A multi-channel temperature data acquisition system and data processing method

Abstract

The application provides a multi-channel temperature data acquisition system and a data processing method, which comprises the following steps: determining a plurality of measuring points of a measuring object; selecting a plurality of to-be-measured points from the plurality of measuring points according to a measuring control model; acquiring a plurality of temperature data of the plurality of to-be-measured points in a preset time period; transmitting the plurality of temperature data to a multi-channel processor after signal conditioning and analog-digital conversion; performing temperature signal calculation and linear correction on the plurality of temperature data by the multi-channel processor to obtain processed temperature data; and generating a temperature monitoring data model of the measuring object by a server according to the processed temperature data. The scheme can selectively measure the temperature of different positions of the measuring object, and can perform multi-stage signal processing and different processing channels on the acquired temperature data, thereby improving the compatibility of the temperature data, the efficiency of temperature data processing, and the accuracy of temperature measurement.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data acquisition, in particular to a multi-channel temperature data acquisition system and a data processing method. BACKGROUND

[0002] With the development of economy and the continuous progress of technology, in the industrial production process, it is necessary to monitor the state of large industrial equipment in working condition in real time, and the real-time detection of temperature is one of the important measurement work. Temperature measurement and control are directly related to major technical and economic indicators such as safety production, improving production efficiency, ensuring product quality, and saving energy.

[0003] In some large production sites or monitoring sites, it is necessary to monitor the real-time environmental temperature information of multiple points in the site, which requires a multi-channel temperature detection scheme, and the existing multi-channel temperature acquisition scheme has some problems. SUMMARY

[0004] The present application is based on the above problems, and proposes a multi-channel temperature data acquisition system and a data processing method. Through the scheme of the present application, the temperature of different positions of the measurement object can be selectively measured, and the collected temperature data can be processed by multiple signal processing and different processing channels, thereby improving the compatibility of temperature data, the efficiency of temperature data processing, and the accuracy of temperature measurement.

[0005] Therefore, one aspect of the present application provides a multi-channel temperature data acquisition system, comprising: a determination module, a selection module, a temperature acquisition module, a control module, a multi-channel processor and a server;

[0006] The determination module is configured to determine a plurality of measurement points of a measurement object.

[0007] The selection module is configured to select a first measurement point and a second measurement point from the plurality of measurement points according to a measurement control model.

[0008] The temperature acquisition module is configured to acquire a plurality of first temperature data of the first measurement point and a plurality of second temperature data of the second measurement point in a preset time period, respectively.

[0009] The control module is configured to transmit the plurality of first temperature data and the plurality of second temperature data to the multi-channel processor after signal conditioning and analog-to-digital conversion.

[0010] The multi-channel processor is configured to perform temperature signal calculation and linearization correction on the plurality of first temperature data and the plurality of second temperature data to obtain third temperature data and fourth temperature data, respectively, and send the third temperature data and the fourth temperature data to the server.

[0011] The server is configured to generate a temperature monitoring data model of the measurement object according to the third temperature data and the fourth temperature data.

[0012] Optionally, the control module is further configured to determine whether the temperature of the measurement object is abnormal according to the third temperature data and the fourth temperature data.

[0013] The selection module is further configured to determine third measurement points and fourth measurement points different from the first measurement points and the second measurement points from the plurality of measurement points when the temperature is abnormal.

[0014] The temperature acquisition module is further configured to acquire fifth temperature data of the third measurement points and sixth temperature data of the fourth measurement points.

[0015] The control module is further configured to determine whether the temperature of the measurement object is abnormal according to the fifth temperature data and the sixth temperature data, and trigger an abnormality processing program when the temperature is abnormal.

[0016] Optionally, the method further comprises a three-dimensional data acquisition module.

[0017] The three-dimensional data acquisition module is configured to acquire three-dimensional point cloud data of the measurement object.

[0018] The server is configured to construct a three-dimensional model of the measurement object according to the three-dimensional point cloud data.

[0019] Optionally, the server is further configured to:

[0020] acquire historical temperature data of the measurement object;

[0021] classify the historical temperature data according to components of the measurement object;

[0022] determine a first component whose temperature abnormality frequency is higher than a preset threshold;

[0023] determine the measurement control model containing a key measurement position according to the first component and the three-dimensional model.

[0024] Optionally, the server is further configured to mark the first temperature data, the second temperature data, the fifth temperature data, and the sixth temperature data on the three-dimensional model.

[0025] Another aspect of the present application provides a multi-channel temperature data processing method, which comprises:

[0026] determining a plurality of measurement points of a measurement object;

[0027] selecting a first measurement point and a second measurement point from the plurality of measurement points according to a measurement control model;

[0028] respectively acquiring a plurality of first temperature data of the first measurement point and a plurality of second temperature data of the second measurement point in a preset time period;

[0029] transmitting the plurality of first temperature data and the plurality of second temperature data to a multi-channel processor after signal conditioning and analog-to-digital conversion;

[0030] respectively performing temperature signal calculation and linearization correction on the plurality of first temperature data and the plurality of second temperature data by the multi-channel processor to obtain third temperature data and fourth temperature data;

[0031] sending the third temperature data and the fourth temperature data to a server;

[0032] generating a temperature monitoring data model of the measurement object according to the third temperature data and the fourth temperature data by the server.

[0033] Optionally, the method further comprises:

[0034] judging whether the temperature of the measurement object is abnormal according to the third temperature data and the fourth temperature data;

[0035] when there is an abnormality, determining a third measurement point and a fourth measurement point different from the first measurement point and the second measurement point from the plurality of measurement points;

[0036] acquiring fifth temperature data of the third measurement point and sixth temperature data of the fourth measurement point;

[0037] judging whether the temperature of the measurement object is abnormal according to the fifth temperature data and the sixth temperature data;

[0038] when there is an abnormality, triggering an abnormality processing program.

[0039] Optionally, before the plurality of measurement points of the measurement object are determined, the method further comprises:

[0040] acquiring three-dimensional point cloud data of the measurement object;

[0041] constructing a three-dimensional model of the measurement object according to the three-dimensional point cloud data.

[0042] Optionally, after the three-dimensional model of the measurement object is constructed according to the three-dimensional point cloud data, the method further comprises:

[0043] acquiring historical temperature data of the measurement object;

[0044] classifying the historical temperature data according to parts of the measurement object;

[0045] determining a first part where the frequency of temperature abnormality occurrence is higher than a preset threshold;

[0046] determining the measurement control model containing a key measurement position according to the first part and the three-dimensional model.

[0047] Optionally, the method further comprises:

[0048] marking the first temperature data, the second temperature data, the fifth temperature data and the sixth temperature data on the three-dimensional model.

[0049] The technical scheme of the present application is as follows: a multi-channel temperature data acquisition system comprises a determination module, a selection module, a temperature acquisition module, a control module, a multi-channel processor and a server; the determination module is used to determine a plurality of measurement points of a measurement object; the selection module is used to select a first measurement point and a second measurement point from the plurality of measurement points according to a measurement control model; the temperature acquisition module is used to respectively acquire a plurality of first temperature data of the first measurement point and a plurality of second temperature data of the second measurement point within a preset time period; the control module is used to transmit the plurality of first temperature data and the plurality of second temperature data to the multi-channel processor after signal conditioning and analog-digital conversion; the multi-channel processor is used to respectively perform temperature signal calculation and linearization correction on the plurality of first temperature data and the plurality of second temperature data to obtain third temperature data and fourth temperature data, and send the third temperature data and the fourth temperature data to the server; and the server is used to generate a temperature monitoring data model of the measurement object according to the third temperature data and the fourth temperature data. Through the technical scheme, temperature measurement can be selectively performed on different positions of the measurement object, and the acquired temperature data can be processed by multiple levels of signal processing and different processing channels, thereby improving the compatibility of the temperature data, the efficiency of temperature data processing and the accuracy of temperature measurement. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 is a schematic block diagram of a multi-channel temperature data acquisition system provided by an embodiment of the present application;

[0051] Figure 2 is a flow chart of a multi-channel temperature data processing method provided by another embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to enable a more clear understanding of the above-mentioned objects, features and advantages of the present application, the present application will be further described in conjunction with the following drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict, if necessary.

[0053] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be apparent to one skilled in the art that the present application can be practiced without the specific details presented herein. In other instances, well-known methods have not been described in detail in order to avoid obscuring the present application.

[0054] The terms "first", "second", and the like in the description and in the claims of the present application and the above drawings are intended to distinguish between similar objects, and are not intended to describe a particular sequential order. Moreover, the terms "include", and "have", and any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, product, or device that comprises a list of steps or units is not limited to the listed steps or units, but can optionally further include additional steps or units not listed, or can optionally further include other steps or units inherent to such process, method, product, or device.

[0055] Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. It will be explicitly understood that the embodiments described herein can be combined with each other, in whole or in part.

[0056] Some embodiments of a multi-channel temperature data acquisition system and a data processing method are described below with reference to Figures 1 to 2

[0057] As shown in Figure 1 , one embodiment of the present application provides a multi-channel temperature data acquisition system, comprising a determination module, a selection module, a temperature acquisition module, a control module, a multi-channel processor and a server;

[0058] The determination module is configured to determine a plurality of measurement points of a measurement object.

[0059] The selection module is configured to select a first measurement point and a second measurement point from the plurality of measurement points according to a measurement control model.

[0060] The temperature acquisition module is configured to respectively acquire a plurality of first temperature data of the first measurement point and a plurality of second temperature data of the second measurement point within a preset time period.

[0061] ​The control module is configured to transmit the first temperature data and the second temperature data to the multi-channel processor after signal conditioning and analog-to-digital conversion.

[0062] The multi-channel processor is configured to perform temperature signal calculation and linearization correction on the first temperature data and the second temperature data to obtain third temperature data and fourth temperature data, and send the third temperature data and the fourth temperature data to the server.

[0063] The server is configured to generate a temperature monitoring data model of the measurement object according to the third temperature data and the fourth temperature data.

[0064] It can be understood that the measurement object can be an industrial production device, a measuring instrument, an automobile engine, or other objects that need to be detected for temperature. In the embodiments of the present application, a plurality of measurement points for measuring the temperature of the measurement object can be determined by analyzing historical data. These measurement points can be key components of the measurement object, elements prone to heat, components with strict temperature control accuracy requirements, temperature sensitive components, and the like.

[0065] The measurement control model is generated by combining trained neural network processing according to historical working data, historical working environment data, historical temperature detection data, historical fault data, three-dimensional model data of the measurement object, product specification data of the measurement object including temperature detection requirements, and the like. The measurement control model is used to determine the trigger, flow / steps, control process, and the like for measuring the temperature of the measurement object. According to the measurement control model, at least a plurality of measurement points with the highest priority, including a first measurement point and a second measurement point, are selected from the plurality of measurement points. It should be noted that the measurement points with the highest priority can be temperature sensitive components with the highest frequency of temperature abnormalities, components with the most strict temperature control accuracy requirements, and the like. The embodiments of the present application do not limit the measurement points with the highest priority.

[0066] In the embodiment, a plurality of first temperature data of the first measuring point and a plurality of second temperature data of the second measuring point are acquired through different acquisition channels / acquisition sensors in a preset time period (which can be the most appropriate detection period obtained according to historical detection data analysis), and the plurality of first temperature data and the plurality of second temperature data are transmitted to a multi-channel processor after signal conditioning and analog-to-digital conversion. The process of signal conditioning and analog-to-digital conversion is as follows: first, the plurality of first temperature data and the plurality of second temperature data are processed by a first amplifier with a fixed amplification factor to increase data processing details, and then the first amplified data are input into a second amplifier with an adjustable amplification factor (the specific amplification factor value is determined according to the accuracy of the temperature value of the measuring point of the specific measuring object) for processing, and after processing, analog-to-digital conversion is performed, and after analog-to-digital conversion, the data are input into a third amplifier with an adjustable amplification factor (the specific amplification factor value can be determined according to the accuracy requirement of the temperature value in the next processing process) for processing, so as to obtain data that can adapt to different accuracy requirements. By setting multiple amplifiers, the small characteristic signals collected can be amplified, and the accuracy of temperature data acquisition is improved.

[0067] It can be understood that, in order to make the processing of temperature data more efficient and more accurate, in the embodiment of the application, a multi-channel processor is adopted to process the temperature data of different measuring points. Specifically, the multi-channel processor inputs the plurality of first temperature data and the plurality of second temperature data into different processing channels, and obtains third temperature data and fourth temperature data after temperature signal calculation and linearization correction. It should be noted that the structures, positions, materials, etc. of different measuring points may be different, and the measuring tools for temperature measurement may be different, which may result in inconsistent types of measured data. The adoption of a multi-channel processor can effectively avoid problems caused by inconsistent types of measured data.

[0068] In the embodiment of the application, the third temperature data and the fourth temperature data are sent to a server, and the server generates a temperature monitoring data model of the measuring object according to the third temperature data and the fourth temperature data, so as to track the temperature state of the measuring object.

[0069] It should be noted that the "first measuring point" and the "second measuring point" in the application are only for illustration, and do not mean that the scheme of the application can only realize the measurement of two measuring points. The embodiment of the application can realize a measurement scheme of more than two measuring points.

[0070] The technical scheme of the embodiment is adopted, the multi-channel temperature data acquisition system comprises a determination module, a selection module, a temperature acquisition module, a control module, a multi-channel processor and a server; the determination module is configured to determine a plurality of measurement points of a measurement object; the selection module is configured to select a first measurement point and a second measurement point from the plurality of measurement points according to a measurement control model; the temperature acquisition module is configured to acquire a plurality of first temperature data of the first measurement point and a plurality of second temperature data of the second measurement point in a preset time period respectively; the control module is configured to transmit the plurality of first temperature data and the plurality of second temperature data to the multi-channel processor after signal conditioning and analog-to-digital conversion; the multi-channel processor is configured to obtain third temperature data and fourth temperature data after temperature signal calculation and linearization correction of the plurality of first temperature data and the plurality of second temperature data respectively, and send the third temperature data and the fourth temperature data to the server; and the server is configured to generate a temperature monitoring data model of the measurement object according to the third temperature data and the fourth temperature data. Through the scheme, temperature measurement can be selectively performed on different positions of the measurement object, and the acquired temperature data can be subjected to multi-stage signal processing and processed by different processing channels, thereby improving the compatibility of the temperature data, the efficiency of temperature data processing and the accuracy of temperature measurement.

[0071] It should be understood that, Figure 1 It should be understood that,

[0072] In some possible embodiments of the present application, the control module is further configured to determine whether the temperature of the measurement object is abnormal according to the third temperature data and the fourth temperature data;

[0073] The selection module is further configured to determine a third measurement point and a fourth measurement point different from the first measurement point and the second measurement point from the plurality of measurement points when there is an abnormality.

[0074] The temperature acquisition module is further configured to acquire fifth temperature data of the third measurement point and sixth temperature data of the fourth measurement point.

[0075] The control module is further configured to determine whether the temperature of the measurement object is abnormal according to the fifth temperature data and the sixth temperature data, and trigger an abnormality processing program when there is an abnormality.

[0076] It can be understood that, in the embodiments of the present application, when it is judged according to the third temperature data and the fourth temperature data that the temperature of the measured object is abnormal, in order to avoid misjudgment, a step of verification is needed, so third and fourth measuring points different from the first and second measuring points are determined from the plurality of measuring points; fifth temperature data of the third measuring point and sixth temperature data of the fourth measuring point are obtained; it is judged according to the fifth temperature data and the sixth temperature data whether the temperature of the measured object is abnormal; when it is abnormal, it indicates that the measured object has temperature abnormality, and an abnormality processing program is triggered to avoid accidents.

[0077] In some possible embodiments of the present application, the three-dimensional data acquisition module is further included.

[0078] The three-dimensional data acquisition module is configured to acquire three-dimensional point cloud data of the measured object.

[0079] The server is configured to construct a three-dimensional model of the measured object according to the three-dimensional point cloud data.

[0080] It can be understood that, in order to make the structure of the measured object clearer for efficient temperature monitoring, in the embodiments of the present application, the three-dimensional model of the measured object is constructed by acquiring the three-dimensional point cloud data of the measured object to assist in temperature measurement. The three-dimensional point cloud data can provide detailed three-dimensional information of the measured object, and the three-dimensional model constructed therefrom is detailed and has high accuracy.

[0081] In some possible embodiments of the present application, the server is further configured to:

[0082] Acquire historical temperature data of the measured object.

[0083] Classify the historical temperature data according to components of the measured object.

[0084] Determine a first component whose frequency of temperature abnormality is higher than a preset threshold.

[0085] Determine the measurement control model containing a key measurement position according to the first component and the three-dimensional model.

[0086] It can be understood that the embodiment provides a generation method of a measurement control model, that is, by acquiring historical temperature data of the measurement object, classifying the historical temperature data according to components of the measurement object, determining a plurality of first components with a frequency of temperature abnormality higher than a preset threshold, determining the measurement control model containing a key measurement position according to the first components and the three-dimensional model, the key measurement position being a point corresponding to the plurality of first components with the frequency of temperature abnormality higher than the preset threshold, and the first measurement point and the second measurement point in the foregoing embodiment can be selected from the key measurement position. Through the embodiment, the monitoring of the frequency of temperature abnormality can be realized, targeted measurement is realized, and work efficiency is improved.

[0087] In some possible embodiments of the present application, the server is further configured to mark the first temperature data, the second temperature data, the fifth temperature data and the sixth temperature data on the three-dimensional model.

[0088] In the embodiment, the temperature data is marked on the measurement three-dimensional model, so that more intuitive visual presentation can be provided, and the user can quickly understand the temperature value of the measurement object.

[0089] Referring to Figure 2 Another embodiment of the present application provides a multi-channel temperature data processing method, which comprises:

[0090] determining a plurality of measurement points of a measurement object;

[0091] selecting a first measurement point and a second measurement point from the plurality of measurement points according to a measurement control model;

[0092] acquiring a plurality of first temperature data of the first measurement point and a plurality of second temperature data of the second measurement point in a preset time period, respectively;

[0093] transmitting the plurality of first temperature data and the plurality of second temperature data to a multi-channel processor after signal conditioning and analog-to-digital conversion;

[0094] performing temperature signal calculation and linearization correction on the plurality of first temperature data and the plurality of second temperature data by the multi-channel processor to obtain third temperature data and fourth temperature data, respectively;

[0095] sending the third temperature data and the fourth temperature data to a server;

[0096] generating a temperature monitoring data model of the measurement object by the server according to the third temperature data and the fourth temperature data.

[0097] It can be understood that the measurement object can be an industrial production device, a measuring instrument, an automobile engine, or other objects that need to be detected for temperature. In the embodiments of the present application, a plurality of measurement points for which temperature measurement of the measurement object is required can be determined through big data analysis of historical data, and these measurement points can be key components of the measurement object, elements that are prone to heat, components that are strictly controlled for temperature control accuracy, temperature-sensitive components, and the like.

[0098] The measurement control model is generated by processing historical working data, historical working environment data, historical temperature detection data, historical fault data, three-dimensional model data of the measurement object, product specification data of the measurement object including temperature detection requirements, and the like, in combination with a trained neural network, and is used to determine triggering, flow / steps, control process, and the like for temperature measurement of the measurement object. According to the measurement control model, a plurality of measurement points with the highest priority, including at least a first measurement point and a second measurement point, are selected from a plurality of measurement points. It should be noted that the measurement points with the highest priority can be temperature-sensitive components with the highest frequency of temperature abnormalities, components with the most stringent requirements for temperature control accuracy, and the like, and the embodiments of the present application do not limit this.

[0099] In the embodiments, a plurality of first temperature data of the first measurement point and a plurality of second temperature data of the second measurement point in a preset time period (which can be the most appropriate detection period obtained according to historical detection data analysis) are respectively acquired through different acquisition channels / acquisition sensors, and the plurality of first temperature data and the plurality of second temperature data are transmitted to a multi-channel processor after signal conditioning and analog-to-digital conversion. The process of signal conditioning and analog-to-digital conversion is as follows: first, the plurality of first temperature data and the plurality of second temperature data are processed by a first amplifier with a fixed amplification factor to increase data processing details, and then the first amplified data are input to a second amplifier with an adjustable amplification factor (the specific amplification factor value is determined according to the accuracy of the temperature value of the measurement point of the specific measurement object) for processing, and after processing, analog-to-digital conversion is performed, and after analog-to-digital conversion is completed, the data are input to a third amplifier with an adjustable amplification factor (the specific amplification factor value can be determined according to the accuracy requirement of the temperature value in the next processing process) for processing, so as to obtain data that can adapt to different accuracy requirements. By setting multiple amplifiers, small characteristic signals collected can be amplified, and the accuracy of temperature data collection is improved.

[0100] It can be understood that, in order to make the processing of temperature data more efficient and more accurate, in the embodiment of the present application, a multi-channel processor is adopted to process the temperature data of different measurement points. Specifically, the multi-channel processor respectively inputs a plurality of the first temperature data and the second temperature data into different processing channels, and obtains third temperature data and fourth temperature data after temperature signal calculation and linearization correction. It should be noted that, due to the possible differences in the structure, position, material and the like of the objects at different measurement points, the types of the temperature measurement tools may also be different, which may result in inconsistent types of the obtained measurement data. The adoption of the multi-channel processor can effectively avoid the problems caused by inconsistent types of the measurement data.

[0101] In the embodiment of the present application, the third temperature data and the fourth temperature data are sent to a server, and the server generates a temperature monitoring data model of the measurement object according to the third temperature data and the fourth temperature data, so as to track the temperature state of the measurement object.

[0102] It should be noted that, in the present application, the "first measurement point" and the "second measurement point" are only for illustration, and do not mean that the present application can only realize the measurement of two measurement points. The embodiment of the present application can realize a measurement scheme of more than two measurement points.

[0103] By adopting the technical scheme of the embodiment, the multi-channel temperature data acquisition method comprises: determining a plurality of measurement points of a measurement object; selecting a first measurement point and a second measurement point from the plurality of measurement points according to a measurement control model; respectively acquiring a plurality of first temperature data of the first measurement point and a plurality of second temperature data of the second measurement point within a preset time period; transmitting the plurality of first temperature data and the plurality of second temperature data to a multi-channel processor after signal conditioning and analog-to-digital conversion; the multi-channel processor respectively performs temperature signal calculation and linearization correction on the plurality of first temperature data and the plurality of second temperature data, and obtains third temperature data and fourth temperature data; and sending the third temperature data and the fourth temperature data to a server; and the server generates a temperature monitoring data model of the measurement object according to the third temperature data and the fourth temperature data. Through the embodiment of the present application, the temperature of different positions of the measurement object can be selectively measured, and the collected temperature data can be processed by multiple levels of signal processing and different processing channels, thereby improving the compatibility of the temperature data, the efficiency of the temperature data processing, and the accuracy of the temperature measurement.

[0104] In some possible embodiments of the present application, the method further comprises:

[0105] determining whether the temperature of the measurement object is abnormal according to the third temperature data and the fourth temperature data;

[0106] when the abnormality exists, determining third measurement points and fourth measurement points different from the first measurement points and the second measurement points from the plurality of measurement points;

[0107] obtaining fifth temperature data of the third measurement points and sixth temperature data of the fourth measurement points;

[0108] determining whether the temperature of the measurement object is abnormal according to the fifth temperature data and the sixth temperature data;

[0109] when the abnormality exists, triggering an abnormality processing program.

[0110] It can be understood that in the embodiments of the present application, when it is determined that the temperature of the measurement object is abnormal according to the third temperature data and the fourth temperature data, in order to avoid misjudgment, a step of verification is needed, so third measurement points and fourth measurement points different from the first measurement points and the second measurement points are determined from the plurality of measurement points; fifth temperature data of the third measurement points and sixth temperature data of the fourth measurement points are obtained; whether the temperature of the measurement object is abnormal is determined according to the fifth temperature data and the sixth temperature data; when the abnormality exists, it indicates that the measurement object has a temperature abnormality, and an abnormality processing program is triggered to avoid accidents.

[0111] In some possible embodiments of the present application, before the plurality of measurement points of the measurement object are determined, the method further comprises:

[0112] obtaining three-dimensional point cloud data of the measurement object;

[0113] constructing a three-dimensional model of the measurement object according to the three-dimensional point cloud data.

[0114] It can be understood that in order to more clearly understand the structure of the measurement object for efficient temperature monitoring, in the embodiments of the present application, the three-dimensional model of the measurement object is constructed by obtaining the three-dimensional point cloud data of the measurement object to assist in temperature measurement. The three-dimensional point cloud data can provide detailed three-dimensional information of the measurement object, and the three-dimensional model constructed therefrom is detailed and has high accuracy.

[0115] In some possible embodiments of the present application, after the three-dimensional model of the measurement object is constructed according to the three-dimensional point cloud data, the method further comprises:

[0116] obtaining historical temperature data of the measurement object;

[0117] classify the historical temperature data according to components of the measurement object;

[0118] determine a first component whose frequency of temperature abnormality is higher than a preset threshold;

[0119] determine the measurement control model containing the key measurement position according to the first component and the three-dimensional model.

[0120] It can be understood that the embodiment provides a method for generating a measurement control model, that is, by acquiring historical temperature data of a measurement object, classifying the historical temperature data according to components of the measurement object, determining a plurality of first components whose frequency of temperature abnormality is higher than a preset threshold, and determining the measurement control model containing the key measurement position according to the first component and the three-dimensional model, the key measurement position is a point corresponding to the plurality of first components whose frequency of temperature abnormality is higher than the preset threshold, and the first measurement position and the second measurement position in the foregoing embodiment can be selected. Through the embodiment, monitoring of the higher frequency of temperature abnormality can be realized, targeted measurement is realized, and work efficiency is improved.

[0121] In some possible embodiments of the present application, the method further comprises:

[0122] marking the first temperature data, the second temperature data, the fifth temperature data, and the sixth temperature data on the three-dimensional model.

[0123] In the embodiment, by marking the temperature data on the measurement three-dimensional model, more intuitive visual presentation can be provided, and a user can quickly understand the temperature value condition of the measurement object.

[0124] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited to the action order described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0125] In the foregoing embodiments, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0126] In several embodiments provided in the present application, it should be understood that the disclosed apparatus can be implemented in other manners. For example, the division of the apparatus embodiments described above is merely illustrative, and the division of the units can be changed according to actual needs. For example, the units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0127] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0128] In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0129] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable memory. Based on this understanding, the technical solutions of the present application essentially or the part of the prior art that contributes to the technical solutions or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a memory and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned memory includes: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0130] Those of ordinary skill in the art can understand that all or part of the steps of the various methods in the above embodiments can be completed by a program instructing related hardware, and the program can be stored in a computer readable memory, which can include a flash disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0131] The above detailed description of the embodiments of the present application is made with specific examples applied to the principles and implementation modes of the present application, and the above description of the embodiments is only used to help understand the method of the present application and its core idea; meanwhile, for the general technical personnel in the art, according to the idea of the present application, the specific implementation mode and the application range can be changed, and the above description of the present application should not be understood as the limitation of the present application.

[0132] Although the present application is disclosed as above, the present application is not limited to this. Any person skilled in the art can easily think of changes or replacements without departing from the spirit and scope of the present application, and can make various changes and modifications, including the combination of different functions and implementation steps, including the implementation mode of software and hardware, which are all within the protection scope of the present application.

Claims

1. A multi-channel temperature data acquisition system, characterized by, The method comprises the following steps: determining a plurality of measurement points of a measurement object; selecting a first measurement point and a second measurement point from the plurality of measurement points according to a measurement control model; acquiring a plurality of first temperature data of the first measurement point and a plurality of second temperature data of the second measurement point in a preset time period respectively; transmitting the plurality of first temperature data and the plurality of second temperature data to a multi-channel processor after signal conditioning and analog-to-digital conversion; performing temperature signal calculation and linearization correction on the plurality of first temperature data and the plurality of second temperature data to obtain third temperature data and fourth temperature data respectively, and sending the third temperature data and the fourth temperature data to a server; generating a temperature monitoring data model of the measurement object according to the third temperature data and the fourth temperature data; judging whether the temperature of the measurement object is abnormal according to the third temperature data and the fourth temperature data; when there is an abnormality, determining a third measurement point and a fourth measurement point different from the first measurement point and the second measurement point from the plurality of measurement points; acquiring fifth temperature data of the third measurement point and sixth temperature data of the fourth measurement point; judging whether the temperature of the measurement object is abnormal according to the fifth temperature data and the sixth temperature data, and triggering an abnormality processing program when there is an abnormality; The measurement control model is generated by combining a trained neural network processing according to historical working data, historical working environment data, historical temperature detection data, historical fault data, three-dimensional model data of the measurement object, and product specification data including temperature detection requirements of the measurement object; the measurement control model is used to determine the trigger condition, measurement process and measurement control process of temperature measurement of the measurement object. The method further comprises the following steps:

2. The multi-channel temperature data acquisition system of claim 1, wherein, acquiring three-dimensional point cloud data of the measurement object; constructing a three-dimensional model of the measurement object according to the three-dimensional point cloud data. The server further comprises the following steps:

3. The multi-channel temperature data acquisition system of claim 2, wherein, acquiring historical temperature data of the measurement object; classifying the historical temperature data according to components of the measurement object; determining a first component whose temperature abnormality frequency is higher than a preset threshold; determining the measurement control model containing a key measurement position according to the first component and the three-dimensional model. The server is further used to mark the first temperature data, the second temperature data, the fifth temperature data and the sixth temperature data on the three-dimensional model.

4. The multi-channel temperature data acquisition system of claim 3, wherein, The method comprises the following steps:

5. A multi-channel temperature data processing method, characterized by, determining a plurality of measurement points of a measurement object; selecting a first measurement point and a second measurement point from the plurality of measurement points according to a measurement control model; ​ Acquire a plurality of first temperature data of the first measuring point and a plurality of second temperature data of the second measuring point in a preset time period respectively; After signal conditioning and analog-digital conversion, transmit the plurality of first temperature data and the plurality of second temperature data to a multi-channel processor; The multi-channel processor respectively performs temperature signal calculation and linearization correction on the plurality of first temperature data and the plurality of second temperature data to obtain third temperature data and fourth temperature data; Send the third temperature data and the fourth temperature data to a server; The server generates a temperature monitoring data model of the measuring object according to the third temperature data and the fourth temperature data; Determine whether the temperature of the measuring object is abnormal according to the third temperature data and the fourth temperature data; When there is an abnormality, determine a third measuring point and a fourth measuring point different from the first measuring point and the second measuring point from a plurality of measuring points; Acquire fifth temperature data of the third measuring point and sixth temperature data of the fourth measuring point; Determine whether the temperature of the measuring object is abnormal according to the fifth temperature data and the sixth temperature data; When there is an abnormality, trigger an abnormality processing program; The measuring control model is generated according to historical working data, historical working environment data, historical temperature detection data, historical fault data, three-dimensional model data of the measuring object, and product specification data including temperature detection requirements, combined with a trained neural network processing; the measuring control model is used to determine the trigger condition, measurement process and measurement control process of temperature measurement of the measuring object.

6. The multi-channel temperature data processing method of claim 5, wherein, Before determining the plurality of measuring points of the measuring object, the method further comprises: Acquire three-dimensional point cloud data of the measuring object; Construct a three-dimensional model of the measuring object according to the three-dimensional point cloud data.

7. The multi-channel temperature data processing method of claim 6, wherein, After constructing the three-dimensional model of the measuring object according to the three-dimensional point cloud data, the method further comprises: Acquire historical temperature data of the measuring object; Classify the historical temperature data according to components of the measuring object; Determine a first component whose temperature abnormality frequency is higher than a preset threshold; Determine the measuring control model containing a key measuring position according to the first component and the three-dimensional model.

8. The multi-channel temperature data processing method of claim 7, wherein, The method further comprises: Mark the first temperature data, the second temperature data, the fifth temperature data and the sixth temperature data on the three-dimensional model.

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