CN116504042A - Abnormal temperature alarm generation method, device, equipment and medium - Google Patents

Abnormal temperature alarm generation method, device, equipment and medium Download PDF

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Publication number
CN116504042A
CN116504042A CN202310467760.2A CN202310467760A CN116504042A CN 116504042 A CN116504042 A CN 116504042A CN 202310467760 A CN202310467760 A CN 202310467760A CN 116504042 A CN116504042 A CN 116504042A
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temperature
target
absolute
threshold
product
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黄书健
龚演平
施理成
卢先锋
寨战争
蔡素雄
杨茂强
潘俊龙
张焕燊
陶莹珊
吕宇桦
刘晨炀
彭威望
季高炜
刘俊威
陈洛奇
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Guangdong Power Grid Co Ltd
Huizhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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Guangdong Power Grid Co Ltd
Huizhou Power Supply Bureau of Guangdong Power Grid Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
    • G01K13/00—Thermometers specially adapted for specific purposes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
    • G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
    • G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines

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  • Control Of Temperature (AREA)
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Abstract

The invention discloses a method, a device, equipment and a medium for generating abnormal temperature alarms, and relates to the technical field of data processing. Comprising the following steps: correcting the current measured temperature by adopting a target network model to obtain a target real temperature of target equipment; if the target real temperature is greater than or equal to any candidate absolute temperature threshold, generating a target absolute temperature alarm of target equipment; determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and generating a relative temperature alarm of the target equipment if the ratio between the first difference value and the second difference value is larger than a preset relative threshold value. According to the scheme, the measured temperature is corrected through a target network model, so that the real temperature is obtained; according to the real temperature, the environment temperature, the normal rated temperature of the target equipment and the highest allowable temperature of the target equipment, an abnormal temperature alarm is generated, and the accuracy of the abnormal temperature alarm is improved.

Description

Abnormal temperature alarm generation method, device, equipment and medium
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method, an apparatus, a device, and a medium for generating an abnormal temperature alarm.
Background
In a substation, temperature is an important indicator of the operating state of the reactive power equipment. The over-high temperature of the power equipment can reduce the insulation strength of insulating materials in the equipment, reduce the service life of the power equipment, lead to the failure of the power equipment and influence the safe and stable operation of a power system. At present, an abnormal temperature alarming mode of the power equipment is generally that an operator measures the temperature of the power equipment from a thermometer to a transformer substation, and judges whether to alarm according to the measured temperature. The technical scheme has the defect of poor alarm accuracy.
Disclosure of Invention
The invention provides a method, a device, equipment and a medium for generating an abnormal temperature alarm, which are used for improving the accuracy of the abnormal temperature alarm.
In a first aspect, the present invention provides a method for generating an abnormal temperature alarm, including:
acquiring the current measured temperature of target equipment;
correcting the current measured temperature by adopting a target network model to obtain a target real temperature of target equipment; the target network model is determined according to the historical measured temperature and the historical real temperature of the candidate equipment;
if the target real temperature is greater than or equal to any candidate absolute temperature threshold, generating a target absolute temperature alarm of target equipment; the candidate absolute temperature threshold is determined according to the target real temperature, the environment temperature, the normal rated temperature of target equipment, the highest allowable temperature of the target equipment and the ratio of the candidate absolute temperature;
Determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and generating a relative temperature alarm of the target equipment if the ratio between the first difference value and the second difference value is larger than a preset relative threshold value.
In a second aspect, the present invention further provides a device for generating an abnormal temperature alarm, including:
the measuring temperature acquisition module is used for acquiring the current measuring temperature of the target equipment;
the real temperature determining module is used for correcting the current measured temperature by adopting the target network model to obtain the target real temperature of the target equipment; the target network model is determined according to the historical measured temperature and the historical real temperature of the candidate equipment;
the absolute alarm generation module is used for generating a target absolute temperature alarm of target equipment if the target real temperature is greater than or equal to any candidate absolute temperature threshold; the candidate absolute temperature threshold is determined according to the target real temperature, the environment temperature, the normal rated temperature of target equipment, the highest allowable temperature of the target equipment and the ratio of the candidate absolute temperature;
the relative alarm generating module is used for determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and if the ratio of the first difference value to the second difference value is larger than a preset relative threshold value, generating a relative temperature alarm of the target equipment.
In a third aspect, an embodiment of the present invention further provides an electronic device, including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the method comprises the steps of
The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of generating an abnormal temperature alert provided by any one of the embodiments of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where computer instructions are stored, where the computer instructions are configured to cause a processor to implement the method for generating an abnormal temperature alarm according to any of the embodiments of the present invention when executed.
The embodiment of the invention acquires the current measurement temperature of the target equipment; correcting the current measured temperature by adopting a target network model to obtain a target real temperature of target equipment; if the target real temperature is greater than or equal to any candidate absolute temperature threshold, generating a target absolute temperature alarm of target equipment; determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and generating a relative temperature alarm of the target equipment if the ratio between the first difference value and the second difference value is larger than a preset relative threshold value. According to the technical scheme, the measured temperature of the target equipment is corrected through the target network model, so that the real temperature of the target equipment is obtained; according to the real temperature, the environment temperature, the normal rated temperature and the highest allowable temperature of the target equipment, the abnormal temperature alarm is generated, and the accuracy of the abnormal temperature alarm is improved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for generating an abnormal temperature alarm according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a method for generating an abnormal temperature alarm according to a second embodiment of the present invention;
FIG. 3 is a flowchart of a method for generating an abnormal temperature alarm according to a third embodiment of the present invention;
fig. 4 is a block diagram of an abnormal temperature alarm generating apparatus according to a fourth embodiment of the present invention;
fig. 5 is a schematic diagram of an electronic device according to a fifth embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent 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 present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," "third," "target," and "original" in the description and claims of the present invention and the above drawings are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of a method for generating an abnormal temperature alarm according to a first embodiment of the present invention, where the method may be executed by an apparatus for generating an abnormal temperature alarm, and the apparatus for generating an abnormal temperature alarm may be implemented in hardware and/or software, and specifically configured in an electronic device, for example, a server.
As shown in fig. 1, the method includes:
s101, acquiring the current measured temperature of the target equipment.
In this embodiment, the target device may be a device to be subjected to abnormal temperature detection, for example, a transformer, a circuit breaker, a transformer, and the like in a substation. The current measured temperature may be a temperature of the target device measured at the current time.
S102, correcting the current measured temperature by adopting a target network model to obtain a target real temperature of target equipment; the target network model is determined according to the historical measured temperature and the historical real temperature of the candidate equipment.
In this embodiment, the target network model is a network model for correcting the current measured temperature, and may be determined according to the historical measured temperature and the historical actual temperature of the candidate device. The candidate device may be a device having a historic measured temperature and a historic true temperature. The historic measured temperature may be a target device measured temperature at a historic time prior to the current time; the historical true temperature may be a target device true temperature at a historical time prior to the current time. Wherein, the corresponding historical time of the historical measured temperature is the same as the corresponding historical time of the historical real temperature.
The invention is not limited to the kind of the target network model, and for example, a BP (Back-propagation) neural network model, an LTSM (Long Short-Term Memory) neural network, an extreme learning machine (Extreme Learning Machines, ELM) and the like can be used. The target real temperature may be the real temperature of the target device at the current time.
Specifically, the current measured temperature is input into the target network model, so that the target network model corrects the current measured temperature, and the output data of the target network model is the target real temperature of the target equipment.
S103, if the target real temperature is greater than or equal to any candidate absolute temperature threshold, generating a target absolute temperature alarm of target equipment; the candidate absolute temperature threshold is determined according to the target real temperature, the environment temperature, the normal rated temperature of the target equipment, the highest allowable temperature of the target equipment and the candidate absolute temperature ratio.
In this embodiment, the candidate absolute temperature threshold may be a threshold that limits the target real temperature; the target absolute temperature alarm is alarm information of the target real temperature of the target equipment being too high; the ambient temperature may be the temperature of the environment surrounding the target device. The normal rated temperature of the target device may be the rated temperature of the target device in a normal operation state. The normal rated temperature of the target device and the maximum allowable temperature of the target device can be set autonomously by the skilled person according to actual demands or practical experience. The candidate absolute temperature ratio may be used to characterize the importance of the normal nominal temperature of the target device to the candidate absolute temperature threshold, and the candidate absolute temperature ratio may be set autonomously by the technician according to actual needs or practical experience.
S104, determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and if the ratio of the first difference value to the second difference value is larger than a preset relative threshold value, generating a relative temperature alarm of the target equipment.
In this embodiment, the preset relative threshold may be set by a technician according to an actual requirement or a practical experience, which is not limited in the present invention, and the relative temperature alarm may be an alarm message that the difference between the target real temperature and the ambient temperature is too high.
Illustratively, the ratio between the first difference and the second difference may be determined as follows:
wherein K is t Representing a ratio between the first difference and the second difference; t is t 1 -t 2 Representing a first difference; t is t 1 -t 0 Representing a second difference; t is t 1 Representing the target real temperature; t is t 2 Indicating the normal rated temperature of the target equipment; t is t 0 Indicating the ambient temperature.
Optionally, the temperature measuring device for measuring the temperature of the target device includes a main control module and a wireless communication module. The main control module is preset with an infrared temperature measuring unit, a voice alarm unit and a temperature display unit. In a specific embodiment, the master control module may be an STM32 single-chip microcomputer. Specifically, the temperature measuring equipment carries out non-contact temperature acquisition on the target equipment; the wireless communication module can upload the current temperature measurement data to the cloud; the cloud end corrects the current temperature measurement data through the target network model to obtain the target real temperature of the target equipment, and sends the target real temperature to the temperature measurement equipment so that a temperature display unit in the temperature measurement equipment displays the target real temperature of the target equipment in the temperature measurement equipment; if the target real temperature is greater than or equal to any candidate absolute temperature threshold, generating a target absolute temperature alarm of target equipment in the cloud; determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and generating a relative temperature alarm of the target equipment in the cloud if the ratio between the first difference value and the second difference value is larger than a preset relative threshold value; if the target absolute temperature alarm and/or the relative temperature alarm of the target equipment are generated in the cloud, the target absolute temperature alarm and/or the relative temperature alarm are sent to a voice alarm unit of the temperature measuring equipment, so that the temperature measuring equipment broadcasts the generation information of the abnormal temperature alarm. The auxiliary decision making function can be provided for operators, and the working efficiency of the operators is improved.
The embodiment of the invention acquires the current measurement temperature of the target equipment; correcting the current measured temperature by adopting a target network model to obtain a target real temperature of target equipment; if the target real temperature is greater than or equal to any candidate absolute temperature threshold, generating a target absolute temperature alarm of target equipment; determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and generating a relative temperature alarm of the target equipment if the ratio between the first difference value and the second difference value is larger than a preset relative threshold value. According to the technical scheme, the measured temperature of the target equipment is corrected through the target network model, so that the real temperature of the target equipment is obtained; according to the real temperature, the environment temperature, the normal rated temperature and the highest allowable temperature of the target equipment, the abnormal temperature alarm is generated, and the accuracy of the abnormal temperature alarm is improved.
Example two
Fig. 2 is a flowchart of a method for generating an abnormal temperature alarm according to a second embodiment of the present invention, where additional optimization is performed based on the technical solution of the foregoing embodiment.
Further, "determining a first product between the normal rated temperature of the target device and the first absolute temperature ratio, a second product between the normal rated temperature of the target device and the second absolute temperature ratio, and a third product between the normal rated temperature of the target device and the third absolute temperature ratio; taking the sum of the first product and the ambient temperature as an auxiliary temperature; and determining a candidate absolute temperature threshold 'of the target equipment according to the auxiliary temperature, the maximum allowable temperature of the target equipment, the ambient temperature, the first product, the second product and the third product, so as to perfect the determination operation of the candidate absolute temperature threshold' of the target equipment.
In the embodiments of the present invention, the details are not described, and reference may be made to the description of the foregoing embodiments.
A method as shown in fig. 2, the method comprising:
s201, determining a first product between the normal rated temperature of the target device and the first absolute temperature ratio, a second product between the normal rated temperature of the target device and the second absolute temperature ratio, and a third product between the normal rated temperature of the target device and the third absolute temperature ratio.
In this embodiment, the candidate absolute temperature ratio may include, but is not limited to, a first absolute temperature ratio, a second absolute temperature ratio, and a third absolute temperature ratio. Wherein the first absolute temperature ratio, the second absolute temperature ratio, and the third absolute temperature ratio increase in order.
S202, taking the sum of the first product and the ambient temperature as an auxiliary temperature.
S203, determining a candidate absolute temperature threshold of the target equipment according to the auxiliary temperature, the highest allowable temperature of the target equipment, the ambient temperature, the first product, the second product and the third product.
Optionally, the candidate absolute temperature threshold includes a first absolute temperature threshold, a second absolute temperature threshold, and a third absolute temperature threshold; wherein the first absolute temperature threshold, the second absolute temperature threshold, and the third absolute temperature threshold are sequentially increased; determining a candidate absolute temperature threshold for the target device based on the auxiliary temperature, the maximum allowable temperature for the target device, the ambient temperature, the first product, the second product, and the third product, comprising: if the auxiliary temperature is less than or equal to the maximum allowable temperature of the target device, taking the auxiliary temperature as a first absolute temperature threshold, taking the sum between the second product and the ambient temperature as a second absolute temperature threshold, and taking the sum between the third product and the ambient temperature as a third absolute temperature threshold; if the auxiliary temperature is greater than the maximum allowable temperature of the target device, the sum between the first product and the maximum allowable temperature is taken as a first absolute temperature threshold, the sum between the second product and the maximum allowable temperature is taken as a second absolute temperature threshold, and the sum between the third product and the ambient temperature is taken as a third absolute temperature threshold.
For example, if the auxiliary temperature is less than or equal to the maximum allowable temperature of the target device, the candidate absolute temperature threshold of the target device may be determined by the following formula:
wherein T is 1 Representing a first absolute temperature threshold; t (T) 2 Representing a second absolute temperature threshold; t (T) 3 Representing a third absolute temperature threshold; t (T) 0 Representing ambient temperature; a, a 1 Representing a first product; a, a 2 Representing a second product; a, a 3 Representing a third product.
For example, if the auxiliary temperature is greater than the maximum allowable temperature of the target device, the candidate absolute temperature threshold of the target device may be determined by the following formula:
wherein T1 represents a first absolute temperature threshold; t2 represents a second absolute temperature threshold; t3 represents a third absolute temperature threshold; t (T) max Representing the highest allowable temperature of the target device; a1 represents a first product; a2 represents a second product; a3 represents a third product.
It can be understood that by adopting the technical scheme, the candidate absolute temperature threshold value of the target equipment is flexibly determined according to the magnitude relation between the auxiliary temperature and the maximum allowable temperature of the target equipment, so that the applicability and the accuracy of the candidate absolute temperature threshold value under different auxiliary temperatures and different maximum allowable temperatures are improved, and the accuracy of generating the target absolute temperature alarm according to the candidate absolute temperature threshold value is further improved.
S204, acquiring the current measured temperature of the target equipment.
S205, correcting the current measured temperature by adopting a target network model to obtain a target real temperature of target equipment; the target network model is determined according to the historical measured temperature and the historical real temperature of the candidate equipment.
S206, if the target real temperature is greater than or equal to any candidate absolute temperature threshold, generating a target absolute temperature alarm of target equipment; the candidate absolute temperature threshold is determined according to the target real temperature, the environment temperature, the normal rated temperature of the target equipment, the highest allowable temperature of the target equipment and the candidate absolute temperature ratio.
S207, determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and generating a relative temperature alarm of the target equipment if the ratio between the first difference value and the second difference value is larger than a preset relative threshold value.
The method comprises the steps of determining a first product between a normal rated temperature of target equipment and a first absolute temperature ratio, a second product between the normal rated temperature of the target equipment and a second absolute temperature ratio, and a third product between the normal rated temperature of the target equipment and a third absolute temperature ratio; taking the sum of the first product and the ambient temperature as an auxiliary temperature; and determining a candidate absolute temperature threshold of the target device according to the auxiliary temperature, the maximum allowable temperature of the target device, the ambient temperature, the first product, the second product and the third product. By adopting the technical scheme, the auxiliary temperature is determined according to the first product and the ambient temperature; and determining the candidate absolute temperature threshold according to the auxiliary temperature, the maximum allowable temperature of the target equipment, the ambient temperature, the first product, the second product and the third product, thereby improving the accuracy of the candidate absolute temperature threshold and further improving the accuracy of generating the target absolute temperature alarm according to the candidate absolute temperature threshold.
Example III
Fig. 3 is a flowchart of a method for generating an abnormal temperature alarm according to a third embodiment of the present invention, where additional optimization is performed based on the technical solution of the foregoing embodiment.
Further, adding a particle swarm algorithm, and performing iterative optimization on the weight and the threshold value of the original network model according to the historical measured temperature and the historical real temperature of the candidate equipment to obtain an optimized original network model; training the optimized original network model according to the historical measured temperature and the historical real temperature of each candidate device to obtain a target network model so as to perfect the determining operation of the target network model.
A method as shown in fig. 3, the method comprising:
and S301, adopting a particle swarm algorithm, and carrying out iterative optimization on the weight and the threshold value of the original network model according to the historical measured temperature and the historical real temperature of the candidate equipment to obtain an optimized original network model.
In this embodiment, the original network model may be an initialized network model. Specifically, a particle swarm algorithm is adopted, and iteration optimization is carried out on the weight and the threshold value of the original network model according to the historical measured temperature and the historical real temperature of the candidate equipment; taking the weight after the preset iteration times as an optimal initial weight, taking a threshold after the preset iteration times as an optimal initial threshold, taking the optimal initial weight as the weight, and taking the original network model with the optimal initial threshold as the original network model after optimization.
Optionally, a particle swarm algorithm is adopted, and iteration optimization is performed on the weight and the threshold of the original network model according to the historical measured temperature and the historical real temperature of the candidate device, so as to obtain an optimized original network model, which comprises the following steps: taking the mean square value of the error between the historical real temperature of each candidate device and the predicted temperature of the original network model as an adaptability function; the predicted temperature is obtained according to the historical measured temperatures of the original neural network and the candidate equipment; and carrying out iterative optimization on the weight and the threshold value of the original network model according to the particle swarm algorithm and the fitness function to obtain the optimized original network model.
Illustratively, the fitness function may be expressed by the following formula:
wherein M represents an fitness function; m represents the number of candidate devices; d, d i Representing the historical true temperature of the ith candidate device; o (o) i Representing the predicted temperature of the i-th candidate device.
In one embodiment, the particle swarm parameters and the number of particles are initialized, and each particle location contains the ownership and threshold of the original network model. And determining the fitness of each particle by adopting a fitness function, and iterating the speed and the position of each particle through the following formula:
v i (t+1)＝wv i (t)+c 1 (t)r 1 (p i (t)-x i (t))+c 2 (t)r 2 (p g (t)-x i (t))；
x i (t+1)＝x i (t)+v i (t+1)；
Wherein t represents the number of iterations; i represents the serial number of the particle; v represents the velocity of the particles; x represents the position of the particle; w represents an inertial weight; c 1 And c 2 Representing a learning factor; r is (r) 1 And r 2 The representation being distributed over [0,1 ]]A random number on the table; p is p i Representing the optimal position of particle i; p is p g Indicating the optimal particle position in the population of particles.
Taking the weight in the optimal particle position of the particle swarm after the preset iterative optimization times as an optimal initial weight; taking a threshold value in the optimal particle position of the particle swarm after the preset iterative optimization times as an optimal initial threshold value; and taking the original network model taking the optimal initial weight as a weight and taking the optimal initial threshold as a threshold as an optimized original network model.
It can be appreciated that by adopting the above technical scheme, according to the historical real temperature of the candidate device and the predicted temperature and the particle swarm algorithm of the original network model, the optimal initial threshold and the optimal initial weight of the original network model for correcting the measured temperature can be obtained, so that the optimized original network model is trained on the basis of the optimal initial threshold and the optimal initial weight, and further, the accuracy of correcting the measured temperature by the target network model and the efficiency of training the network model for correcting the temperature are improved.
S302, training the optimized original network model according to the historical measured temperature and the historical real temperature of each candidate device to obtain a target network model.
Specifically, taking the historical measured temperature of the candidate device as a sample value; for each sample value, determining the predicted temperature of each output layer after the sample value is input into the optimized original network model; if the temperature difference between the predicted temperature of each output layer and the historical real temperature of the candidate device is smaller than the error threshold value corresponding to each output layer, taking the optimized original network model as a target network model; otherwise, the weight and the threshold value of the optimized original network model are adjusted, and the steps are repeated, namely, for each sample value, the predicted temperature of each output layer of the sample value input into the optimized original network model is determined; and if the temperature difference between the predicted temperature of each output layer and the historical real temperature of the candidate equipment is smaller than the error threshold value corresponding to each output layer, taking the optimized original network model as a target network model.
It should be noted that, S301 and S302 are executed only once, and are used for obtaining the target network model according to the historical measured temperature and the historical real temperature of the candidate device by adopting the particle swarm algorithm in advance, so as to directly adopt the target network model to correct the current measured temperature of the target device, and improve the efficiency of determining the target real temperature.
S303, acquiring the current measured temperature of the target equipment.
S304, correcting the current measured temperature by adopting a target network model to obtain a target real temperature of target equipment; the target network model is determined according to the historical measured temperature and the historical real temperature of the candidate equipment.
S305, if the target real temperature is greater than or equal to any candidate absolute temperature threshold, generating a target absolute temperature alarm of target equipment; the candidate absolute temperature threshold is determined according to the target real temperature, the environment temperature, the normal rated temperature of the target equipment, the highest allowable temperature of the target equipment and the candidate absolute temperature ratio.
S306, determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and if the ratio of the first difference value to the second difference value is larger than a preset relative threshold value, generating a relative temperature alarm of the target equipment.
According to the embodiment of the invention, a particle swarm algorithm is adopted, and the weight and the threshold of the original network model are iteratively optimized according to the historical measured temperature and the historical real temperature of the candidate equipment, so that the optimized original network model is obtained; and training the optimized original network model according to the historical measured temperature and the historical real temperature of each candidate device to obtain a target network model. According to the technical scheme, the particle swarm algorithm is adopted, the weight and the threshold of the original network model are optimized in an iterative mode according to the historical measured temperature and the historical real temperature of the candidate equipment, the optimized original network model is trained according to the historical measured temperature and the historical real temperature of each candidate equipment, the target network model is obtained, the accuracy of correcting the current measured temperature of the target network model, namely the accuracy of the target real temperature, is improved, and the accuracy of generating an alarm by the target real temperature is further improved.
Example IV
Fig. 4 is a block diagram of an abnormal temperature alarm generating device according to a fourth embodiment of the present invention, where the present embodiment is applicable to a case of generating an abnormal temperature alarm, and the abnormal temperature alarm generating device may be implemented in hardware and/or software, and specifically configured in an electronic device, for example, a server.
The abnormal temperature alarm generating apparatus shown in fig. 4 includes a measured temperature acquisition module 401, a true temperature determination module 402, an absolute alarm generating module 403, and a relative alarm generating module 404. Wherein,,
a measured temperature obtaining module 401, configured to obtain a current measured temperature of the target device;
the real temperature determining module 402 is configured to correct the current measured temperature by using a target network model to obtain a target real temperature of the target device; the target network model is determined according to the historical measured temperature and the historical real temperature of the candidate equipment;
an absolute alarm generating module 403, configured to generate a target absolute temperature alarm of the target device if the target real temperature is greater than or equal to any candidate absolute temperature threshold; the candidate absolute temperature threshold is determined according to the target real temperature, the environment temperature, the normal rated temperature of target equipment, the highest allowable temperature of the target equipment and the ratio of the candidate absolute temperature;
The relative alarm generating module 404 is configured to determine a first difference between the target real temperature and the normal rated temperature of the target device, and a second difference between the target real temperature and the ambient temperature, and if a ratio between the first difference and the second difference is greater than a preset relative threshold, generate a relative temperature alarm of the target device.
According to the embodiment of the invention, the current measured temperature of the target equipment is obtained through the measured temperature obtaining module; correcting the current measured temperature by a real temperature determining module by adopting a target network model to obtain a target real temperature of target equipment; the target network model is determined according to the historical measured temperature and the historical real temperature of the candidate equipment; generating a target absolute temperature alarm of target equipment if the target real temperature is greater than or equal to any candidate absolute temperature threshold value through an absolute alarm generation module; the candidate absolute temperature threshold is determined according to the target real temperature, the environment temperature, the normal rated temperature of target equipment, the highest allowable temperature of the target equipment and the ratio of the candidate absolute temperature; and determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature through a relative alarm generation module, and if the ratio between the first difference value and the second difference value is larger than a preset relative threshold value, generating a relative temperature alarm of the target equipment. According to the technical scheme, the measured temperature of the target equipment is corrected through the target network model, so that the real temperature of the target equipment is obtained; according to the real temperature, the environment temperature, the normal rated temperature and the highest allowable temperature of the target equipment, the abnormal temperature alarm is generated, and the accuracy of the abnormal temperature alarm is improved.
Optionally, in the apparatus, the candidate absolute temperature ratio includes a first absolute temperature ratio, a second absolute temperature ratio, and a third absolute temperature ratio; the apparatus further comprises:
a temperature product determining module, configured to determine a first product between a normal rated temperature of the target device and a first absolute temperature ratio, a second product between a normal rated temperature of the target device and a second absolute temperature ratio, and a third product between a normal rated temperature of the target device and a third absolute temperature ratio;
an auxiliary temperature determination module for taking the sum of the first product and the ambient temperature as an auxiliary temperature;
and the absolute temperature threshold determining module is used for determining a candidate absolute temperature threshold of the target equipment according to the auxiliary temperature, the highest allowable temperature of the target equipment, the environment temperature, the first product, the second product and the third product.
Optionally, in the apparatus, the candidate absolute temperature threshold includes a first absolute temperature threshold, a second absolute temperature threshold, and a third absolute temperature threshold; wherein the first absolute temperature threshold, the second absolute temperature threshold, and the third absolute temperature threshold are sequentially increased; an absolute temperature threshold determination module comprising:
A first threshold determining unit configured to take the auxiliary temperature as a first absolute temperature threshold, take a sum between the second product and the ambient temperature as a second absolute temperature threshold, and take a sum between the third product and the ambient temperature as a third absolute temperature threshold if the auxiliary temperature is less than or equal to a maximum allowable temperature of the target device;
and the second threshold determining unit is used for taking the sum between the first product and the maximum allowable temperature as a first absolute temperature threshold, taking the sum between the second product and the maximum allowable temperature as a second absolute temperature threshold and taking the sum between the third product and the environmental temperature as a third absolute temperature threshold if the auxiliary temperature is larger than the maximum allowable temperature of the target equipment.
Optionally, the device further includes:
the model optimization module is used for carrying out iterative optimization on the weight and the threshold value of the original network model according to the historical measured temperature and the historical real temperature of the candidate equipment by adopting a particle swarm algorithm to obtain an optimized original network model;
and the target model determining module is used for training the optimized original network model according to the historical measured temperature and the historical real temperature of each candidate device to obtain a target network model.
Optionally, the model optimization module includes:
the fitness function determining unit is used for taking the mean square value of the error between the historical real temperature of each candidate device and the predicted temperature of the original network model as a fitness function; the predicted temperature is obtained according to the historical measured temperatures of the original neural network and the candidate equipment;
and the model optimization unit is used for carrying out iterative optimization on the weight and the threshold value of the original network model according to the particle swarm algorithm and the fitness function to obtain an optimized original network model.
The generation device of the abnormal temperature alarm can execute the generation method of the abnormal temperature alarm provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the generation methods of different abnormal temperature alarms.
Example five
Fig. 5 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 5, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the respective methods and processes described above, such as the generation method of the abnormal temperature alarm.
In some embodiments, the method of generating an abnormal temperature alarm may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the above-described generation method of the abnormal temperature alarm may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the method of generating the abnormal temperature alert in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims (10)

1. A method for generating an abnormal temperature alarm, the method comprising:
acquiring the current measured temperature of target equipment;
correcting the current measured temperature by adopting a target network model to obtain a target real temperature of target equipment; the target network model is determined according to the historical measured temperature and the historical real temperature of the candidate equipment;
if the target real temperature is greater than or equal to any candidate absolute temperature threshold, generating a target absolute temperature alarm of target equipment; the candidate absolute temperature threshold is determined according to the target real temperature, the environment temperature, the normal rated temperature of target equipment, the highest allowable temperature of the target equipment and the candidate absolute temperature ratio;
Determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and generating a relative temperature alarm of the target equipment if the ratio between the first difference value and the second difference value is larger than a preset relative threshold value.
2. The method of claim 1, wherein the candidate absolute temperature ratio comprises a first absolute temperature ratio, a second absolute temperature ratio, and a third absolute temperature ratio; the candidate absolute temperature threshold is determined by:
determining a first product between the normal rated temperature of the target device and the first absolute temperature ratio, a second product between the normal rated temperature of the target device and the second absolute temperature ratio, and a third product between the normal rated temperature of the target device and the third absolute temperature ratio;
taking the sum of the first product and the ambient temperature as an auxiliary temperature;
and determining a candidate absolute temperature threshold of the target equipment according to the auxiliary temperature, the maximum allowable temperature of the target equipment, the ambient temperature, the first product, the second product and the third product.
3. The method of claim 2, wherein the candidate absolute temperature threshold comprises a first absolute temperature threshold, a second absolute temperature threshold, and a third absolute temperature threshold; wherein the first absolute temperature threshold, the second absolute temperature threshold, and the third absolute temperature threshold are sequentially increased;
the determining the candidate absolute temperature threshold of the target device according to the auxiliary temperature, the maximum allowable temperature of the target device, the ambient temperature, the first product, the second product and the third product comprises the following steps:
if the auxiliary temperature is less than or equal to the maximum allowable temperature of the target device, taking the auxiliary temperature as the first absolute temperature threshold, taking the sum between the second product and the ambient temperature as the second absolute temperature threshold, and taking the sum between the third product and the ambient temperature as the third absolute temperature threshold;
if the auxiliary temperature is greater than the maximum allowable temperature of the target device, the sum between the first product and the maximum allowable temperature is taken as the first absolute temperature threshold, the sum between the second product and the maximum allowable temperature is taken as the second absolute temperature threshold, and the sum between the third product and the ambient temperature is taken as the third absolute temperature threshold.
4. The method of claim 1, wherein the target network model is determined by:
adopting a particle swarm algorithm, and carrying out iterative optimization on the weight and the threshold value of the original network model according to the historical measured temperature and the historical real temperature of the candidate equipment to obtain an optimized original network model;
and training the optimized original network model according to the historical measured temperature and the historical real temperature of each candidate device to obtain a target network model.
5. The method according to claim 4, characterized in that it comprises:
taking the mean square value of the error between the historical real temperature of each candidate device and the predicted temperature of the original network model as an adaptability function; the predicted temperature is obtained according to the historical measured temperatures of the original neural network and the candidate equipment;
and carrying out iterative optimization on the weight and the threshold value of the original network model according to the particle swarm algorithm and the fitness function to obtain the optimized original network model.
6. An abnormal temperature alarm generating apparatus, the apparatus comprising:
the measuring temperature acquisition module is used for acquiring the current measuring temperature of the target equipment;
The real temperature determining module is used for correcting the current measured temperature by adopting a target network model to obtain the target real temperature of the target equipment; the target network model is determined according to the historical measured temperature and the historical real temperature of the candidate equipment;
the absolute alarm generation module is used for generating a target absolute temperature alarm of target equipment if the target real temperature is greater than or equal to any candidate absolute temperature threshold; the candidate absolute temperature threshold is determined according to the target real temperature, the environment temperature, the normal rated temperature of target equipment, the highest allowable temperature of the target equipment and the candidate absolute temperature ratio;
the relative alarm generating module is used for determining a first difference value between the target real temperature and the normal rated temperature of the target equipment and a second difference value between the target real temperature and the environment temperature, and if the ratio of the first difference value to the second difference value is larger than a preset relative threshold value, generating a relative temperature alarm of the target equipment.
7. The apparatus of claim 6, wherein the candidate absolute temperature ratio comprises a first absolute temperature ratio, a second absolute temperature ratio, and a third absolute temperature ratio; the apparatus further comprises:
A temperature product determining module, configured to determine a first product between a normal rated temperature of the target device and the first absolute temperature ratio, a second product between a normal rated temperature of the target device and the second absolute temperature ratio, and a third product between a normal rated temperature of the target device and the third absolute temperature ratio;
an auxiliary temperature determination module for taking the sum between the first product and the ambient temperature as an auxiliary temperature;
and the absolute temperature threshold determining module is used for determining a candidate absolute temperature threshold of the target equipment according to the auxiliary temperature, the highest allowable temperature of the target equipment, the environment temperature, the first product, the second product and the third product.
8. The apparatus of claim 7, wherein the candidate absolute temperature threshold comprises a first absolute temperature threshold, a second absolute temperature threshold, and a third absolute temperature threshold; wherein the first absolute temperature threshold, the second absolute temperature threshold, and the third absolute temperature threshold are sequentially increased; the absolute temperature threshold determination module includes:
a first threshold determining unit configured to take an auxiliary temperature as the first absolute temperature threshold, take a sum between a second product and an ambient temperature as the second absolute temperature threshold, and take a sum between a third product and the ambient temperature as the third absolute temperature threshold if the auxiliary temperature is less than or equal to a highest allowable temperature of a target device;
A second threshold determining unit configured to, if the auxiliary temperature is greater than a maximum allowable temperature of a target device, take a sum between a first product and the maximum allowable temperature as the first absolute temperature threshold, take a sum between a second product and the maximum allowable temperature as the second absolute temperature threshold, and take a sum between a third product and an ambient temperature as the third absolute temperature threshold.
9. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of generating an abnormal temperature alert of any one of claims 1-5.
10. A computer readable storage medium storing computer instructions for causing a processor to implement the method of generating an abnormal temperature alert according to any one of claims 1-5 when executed.
CN202310467760.2A 2023-04-27 2023-04-27 Abnormal temperature alarm generation method, device, equipment and medium Pending CN116504042A (en)

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CN202310467760.2A CN116504042A (en) 2023-04-27 2023-04-27 Abnormal temperature alarm generation method, device, equipment and medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310467760.2A CN116504042A (en) 2023-04-27 2023-04-27 Abnormal temperature alarm generation method, device, equipment and medium

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Publication Number Publication Date
CN116504042A true CN116504042A (en) 2023-07-28

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