboratory management platform or a laboratory manager through alarm reminding equipment such as an alarm and/or a short message cat and the like so that the laboratory manager can respond and treat the abnormal conditions of constant temperature and constant humidity in time.

In the step S4, the temperature control adjustment process may also be automatically performed when a constant temperature abnormal condition is found, that is, when the current temperature of a certain measuring point in the laboratory is found not to be in the preset constant temperature interval according to the temperature three-dimensional distribution condition, the method further includes, but is not limited to: if the current temperature of a certain measuring point is lower than the preset constant temperature interval, starting heating equipment closest to the certain measuring point to heat until the temperature of the certain measuring point is found to return to the preset constant temperature interval, wherein the heating equipment is arranged in the laboratory; if the current temperature of a certain measuring point is higher than the preset constant temperature interval, starting the refrigerating equipment closest to the certain measuring point to cool until the temperature of the certain measuring point is found to return to the preset constant temperature interval, wherein the refrigerating equipment is arranged in the laboratory. The aforementioned heating and cooling devices may be separate existing devices, such as a condenser (i.e. as the heating device) and an evaporator (i.e. as the cooling device) in a heat pump system, or may be integrated existing devices, such as an air conditioner. Therefore, the constant temperature environment of the laboratory can be automatically maintained by the temperature control and adjustment mode. In addition, the heating device may be a hot air supply port (increasing the flow rate of the hot air supply corresponds to starting the heating device) in the existing heating and ventilation system, and the cooling device may be a cold air supply port (increasing the flow rate of the cold air supply corresponds to starting the cooling device) in the existing heating and ventilation system.

In the step S4, the humidity control adjustment process may also be automatically performed when a constant humidity abnormal condition is found, that is, when the current humidity of a certain measurement point in the laboratory is found not to be in the preset constant humidity range according to the three-dimensional humidity distribution condition, the method further includes, but is not limited to: if the current humidity of the certain measuring point is lower than the preset constant humidity interval, starting an air humidifier nearest to the certain measuring point to humidify until the humidity of the certain measuring point is found to return to the preset constant humidity interval, wherein the air humidifier is arranged in the laboratory; and if the current humidity of the certain measuring point is higher than the preset constant humidity interval, starting heating equipment closest to the certain measuring point to dry until the humidity of the certain measuring point is found to return to the preset constant humidity interval, wherein the heating equipment is arranged in the laboratory. The air humidifier and the heating device can also be realized by adopting the existing corresponding products. Therefore, the constant humidity environment of the laboratory can be automatically maintained by the humidity control adjustment mode.

According to the laboratory constant temperature and constant humidity abnormality alarming method described in the steps S1-S4, an alarming scheme based on temperature and humidity space inversion and temperature and humidity abnormality judgment of any measuring point in a laboratory is provided, namely, position and temperature and humidity correlation are carried out according to temperature and humidity acquired by the temperature and humidity sensor in real time, temperature and humidity measured values of a plurality of real measuring points are obtained, three-dimensional temperature and humidity distribution conditions in the laboratory are obtained through inversion according to the temperature and humidity measured values, and finally, for any measuring point in the laboratory, if the current temperature and humidity of the corresponding measuring point is found to be not in a preset constant temperature and constant humidity interval according to the three-dimensional temperature and humidity distribution conditions, abnormality of the laboratory constant temperature and constant humidity environment is judged, alarming actions are triggered, and therefore sudden high temperature, low temperature, high humidity and/or low humidity are not required to be transmitted to the installation position of the sensor, the constant temperature and constant humidity abnormality can be found timely, the treatment time of the abnormal situation can not be delayed, and the maintenance of the constant temperature and constant humidity environment of the laboratory is facilitated, and practical application and popularization are facilitated.

The embodiment further provides a possible design one of how to obtain the three-dimensional distribution of the temperature and the humidity based on the inversion of the kriging interpolation based on the technical scheme of the first aspect, that is, according to the measured values of the temperature and the humidity at the plurality of real measurement points, the three-dimensional distribution of the temperature and the humidity in the laboratory based on the inversion of the kriging interpolation based on the real-time inversion of the kriging interpolation, including but not limited to the following steps S301 to S314.

S301, respectively calculating the temperature and humidity half variance of each pair of real measurement points in the plurality of real measurement points according to the temperature and humidity actual measurement values of the plurality of real measurement points to obtain the temperature and humidity half variance values of the plurality of pairs of real measurement points, and further calculating the distance values of the plurality of pairs of real measurement points according to the known coordinates of the plurality of real measurement points, wherein the temperature and humidity refer to temperature or humidity.

In the step S301, the temperature and humidity half variance represents half of the square of the difference between the measured temperature and humidity values of the two measurement points, i.e. the temperature and humidity half variance values of the measurement points a and BWherein Z is _A Representing the measured temperature and humidity value Z of the measuring point A _B And the measured temperature and humidity value of the measuring point B is shown. The temperature and humidity half variance of any two points is related to the distance between any two points, so that the distance values of the plurality of pairs of actual measurement points also need to be calculated.

Before the step S301, it is considered that the estimation is performed based on a common kriging method, and the data required by the common kriging method is subjected to normal distribution, preferably, before calculating the half variance of the temperature and humidity of each pair of real measurement points in the plurality of real measurement points according to the measured values of the temperature and humidity of the real measurement points, the method further includes, but is not limited to: judging whether the temperature and humidity measured values of the real measuring points are subjected to normal distribution or not; if not, performing power transformation or logarithmic transformation on the temperature and humidity measured values of the plurality of actual measurement pointsAnd (3) performing replacement processing to obtain a new temperature and humidity actual measurement value which is subjected to normal distribution and is of the plurality of actual measurement points. The specific way of the above-mentioned judgment is the existing conventional way, for example based on the condition of obeying normal distribution (i.e. if the random variable X obeys a mathematical expectation of μ, variance of σ ² Is expressed as N (mu, sigma) ² ) A) to make the determination. The specific formula of the power transformation process is as follows:the specific formula of the logarithmic transformation processing is as follows:wherein Z (x) represents the measured value of temperature and humidity before treatment,>the obtained measured new temperature and humidity value is represented, and eta represents a preset positive coefficient.

S302, determining a hysteresis distance h ₁ And a longest distance value H among the distance values of the plurality of pairs of real measurement points _max Wherein h is ₁ Represents a positive number, H _max Representing greater than h ₁ Positive numbers of (a).

In the step S302, the hysteresis distance is an academic word in the kriging method, and the determination may be performed manually, randomly, or in some automatic manner.

S303, according to the hysteresis distance h ₁ The first interval (0, H _max ]Divided into a plurality of first subintervals as follows: (0, h) ₁ ],(h ₁ ,2*h ₁ ],…,((k-1)*h ₁ ,k*h ₁ ],…,((K-1)*h ₁ ,H _max ]Wherein k=celing (H _max /h ₁ ) Ceiling () represents an upward rounding function, and K represents a positive integer less than K.

In the step S303, for example, if the hysteresis distance h ₁ Is 1m, the longest distance value H _max For 10 meters, the first interval may be divided into 10 (i.e., k=10) first sub-intervals.

S304, dividing the real measurement points into a plurality of first groups corresponding to the first subintervals one by one according to the attribution relation between the distance values of the real measurement points and the first subintervals.

In the step S304, for example, if the distance value of a certain pair of real measurement points is 6.8, the certain pair of real measurement points may be divided into a certain first group corresponding to a certain first subinterval (6, 7), and so on.

S305, calculating to obtain a temperature and humidity half variance average value and a distance average value of each first group in the plurality of first groups according to the temperature and humidity half variance values and the distance values of the plurality of pairs of real measurement points.

S306, fitting to obtain model coefficients of a plurality of experimental variation function models according to the temperature and humidity half variance average values and the distance average values of the first groups, wherein the temperature and humidity half variance average values are used as experimental variation function values in the fitting process, and the distance average values are used as regional variables to the distances from the to-be-estimated measuring points in the fitting process.

In the step S306, the experimental variogram model is an important research tool of the kriging method, and specifically, the plurality of experimental variogram models include, but are not limited to, any combination of the following models (a) - (C):

(A) A spherical model, expressed as:

(B) An exponential model, expressed as:

(C) The Gaussian model has the expression:

in the above expression, γ (h) represents an experimental variationThe difference function value, h represents the distance from the regional variable to the point to be estimated, C ₀ The base value is represented as a first model coefficient, C represents the camber (i.e., represents the maximum value of the spatial variation of the zoned variable) as a second model coefficient, and a represents the course (i.e., represents the range in which the zoned variable has relevance) as a third model coefficient. The model coefficients that need to be fitted include the abutment values C ₀ Arch height C and variation a. The specific manner of fitting described above may be, but is not limited to, the use of least squares. In addition, for the non-last group to which the non-real-point pair belongs in the first groups, the corresponding temperature and humidity half variance average value and the distance average value are considered to be zero, so that the fitting value is not provided, and the non-last group needs to be skipped in the fitting process.

S307, performing error analysis by using model coefficients of the experimental variation function models according to the temperature and humidity actual measurement values of the real measurement points to obtain model quality evaluation index values of each experimental variation function model in the experimental variation function models.

In the step S307, the model quality assessment index values include, but are not limited to, average error values, root mean square error values, normalized root mean square error values, and/or average standard error values, and the calculation formulas of the foregoing index values are as follows:

average error value

Root mean square error value

Normalized root mean square error value

Average standard error value

In the above formula, NRepresents the total number of real measurement points, n represents a positive integer, Z (x _n ) The temperature and humidity measured value of the nth actual measurement point is shown,representing the temperature and humidity estimated value delta of the nth actual measurement point ² Representing the square root of the variance. Because the temperature and humidity estimation value is required in the process of obtaining the model quality estimation index value, specifically, according to the temperature and humidity actual measurement values of the real measurement points, the model coefficients of the experimental variogram models are applied to perform error analysis, so as to obtain the model quality estimation index value of each experimental variogram model in the experimental variogram models, which includes but is not limited to the following steps S3071 to S3072.

S3071, aiming at each experimental variation function model in the experimental variation function models, acquiring corresponding temperature and humidity estimated values of the real measurement points by adopting a cross verification mode according to the temperature and humidity measured values of the real measurement points and corresponding model coefficients.

In the step S3071, the specific idea of the cross-validation method is as follows: removing one of the plurality of actual measurement points, calculating a temperature and humidity estimated value of the removed point by using the temperature and humidity measured values of the remaining actual measurement points, and repeating the operation until the temperature and humidity estimated values of all the actual measurement points are obtained, namely, specifically, aiming at each experimental variogram model in the plurality of experimental variogram models, obtaining the temperature and humidity estimated values of the corresponding and the plurality of actual measurement points by adopting a cross verification mode according to the temperature and humidity measured values of the plurality of actual measurement points and corresponding model coefficients, wherein the method comprises the following steps S30711 to S30712.

S30711. for each target real point (i.e. the removed one) among the plurality of real points, all other real points (i.e. the remaining real points) among the plurality of real points are determined as corresponding plurality of reference real points.

S30712, calculating corresponding temperature and humidity estimated values according to the model parameters of a certain experimental variogram model and the temperature and humidity measured values of a plurality of reference actual points of the certain target actual points according to the certain experimental variogram model and the certain target actual points in the plurality of experimental variogram models according to the following steps S307121-S307123.

S307121, calculating distance values from the certain target actual measurement point to each of the plurality of reference actual measurement points of the certain target actual measurement point according to the known coordinates of the plurality of reference actual measurement points of the certain target actual measurement point and the known coordinates of the certain target actual measurement point, substituting the distance values as regional variables to the to-be-estimated measurement point into the certain experimental variation function model, and then calculating experimental variation function values of the certain target actual measurement point and each of the plurality of reference actual measurement points of the certain target actual measurement point by applying model parameters of the certain experimental variation function model.

S307122, according to the half variance value of the temperature and the humidity of each pair of the reference actual measurement points in the plurality of reference actual measurement points of the certain target actual measurement point and the experimental variation function value of each reference actual measurement point in the plurality of reference actual measurement points of the certain target actual measurement point, establishing and solving a common Kriging equation set to obtain a plurality of reference weight coefficients corresponding to the plurality of reference actual measurement points of the certain target actual measurement point one by one.

In the step S307122, the specific establishing and solving process of the common kriging equation set may be derived with reference to the subsequent steps S311-S312, which are not described herein.

S307123, calculating to obtain a temperature and humidity estimated value of the certain target actual measurement point according to the temperature and humidity actual measurement values of the plurality of reference actual measurement points of the certain target actual measurement point and the plurality of reference weight coefficients.

In the step S307123, a specific calculation formula can be derived with reference to the following step S313, and will not be described herein.

S3072, calculating corresponding model quality evaluation index values according to the temperature and humidity measured values of the real measurement points and the temperature and humidity estimated values of the real measurement points aiming at the experimental variation function models.

S308, determining an optimal experimental variogram model which can best meet the model optimal preset condition from the experimental variogram models according to the model quality evaluation index values of the experimental variogram models.

In the step S308, the model preferably includes, but is not limited to, having an average error value close to 0, a normalized root mean square error value close to 1, and/or a root mean square error value close to an average standard error value. The better the model is satisfied with the preset condition, the better the quality of the corresponding model is.

S309, determining m real measuring points around the target measuring point from the real measuring points according to the known coordinates of the real measuring points and the known coordinates of the target measuring point in the laboratory, wherein m represents a positive integer greater than 2.

In the step S309, the target measurement point may be a real measurement point or an non-real measurement point (i.e., a measurement point that needs to be estimated). The specific area around the target measuring point may be a circular area with the target measuring point as the center and a radius of a specific value, where the specific value may be adjusted appropriately according to the search result of the actual measuring point, for example, the radius value is enlarged when m is too small, and the radius value is reduced when m is too large.

S310, calculating distance values from the target measuring point to each of the m real measuring points according to the known coordinates of the target measuring point and the known coordinates of the m real measuring points, substituting the distance values as regional variables to the to-be-estimated measuring points into the optimal experimental variation function model, and then applying model coefficients of the optimal experimental variation function model to calculate experimental variation function values of the target measuring point and each of the m real measuring points.

S311, according to the half variance value of the temperature and the humidity of each pair of the m actual measurement points and the experimental variation function values of the target measurement point and each of the m actual measurement points, establishing the following ordinary kriging equation set:

wherein i and j each represent a positive integer, lambda _i Representing the weight coefficient corresponding to the ith real point in the m real points and to be solved, and gamma (x) _i ,x _j ) The temperature and humidity half-variance value corresponding to the ith real measurement point and the jth real measurement point in the m real measurement points is represented, u represents the Lagrange multiplier factor to be solved, and gamma (x) _i ,x ₀ ) And the experimental variation function value of the target measuring point and the ith real measuring point is represented.

In the step S311, the normal kriging equation set is established based on kriging interpolation and includes an equation set of m+1 equations, wherein, An unbiased estimation condition for the kriging interpolation.

S312, solving the common kriging equation set to obtain m weight coefficients corresponding to the m real measurement points one by one.

In the step S312, since there are only m+1 unknowns in the ordinary kriging equation set, m weight coefficients corresponding to the m real points one to one can be obtained by solving based on a conventional solving equation means.

S313, according to the temperature and humidity actual measurement values of the m actual measurement points, calculating to obtain a temperature and humidity estimated value Z (x) of the target measurement point according to the following formula ₀ )：

Wherein Z (x) _i ) And the temperature and humidity measured value of the ith real measurement point is shown.

In the step S313, since the measured temperature and humidity value may be regarded as an attribute value of a known point and the temperature and humidity may be regarded as a plurality of realizations of the random field, the temperature and humidity estimation result in the laboratory may be estimated/interpolated by the above formula.

S314, taking the temperature and humidity estimated values of all the target measuring points in the whole domain of the laboratory as the three-dimensional distribution condition of the temperature and humidity in the laboratory.

Based on the first possible design, the three-dimensional temperature and humidity distribution result meeting the use requirement and the precision requirement can be quickly and efficiently obtained by only depending on the actual measurement data of a small number of actual measurement points, the required time is greatly shortened, and the three-dimensional temperature and humidity distribution method has certain theoretical significance and higher engineering practical value.

The embodiment also provides a method for automatically determining the proper hysteresis distance h based on the technical scheme of the first possible design ₁ Two possible designs of (2), i.e. determining the hysteresis h ₁ Including but not limited to the following steps S3031 to S3034.

S3031, in the interval (0, H) _max ]A value is selected as the hysteresis distance h ₁ Then step S3032 is performed, wherein H _max The longest distance value among the distance values of the plurality of pairs of real measurement points is represented.

In the step S3031, the specific selection method may be, but not limited to, a random value method.

S3032, aiming at each experimental variogram model in a plurality of experimental variogram models, according to the hysteresis distance h ₁ And (3) acquiring corresponding temperature and humidity estimated values of the plurality of actual measurement points by adopting a cross verification mode and then executing step S3033.

In the step S3032, the specific concept of the cross-validation method is similar to that of the step S3071, specifically, for each experimental variogram model among a plurality of experimental variogram models, according to the hysteresis distance h ₁ The method comprises the steps of obtaining corresponding temperature and humidity estimated values of the plurality of actual measurement points by adopting a cross verification mode, including but not limited to the following steps S30321 to S30322:

S30321. for each target real point among the plurality of real points, determining all other real points among the plurality of real points as corresponding plurality of reference real points.

S30322, aiming at a certain experimental variogram model in a plurality of experimental variogram models and a certain target actual point in a plurality of actual points, according to the hysteresis distance h ₁ The corresponding estimated temperature and humidity values are obtained by calculating the current value of the experimental variation function model, the model parameters of the experimental variation function model and the actual temperature and humidity values of a plurality of reference actual points of the target actual point according to the following steps S303221 to S303228.

S303221 determining the longest distance value among the distance values of the plurality of pairs of reference real pointsThe plurality of pairs of reference real points refer to all point pairs in the plurality of reference real points of the certain target real point.

S303222 according to the hysteresis distance h ₁ Will be the second intervalDivided into a plurality of second subintervals as follows:

wherein,

the celing () represents a round-up function,representing less than->Is a positive integer of (a).

S303223, dividing the plurality of pairs of reference real measurement points into a plurality of second groups corresponding to the plurality of second subintervals one by one according to the attribution relation between the distance values of the plurality of pairs of reference real measurement points and the plurality of second subintervals.

S303224, calculating to obtain a temperature and humidity half variance average value and a distance average value of each second group in the plurality of second groups according to the temperature and humidity half variance values and the distance values of the plurality of pairs of reference real points.

S303225, fitting to obtain a model coefficient of the experimental variation function model according to the temperature and humidity half variance average value and the distance average value of each second group, wherein the temperature and humidity half variance average value is used as an experimental variation function value in the fitting process, and the distance average value is used as a distance from a regional variable to a to-be-estimated measuring point in the fitting process.

S303226, calculating distance values from the certain target actual measurement point to each of the plurality of reference actual measurement points of the certain target actual measurement point according to the known coordinates of the plurality of reference actual measurement points of the certain target actual measurement point and the known coordinates of the certain target actual measurement point, substituting the distance values as regional variables to the to-be-estimated measurement point into the certain experimental variation function model, and then applying model parameters of the certain experimental variation function model to calculate experimental variation function values of the certain target actual measurement point and each of the plurality of reference actual measurement points of the certain target actual measurement point.

S303227, according to the half variance value of the temperature and the humidity of each pair of the reference actual measurement points in the plurality of reference actual measurement points of the certain target actual measurement point and the experimental variation function value of each reference actual measurement point in the plurality of reference actual measurement points of the certain target actual measurement point, establishing and solving a common Kriging equation set to obtain a plurality of reference weight coefficients corresponding to the plurality of reference actual measurement points of the certain target actual measurement point one by one.

S303228, calculating to obtain the temperature and humidity estimated value of the certain target actual measurement point according to the temperature and humidity actual measurement values of the plurality of reference actual measurement points of the certain target actual measurement point and the plurality of reference weight coefficients.

The details of steps S303221 to S303228 can be derived by referring to similar steps in the first aspect, and are not described herein.

S3033, calculating corresponding model quality evaluation index values according to the temperature and humidity measured values of the real measurement points and the temperature and humidity estimated values of the real measurement points aiming at the experimental variation function models, and executing step S3034.

In the step S3034, the iteration stop condition may be set based on, but not limited to, some index threshold, for example, including an average error value smaller than a preset average error threshold and/or a normalized root mean square error value greater than a preset normalized root mean square error threshold, etc., so as to measure whether a more ideal experimental variation function model is obtained. In addition, the specific manner of reselection may be, but not limited to, a random value manner.

Based on the second design, the appropriate hysteresis distance h for obtaining the ideal model can be automatically determined by the cross-validation and iteration modes ₁ So as to further facilitate the rapid and efficient acquisition of the final three-dimensional temperature and humidity distribution result.

As shown in fig. 2, in a second aspect of the present embodiment, a virtual device for implementing the laboratory constant temperature and humidity abnormality alarm method according to the first aspect or any possible design of the first aspect is provided, where the virtual device includes a detection signal receiving module, a temperature and humidity correlation module, a temperature and humidity distribution inversion module, and an abnormality alarm triggering module that are sequentially connected in a communication manner;

The working process, working details and technical effects of the foregoing device provided in the second aspect of the present embodiment may refer to the first aspect or any possible design of the laboratory constant temperature and humidity abnormality alarm method in the first aspect, which are not described herein.

As shown in fig. 3, a third aspect of the present embodiment provides a computer device for executing the laboratory constant temperature and humidity abnormality alarm method according to the first aspect or any of the possible designs of the first aspect, where the computer device includes a memory, a processor, and a transceiver, which are sequentially connected in communication, where the memory is configured to store a computer program, the transceiver is configured to send and receive a message, and the processor is configured to read the computer program, and execute the laboratory constant temperature and humidity abnormality alarm method according to the first aspect or any of the possible designs of the first aspect. By way of specific example, the Memory may include, but is not limited to, random-Access Memory (RAM), read-Only Memory (ROM), flash Memory (Flash Memory), first-in first-out Memory (First Input First Output, FIFO), and/or first-in last-out Memory (First Input Last Output, FILO), etc.; the processor may be, but is not limited to, a microprocessor of the type STM32F105 family. In addition, the computer device may include, but is not limited to, a power module, a display screen, and other necessary components.

The working process, working details and technical effects of the foregoing computer device provided in the third aspect of the present embodiment may refer to the first aspect or any possible design of the laboratory constant temperature and humidity abnormality alarm method in the first aspect, which are not described herein.

A fourth aspect of the present embodiment provides a computer-readable storage medium storing instructions comprising the laboratory constant temperature and humidity abnormality alarm method as described in the first aspect or any of the possible designs of the first aspect, i.e. the computer-readable storage medium has instructions stored thereon that, when executed on a computer, perform the laboratory constant temperature and humidity abnormality alarm method as described in the first aspect or any of the possible designs of the first aspect. The computer readable storage medium refers to a carrier for storing data, and may include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash Memory, and/or a Memory Stick (Memory Stick), where the computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable devices.

The working process, working details and technical effects of the foregoing computer readable storage medium provided in the fourth aspect of the present embodiment may refer to the laboratory constant temperature and humidity abnormality alarm method as described in the first aspect or any possible design in the first aspect, and will not be described herein.

A fifth aspect of the present embodiments provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the laboratory constant temperature and humidity anomaly alarm method as described in the first aspect or any of the possible designs of the first aspect. Wherein the computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus.

Finally, it should be noted that: the foregoing description is only of the preferred embodiments of the invention and is not intended to limit the scope of the invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. The laboratory constant temperature and humidity abnormality alarming method is characterized by comprising the following steps of:

According to the temperature actual measurement values of the plurality of actual measurement points, obtaining the three-dimensional distribution condition of the temperature in the laboratory through real-time inversion, and according to the humidity actual measurement values of the plurality of actual measurement points, obtaining the three-dimensional distribution condition of the humidity in the laboratory through real-time inversion, specifically comprising: respectively calculating the temperature and humidity half variance of each pair of real measurement points in the plurality of real measurement points according to the temperature and humidity actual measurement values of the plurality of real measurement points to obtain temperature and humidity half variance values of the plurality of pairs of real measurement points, and calculating the distance values of the plurality of pairs of real measurement points according to the known coordinates of the plurality of real measurement points, wherein the temperature and humidity refer to temperature or humidity; determining hysteresis distance h ₁ And a longest distance value H among the distance values of the plurality of pairs of real measurement points _max Wherein h is ₁ Represents a positive number, H _max Representing greater than h ₁ Positive numbers of (a); according to the hysteresis distance h ₁ The first interval (0, H _max ]Divided into a plurality of first subintervals as follows: (0, h) ₁ ],(h ₁ ,2*h ₁ ],…,((k-1)*h ₁ ,k*h ₁ ],…,((K-1)*h ₁ ,H _max ]Wherein k=celing (H _max /h ₁ ) Ceiling () represents an upward rounding function, K represents a positive integer less than K; dividing the pairs of real measurement points into a plurality of first groups corresponding to the first subintervals one by one according to the attribution relation between the distance values of the pairs of real measurement points and the first subintervals; according to the temperature and humidity half variance values and the distance values of the real measuring points, calculating to obtain a temperature and humidity half variance average value and a distance average value of each first group in the first groups; fitting to obtain model coefficients of a plurality of experimental variation function models according to the temperature and humidity half variance average values and the distance average values of the first groups, wherein the temperature and humidity half variance average values are used as experimental variation function values in the fitting process, and the distance average values are used as regional variables to the distances from the points to be estimated in the fitting process; according to the temperature and humidity measured values of the real measurement points, performing error analysis by using model coefficients of the experimental variation function models to obtain model quality evaluation index values of each experimental variation function model in the experimental variation function models; according to the model quality evaluation index values of the experimental variation function models, determining an optimal experimental variation function model which can best meet the model optimal preset condition from the experimental variation function models; determining m real measurement points around the target measurement point from the plurality of real measurement points according to the known coordinates of the plurality of real measurement points and the known coordinates of the target measurement point in the laboratory, wherein m represents a positive integer greater than 2; according to the known coordinates of the target measuring point and the known coordinates of the m real measuring points, calculating to obtain distance values from the target measuring point to each of the m real measuring points, substituting the distance values as regional variables to the measuring point to be estimated into the optimal experimental variation function model, and then applying model coefficients of the optimal experimental variation function model to calculate to obtain experimental variation function values of the target measuring point and each of the m real measuring points; according to the half variance value of the temperature and humidity of each pair of the m actual measurement points and the experimental variation function value of the target measurement point and each of the m actual measurement points, the following common kriging is established A system of gold equations:

wherein i and j each represent a positive integer, lambda _i Representing the weight coefficient corresponding to the ith real point in the m real points and to be solved, and gamma (x) _i ,x _j ) The temperature and humidity half-variance value corresponding to the ith real measurement point and the jth real measurement point in the m real measurement points is represented, u represents the Lagrange multiplier factor to be solved, and gamma (x) _i ,x ₀ ) The experimental variation function values of the target measuring point and the ith real measuring point are represented; solving the common kriging equation set to obtain m weight coefficients corresponding to the m real measuring points one by one; according to the temperature and humidity actual measurement values of the m real measurement points, the temperature and humidity estimated value Z (x) of the target measurement point is calculated according to the following formula ₀ )：

Wherein Z (x) _i ) The temperature and humidity measured value of the ith real measurement point is represented; taking the temperature and humidity estimated values of all the target measuring points in the whole domain in the laboratory as the three-dimensional distribution condition of the temperature and humidity in the laboratory;

2. The laboratory constant temperature and humidity abnormality alarm method according to claim 1, wherein the plurality of temperature and humidity sensors includes temperature and humidity sensors respectively arranged at a top surface center, a ground center, and respective sidewall centers in the laboratory.

3. The laboratory constant temperature and humidity anomaly alarm method according to claim 1, wherein a hysteresis distance h is determined ₁ The method comprises the following steps S3031 to S3034:

4. The laboratory constant temperature and humidity abnormality alarm method according to claim 1, characterized in that when it is found from the temperature three-dimensional distribution condition that the current temperature of a certain measurement point in the laboratory is not within the preset constant temperature interval, the method further comprises:

5. The laboratory constant temperature and humidity abnormality alarm method according to claim 1, wherein when it is found that the current humidity of a certain measurement point in the laboratory is not within the preset constant humidity interval according to the humidity three-dimensional distribution condition, the method further comprises:

6. A computer device comprising a memory, a processor and a transceiver in communication connection in sequence, wherein the memory is used for storing a computer program, the transceiver is used for receiving and transmitting messages, and the processor is used for reading the computer program and executing the laboratory constant temperature and humidity abnormality alarm method according to any one of claims 1 to 5.

7. A computer readable storage medium having instructions stored thereon which, when executed on a computer, perform the laboratory constant temperature and humidity anomaly alarm method of any one of claims 1 to 5.