CN118168115A - Heating ventilation air conditioner fault detection system based on data analysis - Google Patents
Heating ventilation air conditioner fault detection system based on data analysis Download PDFInfo
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Abstract
The invention belongs to the field of air conditioner fault detection, relates to a data analysis technology, and is used for solving the problem that the accuracy of a fault detection result of an existing heating ventilation air conditioner fault detection system is low, in particular to a heating ventilation air conditioner fault detection system based on data analysis, which comprises a fault detection platform, wherein the fault detection platform is in communication connection with an operation detection module, a fault analysis module and a storage module; the operation detection module is used for detecting and analyzing the operation state of the heating ventilation air conditioner: generating a detection period, dividing the detection period into a plurality of detection periods, and acquiring temperature difference data WY, humidity difference data SY and flow difference data LY of the heating ventilation air conditioner in the detection periods; the invention can detect and analyze the operation state of the heating ventilation air conditioner, then process and calculate the operation parameters in each detection period in a periodical analysis mode to obtain the operation coefficient, and analyze and evaluate the abnormal degree of the operation state of the heating ventilation air conditioner through the operation coefficient.
Description
Technical Field
The invention belongs to the field of air conditioner fault detection, relates to a data analysis technology, and particularly relates to a heating ventilation air conditioner fault detection system based on data analysis.
Background
The system for detecting faults of the heating ventilation air conditioning system is a comprehensive system for detecting and diagnosing faults of the heating ventilation air conditioning system, and detects and diagnoses various faults by collecting and analyzing operation data of the heating ventilation air conditioning system and provides corresponding maintenance and repair suggestions.
The existing heating ventilation air conditioner fault detection system cannot collect multipoint parameters of an air conditioner coverage area, meanwhile cannot analyze by combining dynamic change characteristics of all parameters, and therefore accuracy of fault detection results of the heating ventilation air conditioner is low.
The application provides a solution to the technical problem.
Disclosure of Invention
The invention aims to provide a heating ventilation air conditioner fault detection system based on data analysis, which is used for solving the problem that the accuracy of the fault detection result of the conventional heating ventilation air conditioner fault detection system is low;
The technical problems to be solved by the invention are as follows: how to provide a heating ventilation air conditioner fault detection system based on data analysis, which can perform multipoint parameter acquisition on an air conditioner coverage area.
The aim of the invention can be achieved by the following technical scheme:
the heating ventilation air conditioner fault detection system based on data analysis comprises a fault detection platform, wherein the fault detection platform is in communication connection with an operation detection module, a fault analysis module and a storage module;
The operation detection module is used for detecting and analyzing the operation state of the heating ventilation air conditioner: generating a detection period, dividing the detection period into a plurality of detection periods, and acquiring temperature difference data WY, humidity difference data SY and flow difference data LY of the heating ventilation air conditioner in the detection periods; the operation coefficient YX of the detection period is obtained by carrying out numerical calculation on temperature difference data WY, humidity difference data SY and flow difference data LY; transmitting the operation coefficient YX of the detection period to a fault analysis module through a fault detection platform;
the fault analysis module is used for carrying out early warning analysis on the operation faults of the heating ventilation air conditioner.
As a preferred embodiment of the present invention, the acquisition process of the temperature difference data WY includes: setting a plurality of detection points in a coverage area of the heating ventilation air conditioner, acquiring an air temperature value of the detection points and a temperature value set by a heating ventilation air conditioner control panel in real time, marking an absolute value of a temperature value difference value set by the air temperature value and the control panel as a temperature deviation value of the detection points, marking the maximum value of the temperature deviation value of the detection points in a detection period as a temperature deviation value of the detection points, summing the temperature deviation values of all the detection points, and averaging to obtain temperature deviation data WY.
As a preferred embodiment of the present invention, the acquisition process of the wet data SY includes: and acquiring the air humidity value of the detection point and the humidity value set by the control panel in real time, marking the absolute value of the difference value between the air humidity value and the humidity value set by the control panel as a humidity deviation value, marking the maximum value of the humidity deviation value of the detection point in the detection period as the humidity deviation value of the detection point, summing the humidity deviation values of all the detection points, and taking the average value to obtain the humidity deviation data SY.
As a preferred embodiment of the present invention, the acquisition process of the alien data LY includes: the method comprises the steps of obtaining an air flow velocity value of a detection point and a wind speed value set by a control panel in real time, marking an absolute value of a difference value between the air flow velocity value and the wind speed value set by the control panel as a flow deviation value, marking a maximum value of the flow deviation value of the detection point in a detection period as a flow deviation value, summing the flow deviation values of all the detection points, and taking an average value to obtain flow deviation data LY.
As a preferred implementation mode of the invention, the specific process of the fault analysis module for carrying out early warning analysis on the operation faults of the heating ventilation air conditioner comprises the following steps: the operation coefficients YX of all the detection periods are summed and averaged to obtain an operation representation value, variance calculation is carried out on the operation coefficients YX of all the detection periods to obtain an operation stability value, an operation representation threshold and an operation stability threshold are obtained through a storage module, the operation representation value and the operation stability value are respectively compared with the operation representation threshold and the operation stability threshold, and whether the operation state of the heating ventilation air conditioner meets the requirement or not is judged according to the comparison result.
As a preferred embodiment of the present invention, the specific process of comparing the operation performance value and the operation stability value with the operation performance threshold and the operation stability threshold, respectively, includes: if the operation representation value is smaller than the operation representation threshold value and the operation stability value is smaller than the operation stability threshold value, judging that the operation state of the heating ventilation air conditioner meets the requirement, generating an operation normal signal and sending the operation normal signal to the fault detection platform; if the operation representation value is greater than or equal to the operation representation threshold value and the operation stability value is smaller than the operation stability threshold value, judging that the heating ventilation air conditioner has continuous faults, generating continuous abnormal signals and sending the continuous abnormal signals to mobile phone terminals of management staff through a fault detection platform; if the operation stability value is greater than or equal to the operation stability threshold value, judging that the heating ventilation air conditioner has intermittent faults, generating intermittent abnormal signals and sending the intermittent abnormal signals to a mobile phone terminal of a manager through a fault detection platform.
As a preferred embodiment of the invention, the working method of the heating ventilation and air conditioning fault detection system based on data analysis comprises the following steps:
Step one: detecting and analyzing the running state of the heating ventilation air conditioner: generating a detection period, dividing the detection period into a plurality of detection periods, acquiring temperature difference data WY, humidity difference data SY and flow difference data LY of the heating ventilation air conditioner in the detection periods, and performing numerical calculation to obtain an operation coefficient YX of the detection periods;
Step two: and carrying out early warning analysis on the operation faults of the heating ventilation air conditioner: summing the running coefficients YX of all the detection periods, taking an average value to obtain a running representation value, and performing variance calculation on the running coefficients YX of all the detection periods to obtain a running stability value;
Step three: comparing the operation representation value and the operation stability value with an operation representation threshold value and an operation stability threshold value respectively, generating an operation normal signal, a continuous abnormal signal or an intermittent abnormal signal according to the comparison results, and sending the operation normal signal, the continuous abnormal signal or the intermittent abnormal signal to a fault detection platform.
The invention has the following beneficial effects:
1. The operation detection module can detect and analyze the operation state of the heating ventilation air conditioner, multiple groups of operation parameters are acquired in a multipoint real-time acquisition mode, then the operation parameters in each detection period are processed and calculated in a periodic analysis mode to obtain operation coefficients, and the abnormal degree of the operation state of the heating ventilation air conditioner is analyzed and evaluated through the operation coefficients;
2. The fault analysis module can perform early warning analysis on the operation faults of the heating ventilation air conditioner, the operation coefficients of all detection periods in the detection period are subjected to advanced treatment to obtain an operation representation value and an operation stable value, whether the heating ventilation air conditioner has faults or not and fault characteristics are judged through the operation representation value and the operation stable value, and the treatment efficiency of the heating ventilation air conditioner during faults is improved.
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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 flowchart of a method according to a second embodiment of the 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.
Example 1
As shown in FIG. 1, the heating ventilation air conditioner fault detection system based on data analysis comprises a fault detection platform, wherein the fault detection platform is in communication connection with an operation detection module, a fault analysis module and a storage module.
The operation detection module is used for detecting and analyzing the operation state of the heating ventilation air conditioner: generating a detection period and dividing the detection period into a plurality of detection periods, and acquiring temperature difference data WY, humidity difference data SY and flow difference data LY of the heating ventilation air conditioner in the detection periods, wherein the acquisition process of the temperature difference data WY comprises the following steps: setting a plurality of detection points in a coverage area of the heating ventilation air conditioner, acquiring an air temperature value of the detection points and a temperature value set by a heating ventilation air conditioner control panel in real time, marking an absolute value of a temperature value difference value set by the air temperature value and the control panel as a temperature deviation value of the detection points, marking the maximum value of the temperature deviation value of the detection points in a detection period as a temperature deviation value of the detection points, summing the temperature deviation values of all the detection points, and averaging to obtain temperature deviation data WY; the acquisition process of the wet data SY comprises the following steps: acquiring an air humidity value of a detection point and a humidity value set by a control panel in real time, marking an absolute value of a difference value between the air humidity value and the humidity value set by the control panel as a humidity deviation value, marking a maximum value of the humidity deviation value of the detection point in a detection period as a humidity deviation value of the detection point, summing the humidity deviation values of all the detection points, and taking an average value to obtain humidity deviation data SY; the acquisition process of the alien data LY comprises the following steps: acquiring an air flow velocity value of a detection point and a wind speed value set by a control panel in real time, marking an absolute value of a difference value between the air flow velocity value and the wind speed value set by the control panel as a flow deviation value, marking a maximum value of the flow deviation value of the detection point in a detection period as a flow deviation value, summing the flow deviation values of all the detection points, and taking an average value to obtain flow deviation data LY; obtaining an operation coefficient YX of the detection period by a formula yx=α1×wy+α2×sy+α3×ly, wherein α1, α2 and α3 are proportionality coefficients, and α1 > α2 > α3 > 1; transmitting the operation coefficient YX of the detection period to a fault analysis module through a fault detection platform; detecting and analyzing the operation state of the heating ventilation air conditioner, acquiring a plurality of groups of operation parameters in a multipoint real-time acquisition mode, processing and calculating the operation parameters in each detection period in a periodic analysis mode to obtain an operation coefficient, and analyzing and evaluating the abnormal degree of the operation state of the heating ventilation air conditioner through the operation coefficient.
The fault analysis module is used for carrying out early warning analysis on the operation faults of the heating ventilation air conditioner: summing the running coefficients YX of all the detection periods, taking an average value to obtain a running representation value, calculating variances of the running coefficients YX of all the detection periods to obtain a running stability value, obtaining a running representation threshold and a running stability threshold through a storage module, and comparing the running representation value and the running stability value with the running representation threshold and the running stability threshold respectively: if the operation representation value is smaller than the operation representation threshold value and the operation stability value is smaller than the operation stability threshold value, judging that the operation state of the heating ventilation air conditioner meets the requirement, generating an operation normal signal and sending the operation normal signal to the fault detection platform; if the operation representation value is greater than or equal to the operation representation threshold value and the operation stability value is smaller than the operation stability threshold value, judging that the heating ventilation air conditioner has continuous faults, generating continuous abnormal signals and sending the continuous abnormal signals to mobile phone terminals of management staff through a fault detection platform; if the operation stability value is greater than or equal to the operation stability threshold value, judging that the heating ventilation air conditioner has intermittent faults, generating intermittent abnormal signals and sending the intermittent abnormal signals to a mobile phone terminal of a manager through a fault detection platform; and carrying out early warning analysis on the operation faults of the heating ventilation air conditioner, carrying out advanced treatment on the operation coefficients of all detection periods in the detection period to obtain an operation representation value and an operation stable value, judging whether the heating ventilation air conditioner has faults or not and judging fault characteristics according to the operation representation value and the operation stable value, and improving the treatment efficiency of the heating ventilation air conditioner when the heating ventilation air conditioner has faults.
Example two
As shown in fig. 2, a heating ventilation and air conditioning fault detection method based on data analysis comprises the following steps:
Step one: detecting and analyzing the running state of the heating ventilation air conditioner: generating a detection period, dividing the detection period into a plurality of detection periods, acquiring temperature difference data WY, humidity difference data SY and flow difference data LY of the heating ventilation air conditioner in the detection periods, and performing numerical calculation to obtain an operation coefficient YX of the detection periods;
Step two: and carrying out early warning analysis on the operation faults of the heating ventilation air conditioner: summing the running coefficients YX of all the detection periods, taking an average value to obtain a running representation value, and performing variance calculation on the running coefficients YX of all the detection periods to obtain a running stability value;
Step three: comparing the operation representation value and the operation stability value with an operation representation threshold value and an operation stability threshold value respectively, generating an operation normal signal, a continuous abnormal signal or an intermittent abnormal signal according to the comparison results, and sending the operation normal signal, the continuous abnormal signal or the intermittent abnormal signal to a fault detection platform.
When the heating ventilation air conditioner fault detection system based on data analysis works, a detection period is generated and divided into a plurality of detection periods, temperature difference data WY, humidity difference data SY and flow difference data LY of the heating ventilation air conditioner in the detection periods are obtained, and a running coefficient YX of the detection periods is obtained through numerical calculation; summing the running coefficients YX of all the detection periods, taking an average value to obtain a running representation value, and performing variance calculation on the running coefficients YX of all the detection periods to obtain a running stability value; comparing the operation representation value and the operation stability value with an operation representation threshold value and an operation stability threshold value respectively, generating an operation normal signal, a continuous abnormal signal or an intermittent abnormal signal according to the comparison results, and sending the operation normal signal, the continuous abnormal signal or the intermittent abnormal signal to a fault detection platform.
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: the formula yx=α1×wy+α2×sy+α3×ly; 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, alpha 2 and alpha 3 which are 3.52, 2.89 and 2.31 respectively;
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 in direct proportion to the value of the temperature difference 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 heating ventilation air conditioner fault detection system based on data analysis is characterized by comprising a fault detection platform, wherein the fault detection platform is in communication connection with an operation detection module, a fault analysis module and a storage module;
The operation detection module is used for detecting and analyzing the operation state of the heating ventilation air conditioner: generating a detection period, dividing the detection period into a plurality of detection periods, and acquiring temperature difference data WY, humidity difference data SY and flow difference data LY of the heating ventilation air conditioner in the detection periods; the operation coefficient YX of the detection period is obtained by carrying out numerical calculation on temperature difference data WY, humidity difference data SY and flow difference data LY; transmitting the operation coefficient YX of the detection period to a fault analysis module through a fault detection platform;
the fault analysis module is used for carrying out early warning analysis on the operation faults of the heating ventilation air conditioner.
2. The heating ventilation and air conditioning fault detection system based on data analysis according to claim 1, wherein the process of obtaining the temperature difference data WY comprises: setting a plurality of detection points in a coverage area of the heating ventilation air conditioner, acquiring an air temperature value of the detection points and a temperature value set by a heating ventilation air conditioner control panel in real time, marking an absolute value of a temperature value difference value set by the air temperature value and the control panel as a temperature deviation value of the detection points, marking the maximum value of the temperature deviation value of the detection points in a detection period as a temperature deviation value of the detection points, summing the temperature deviation values of all the detection points, and averaging to obtain temperature deviation data WY.
3. The heating ventilation and air conditioning fault detection system based on data analysis according to claim 2, wherein the process of acquiring the wet data SY comprises: and acquiring the air humidity value of the detection point and the humidity value set by the control panel in real time, marking the absolute value of the difference value between the air humidity value and the humidity value set by the control panel as a humidity deviation value, marking the maximum value of the humidity deviation value of the detection point in the detection period as the humidity deviation value of the detection point, summing the humidity deviation values of all the detection points, and taking the average value to obtain the humidity deviation data SY.
4. A hvac fault detection system based on data analysis as set forth in claim 3, wherein the process of obtaining the alien data LY comprises: the method comprises the steps of obtaining an air flow velocity value of a detection point and a wind speed value set by a control panel in real time, marking an absolute value of a difference value between the air flow velocity value and the wind speed value set by the control panel as a flow deviation value, marking a maximum value of the flow deviation value of the detection point in a detection period as a flow deviation value, summing the flow deviation values of all the detection points, and taking an average value to obtain flow deviation data LY.
5. The data analysis-based heating, ventilation and air conditioning fault detection system according to claim 4, wherein the specific process of performing early warning analysis on the operation fault of the heating, ventilation and air conditioning by the fault analysis module comprises: the operation coefficients YX of all the detection periods are summed and averaged to obtain an operation representation value, variance calculation is carried out on the operation coefficients YX of all the detection periods to obtain an operation stability value, an operation representation threshold and an operation stability threshold are obtained through a storage module, the operation representation value and the operation stability value are respectively compared with the operation representation threshold and the operation stability threshold, and whether the operation state of the heating ventilation air conditioner meets the requirement or not is judged according to the comparison result.
6. The system for detecting a failure of a hvac system based on data analysis of claim 5, wherein comparing the running performance value and the running stability value with the running performance threshold and the running stability threshold, respectively, comprises: if the operation representation value is smaller than the operation representation threshold value and the operation stability value is smaller than the operation stability threshold value, judging that the operation state of the heating ventilation air conditioner meets the requirement, generating an operation normal signal and sending the operation normal signal to the fault detection platform; if the operation representation value is greater than or equal to the operation representation threshold value and the operation stability value is smaller than the operation stability threshold value, judging that the heating ventilation air conditioner has continuous faults, generating continuous abnormal signals and sending the continuous abnormal signals to mobile phone terminals of management staff through a fault detection platform; if the operation stability value is greater than or equal to the operation stability threshold value, judging that the heating ventilation air conditioner has intermittent faults, generating intermittent abnormal signals and sending the intermittent abnormal signals to a mobile phone terminal of a manager through a fault detection platform.
7. A hvac fault detection system based on data analysis according to any one of claims 1-6, wherein the operating method of the hvac fault detection system based on data analysis comprises the steps of:
Step one: detecting and analyzing the running state of the heating ventilation air conditioner: generating a detection period, dividing the detection period into a plurality of detection periods, acquiring temperature difference data WY, humidity difference data SY and flow difference data LY of the heating ventilation air conditioner in the detection periods, and performing numerical calculation to obtain an operation coefficient YX of the detection periods;
Step two: and carrying out early warning analysis on the operation faults of the heating ventilation air conditioner: summing the running coefficients YX of all the detection periods, taking an average value to obtain a running representation value, and performing variance calculation on the running coefficients YX of all the detection periods to obtain a running stability value;
Step three: comparing the operation representation value and the operation stability value with an operation representation threshold value and an operation stability threshold value respectively, generating an operation normal signal, a continuous abnormal signal or an intermittent abnormal signal according to the comparison results, and sending the operation normal signal, the continuous abnormal signal or the intermittent abnormal signal to a fault detection platform.
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